We present results for simulated climate and climate change from a newly developed high-resolution global climate model (GFDL CM2.5). The GFDL CM2.5 model has an atmospheric resolution of approximately 50 Km in the horizontal, with 32 vertical levels. The horizontal resolution in the ocean ranges from 28 Km in the tropics to 8 Km at high latitudes, with 50 vertical levels. This resolution allows the explicit simulation of some mesoscale eddies in the ocean, particularly at lower latitudes. We present analyses based on the output of a 280 year control simulation; we also present results based on a 140 year simulation in which atmospheric CO2 increases at 1% per year until doubling after 70 years. Results are compared to the GFDL CM2.1 climate model, which has somewhat similar physics but coarser resolution. The simulated climate in CM2.5 shows marked improvement over many regions, especially the tropics, including a reduction in the double ITCZ and an improved simulation of ENSO. Regional precipitation features are much improved. The Indian monsoon and Amazonian rainfall are also substantially more realistic in CM2.5. The response of CM2.5 to a doubling of atmospheric CO2 has many features in common with CM2.1, with some notable differences. For example, rainfall changes over the Mediterranean appear to be tightly linked to topography in CM2.5, in contrast to CM2.1 where the response is more spatially homogeneous. In addition, in CM2.5 the near-surface ocean warms substantially in the high latitudes of the Southern Ocean, in contrast to simulations using CM2.1.

Uncertainties in physical parameters of coupled models are an important source of model bias and adversely impact initialisation for climate prediction. Data assimilation using error covariances derived from model dynamics to extract observational information provides a promising approach to optimise parameter values so as to reduce such bias. However, effective parameter estimation in a coupled model is usually difficult because the error covariance between a parameter and the model state tends to be noisy due to multiple sources of model uncertainties. Using a simple coupled model consisting of the 3-variable Lorenz model and a slowly varying slab ‘ocean’, this study first investigated how to enhance the signal-to-noise ratio in covariances between model states and parameters, and then designed a data assimilation scheme for enhancive parameter correction (DAEPC). In DAEPC, parameter estimation is facilitated after state estimation reaches a ‘quasiequilibrium’ where the uncertainty of coupled model states is sufficiently constrained by observations so that the covariance between a parameter and the model state is signal dominant. The observation-updated parameters are applied to improving the next cycle of state estimation and the refined covariance of parameter and model state further improves parameter correction. Performing dynamically adaptive state and parameter estimations with speedy convergence, DAEPC provides a systematic way to estimate the whole array of coupled model parameters using observations, and produces more accurate state estimates. Forecast experiments show that the DAEPC initialisation with observation-estimated parameters greatly improves the model predictability - while valid ‘atmospheric’ forecasts are extended two times longer, the ‘oceanic’ predictability is almost tripled. The simple model results here provide some insights for improving climate estimation and prediction with a coupled general circulation model.

The impact of climate warming on the upper layer of the Bering Sea is investigated by using a high-resolution coupled global climate model. The model is forced by increasing atmospheric CO2 at a rate of 1% per year until CO2 reaches double its initial value (after 70 years), after which it is held constant. In response to this forcing, the upper layer of the Bering Sea warms by about 2°C in the southeastern shelf and by a little more than 1°C in the western basin. The wintertime ventilation to the permanent thermocline weakens in the western Bering Sea. After CO2 doubling, the southeastern shelf of the Bering Sea becomes almost ice-free in March, and the stratification of the upper layer strengthens in May and June. Changes of physical condition due to the climate warming would impact the pre-condition of spring bio-productivity in the southeastern shelf.

Observations and numerical modelling experiments provide evidence for links between variability in the Atlantic Meridional Overturning Circulation (AMOC) and global climate patterns. Reduction in the strength of the overturning circulation is thought to have played a key role in rapid climate change in the past and may have the potential to significantly influence climate change in the future, as noted in the last two IPCC assessment reports (2001, 2007). Both IPCC reports also highlighted the significant uncertainties that exist regarding the future behaviour of the AMOC under global warming. Model results suggest that changes in the AMOC can impact surface air temperature, precipitation patterns and sea level, particularly in areas bordering the North Atlantic, thus affecting human populations. Here current understanding of past, present and future change in the AMOC and the effects of such changes on climate are reviewed. The focus is on observations of the AMOC, how the AMOC influences climate and in what way the AMOC is likely to change over the next few decades and the 21st century. The potential for decadal prediction of the AMOC is also discussed. Finally, the outstanding challenges and possible future directions for AMOC research are outlined.

Using two fully coupled ocean-atmosphere models of CM2.1 (the Climate Model version 2.1 developed at the Geophysical Fluid Dynamics Laboratory) and CM2.5 (a new high-resolution climate model based on CM2.1), the characteristics and sources of SST and precipitation biases associated with the Atlantic ITCZ have been investigated. CM2.5 has an improved simulation of the annual mean and the annual cycle of the rainfall over the Sahel and the northern South America, while CM2.1 shows excessive Sahel rainfall and lack of northern South America rainfall in boreal summer. This marked improvement in CM2.5 is due to not only high-resolved orography, but also a significant reduction of biases in the seasonal meridional migration of the ITCZ. In particular, the seasonal northward migration of the ITCZ in boreal summer is coupled to the seasonal variation of the SST and a subsurface doming of the thermocline in the northeastern tropical Atlantic, known as the Guinea Dome. Improvements in the ITCZ allow for better representation of the coupled processes that are important for an abrupt seasonally phase-locked decay of the interannual SST anomaly in the northern tropical Atlantic. Nevertheless, the differences between CM2.5 and CM2.1 were not sufficient to reduce the warm SST biases in the eastern equatorial region and Angola-Benguela Area. The weak bias of southerly winds along the southwestern African coast associated with the excessive southward migration bias of the ITCZ may be a key to improve the warm SST biases there.

Quantifying how global warming impacts the spatiotemporal distribution of precipitation represents a key scientific challenge with profound implications for human systems. Utilizing monthly precipitation data from Coupled Model Intercomparison Project (CMIP3) climate change simulations, the results here show that the occurrence of very dry (<0.5 mm/day) and very wet (>10 mm/day) months comprises a straightforward, robust metric of anthropogenic warming on tropical land region rainfall. In particular, differencing tropicswide precipitation frequency histograms for 25-year periods over the late 21st and 20th centuries shows increased late-21st-century occurrence of both histogram extremes in the model ensemble and across individual models. Mechanistically, such differences are consistent with the view of enhanced tropical precipitation spatial gradients. Similar diagnostics are calculated for two 15-year subperiods over 1979-2008 for the CMIP3 models and three observational precipitation products to assess whether the signature of late-21st-century warming has already emerged in response to recent warming. While both the observations and CMIP3 ensemble-mean hint at similar amplification in the warmer (1994-2008) subinterval, the changes are not robust, as substantial differences are evident among the observational products and the intraensemble spread is large. Comparing histograms computed from the warmest and coolest years of the observational period further demonstrates effects of internal variability, notably the El Niño/Southern Oscillation, which appear to oppose the impact quasi-uniform anthropogenic warming on the wet tail of the monthly precipitation distribution. These results identify the increase of very dry and wet occurrences in monthly precipitation as a potential signature of anthropogenic global warming but also highlight the continuing dominance of internal climate variability on even bulk measures of tropical rainfall.

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

Initial-value predictability measures the degree to which the initial state can influence predictions. In this paper, the initial-value predictability of six atmosphere–ocean general circulation models in the North Pacific and North Atlantic is quantified and contrasted by analyzing long control integrations with time invariant external conditions. Through the application of analog and multivariate linear regression methodologies, average predictability properties are estimated for forecasts initiated from every state on the control trajectories. For basinwide measures of predictability, the influence of the initial state tends to last for roughly a decade in both basins, but this limit varies widely among the models, especially in the North Atlantic. Within each basin, predictability varies regionally by as much as a factor of 10 for a given model, and the locations of highest predictability are different for each model. Model-to-model variations in predictability are also seen in the behavior of prominent intrinsic basin modes. Predictability is primarily determined by the mean of forecast distributions rather than the spread about the mean. Horizontal propagation plays a large role in the evolution of these signals and is therefore a key factor in differentiating the predictability of the variousmodels.

This study focuses on the statistical modeling of the Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE) for the North Atlantic basin over the period 1949-2008, which are metrics routinely used to assess tropical storm activity, and their sensitivity to sea surface temperature (SST) changes. To describe the variability exhibited by the data, four different statistical distributions are considered (gamma, Gumbel, lognormal, and Weibull), and tropical Atlantic and tropical mean SSTs are used as predictors. Model selection, both in terms of significant covariates and their functional relation to the parameters of the statistical distribution, is performed using two penalty criteria. Two different SST data sets are considered (UK Met Offices HadISSTv1 and NOAAs Extended Reconstructed ERSSTv3b) to examine the sensitivity of the results to the input data. The statistical models presented in this study are able to well describe the variability in the observations according to several goodness-of-fit diagnostics. Both tropical Atlantic and tropical mean SSTs are significant predictors, independently of the SST input data, penalty criterion, and tropical storm activity metric. The application of these models to centennial reconstructions and seasonal forecasting is illustrated. The sensitivity of North Atlantic tropical cyclone frequency, duration, and intensity is examined for both uniform and non-uniform SST changes. Under uniform SST warming, these results indicate that there is a modest sensitivity of intensity, and a decrease in tropical storm and hurricane frequencies. On the other hand, increases of tropical Atlantic SST relative to the tropical mean SST suggest an increase in intensity and frequency of North Atlantic tropical storms and hurricanes.

Time series of US landfalling and North Atlantic hurricane counts and their ratios over the period 1878–2008 are modeled using tropical Atlantic sea surface temperature (SST), tropical mean SST, North Atlantic Oscillation (NAO), and Southern Oscillation Index (SOI). Two SST input data are employed to examine the uncertainties in the reconstructed SST data on the modeling results. Due to the likely undercount of recorded hurricanes in the earliest part of the record, we consider both the uncorrected hurricane record (HURDAT), and a time series with a recently proposed undercount correction. Modeling of the count data is performed using a conditional Poisson regression model, in which the rate of occurrence can depend linearly or nonlinearly on the climate indices. Model selection is performed following a stepwise approach and using two penalty criteria. These results do not allow identifying a single “best” model due to the different model configurations (different SST data, corrected versus uncorrected datasets, penalty criteria). Despite the lack of an objectively identified unique final model, we recommend a set of models in which the parameter of the Poisson distribution depends linearly on tropical Atlantic and tropical mean SSTs. Modeling of the fractions of North Atlantic hurricanes making US landfall is performed using a binomial regression model. Similar to the count data, it is not possible to identify a single “best” model, but different model configurations are obtained depending on the SST data, undercount correction, and penalty criterion. These results suggest that these fractions are controlled by local (related to the NAO) and remote (SOI and tropical mean SST) effects.

Assessing potential changes in North Atlantic (NA) tropical storm (TS) activity this century is of paramount societal and economic significance, and the topic of intense scientific research1. We explore projections of NA TS changes over the twenty-first century by applying a statistical downscaling methodology2, 3 to a suite of experiments with the latest state-of-the-art global coupled climate models4. We also apply a methodology5 to partition the dominant sources of uncertainty in the TS projections. We find that over the first half of the twenty-first century radiative forcing changes act to increase NA TS frequency; this increase arises from radiative forcings other than increasing CO2 (probably aerosols). However, NA TS trends over the entire twenty-first century are of ambiguous sign. We find that for NA TS frequency, in contrast to sea surface temperature (SST), the largest uncertainties are driven by the chaotic nature of the climate system and by the climate response to radiative forcing. These results highlight the need to better understand the processes controlling patterns of SST change in response to radiative forcing and internal climate variability to constrain estimates of future NA TS activity. Coordinated experiments isolating forcing agents in projections should improve our understanding, and would enable better assessment of future TS activity.

50 ENSO experts, including 15 graduate students and early career postdocs met to discuss existing approaches to assess ENSO in coupled GCMs, review the recent progress, and propose recommendations for future research.

Most coupled general circulation models (GCMs) perform poorly in the tropical Atlantic in terms of climatological seasonal cycle and interannual variability. The reasons for this poor performance are investigated in a suite of sensitivity experiments with the Geophysical Fluid Dynamics Laboratory (GFDL) coupled GCM. The experiments show that a significant portion of the equatorial SST biases in the model is due to weaker than observed equatorial easterlies during boreal spring. Due to these weak easterlies, the tilt of the equatorial thermocline is reduced, with shoaling in the west and deepening in the east. The erroneously deep thermocline in the east prevents cold tongue formation in the following season despite vigorous upwelling, thus inhibiting the Bjerknes feedback. It is further shown that the surface wind errors are due, in part, to deficient precipitation over equatorial South America and excessive precipitation over equatorial Africa, which already exist in the uncoupled atmospheric GCM. Additional tests indicate that the precipitation biases are highly sensitive to land surface conditions such as albedo and soil moisture. This suggests that improving the representation of land surface processes in GCMs offers a way of improving their performance in the tropical Atlantic. The weaker than observed equatorial easterlies also contribute remotely, via equatorial and coastal Kelvin waves, to the severe warm SST biases along the southwest African coast. However, the strength of the subtropical anticyclo

The study of climate impacts on Living Marine Resources (LMRs) has increased rapidly in recent years with the availability of climate model simulations contributed to the assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Collaboration between climate and LMR scientists and shared understanding of critical challenges for such applications are essential for developing robust projections of climate impacts on LMRs. This paper assesses present approaches for generating projections of climate impacts on LMRs using IPCC-class climate models, recommends practices that should be followed for these applications, and identifies priority developments that could improve current projections. Understanding of the climate system and its representation within climate models has progressed to a point where many climate model outputs can now be used effectively to make LMR projections. However, uncertainty in climate model projections (particularly biases and inter-model spread at regional to local scales), coarse climate model resolution, and the uncertainty and potential complexity of the mechanisms underlying the response of LMRs to climate limit the robustness and precision of LMR projections. A variety of techniques including the analysis of multi-model ensembles, bias corrections, and statistical and dynamical downscaling can ameliorate some limitations, though the assumptions underlying these approaches and the sensitivity of results to their application must be assessed for each application. Developments in LMR science that could improve current projections of climate impacts on LMRs include improved understanding of the multi-scale mechanisms that link climate and LMRs and better representations of these mechanisms within more holistic LMR models. These developments require a strong baseline of field and laboratory observations including long time-series and measurements over the broad range of spatial and temporal scales over which LMRs and climate interact. Priority developments for IPCC-class climate models include improved model accuracy (particularly at regional and local scales), inter-annual to decadal-scale predictions, and the continued development of earth system models capable of simulating the evolution of both the physical climate system and biosphere. Efforts to address these issues should occur in parallel and be informed by the continued application of existing climate and LMR models.

Given that over the course of the next 10–30 years the magnitude of natural decadal variations may rival that of anthropogenically forced climate change on regional scales, it is envisioned that initialized decadal predictions will provide important information for climate-related management and adaptation decisions. Such predictions are presently one of the grand challenges for the climate community. This requires identifying those physical phenomena—and their model equivalents—that may provide additional predictability on decadal time scales, including an assessment of the physical processes through which anthropogenic forcing may interact with or project upon natural variability. Such a physical framework is necessary to provide a consistent assessment (and insight into potential improvement) of the decadal prediction experiments planned to be assessed as part of the IPCC's Fifth Assessment Report.

The North Brazil Current (NBC) connects the North and South Atlantic and is the major pathway for the surface return flow of the Atlantic meridional overturning circulation (AMOC). Here, we calculate the NBC geostrophic transport time series based on 5 decades of observations near the western boundary off the coast of Brazil. Results reveal a multidecadal NBC variability that lags Labrador Sea deep convection by a few years. The NBC transport time series is coherent with the Atlantic Multidecadal Oscillation in sea surface temperature, which also has been widely linked to AMOC fluctuations in previous modeling studies. Our results thus suggest that the observed multidecadal NBC transport variability is a useful indicator for AMOC variations. The suggested connection between the NBC and AMOC is assessed in a 700 year control simulation of the Geophysical Fluid Dynamics Laboratory's CM2.1 coupled climate model. The model results are in agreement with observations and further demonstrate that the variability of NBC transport is a good index for tracking AMOC variations. Concerning the debate about whether a slowdown of AMOC has already occurred under global warming, the observed NBC transport time series suggests strong multidecadal variability but no significant trend.

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol-cloud interactions, chemistry-climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical-system component of earth-system models and models for decadal prediction in the near-term future, for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud-droplet activation by aerosols, sub-grid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with eco-system dynamics and hydrology. Most basic circulation features in AM3 are simulated as realistically, or more so, than in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks and the intensity distributions of precipitation remain problematic, as in AM2. The last two decades of the 20th century warm in CM3 by .32°C relative to 1881-1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of .56°C and .52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol cloud interactions, and its warming by late 20th century is somewhat less realistic than in CM2.1, which warmed .66°C but did not include aerosol cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud-aerosol interactions to limit greenhouse gas warming in a way that is consistent with observed global temperature changes.

The simulated impact of the Atlantic Meridional Overturning Circulation (AMOC) on the low frequency variability of the Arctic Surface Air temperature (SAT) and sea-ice extent is studied with a 1000 year-long segment of a control simulation of GFDL CM2.1 climate model. The simulated AMOC variations in the control simulation are found to be significantly anti-correlated with the Arctic sea-ice extent anomalies and significantly correlated with the Arctic SAT anomalies on decadal timescales in the Atlantic sector of the Arctic. The maximum anti-correlation with the Arctic sea-ice extent and the maximum correlation with the Arctic SAT occur when the AMOC Index leads by one year. An intensification of the AMOC is associated with a sea-ice decline in the Labrador, Greenland and Barents Seas in the control simulation, with the largest change occurring in the winter. The recent declining trend in the satellite observed sea-ice extent also shows a similar pattern in the Atlantic sector of the Arctic in the winter, suggesting the possibility of a role of the AMOC in the recent Arctic sea-ice decline in addition to anthropogenic greenhouse gas induced warming. However, in the summer, the simulated sea-ice response to the AMOC in the Pacific sector of the Arctic is much weaker than the observed declining trend, indicating a stronger role for other climate forcings or variability in the recently observed summer sea-ice decline in the Chukchi, Beaufort, East Siberian and Laptev Seas.

Recent studies have suggested that the leading modes of North Atlantic subsurface temperature (T_sub) and sea surface height (SSH) anomalies are induced by Atlantic meridional overturning circulation (AMOC) variations and can be used as fingerprints of AMOC variability. Based on these fingerprints of the AMOC in the GFDL CM2.1 coupled climate model, a linear statistical predictive model of observed fingerprints of AMOC variability is developed in this study. The statistical model predicts a weakening of AMOC strength in a few years after its peak around 2005. Here, we show that in the GFDL coupled climate model assimilated with observed subsurface temperature data, including recent Argo network data (2003–2008), the leading mode of the North Atlantic T_sub anomalies is similar to that found with the objectively analyzed T_sub data and highly correlated with the leading mode of altimetry SSH anomalies for the period 1993–2008. A statistical auto-regressive (AR) model is fit to the time-series of the leading mode of objectively analyzed detrended North Atlantic T_sub anomalies (1955–2003) and is applied to assimilated T_sub and altimetry SSH anomalies to make predictions. A similar statistical AR model, fit to the time-series of the leading mode of modeled T_sub anomalies from the 1000-year GFDL CM2.1 control simulation, is applied to predict modeled T_sub, SSH, and AMOC anomalies. The two AR models show comparable skills in predicting observed T_sub and modeled T_sub, SSH and AMOC variations.

We studied the relationship between the dominant patterns of sea surface temperature (SST) variability in the North Pacific and the North Atlantic. The patterns are known as the Pacific Decadal Oscillation (PDO) and the Atlantic Multi-decadal Oscillation (AMO). In the analysis we used two different observational data sets for SST. Due to the high degree of serial correlation in the PDO and AMO time series, various tests were carried out to assess the significance of the correlations. The results demonstrated that the correlations are significant when the PDO leads the AMO by 1 year and when the AMO leads the PDO by 11–12 years. The possible physical processes involved are discussed, along with their potential implication for decadal prediction.

The sensitivity of the North Atlantic Ocean Circulation to an abrupt change in the Nordic Sea overflow is investigated for the first time using a high resolution eddy-permitting global coupled ocean-atmosphere model (GFDL CM2.5). The Nordic Sea overflow is perturbed through the change of the bathymetry in GFDL CM2.5. We analyze the Atlantic Meridional Overturning Circulation (AMOC) adjustment process and the downstream oceanic response to the perturbation. The results suggest that north of 34N, AMOC changes induced by changes in the Nordic Sea overflow propagate on the slow tracer advection time scale, instead of the fast Kelvin wave time scale, resulting in a time lead of several years between subpolar and subtropical AMOC changes. The results also show that a stronger and deeper-penetrating Nordic Sea overflow leads to stronger and deeper AMOC, stronger northward ocean heat transport, reduced Labrador Sea deep convection, stronger cyclonic Northern Recirculation Gyre (NRG), westward shift of the North Atlantic Current (NAC) and southward shift of the Gulf Stream, warmer sea surface temperature (SST) east of Newfoundland and colder SST south of the Grand Banks, stronger and deeper NAC and Gulf Stream, and stronger oceanic eddy activities along the NAC and the Gulf Stream paths. A stronger/weaker Nordic Sea overflow also leads to a contracted/expanded subpolar gyre (SPG). This sensitivity study points to the important role of the Nordic Sea overflow in the large scale North Atlantic ocean circulation, and it is crucial for climate models to have a correct representation of the Nordic Sea overflow.

Moisture and heat fluxes from the land surface to the atmosphere form a critical nexus between surface hydrology and atmospheric processes, particularly those relevant to precipitation. Although current theory suggests that soil moisture generally has a positive impact on subsequent precipitation, individual studies have shown support both for and against this positive feedback. Broad assessment of the coupling between soil moisture and evapotranspiration, and evapotranspiration and precipitation, has been limited by a lack of large-scale observations. Quantification of the influence of evapotranspiration on precipitation remains particularly uncertain. Here, we develop and apply physically based, objective metrics for quantifying the impacts of surface evaporative and sensible heat fluxes on the frequency and intensity of convective rainfall during summer, using North American reanalysis data. We show that high evaporation enhances the probability of afternoon rainfall east of the Mississippi and in Mexico. Indeed, variations in surface fluxes lead to changes in afternoon rainfall probability of between 10 and 25% in these regions. The intensity of rainfall, by contrast, is largely insensitive to surface fluxes. We suggest that local surface fluxes represent an important trigger for convective rainfall in the eastern United States and Mexico during the summer, leading to a positive evaporation–precipitation feedback.

The second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multi-model “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

Skillfully predicting North Atlantic hurricane activity months in advance is of potential societal significance and a useful test of our understanding of the factors controlling hurricane activity. We describe a statistical-dynamical hurricane forecasting system, based on a statistical hurricane model, with explicit uncertainty estimates, built from a suite of high-resolution global atmospheric dynamical model integrations spanning a broad range of climate states. The statistical model uses two climate predictors: the sea surface temperature (SST) in the tropical North Atlantic and SST averaged over the global tropics. The choice of predictors is motivated by physical considerations, results of high-resolution hurricane modeling and of statistical modeling of the observed record. The statistical hurricane model is applied to a suite of initialized dynamical global climate model forecasts of SST to predict North Atlantic hurricane frequency, which peaks in the August-October season, from different starting dates. Retrospective forecasts of the 1982-2009 period indicate that skillful predictions can be made from as early as November of the previous year – that is, skillful forecasts for the coming North Atlantic hurricane season could be made as the current one is closing. Based on forecasts initialized between November 2009 and March 2010, the model system predicts that the upcoming 2010 North Atlantic hurricane season will likely be more active than the 1982- 2009 climatology, with the forecasts initialized in March 2010 predicting an expected hurricane count of eight and a 50% probability of counts between six (the 1966-2009 median) and nine.

This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The climate model, known as CM3, is formulated with effectively the same ocean and sea ice components as the earlier GFDL climate model, CM2.1, yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. We anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than CM2.1, which adversely impacts the interior biases.

In this study we assess the impact of imperfect sampling in the pre-satellite era (between 1878 and 1965) on North Atlantic hurricane activity measures, and on the long-term trends in those measures. Our results suggest that a substantial upward adjustment of hurricane counts is needed prior to 1965 to account for likely ‘missed’ hurricanes due to sparse density of reporting ship traffic. After adjusting for our estimate of ‘missed’ hurricanes in the basin, the long-term (1878-2008) trend in hurricane counts changes from significantly positive to no significant change (with a nominally negative trend). The adjusted hurricane count record is more strongly connected to the difference between main development region (MDR) sea surface temperature (SST) and tropical-mean SST, than with MDR SST. Our results do not support the notion that the warming of the tropical North Atlantic due to anthropogenic greenhouse gas emissions has caused Atlantic hurricane frequency to increase.

The impact of future anthropogenic forcing on the frequency of tropical storms in the North Atlantic basin has been the subject of intensive investigation. However, whether the number of North Atlantic tropical storms will increase or decrease in a warmer climate is still heavily debated and a consensus has yet to be reached. To shed light on this issue, the authors use a recently developed statistical model, in which the frequency of North Atlantic tropical storms is modeled by a conditional Poisson distribution with rate of occurrence parameter that is a function of tropical Atlantic and mean tropical sea surface temperatures (SSTs). It is shown how the disagreement among dynamical modeling projections of late-twenty-first-century tropical storm frequency can be largely explained by differences in large-scale SST patterns from the different climate model projections used in these studies. The results do not support the notion of large (~200%) increases in tropical storm frequency in the North Atlantic basin over the twenty-first century in response to increasing greenhouse gases (GHGs). Because the statistical model is computationally inexpensive, it is used to examine the impact of different climate models and climate change scenarios on the frequency of North Atlantic tropical storms. The authors estimate that the dominant drivers of uncertainty in projections of tropical storm frequency over the twenty-first century are internal climate variations and systematic intermodel differences in the response of SST patterns to increasing GHGs. Relative to them, uncertainties in total GHG emissions or other climate forcings, within the scenarios explored here, represent a minor source of uncertainty in tropical storm frequency projections. These results suggest that reducing uncertainty in future projections of North Atlantic tropical storm frequency may depend as critically on reducing the uncertainty in the sensitivity of tropical Atlantic warming relative to the tropical mean, in response to GHG increase, as on improving dynamical or statistical downscaling techniques. Moreover, the large uncertainties on century-scale trends that are due to internal climate variability are likely to remain irreducible for the foreseeable future. As a further illustration of the statistical model’s utility, the authors model projected changes in U.S. landfalling tropical storm activity under a variety of different climate change scenarios and climate models. These results are similar to those for the overall number of North Atlantic tropical storms, and do not point to a large increase in U.S. landfalling tropical storms over the twenty-first century in response to increasing GHGs.

The number of North Atlantic tropical storms lasting two days or less exhibits a very large increase starting from the middle of the twentieth century. Still lacking are quantitative analyses to assess whether this behavior is more likely associated with climate variability or with changes in the observational system. By using statisti- cal methods combined with the current understanding of the physical processes, we provide further supporting evidence that the trend in North Atlantic tropical storms lasting two days or less is likely to be spurious. These results imply that studies ex- amining trends in the frequency of North Atlantic tropical storms from the nineteenth century should focus on storms of duration greater than about two days.

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement (‘‘downscaling’’), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climatemodels and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median 211%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate change impacts on water.

This study demonstrates a reconstruction of salinity profiles for the global ocean for the period 1993-2008. All available T-S profiles from the GTSPP and Argo data are divided in two subsets; one half used for producing the vertical coupled T-S EOF modes and the other for the verification. We employ a weighted least square method that minimizes the misfits between the predetermined EOF structures and independent observed temperature and altimetry data. Verification shows that the South Indian and North Atlantic Oceans maintain good correlations to 900 m depth between the observed and reconstructed salinity with altimetry data. Meanwhile, the Pacific and Antarctic Oceans below 500 m show significant negative correlations, which is associated with the relationship between steric height and salinity variability in these basins. In order to guarantee general agreements with observations for all ocean depths, we calculate a regional correlation index considering the impact of altimetry data and employ it for our final products. Except for the surface ocean, the pseudo salinity profiles show general improvements compared to the existing climatology and the reanalysis outputs from the GFDL’s ensemble coupled data assimilation system. Near the surface layer, reanalysis outputs show a relatively high performance due to the coupling between the atmosphere and ocean. Assimilation system produces reliable surface flux variability not accounted for the construction of the global pseudo salinity profiles. These results encourage the application of the global pseudo salinity profiles into an assimilation system for the 20th century when the observed salinity data are sparse.

The scarcity of salinity observations prior to the Argo period makes it tremendously difficult to estimate ocean states. By using the so-called pseudo salinity profiles constructed from temperature and altimetry information, here we show the improvement of salinity representation estimated by the ensemble coupled data assimilation system of the Geophysical Fluid Dynamics Laboratory. The comparisons with climatology and independent observations show that the pseudo salinity data considerably improve the assimilation skill for the pre-Argo period (1993- 2001). For the Argo period (2002-2007), there is little degradation of the assimilation skill using pseudo salinity instead of Argo observations. This result ensures the robustness of the new assimilation fields with pseudo salinity for the pre-Argo period when salinity observations are sparse. We also suggest that the interannual variability of the existing reanalysis products could suffer from erroneously-estimated discontinuities due to the non-stationary nature of the salinity observing system.

The retrospective forecast skill of three coupled climate models (NCEP CFS, GFDL CM2.1, and CAWCR POAMA 1.5) and their multi-model ensemble (MME) is evaluated, focusing on the Northern Hemisphere (NH) summer upper-tropospheric circulation along with surface temperature and precipitation for the 25-year period of 1981–2005. The seasonal prediction skill for the NH 200-hPa geopotential height basically comes from the coupled models’ ability in predicting the first two empirical orthogonal function (EOF) modes of interannual variability, because the models cannot replicate the residual higher modes. The first two leading EOF modes of the summer 200-hPa circulation account for about 84% (35.4%) of the total variability over the NH tropics (extratropics) and offer a hint of realizable potential predictability. The MME is able to predict both spatial and temporal characteristics of the first EOF mode (EOF1) even at a 5-month lead (January initial condition) with a pattern correlation coefficient (PCC) skill of 0.96 and a temporal correlation coefficient (TCC) skill of 0.62. This long-lead predictability of the EOF1 comes mainly from the prolonged impacts of El Niño-Southern Oscillation (ENSO) as the EOF1 tends to occur during the summer after the mature phase of ENSO. The second EOF mode (EOF2), on the other hand, is related to the developing ENSO and also the interdecadal variability of the sea surface temperature over the North Pacific and North Atlantic Ocean. The MME also captures the EOF2 at a 5-month lead with a PCC skill of 0.87 and a TCC skill of 0.67, but these skills are mainly obtained from the zonally symmetric component of the EOF2, not the prominent wavelike structure, the so-called circumglobal teleconnection (CGT) pattern. In both observation and the 1-month lead MME prediction, the first two leading modes are accompanied by significant rainfall and surface air temperature anomalies in the continental regions of the NH extratropics. The MME’s success in predicting the EOF1 (EOF2) is likely to lead to a better prediction of JJA precipitation anomalies over East Asia and the North Pacific (central and southern Europe and western North America).

During boreal summer, convective activity over the eastern Pacific (EPAC) inter-tropical convergence zone (ITCZ) exhibits vigorous intraseasonal variability (ISV). Previous observational studies identified two dominant ISV modes over the EPAC, i.e., a 40-day mode and a quasi-biweekly mode (QBM). The 40-day ISV mode is generally considered a local expression of the Madden-Julian Oscillation. However, in addition to the eastward propagation, northward propagation of the 40-day mode is also evident. The QBM mode bears a smaller spatial scale than the 40-day mode, and is largely characterized by northward propagation. While the ISV over the EPAC exerts significant influences on regional climate/weather systems, investigation of contemporary model capabilities in representing these ISV modes over the EPAC is limited. In this study, the model fidelity in representing these two dominant ISV modes over the EPAC is assessed by analyzing six atmospheric and three coupled general circulation models (GCMs), including one super-parameterized GCM (SPCAM) and one recently developed high-resolution GCM (GFDL HIRAM) with horizontal resolution of about 50 km. While it remains challenging for GCMs to faithfully represent these two ISV modes including their amplitude, evolution patterns, and periodicities, encouraging simulations are also noted. In general, SPCAM and HIRAM exhibit relatively superior skill in representing the two ISV modes over the EPAC. While the advantage of SPCAM is achieved through explicit representation of the cumulus process by the embedded 2-D cloud resolving models, the improved representation in HIRAM could be ascribed to the employment of a strongly entraining plume cumulus scheme, which inhibits the deep convection, and thus effectively enhances the stratiform rainfall. The sensitivity tests based on HIRAM also suggest that fine horizontal resolution could also be conducive to realistically capture the ISV over the EPAC, particularly for the QBM mode. Further analysis illustrates that the observed 40-day ISV mode over the EPAC is closely linked to the eastward propagating ISV signals from the Indian Ocean/Western Pacific, which is in agreement with the general impression that the 40-day ISV mode over the EPAC could be a local expression of the global Madden-Julian Oscillation (MJO). In contrast, the convective signals associated with the 40-day mode over the EPAC in most of the GCM simulations tend to originate between 150°E and 150°W, suggesting the 40-day ISV mode over the EPAC might be sustained without the forcing by the eastward propagating MJO. Further investigation is warranted towards improved understanding of the origin of the ISV over the EPAC.

The influence of oceanic changes on tropical cyclone activity is investigated using observational estimates of Sea Surface Temperature (SST), air-sea fluxes and ocean subsurface thermal structure over the period 1998–2007. SST conditions are examined before, during, and after the passage of tropical cyclones, through Lagrangian composites along cyclone tracks across all ocean basins, with particular focus on the North Atlantic. We explore the influence of translation speed by separating tropical cyclones according to the translation speed divided by the coriolis parameter. On average for tropical cyclones up to category 2, SST cooling becomes larger as cyclone intensity increases, peaking at 1.8K in the North Atlantic. Beyond category 2 hurricanes, however, the cooling no longer follows an increasing monotonic relationship with intensity. In the North Atlantic, the cooling for stronger hurricanes decreases, while in other ocean basins the cyclone-induced cooling does not significantly differ from Category 2 to Category 5 tropical cyclones, with the exception of the South Pacific. Since the SST response is non-monotonic, with stronger cyclones producing more cooling up to category 2, but producing less or approximately equal cooling for categories 3–5, the observations indicate that oceanic feedbacks can inhibit intensification of cyclones. This result implies that large-scale oceanic conditions are important for tropical cyclone intensity, since they control oceanic sensitivity to atmospheric forcing. Ocean sub-surface thermal data provides additional support for this dependence, showing weaker upper ocean stratification for stronger tropical cyclones. Intensification is suppressed due to negative ocean feedback when stratification favors large SST cooling, but the ability of tropical cyclones to intensify is not inhibited when stratification is weak and cyclone-induced SST cooling is small. Thus, after accounting for tropical cyclone translation speeds and latitudes, it is argued that reduced cooling under extreme tropical cyclones is the manifestation of oceanic conditions on the ability of tropical cyclones to intensify.

We assess the vertical distribution of cloud feedbacks in coupled climate models, taking care to distinguish between cloud feedbacks and a change in cloud forcing. We show that the effect of cloud changes on the longwave fluxes provides a strong positive feedback that is broadly consistent across models. In contrast, the effect of cloud changes on the shortwave fluxes ranges from a modest negative to a strong positive feedback, and is responsible for most of the intermodel spread in net cloud feedback. The feedback from high clouds is positive in all models, and is consistent with that anticipated by the Proportionately Higher Anvil Temperature hypothesis over the tropics. In contrast, low cloud cover is responsible for roughly three-quarters of the difference in global mean net cloud feedback among models, with the largest contributions from regions associated with low-level subtropical marine cloud systems.

The response of the Walker circulation to Last Glacial Maximum (LGM) forcing is analyzed using an ensemble of six coordinated coupled climate model experiments. The tropical atmospheric overturning circulation strengthens in all models in a manner that is dictated by the response of the hydrological cycle to tropical cooling. This response arises from the same mechanism that has been found to explain the weakening of the tropical circulation in response to anthropogenic global warming, but with opposite sign. Analysis of the model differences shows that the ascending branch of the Walker circulation strengthens via this mechanism, but vertical motion also weakens over areas of the Maritime Continent exposed due to lower sea level. Each model exhibits a different balance between these two mechanisms, and the result is a Pacific Walker circulation response that is not robust. Further, even those models that simulate a stronger Walker circulation during the LGM do not simulate clear patterns of surface cooling, such as La Niña-like cooling or enhanced equatorial cooling, as proposed by previous studies. In contrast, the changes in the Walker circulation have a robust and distinctive signature on the tilt of the equatorial thermocline, as expected from zonal momentum balance. The changes in the Walker circulation also have a clear signature on the spatial pattern of the precipitation changes. A reduction of the east-west salinity contrast in the Indian Ocean is related to the precipitation changes resulting from a weakening of the Indian Walker circulation. These results indicate that proxies of thermocline depth and sea surface salinity can be used to detect actual LGM changes in the Pacific and Indian Walker circulations, respectively and help constrain the sensitivity of the Walker circulation to tropical cooling.

Air pollution (ozone and particulate matter in surface air) is strongly linked to synoptic weather and thus is likely sensitive to climate change. In order to isolate the responses of air pollutant transport and wet removal to a warming climate, we examine a simple carbon monoxide (CO)–like tracer (COt) and a soluble version (SAt), both with the 2001 CO emissions, in simulations with the GFDL chemistry-climate model (AM3) for present (1981-2000) and future (2081-2100) climates. In 2081-2100, projected reductions in lower tropospheric ventilation and wet deposition exacerbate surface air pollution as evidenced by higher surface COt and SAt concentrations. However, the average horizontal general circulation patterns in 2081-2100 are similar to 1981-2000, so the spatial distribution of COt changes little. Precipitation is an important factor controlling soluble pollutant wet removal, but the total global precipitation change alone does not necessarily indicate the sign of the soluble pollutant response to climate change. Over certain latitudinal bands, however, the annual wet deposition change can be explained mainly by the simulated changes in large-scale (LS) precipitation. In regions such as North America, differences in the seasonality of LS precipitation and tracer burdens contribute to an apparent inconsistency of changes in annual wet deposition versus annual precipitation. As a step towards an ultimate goal of developing a simple index that can be applied to infer changes in soluble pollutants directly from changes in precipitation fields as projected by physical climate models, we explore here a “Diagnosed Precipitation Impact” (DPI) index. This index captures the sign and magnitude (within 50%) of the relative annual mean changes in the global wet deposition of the soluble pollutant. DPI can only be usefully applied in climate models in which LS precipitation dominates wet deposition and horizontal transport patterns change little as climate warms. Our findings support the need for tighter emission regulations, for both soluble and insoluble pollutants, to obtain a desired level of air quality as climate warms.

This paper examines the ability of recent versions of the Geophysical Fluid Dynamics Laboratory Operational Hurricane Forecast Model (GHM) to reproduce the observed relationship between hurricane intensity and hurricane-induced Sea Surface Temperature (SST) cooling. The analysis was performed by taking a Lagrangian composite of all hurricanes in the North Atlantic from 1998–2009 in observations and 2005–2009 for the GHM. A marked improvement in the intensity-SST relationship for the GHM compared to observations was found between the years 2005 and 2006–2009 due to the introduction of warm-core eddies, a representation of the loop current, and changes to the drag coefficient parameterization for bulk turbulent flux computation. A Conceptual Hurricane Intensity Model illustrates the essential steady-state characteristics of the intensity-SST relationship and is explained by two coupled equations for the atmosphere and ocean. The conceptual model qualitatively matches observations and the 2006–2009 period in the GHM, and presents supporting evidence for the conclusion that weaker upper oceanic thermal stratification in the Gulf of Mexico, caused by the introduction of the loop current and warm core eddies, is crucial to explaining the observed SST-intensity pattern. The diagnostics proposed by the conceptual model offer an independent set of metrics for comparing operational hurricane forecast models to observations.

Rainfall and flooding associated with landfalling tropical cyclones are examined through empirical analyses of three hurricanes (Frances, Ivan, and Jeanne) that affected large portions of the eastern U.S. during September 2004. Three rainfall products are considered for the analyses: NLDAS, Stage IV, and TMPA. Each of these products has strengths and weaknesses related to their spatio-temporal resolution and accuracy in estimating rainfall. Based on our analyses, we recommend using the Stage IV product when studying rainfall distribution in landfalling tropical cyclones due to its fine spatial and temporal resolutions (about 4-km and hourly) and accuracy, and the capability of estimating rainfall up to 150 km from the coast. Lagrangian analyses of rainfall distribution relative to the track of the storm are developed to represent evolution of the temporal and spatial structure of rainfall. Analyses highlight the profound changes in rainfall distribution near landfall, the changing contributions to the rainfall field from eyewall convection, inner rain bands and outer rain bands, and the key role of orographic amplification of rainfall. We also present new methods for examining spatial extreme of flooding from tropical cyclones and illustrate the links between evolving rainfall structure and spatial extent of flooding.

The sensitivity of Northern Hemisphere sea ice cover to global temperature change is examined in a group of climate models and in the satellite era observations. The models are found to have well defined, distinguishable sensitivities in climate change experiments. The satellite era observations show a larger sensitivity - a larger decline per degree warming - than any of the models. To evaluate the role of natural variability in this discrepancy, the sensitivity PDF is constructed based upon the observed trends and natural variability of multi-decadal ice cover and global temperature trends in a long control run of the GFDL CM2.1 climate model. This comparison shows that the model sensitivities range from about one to more than two pseudo-standard deviations of the variability smaller than observations indicate. The impact of natural Atlantic multi-decadal temperature trends (as simulated by the GFDL model) on the sensitivity distribution is examined and found to be minimal.

The distribution of radiocarbon (¹⁴C) in the ocean and atmosphere has fluctuated on timescales ranging from seasons to millennia. It is thought that these fluctuations partly reflect variability in the climate system, offering a rich potential source of information to help understand mechanisms of past climate change. Here, a long simulation with a new, coupled model is used to explore the mechanisms that redistribute ¹⁴C within the Earth system on inter-annual to centennial timescales. The model, CM2Mc, is a lower-resolution version of the Geophysical Fluid Dynamics Laboratory's CM2M model, uses no flux adjustments, and incorporates a simple prognostic ocean biogeochemistry model including ¹⁴C. The atmospheric ¹⁴C and radiative boundary conditions are held constant, so that the oceanic distribution of ¹⁴C is only a function of internal climate variability. The simulation displays previously-described relationships between tropical sea surface ¹⁴C and the model-equivalents of the El Niño Southern Oscillation and Indonesian Throughflow. Sea surface ¹⁴C variability also arises from fluctuations in the circulations of the subarctic Pacific and Southern Ocean, including North Pacific decadal variability, and episodic ventilation events in the Weddell Sea that are reminiscent of the Weddell Polynya of 1974–1976. Interannual variability in the air-sea balance of ¹⁴C is dominated by exchange within the belt of intense Southern Westerly winds, rather than at the convective locations where the surface ¹⁴C is most variable. Despite significant interannual variability, the simulated impact on air-sea exchange is an order of magnitude smaller than the recorded atmospheric ¹⁴C variability of the past millennium. This result partly reflects the importance of variability in the production rate of ¹⁴C in determining atmospheric ¹⁴C, but may also reflect an underestimate of natural climate variability, particularly in the Southern Westerly winds.

A skillful decadal prediction that foretells varying regional climate conditions over seasonal-interannual to multidecadal time scales is of societal significance. However, predictions initialized from the climate observing system tend to drift away from observed states towards the imperfect model climate due to model biases arising from imperfect model equations, numeric schemes and physical parameterizations, as well as the errors in the values of model parameters. Here I show how to mitigate the model bias through optimizing model parameters using observations so as to constrain the model drift in climate predictions with a simple decadal prediction model. Results show that the coupled state-parameter optimization with observations greatly enhances the predictability of the coupled model. While valid “atmospheric” forecasts are extended by more than 5 times, the decadal predictability of the “deep ocean” is almost doubled. The coherence of optimized model parameters and states is critical to improve the long time scale predictions.

A skillful decadal prediction that foretells varying regional climate conditions over seasonal-interannual to multidecadal time scales is of societal significance. However, predictions initialized from the climate observing system tend to drift away from observed states towards the imperfect model climate due to model biases arising from imperfect model equations, numeric schemes and physical parameterizations, as well as the errors in the values of model parameters. Here a simple coupled model that simulates the fundamental features of the real climate system and a “twin” experiment framework are designed to study the impact of initialization and parameter optimization on decadal predictions. One model simulation is treated as “truth” and sampled to produce “observations” that are assimilated into other simulations to produce “observation”-estimated states and parameters. The degree to which the model forecasts based on different estimates recover the truth is an assessment of the impact of coupled initial shocks and parameter optimization on climate predictions of interests. The results show that the coupled model initialization through coupled data assimilation in which all coupled model components are coherently adjusted by observations minimizes the initial coupling shocks that reduce the forecast errors on seasonal-interannual time scales. Model parameter optimization with observations effectively mitigates the model bias, thus constraining the model drift in long time scale predictions. The coupled model state-parameter optimization greatly enhances the model predictability. While valid “atmospheric” forecasts are extended 5 times, the decadal predictability of the “deep ocean” is almost doubled. The coherence of optimized model parameters and states is critical to improve the long time scale predictions.

Climate model simulations run as part of the Climate Variability and Predictability (CLIVAR) Drought Working Group initiative were analyzed to determine the impact of three patterns of sea surface temperature (SST) anomalies on drought and pluvial frequency and intensity around the world. The three SST forcing patterns include a global pattern similar to the background warming trend, a pattern in the Pacific, and a pattern in the Atlantic. Five different global atmospheric models were forced by fixed SSTs to test the impact of these SST anomalies on droughts and pluvials relative to a climatologically forced control run. The five models generally yield similar results in the locations of drought and pluvial frequency changes throughout the annual cycle in response to each given SST pattern. In all of the simulations, areas with an increase in the mean drought (pluvial) conditions tend to also show an increase in the frequency of drought (pluvial) events. Additionally, areas with more frequent extreme events also tend to show higher intensity extremes. The cold Pacific anomaly increases drought occurrence in the United States and southern South America and increases pluvials in Central America and northern and central South America. The cold Atlantic anomaly increases drought occurrence in southern Central America, northern South America, and central Africa and increases pluvials in central South America. The warm Pacific and Atlantic anomalies generally lead to reversals of the drought and pluvial increases described with the corresponding cold anomalies. More modest impacts are seen in other parts of the world. The impact of the trend pattern is generally more modest than that of the two other anomaly patterns.

Simulations from a fine-resolution global coupled model, the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.4 (CM2.4), are presented, and the results are compared with a coarse version of the same coupled model, CM2.1, under idealized climate change scenarios. A particular focus is given to the dynamical response of the Southern Ocean and the role played by the eddies—parameterized or permitted— in setting the residual circulation and meridional density structure. Compared to the case in which eddies are parameterized and consistent with recent observational and idealized modeling studies, the eddy-permitting integrations of CM2.4 show that eddy activity is greatly energized with increasing mechanical and buoyancy forcings, buffering the ocean to atmospheric changes, and the magnitude of the residual oceanic circulation response is thus greatly reduced. Although compensation is far from being perfect, changes in poleward eddy fluxes partially compensate for the enhanced equatorward Ekman transport, leading to weak modifications in local isopycnal slopes, transport by the Antarctic Circumpolar Current, and overturning circulation. Since the presence of active ocean eddy dynamics buffers the oceanic response to atmospheric changes, the associated atmospheric response to those reduced ocean changes is also weakened. Further, it is hypothesized that present numerical approaches for the parameterization of eddy-induced transports could be too restrictive and prevent coarse-resolution models from faithfully representing the eddy response to variability and change in the forcing fields.

The fast and slow components of global warming in a comprehensive climate model are isolated by examining the response to an instantaneous return to pre-industrial forcing. The response is characterized by an initial fast exponential decay with an e-folding time smaller than 5 years, leaving behind a remnant that evolves more slowly. The slow component is estimated to be small at present, as measured by the global mean near-surface air temperature, and, in the model examined, grows to 0.4C by 2100 in the A1B SRES scenario and then to 1.4C by 2300 if one holds radiative forcing fixed after 2100. The dominance of the fast component at present is supported by examining the response to an instantaneous doubling of CO₂ and by the excellent fit to the model's ensemble mean 20th century evolution with a simple one-box model with no long times scales.

It has been suggested that a strengthening of the Southern Hemisphere winds would induce a more vigorous overturning through an increased northward Ekman flux, bringing more light waters into the oceanic basins and enhancing the upwelling of North Atlantic Deep Water in the Southern Ocean, thereby increasing ocean ventilation. We present here simulations from a coarse and a fine resolution version of a coupled model subject to idealized wind stress changes in the Southern Ocean. In the fine resolution eddy-permitting model, we find that changes in poleward eddy fluxes largely compensate for the enhanced equatorward Ekman transport in the Southern Ocean. As a consequence, northward transport of light waters, pycnocline depth, Northern Hemisphere overturning and Southern Ocean upwelling anomalies are much reduced compared with simulations in the coarse resolution model with parameterized eddies. These results point to a relatively weak sensitivity of present-day global ocean

The Atlantic Meridional Overturning Circulation (AMOC) has an important influence on climate, and yet we lack adequate observations of this circulation. Here we assess the adequacy of past and current widely deployed routine observing systems for monitoring the AMOC and associated North Atlantic climate. To do so we draw on two independent simulations of the 20th century using an IPCC AR4 coupled climate model. We treat one simulation as “truth” and sample it according to the observing system we are evaluating. We then assimilate these synthetic “observations” into the second simulation within a fully-coupled system that instantaneously exchanges information among all coupled components and produces a nearly balanced and coherent estimate for global climate states including the North Atlantic climate system. The degree to which the assimilation recovers the “truth” is an assessment of the adequacy of the observing system being evaluated. As the coupled system responds to the constraint of the atmosphere or ocean, the assessment of the recovery for climate quantities such as Labrador Sea Water (LSW) and the North Atlantic Oscillation increases our understanding for the factors that determine AMOC variability. For example, we found the low-frequency sea-surface forcings provided by the atmospheric and sea-surface temperature observations can excite a LSW variation that governs the long time scale variability of the AMOC. When we use the most complete modern observing system consisting of atmospheric winds and temperature, along with Argo ocean temperature and salinity down to 2000 meters, a skill estimate of AMOC reconstruction is 90% (out of 100% maximum). Similarly encouraging results hold for other quantities, such as LSW. The past XBT observing system, in which deep ocean temperature and salinity were not available, has a lesser ability to recover the “truth” AMOC (the skill is reduced to 52%). While these results raise concerns about our ability to properly characterize past variations of the AMOC, they also hold promise for future monitoring of the AMOC and for initializing prediction models.

Understanding the plausible causes for the observed high dust concentrations in Antarctic ice cores during the Last Glacial Maximum (LGM) is crucial for interpreting the Antarctic dust records in the past climates and could provide insights into dust variability in future climates. Using the Geophysical Fluid Dynamics Laboratory (GFDL) General Circulation Models, we conduct an investigation into the various factors modulating dust emission, transport and deposition, with a view towards an improved quantification of the LGM dust enhancements in the Antarctic ice cores. The model simulations show that the expansion of source areas and changes in the Antarctic ice accumulation rates together can account for most of the observed increase of dust concentrations in the Vostok, Dome C and Taylor Dome cores, but there is an overestimate of the LGM-to-present ratio in the case of the Byrd core. The source expansion due to the lowering of sea level yields a factor of 2–3 higher contribution than that due to the reduction of continental vegetation. The changes in other climate parameters (e.g., SH precipitation change) are estimated to be relatively less important within the context of this sensitivity study, while the model-simulated LGM surface winds yield a 20–30 % reduction rather than an increase in dust deposition in Antarctica. This research yields insights towards a fundamental understanding of the causes for the significant enhancement of the dust deposition in the Antarctic ice cores during the LGM.

The North Atlantic is among the few places where decadal climate variations are considered potentially predictable. The physical mechanisms of the decadal variability are hypothesized to be associated with fluctuations of the Atlantic meridional overturning circulation (AMOC). Perfect model predictability experiments using the GFDL CM2.1 climate model are analyzed to investigate the potential predictability of the AMOC. Results indicate that the AMOC is predictable up to 20 years. We further connect AMOC predictability to readily observable fields. We show that modeled surface and subsurface signatures of AMOC variations defined by characteristic patterns of sea surface height, subsurface temperature, and upper ocean heat content anomalies, have a potential predictability similar to the AMOC's. Since we have longer observational records for these quantities than for direct measurements of the AMOC, our study highlights a potentially new promising method for monitoring AMOC variations, and hence assessing the predictability of the real climate system.

The second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) is aimed at quantifying, with a suite of long-range forecast systems, the degree to which realistic land surface initialization contributes to the skill of subseasonal precipitation and air temperature forecasts. Results, which focus here on North America, show significant contributions to temperature prediction skill out to two months across large portions of the continent. For precipitation forecasts, contributions to skill are much weaker but are still significant out to 45 days in some locations. Skill levels increase markedly when calculations are conditioned on the magnitude of the initial soil moisture anomaly.

A review of the science on the relationship between climate change and tropical cyclones (TCs) is presented. Topics include changes in aspects of tropical climate that are relevant to TC activity; observed trends and low-frequency variability of TC activity; paleoclimate proxy studies; theoretical and modeling studies; future projections; roadblocks to resolution of key issues; and recommendations for making future progress.

Records of Atlantic basin tropical cyclones (TCs) since the late nineteenth century indicate a very large upward trend in storm frequency. This increase in documented TCs has been previously interpreted as resulting from anthropogenic climate change. However, improvements in observing and recording practices provide an alternative interpretation for these changes: recent studies suggest that the number of potentially missed TCs is sufficient to explain a large part of the recorded increase in TC counts. This study explores the influence of another factor—TC duration—on observed changes in TC frequency, using a widely used Atlantic hurricane database (HURDAT). It is found that the occurrence of short-lived storms (duration of 2 days or less) in the database has increased dramatically, from less than one per year in the late nineteenth–early twentieth century to about five per year since about 2000, while medium- to long-lived storms have increased little, if at all. Thus, the previously documented increase in total TC frequency since the late nineteenth century in the database is primarily due to an increase in very short-lived TCs. The authors also undertake a sampling study based upon the distribution of ship observations, which provides quantitative estimates of the frequency of missed TCs, focusing just on the moderate to long-lived systems with durations exceeding 2 days in the raw HURDAT. Upon adding the estimated numbers of missed TCs, the time series of moderate to long-lived Atlantic TCs show substantial multidecadal variability, but neither time series exhibits a significant trend since the late nineteenth century, with a nominal decrease in the adjusted time series. Thus, to understand the source of the century-scale increase in Atlantic TC counts in HURDAT, one must explain the relatively monotonic increase in very short-duration storms since the late nineteenth century. While it is possible that the recorded increase in short-duration TCs represents a real climate signal, the authors consider that it is more plausible that the increase arises primarily from improvements in the quantity and quality of observations, along with enhanced interpretation techniques. These have allowed National Hurricane Center forecasters to better monitor and detect initial TC formation, and thus incorporate increasing numbers of very short-lived systems into the TC database.

Whether the characteristics of tropical cyclones have changed or will change in a warming climate — and if so, how — has been the subject of considerable investigation, often with conflicting results. Large amplitude fluctuations in the frequency and intensity of tropical cyclones greatly complicate both the detection of long-term trends and their attribution to rising levels of atmospheric greenhouse gases. Trend detection is further impeded by substantial limitations in the availability and quality of global historical records of tropical cyclones. Therefore, it remains uncertain whether past changes in tropical cyclone activity have exceeded the variability expected from natural causes. However, future projections based on theory and high-resolution dynamical models consistently indicate that greenhouse warming will cause the globally averaged intensity of tropical cyclones to shift towards stronger storms, with intensity increases of 2–11% by 2100. Existing modelling studies also consistently project decreases in the globally averaged frequency of tropical cyclones, by 6–34%. Balanced against this, higher resolution modelling studies typically project substantial increases in the frequency of the most intense cyclones, and increases of the order of 20% in the precipitation rate within 100 km of the storm centre. For all cyclone parameters, projected changes for individual basins show large variations between different modelling studies.

Several recent models suggest that the frequency of Atlantic tropical cyclones could decrease as the climate warms. However, these models are unable to reproduce storms of category 3 or higher intensity. We explored the influence of future global warming on Atlantic hurricanes with a downscaling strategy by using an operational hurricane-prediction model that produces a realistic distribution of intense hurricane activity for present-day conditions. The model projects nearly a doubling of the frequency of category 4 and 5 storms by the end of the 21st century, despite a decrease in the overall frequency of tropical cyclones, when the downscaling is based on the ensemble mean of 18 global climate-change projections. The largest increase is projected to occur in the Western Atlantic, north of 20°N.

Based on independent observations, we estimate the sea level budget and linear trends for individual ocean basins and the world ocean during 2004–2007. Even though it is confirmed that the seasonal variation of global sea level is balanced by the different sea level components (total sea level change from satellite altimetry equals to the sum of the steric height contribution obtained by Argo profiles and any variability in ocean mass observed from GRACE), basin-scale sea level budgets show very different characteristics. Sea level budgets over the South Pacific and Antarctic Ocean maintain a good balance both on seasonal to interannual time scales. Meanwhile, only the satellite altimeter data exhibits a large 4-year trend over the South Indian Ocean. This basin significantly impacts the magnitude of the disagreement for the global sea level budget. Large differences among the 3 different gravity fields related to the hydrologic signals in the Atlantic and Indian Ocean could be one of the major causes of the imbalance in the global sea level budget.

Given observed initial conditions, how well do coupled atmosphere–ocean models predict precipitation climatology with 1-month lead forecast? And how do the models’ biases in climatology in turn affect prediction of seasonal anomalies? We address these questions based on analysis of 1-month lead retrospective predictions for 21 years of 1981–2001 made by 13 state-of-the-art coupled climate models and their multi-model ensemble (MME). The evaluation of the precipitation climatology is based on a newly designed metrics that consists of the annual mean, the solstitial mode and equinoctial asymmetric mode of the annual cycle, and the rainy season characteristics. We find that the 1-month lead seasonal prediction made by the 13-model ensemble has skills that are much higher than those in individual model ensemble predictions and approached to those in the ERA-40 and NCEP-2 reanalysis in terms of both the precipitation climatology and seasonal anomalies. We also demonstrate that the skill for individual coupled models in predicting seasonal precipitation anomalies is positively correlated with its performances on prediction of the annual mean and annual cycle of precipitation. In addition, the seasonal prediction skill for the tropical SST anomalies, which are the major predictability source of monsoon precipitation in the current coupled models, is closely link to the models’ ability in simulating the SST mean state. Correction of the inherent bias in the mean state is critical for improving the long-lead seasonal prediction. Most individual coupled models reproduce realistically the long-term annual mean precipitation and the first annual cycle (solstitial mode), but they have difficulty in capturing the second annual (equinoctial asymmetric) mode faithfully, especially over the Indian Ocean (IO) and Western North Pacific (WNP) where the seasonal cycle in SST has significant biases. The coupled models replicate the monsoon rain domains very well except in the East Asian subtropical monsoon and the tropical WNP summer monsoon regions. The models also capture the gross features of the seasonal march of the rainy season including onset and withdraw of the Asian–Australian monsoon system over four major sub-domains, but striking deficiencies in the coupled model predictions are observed over the South China Sea and WNP region, where considerable biases exist in both the amplitude and phase of the annual cycle and the summer precipitation amount and its interannual variability are underestimated.

Monthly averaged total volume transport of the Indonesian throughflow (ITF) estimated by 14 global ocean data assimilation (ODA) products that are decade to multi-decade long are compared among themselves and with observations from the INSTANT Program (2004–2006). The main goals of the comparisons are to examine the consistency and evaluate the skill of different ODA products in simulating ITF transport. The ensemble averaged, time-mean value of ODA estimates is 13.6 Sv (1 Sv = 106 m3/s) for the common 1993–2001 period and 13.9 Sv for the 2004–2006 INSTANT Program period. These values are close to the 15-Sv estimate derived from INSTANT observations. All but one ODA time-mean estimate fall within the range of uncertainty of the INSTANT estimate. In terms of temporal variability, the scatter among different ODA estimates averaged over time is 1.7 Sv, which is substantially smaller than the magnitude of the temporal variability simulated by the ODA systems. Therefore, the overall “signal-to-noise” ratio for the ensemble estimates is larger than one. The best consistency among the products occurs on seasonal-to-interannual time scales, with generally stronger (weaker) ITF during boreal summer (winter) and during La Nina (El Nino) events. The scatter among different products for seasonal-to-interannual time scales is approximately 1 Sv. Despite the good consistency, systematic difference is found between most ODA products and the INSTANT observations. All but the highest-resolution (18 km) ODA product show a dominant annual cycle while the INSTANT estimate and the 18-km product exhibit a strong semi-annual signal. The coarse resolution is an important factor that limits the level of agreement between ODA and INSTANT estimates. Decadal signals with periods of 10–15 years are seen. The most conspicuous and consistent decadal change is a relatively sharp increase in ITF transport during 1993–2000 associated with the strengthening tropical Pacific trade wind. Most products do not show a weakening ITF after the mid-1970s’ associated with the weakened Pacific trade wind. The scatter of ODA estimates is smaller after than before 1980, reflecting the impact of the enhanced observations after the 1980s. To assess the representativeness of using the average over a three-year period (e.g., the span of the INSTANT Program) to describe longer-term mean, we investigate the temporal variations of the three-year low-pass ODA estimates. The average variation is about 3.6 Sv, which is largely due to the increase of ITF transport from 1993 to 2000. However, the three-year average during the 2004–2006 INSTANT Program period is within 0.5 Sv of the long-term mean for the past few decades.

A “biased twin” experiment using two coupled general circulation models (CGCMs) that are biased with respect to each other is used to study the impact of deep ocean bias on ensemble ocean data assimilation. The “observations” drawn from one CGCM based on the Argo network are assimilated into the other. Traditional ensemble filtering can successfully recover the upper-ocean temperature and salinity of the target model but it usually fails to converge in the deep ocean where the model bias is large compared to the ocean’s intrinsic variability. The inconsistency between the well-constrained upper ocean and poorly constrained deep ocean generates spurious assimilation currents. An adaptively inflated ensemble filter is designed to enhance the consistency of upper- and deep-ocean adjustments, based on “climatological” standard deviations being adaptively updated by observations. The new algorithm reduces deep-ocean errors greatly, in particular, reducing current errors up to 70% and vertical motion errors up to 50%. Specifically, the tropical circulation is greatly improved with a better representation of the undercurrent, upwelling, and Western Boundary Current systems. The structure of the subtropical gyre is also substantially improved. Consequently, the new algorithm leads to better estimates of important global hydrographic features such as global overturning and pycnocline depth. Based on these improved estimates, decadal trends of basin-scale heat content and salinity as well as the seasonal–interannual variability of the tropical ocean are constructed coherently. Interestingly, the Indian Ocean (especially the north Indian Ocean), which is associated with stronger atmospheric feedbacks, is the most sensitive basin to the covariance formulation used in the assimilation. Also, while reconstruction of the local thermohaline structure plays a leading-order role in estimating the decadal trend of the Atlantic meridional overturning circulation (AMOC), more accurate estimates of the AMOC variability require coupled assimilation to produce coherently improved external forcings as well as internal heat and salt transport.

The Indian Ocean exhibits strong variability on a number of time scales, including prominent intraseasonal variations in both the atmosphere and ocean. Of particular interest is the south tropical Indian Ocean thermocline ridge, a region located between 12° and 5°S, which exhibits prominent variability in sea surface temperature (SST) due to dominant winds that raise the thermocline and shoal the mixed layer. In this paper, submonthly (less than 30 day) cooling events in the thermocline ridge region are diagnosed with observations and models, and are related to large-scale conditions in the Indo-Pacific region. Observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) satellite were used to identify 16 cooling events in the period 1998–2007, which on average cannot be fully accounted for by air–sea enthalpy fluxes. Analysis of observations and a hierarchy of models, including two coupled global climate models (GFDL CM2.1 and GFDL CM2.4), indicates that ocean dynamical changes are important to the cooling events. For extreme cooling events (above 2.5 standard deviations), air–sea enthalpy fluxes account for approximately 50% of the SST signature, and oceanic processes cannot in general be neglected. For weaker cooling events (1.5–2.5 standard deviations), air–sea enthalpy fluxes account for a larger fraction of the SST signature. Furthermore, it is found that cooling events are preconditioned by large-scale, low-frequency changes in the coupled ocean–atmosphere system. When the thermocline is unusually shallow in the thermocline ridge region, cooling events are more likely to occur and are stronger; these large-scale conditions are more (less) likely during La Niña (El Niño/Indian Ocean dipole) events. Strong cooling events are associated with changes in atmospheric convection, which resemble the Madden–Julian oscillation, in both observations and the models.

As in the observed record, the termination of El Niño in the coupled IPCC-AR4 climate models involves meridional processes tied to the seasonal cycle. These meridional processes both precondition the termination of El Niño events in general and lead to a peculiar termination of extreme El Niño events (such as those of 1982–83 and 1997–98), in which the eastern equatorial Pacific warm sea surface temperature anomalies (SSTA) persist well into boreal spring/early-summer. The mechanisms controlling the peculiar termination of extreme El Niño events, which involves to the development of an equatorially centred intertropical convergence zone, are consistent across the four models that exhibit extreme El Niños and observational record, suggesting that this peculiar termination represents a general feature of extreme El Niños. Further, due to their unusual termination, extreme El Niños exhibit an apparent eastward propagation of their SSTA, which can strongly influence estimates of the apparent propagation of ENSO over multi-decadal periods. Interpreting these propagation changes as evidence of changes in the underlying dynamical feedbacks behind El Niño could therefore be misleading, given the strong influence of a single extreme event.

Spatial variations in sea surface temperature (SST) and rainfall changes over the tropics are investigated based on ensemble simulations for the first half of the twenty-first century under the greenhouse gas (GHG) emission scenario A1B with coupled ocean–atmosphere general circulation models of the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR). Despite a GHG increase that is nearly uniform in space, pronounced patterns emerge in both SST and precipitation. Regional differences in SST warming can be as large as the tropical-mean warming. Specifically, the tropical Pacific warming features a conspicuous maximum along the equator and a minimum in the southeast subtropics. The former is associated with westerly wind anomalies whereas the latter is linked to intensified southeast trade winds, suggestive of wind–evaporation–SST feedback. There is a tendency for a greater warming in the northern subtropics than in the southern subtropics in accordance with asymmetries in trade wind changes. Over the equatorial Indian Ocean, surface wind anomalies are easterly, the thermocline shoals, and the warming is reduced in the east, indicative of Bjerknes feedback. In the midlatitudes, ocean circulation changes generate narrow banded structures in SST warming. The warming is negatively correlated with wind speed change over the tropics and positively correlated with ocean heat transport change in the northern extratropics. A diagnostic method based on the ocean mixed layer heat budget is developed to investigate mechanisms for SST pattern formation. Tropical precipitation changes are positively correlated with spatial deviations of SST warming from the tropical mean. In particular, the equatorial maximum in SST warming over the Pacific anchors a band of pronounced rainfall increase. The gross moist instability follows closely relative SST change as equatorial wave adjustments flatten upper-tropospheric warming. The comparison with atmospheric simulations in response to a spatially uniform SST warming illustrates the importance of SST patterns for rainfall change, an effect overlooked in current discussion of precipitation response to global warming. Implications for the global and regional response of tropical cyclones are discussed.

Low-frequency modulation of and change under global warming in the Indian Ocean Dipole (IOD) mode is investigated based on a pair of long simulations with a coupled ocean-atmosphere general circulation model, one under constant climate forcing and one forced by increasing greenhouse gas concentrations. In the unforced simulation, IOD variance displays slow modulation significant in amplitude. It is found that the mean thermocline depth in the eastern equatorial Indian Ocean (EEIO) is important for the slow modulation, skewness and ENSO-correlation of IOD. IOD variance increases as the EEIO thermocline shoals and thermocline feedback strengthens. In the global warming simulation, the Walker circulation slows down with easterly wind changes in the equatorial Indian Ocean. The thermocline shoals in the EEIO. Thermocline feedback intensifies but surprisingly IOD variance does not. Zonal wind anomalies associated with IOD are found to weaken, likely due to increased static stability of the troposphere in global warming. Linear model experiments confirm this stability effect to reduce circulation response to a sea surface temperature dipole. The opposing changes in thermocline and atmospheric feedbacks result in little change in IOD variance but the shoaling thermocline weakens IOD skewness. Little change under global warming in IOD variance in the model suggests that the apparent intensification of IOD activity for the recent decades is likely part of natural, chaotic modulation of the ocean-atmosphere system.

El Niño and La Niña comprise the dominant mode of tropical climate variability: the El Niño and Southern Oscillation (ENSO) phenomenon. ENSO variations influence climate, ecosystems, and societies around the globe. It is, therefore, of great interest to understand the character of past and future ENSO variations. In this brief review, we explore our current understanding of these issues. The amplitude and character of ENSO have been observed to exhibit substantial variations on timescales of decades to centuries; many of these changes over the past millennium resemble those that arise from internally generated climate variations in an unforced climate model. ENSO activity and characteristics have been found to depend on the state of the tropical Pacific climate system, which is expected to change in the 21st century in response to changes in radiative forcing (including increased greenhouse gases) and internal climate variability. However, the extent and character of the response of ENSO to increased in greenhouse gases are still a topic of considerable research, and given the results published to date, we cannot yet rule out possibilities of an increase, decrease, or no change in ENSO activity arising from increases in CO₂. Yet we are fairly confident that ENSO variations will continue to occur and influence global climate in the coming decades and centuries. Changes in continental climate, however, could alter the remote impacts of El Niño and La Niña.

Climate models robustly predict that the climate of southwestern North America, defined as from the western Great Plains to the Pacific Ocean and from the Oregon border to southern Mexico, will dry throughout the current century as a consequence of rising greenhouse gases. This regional drying is part of a general drying of the subtropics and poleward expansion of the subtropical dry zones. It is shown that the drying is driven by a reduction of of winter season precipitation associated with a poleward broadening of the North Pacific storm track and increased moisture divergence by transient eddies. Observations to date cannot confirm that this transition to a drier climate is already underway due to the presence of large amplitude decadal variations of presumed natural origin but it is anticipated that the anthropogenic drying will reach the amplitude of natural decadal variability by mid-century. In addition to this drop in total precipitation warming is already causing a decline in mountain snow mass and an advance of spring snow melt disrupting the natural water storage systems that are part of the regions water supply system. Uncertainties in how radiative forcing will impact the tropical Pacific climate system create uncertainties in the amplitude of drying in southwest North America with a La Niña-like response creating a worst case scenario of greater drying.

The authors analyze and model time series of annual counts of tropical storms lasting more than 2 days in the North Atlantic basin and U.S. landfalling tropical storms over the period 1878–2008 in relation to different climate indices. The climate indices considered are the tropical Atlantic sea surface temperature (SST), tropical mean SST, the North Atlantic Oscillation (NAO), and the Southern Oscillation index (SOI). Given the uncertainties associated with a possible tropical storm undercount in the presatellite era, two different time series of counts for the North Atlantic basin are employed: one is the original (uncorrected) tropical storm record maintained by the National Hurricane Center and the other one is with a correction for the estimated undercount associated with a changing observation network. Two different SST time series are considered: the Met Office’s HadISSTv1 and NOAA’s Extended Reconstructed SST. Given the nature of the data (counts), a Poisson regression model is adopted. The selection of statistically significant covariates is performed by penalizing models for adding extra parameters and two penalty functions are used. Depending on the penalty function, slightly different models, both in terms of covariates and dependence of themodel’s parameter, are obtained, showing that there is not a ‘‘single best’’model.Moreover, results are sensitive to the undercount correction and the SST time series. Suggestions concerning the model to use are provided, driven by both the outcomes of the statistical analyses and the current understanding of the underlying physical processes responsible for the genesis, development, and tracks of tropical storms in the North Atlantic basin. Although no single model is unequivocally superior to the others, the authors suggest a very parsimonious family ofmodels using as covariates tropical Atlantic and tropical mean SSTs.

The mechanisms of changes in the large-scale hydrological cycle projected by 15 models participating in the Coupled Model Intercomparison Project phase 3 and used for the Intergovernmental Panel on Climate Change’s Fourth Assessment Report are analyzed by computing differences between 2046 and 2065 and 1961 and 2000. The contributions to changes in precipitation minus evaporation, P2E, caused thermodynamically by changes in specific humidity, dynamically by changes in circulation, and by changes in moisture transports by transient eddies are evaluated. The thermodynamic and dynamic contributions are further separated into advective and divergent components. The nonthermodynamic contributions are then related to changes in the mean and transient circulation. The projected change in P 2 E involves an intensification of the existing pattern of P2E with wet areas [the intertropical convergence zone (ITCZ) and mid- to high latitudes] getting wetter and arid and semiarid regions of the subtropics getting drier. In addition, the subtropical dry zones expand poleward. The accentuation of the twentieth-century pattern of P2E is in part explained by increases in specific humidity via both advection and divergence terms. Weakening of the tropical divergent circulation partially opposes the thermodynamic contribution by creating a tendency to decreased P2E in the ITCZ and to increased P2E in the descending branches of the Walker and Hadley cells. The changing mean circulation also causes decreased P 2 E on the poleward flanks of the subtropics because the descending branch of the Hadley Cell expands and the midlatitude meridional circulation cell shifts poleward. Subtropical drying and poleward moistening are also contributed to by an increase in poleward moisture transport by transient eddies. The thermodynamic contribution to changing P 2 E, arising from increased specific humidity, is almost entirely accounted for by atmospheric warming under fixed relative humidity.

The El Niño–Southern Oscillation (ENSO) is a naturally occurring fluctuation that originates in the tropical Pacific region and affects ecosystems, agriculture, freshwater supplies, hurricanes and other severe weather events worldwide. Under the influence of global warming, the mean climate of the Pacific region will probably undergo significant changes. The tropical easterly trade winds are expected to weaken; surface ocean temperatures are expected to warm fastest near the equator and more slowly farther away; the equatorial thermocline that marks the transition between the wind-mixed upper ocean and deeper layers is expected to shoal; and the temperature gradients across the thermocline are expected to become steeper. Year-to-year ENSO variability is controlled by a delicate balance of amplifying and damping feedbacks, and one or more of the physical processes that are responsible for determining the characteristics of ENSO will probably be modified by climate change. Therefore, despite considerable progress in our understanding of the impact of climate change on many of the processes that contribute to El Niño variability, it is not yet possible to say whether ENSO activity will be enhanced or damped, or if the frequency of events will change.

Retrospective predictions of seasonal hurricane activity in the Atlantic and East Pacific are generated using an atmospheric model with 50km horizontal resolution and simply persisting sea surface temperature (SST) anomalies from June through the hurricane season. Using an ensemble of 5 realizations for each year between 1982 and 2008, the correlations of the model mean with observations of basin-wide hurricane frequency are 0.69 in the North Atlantic and 0.58 in the East Pacific. In the North Atlantic, a significant part of the degradation in skill as compared to a model forced with observed SSTs during the hurricane season (correlation 0.78) can be explained by the change from June through the hurricane season in one parameter, the difference between the SST in the main development region and the tropical mean SST. In fact, simple linear regression models with this one predictor perform nearly as well as the full dynamical model for basin-wide hurricane frequency in both the East Pacific and the North Atlantic. The implication is that the quality of seasonal forecasts based on a coupled atmosphere-ocean model will depend in large part on the model’s ability to predict the evolution of this difference between main development region SST and tropical mean SST.

Because ocean color alters the absorption of sunlight, it can produce changes in sea surface temperatures with further impacts on atmospheric circulation. These changes can project onto fields previously recognized to alter the distribution of tropical cyclones. If the North Pacific subtropical gyre contained no absorbing and scattering materials, the result would be to reduce subtropical cyclone activity in the subtropical Northwest Pacific by 2/3, while concentrating cyclone tracks along the equator. Predicting tropical cyclone activity using coupled models may thus require consideration of the details of how heat moves into the upper thermocline as well as biogeochemical cycling.

We propose a modification to the standard forcing/feedback diagnostic energy balance model to account for 1) differences between effective and equilibrium climate sensitivities and 2) the variation of effective sensitivity over time in climate change experiments with coupled atmosphere-ocean climate models. In the spirit of Hansen et al (2005) we introduce an efficacy factor to the ocean heat uptake. Comparing the time-evolution of the surface warming in high and low efficacy models demonstrates the role of this efficacy in the transient response to CO2 forcing. Abrupt CO2 increase experiments show that the large efficacy of the Geophysical Fluid Dynamics Laboratory's CM2.1 model sets up in the first two decades following the increase in forcing. The use of an efficacy is necessary to fit this model's global mean temperature evolution in periods with both increasing and stable forcing. The inter-model correlation of transient climate response with ocean heat uptake efficacy is greater than its correlation with equilibrium climate sensitivity in an ensemble of climate models used for the 3rd and 4th IPCC assessments. When computed at the time of doubling in the standard experiment with 1%/yr increase in CO2, the efficacy is variable amongst the models but is generally greater than 1, averages between 1.3 and 1.4, and is as large as 1.75 in several models.

Recent studies report that two types of El Niño events have been observed. One is the cold tongue (CT) El Niño, which is characterized by relatively large sea surface temperature (SST) anomalies in the eastern Pacific, and the other is the warm pool (WP) El Niño, in which SST anomalies are confined to the central Pacific. Here, both types of El Niño events are analyzed in a long-term coupled GCM simulation. The present model simulates the major observed features of both types of El Niño, incorporating the distinctive patterns of each oceanic and atmospheric variable. It is also demonstrated that each type of El Niño has quite distinct dynamic processes, which control their evolutions. The CT El Niño exhibits strong equatorial heat discharge poleward and thus the dynamical feedbacks control the phase transition from a warm event to a cold event. On the other hand, the discharge process in the WP El Niño is weak because of its spatial distribution of ocean dynamic field. The positive SST anomaly of WP El Niño is thermally damped through the intensified evaporative cooling.

A variety of observational and modeling studies show that changes in the Atlantic Meridional Overturning Circulation (AMOC) can induce rapid global scale climate change. In particular, a substantially weakened AMOC leads to a southward shift of the Intertropical Convergence Zone (ITCZ) in both the Atlantic and the Pacific. However, the simulated amplitudes of the AMOC induced tropical climate change differ substantially among different models. In this paper, we study the sensitivity to cloud feedback of the climate response to a change in the AMOC using a coupled ocean-atmosphere model (GFDL CM2.1). Without cloud feedback, the simulated AMOC-induced climate change in this model is weakened substantially. Low cloud feedback has a strong amplifying impact on the tropical ITCZ shift in this model, while the effects of high cloud feedback are weaker. We conclude that cloud feedback is an important contributor to the uncertainty in the global response to AMOC changes.

The Atlantic meridional overturning circulation (AMOC) simulated in various ocean-only and coupled atmosphere–ocean numerical models often varies in time because of either forced or internal variability. The path of the Gulf Stream (GS) is one diagnostic variable that seems to be sensitive to the amplitude of the AMOC, yet previous modeling studies show a diametrically opposed relationship between the two variables. In this note this issue is revisited, bringing together ocean observations and comparisons with the GFDL Climate Model version 2.1 (CM2.1), both of which suggest a more southerly (northerly) GS path when the AMOC is relatively strong (weak). Also shown are some examples of possible diagnostics to compare various models and observations on the relationship between shifts in GS path and changes in AMOC strength in future studies.

AMOC variations are often thought to propagate with the Kelvin wave speed, resulting in a short time lead between high and low latitudes AMOC variations. However as shown in this paper using a coupled climate model (GFDL CM2.1), with the existence of interior pathways of North Atlantic Deep Water (NADW) from Flemish Cap to Cape Hatteras as that observed recently, AMOC variations estimated in density space propagate with the advection speed in this region, resulting in a much longer time lead (several years) between subpolar and subtropical AMOC variations and providing a more useful predictability. The results suggest that AMOC variations have significant meridional coherence in density space, and monitoring AMOC variations in density space at higher latitudes might reveal a stronger signal with a several-year time lead.

Extensive modeling studies show that changes in the anthropogenic forcing due to increasing greenhouse gases might lead to a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) in the 21st century, but the AMOC weakening estimated in most previous modeling studies is in depth space. Us- ing a coupled ocean atmosphere model (GFDL CM2.1), this paper shows that in density space, the anthropogenically forced AMOC changes over the 21st cen- tury are intensified at northern high latitudes (nearly twice of those at lower lat- itudes) due to changes in the North Atlantic Deep Water (NADW) formation. In contrast, anthropogenically forced AMOC changes are much smaller in depth space at the same northern high latitudes. Hence projecting AMOC changes in depth space would lead to a significant underestimation of AMOC changes as- sociated with changes in NADW formation. The result suggests that monitor- ing AMOC change signal at northern high latitudes in density space might re- veal a much stronger signal than that at lower latitudes. The simulated AMOC changes in density space under anthropogenic forcing can not be distinguished from that induced by natural AMOC variability for at least the first 20 years of the 21st century, although the signal can be detected over a much longer period.

Ice core records of polar temperatures and greenhouse gases document abrupt millennial-scale oscillations that suggest the reduction or shutdown of thermohaline Circulation (THC) in the North Atlantic Ocean may induce the abrupt cooling in the northern hemisphere. It remains unknown, however, whether the sea surface temperature (SST) is cooling or warming in the Kuroshio of the Northwestern Pacific during the cooling event. Here we present an AMS 14C-dated foraminiferal Mg/Ca SST record from the central Okinawa Trough and document that the SST variations exhibit two steps of warming since 21 ka --- at 14.7 ka and 12.8 ka, and a cooling (~1.5°C) during the interval of the Younger Dryas. By contrast, we observed no SST change or oceanic warming (~1.5-2°C) during the episodes of Northern Hemisphere cooling between ~21-40 ka. We therefore suggest that the “Antarctic-like” timing and amplitude of millennial-scale SST variations in the subtropical Northwestern Pacific between 20- 40 ka may have been determined by rapid ocean adjustment processes in response to abrupt wind stress and meridional temperature gradient changes in the North Pacific.

Ocean water clarity affects the distribution of shortwave heating in the water column. In a one-dimensional time-mean sense, increased clarity would be expected to cool the surface and heat subsurface depths as shortwave radiation penetrates deeper into the water column. However, wind-driven upwelling, boundary currents, and the seasonal cycle of mixing can bring water heated at depth back to the surface. This warms the equator and cools the subtropics throughout the year while reducing the amplitude of the seasonal cycle of temperature in polar regions. This paper examines how these changes propagate through the climate system in a coupled model with an isopycnal ocean component focusing on the different impacts associated with removing shading from different regions. Increasing shortwave penetration along the equator causes warming to the south of the equator. Increasing it in the relatively clear gyres off the equator causes the Hadley cells to strengthen and the subtropical gyres to shift equatorward. Increasing shortwave penetration in the less clear regions overlying the oxygen minimum zones causes the cold tongue to warm and the Walker circulation to weaken. Increasing shortwave penetration in the high-latitude Southern Ocean causes an increase in the formation of mode water from subtropical water. The results suggest that more attention be paid to the processes distributing heat below the mixed layer.

We propose a new approach to decompose observed climate variations over the Atlantic Hurricane Basin's main development region (MDR) into components attributable to radiative forcing changes and to internal oceanic variability. Our attribution suggests that the observed multidecadal anomalies of vertical shear (Uz) and a simple index of maximum potential intensity (SIMPI) for tropical cyclones are both dominated by internal variability, consistent with multidecadal variations of Atlantic Hurricane activity; changes in radiative forcing led to increasing Uz and decreasing SIMPI since the late 50's, unfavorable for Atlantic Hurricane activity. Physically, at least for the GFDL model, sea surface temperature (SST) anomalies induced by ocean heat transport variations are more efficient in producing negative Uz anomalies than that induced by altered radiative forcing.

The U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land–atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere–ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Niño–Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern. One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the United States tends to occur when the two oceans have anomalies of opposite signs. Further highlights of the response over the United States to the Pacific forcing include precipitation signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. The response to the positive SST trend forcing pattern is an overall surface warming over the world’s land areas, with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all of the models. It is hoped that these early results, as well as those reported in the other contributions to this special issue on drought, will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world.

Sulfate aerosols resulting from strong volcanic explosions last for 2–3 years in the lower stratosphere. Therefore it was traditionally believed that volcanic impacts produce mainly short-term, transient climate perturbations. However, the ocean integrates volcanic radiative cooling and responds over a wide range of time scales. The associated processes, especially ocean heat uptake, play a key role in ongoing climate change. However, they are not well constrained by observations, and attempts to simulate them in current climate models used for climate predictions yield a range of uncertainty. Volcanic impacts on the ocean provide an independent means of assessing these processes. This study focuses on quantification of the seasonal to multidecadal time scale response of the ocean to explosive volcanism. It employs the coupled climate model CM2.1, developed recently at the National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory, to simulate the response to the 1991 Pinatubo and the 1815 Tambora eruptions, which were the largest in the 20th and 19th centuries, respectively. The simulated climate perturbations compare well with available observations for the Pinatubo period. The stronger Tambora forcing produces responses with higher signal-to-noise ratio. Volcanic cooling tends to strengthen the Atlantic meridional overturning circulation. Sea ice extent appears to be sensitive to volcanic forcing, especially during the warm season. Because of the extremely long relaxation time of ocean subsurface temperature and sea level, the perturbations caused by the Tambora eruption could have lasted well into the 20th century.nd sea level, the perturbations caused by the Tambora eruption could last well into the 20th century.

There is a new perspective of a continuum of prediction problems, with a blurring of the distinction between short-term predictions and long-term climate projections. At the heart of this new perspective is the realization that all climate system predictions, regardless of time scale, share common processes and mechanisms; moreover, interactions across time and space scales are fundamental to the climate system itself. Further, just as seasonal-to-interannual predictions start from an estimate of the state of the climate system, there is a growing realization that decadal and longer-term climate predictions could be initialized with estimates of the current observed state of the atmosphere, oceans, cryosphere, and land surface. Even though the prediction problem itself is seamless, the best practical approach to it may be described as unified: models aimed at different time scales and phenomena may have large commonality but place emphasis on different aspects of the system. The potential benefits of this commonality are significant and include improved predictions on all time scales and stronger collaboration and shared knowledge, infrastructure, and technical capabilities among those in the weather and climate prediction communities.

A new field of study, “decadal prediction,” is emerging in climate science. Decadal prediction lies between seasonal/interannual forecasting and longer-term climate change projections, and focuses on time-evolving regional climate conditions over the next 10–30 yr. Numerous assessments of climate information user needs have identified this time scale as being important to infrastructure planners, water resource managers, and many others. It is central to the information portfolio required to adapt effectively to and through climatic changes. At least three factors influence time-evolving regional climate at the decadal time scale: 1) climate change commitment (further warming as the coupled climate system comes into adjustment with increases of greenhouse gases that have already occurred), 2) external forcing, particularly from future increases of greenhouse gases and recovery of the ozone hole, and 3) internally generated variability. Some decadal prediction skill has been demonstrated to arise from the first two of these factors, and there is evidence that initialized coupled climate models can capture mechanisms of internally generated decadal climate variations, thus increasing predictive skill globally and particularly regionally. Several methods have been proposed for initializing global coupled climate models for decadal predictions, all of which involve global time-evolving three-dimensional ocean data, including temperature and salinity. An experimental framework to address decadal predictability/prediction is described in this paper and has been incorporated into the coordinated Coupled Model Intercomparison Model, phase 5 (CMIP5) experiments, some of which will be assessed for the IPCC Fifth Assessment Report (AR5). These experiments will likely guide work in this emerging field over the next 5 yr.

The atmospheric and land components of the Geophysical Fluid Dynamics Laboratory’s climate model CM2.1 is used with climatological sea surface temperatures (SSTs) to investigate the relative climatic impacts of historical anthropogenic land cover change (LCC) and realistic SST anomalies. The SST forcing anomalies used are analogous to signals induced by an El Nino-Southern Oscillation (ENSO), a North Atlantic Oscillation (NAO), and the background trend. Coherent areas of LCC are represented throughout much of central and eastern Europe, northern India, southeastern China, and on either side of the ridge of the Appalachian Mountains in North America. Smaller areas of change are present in various tropical regions. The land cover changes in the model are almost exclusively a conversion of forests to grasslands. Model results show that LCC has a negligible impact on the global scale, while the SST anomalies—particularly the ENSO-like signal—have a statistically significant global impact. However, in the regions where the land surface has been altered, the impact of LCC can be equally or more important than the SST forcing patterns in determining the seasonal cycle of the surface water and energy balance. LCC also perturbs the local air temperature and rainfall at a similar level of statistical significance as the SST anomalies. This suggests that proper representation of land cover conditions is essential in the design of climate model experiments, particularly if results are to be used for regional-scale assessments of climate change impacts.

Atlantic tropical cyclone activity has trended upward in recent decades. The increase coincides with favorable changes in local sea surface temperature and other environmental indices, principally associated with vertical shear and the thermodynamic profile. The relative importance of these environmental factors has not been firmly established. A recent study using a high-resolution dynamical downscaling model has captured both the trend and interannual variations in Atlantic storm frequency with considerable fidelity. In the present work, this downscaling framework is used to assess the importance of the large-scale thermodynamic environment relative to other factors influencing Atlantic tropical storms. Separate assessments are done for the recent multidecadal trend (1980–2006) and a model-projected global warming environment for the late 21st century. For the multidecadal trend, changes in the seasonal-mean thermodynamic environment (sea surface temperature and atmospheric temperature profile at fixed relative humidity) account for more than half of the observed increase in tropical cyclone frequency, with other seasonal-mean changes (including vertical shear) having a somewhat smaller combined effect. In contrast, the model’s projected reduction in Atlantic tropical cyclone activity in the warm climate scenario appears to be driven mostly by increased seasonal-mean vertical shear in the western Atlantic and Caribbean rather than by changes in the SST and thermodynamic profile.

We have developed a dynamic land model (LM3V) able to simulate ecosystem dynamics and exchanges of water, energy, and CO2 between land and atmosphere. LM3V is specifically designed to address the consequences of land use and land management changes including cropland and pasture dynamics, shifting cultivation, logging, fire, and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V, forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation data, and four historic scenarios of land use change for 1700–2000. Our analysis suggests a net terrestrial carbon source due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference in the historic cropland distribution. This magnitude is substantially smaller than previous estimates from other models, largely due to our estimates of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural land clearing since the 1960s. For the 1990s, our estimates for the pastures' carbon flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9 GtC/a. Our process-based model suggests a smaller net deforestation source than earlier bookkeeping models because it accounts for decelerated net conversion of primary forest to agriculture and for stronger secondary vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher than the range reported here because of uncertainty in the biomass recovery under changing ambient conditions, including atmospheric CO2 concentration, nutrients availability, and climate.

Changes in continental water stores, largely human-induced, affect sea level. Better hydrological models and observations could clarify the land's role in sea-level variations.

The impact of oceanic observing systems, external radiative forcings due to greenhouse gas and natural aerosol (GHGNA), and oceanic initial conditions on long time variability of oceanic heat content and salinity is assessed by the assimilation of oceanic “observations” in the context of a “perfect” Intergovernmental Panel on Climate Change Fourth Assessment Report model. According to times and locations at which observations are available, the 20th century expendable bathythermograph (XBT) temperature and 21st century Argo temperature and salinity observations are drawn from a model simulation (set as the “truth”) with historical GHGNA radiative forcings. These model observations are assimilated into another coupled model simulation based on temporally varying or fixed year GHGNA values and different oceanic initial conditions. The degree to which the assimilation recovers the truth variability of oceanic heat content and salinity is an assessment of the impact of each factor on the detection of the oceanic “climate.” Results show that both the 20th century XBT and 21st century Argo observations adequately capture the basin-scale variability of heat content. The Argo salinity observations appear to be necessary to reproduce the North Atlantic thermohaline structure and variability. The addition of historical radiative forcings does not make a significant contribution to the detection skill. The initial conditions spun up by historical GHGNA produce better detection skill than the initial conditions spun up by preindustrial fixed year GHGNA due to reduced assimilation shocks. While the 20th century XBT temperature observations alone capture some basic features of salinity variations of the tropical ocean due to the strong T-S relationship from tropical air-sea interactions, the Argo salinity observations are important for global state estimation, particularly in high latitudes where haline effects on ocean density are greater.

A new World Ocean atlas of monthly temperature and salinity, based on individual profiles for 2003–2007 (WOA21c), is constructed and compared with the World Ocean Atlas 2001 (WOA01), the World Ocean Atlas 2005 (WOA05), and the data assimilation analysis from the Coupled Data Assimilation (CDA) system developed by the Geophysical Fluid Dynamics Laboratory (GFDL). First, we established a global data management system for quality control (QC) of oceanic observed data both in real time and delayed mode. Delayed mode QC of Argo floats identified about 8.5% (3%) of the total floats (profiles) up to December 2007 as having a significant salinity offset of more than 0.05. Second, all QCed data were gridded at 1° by 1° horizontal resolution and 23 standard depth levels using six spatial scales (large and small longitudinal, latitudinal, and cross-isobath) and a temporal scale. Analyzed mean temperature in WOA21c is warm with respect to WOA01 and WOA05, while salinity difference is less evident. Consistent differences among WOA01, WOA05, and WOA21c are found both in the fully and subsampled data set, which indicates a large impact of recent observations on the existing climatologies. Root mean square temperature and salinity differences and offsets of the GFDL's CDA results significantly decrease in the order of WOA01, WOA05, and WOA21c in most oceans and depths as well. This result suggests that the WOA21c is of use for the collocated assessment approach especially for high-performance assimilation models on the global scale.

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 onetier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Ni ńo 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Nińo 3.4 SST variation. The forecasts for 2 m air temperature are better in El Nińo years than in La Nińa years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the onetier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.

The Madden–Julian oscillation (MJO) interacts with and influences a wide range of weather and climate phenomena (e.g., monsoons, ENSO, tropical storms, midlatitude weather), and represents an important, and as yet unexploited, source of predictability at the subseasonal time scale. Despite the important role of the MJO in our climate and weather systems, current global circulation models (GCMs) exhibit considerable shortcomings in representing this phenomenon. These shortcomings have been documented in a number of multimodel comparison studies over the last decade. However, diagnosis of model performance has been challenging, and model progress has been difficult to track, because of the lack of a coherent and standardized set of MJO diagnostics. One of the chief objectives of the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group is the development of observation-based diagnostics for objectively evaluating global model simulations of the MJO in a consistent framework. Motivation for this activity is reviewed, and the intent and justification for a set of diagnostics is provided, along with specification for their calculation, and illustrations of their application. The diagnostics range from relatively simple analyses of variance and correlation, to more sophisticated space–time spectral and empirical orthogonal function analyses. These diagnostic techniques are used to detect MJO signals, to construct composite life cycles, to identify associations of MJO activity with the mean state, and to describe interannual variability of the MJO.

The ability of eight climate models to simulate the Madden–Julian oscillation (MJO) is examined using diagnostics developed by the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group. Although the MJO signal has been extracted throughout the annual cycle, this study focuses on the boreal winter (November–April) behavior. Initially, maps of the mean state and variance and equatorial space–time spectra of 850-hPa zonal wind and precipitation are compared with observations. Models best represent the intraseasonal space–time spectral peak in the zonal wind compared to that of precipitation. Using the phase–space representation of the multivariate principal components (PCs), the life cycle properties of the simulated MJOs are extracted, including the ability to represent how the MJO evolves from a given subphase and the associated decay time scales. On average, the MJO decay (e-folding) time scale for all models is shorter (20–29 days) than observations (31 days). All models are able to produce a leading pair of multivariate principal components that represents eastward propagation of intraseasonal wind and precipitation anomalies, although the fraction of the variance is smaller than observed for all models. In some cases, the dominant time scale of these PCs is outside of the 30–80-day band. Several key variables associated with the model’s MJO are investigated, including the surface latent heat flux, boundary layer (925 hPa) moisture convergence, and the vertical structure of moisture. Low-level moisture convergence ahead (east) of convection is associated with eastward propagation in most of the models. A few models are also able to simulate the gradual moistening of the lower troposphere that precedes observed MJO convection, as well as the observed geographical difference in the vertical structure of moisture associated with the MJO. The dependence of rainfall on lower tropospheric relative humidity and the fraction of rainfall that is stratiform are also discussed, including implications these diagnostics have for MJO simulation. Based on having the most realistic intraseasonal multivariate empirical orthogonal functions, principal component power spectra, equatorial eastward propagating outgoing longwave radiation (OLR), latent heat flux, low-level moisture convergence signals, and vertical structure of moisture over the Eastern Hemisphere, the superparameterized Community Atmosphere Model (SPCAM) and the ECHAM4/Ocean Isopycnal Model (OPYC) show the best skill at representing the MJO.

A global atmospheric model with roughly 50 km horizontal grid spacing is used to simulate the interannual variability of tropical cyclones using observed sea surface temperatures (SSTs) as the lower boundary condition. The model's convective parameterization is based on a closure for shallow convection, with much of the deep convection allowed to occur on resolved scales. Four realizations of the period 1981–2005 are generated. The correlation of yearly Atlantic hurricane counts with observations is greater than 0.8 when the model is averaged over the four realizations, supporting the view that the random part of this annual Atlantic hurricane frequency (the part not predictable given the SSTs) is relatively small (< 2 hurricanes/yr). Correlations with observations are lower in the East, West and South Pacific (roughly 0.6, 0.5 and 0.3) and insignificant in the Indian ocean. The model trends in Northern Hemisphere basin-wide frequency are consistent with the observed trends in the IBTrACS database. The model generates an upward trend of hurricane frequency in the Atlantic and downward trends in the East and West Pacific over this time frame. The model produces a negative trend in the Southern Hemisphere that is larger than that in the IBTrACS. The same model is used to simulate the response to the SST anomalies generated by coupled models in the CMIP3 archive, using the late 21st century in the A1B scenario. Results are presented for SST anomalies computed by averaging over 18 CMIP3 models and from individual realizations from three models. A modest reduction of global and Southern Hemisphere hurricane frequency is obtained in each case, but the results in individual Northern Hemisphere basins differ among the models. The vertical shear in the Atlantic Main Development Region (MDR) and the difference between the MDR SST and the tropical mean SST are well correlated with the model's Atlantic storm frequency, both for interannual variability and for the intermodel spread in global warming projections.

The climate response of the equatorial Pacific to increased greenhouse gases is investigated using numerical experiments from 11 climate models participating in the Intergovernmental Panel on Climate Change’s Fourth Assessment Report. Multimodel mean climate responses to CO2 doubling are identified and related to changes in the heat budget of the surface layer. Weaker ocean surface currents driven by a slowing down of the Walker circulation reduce ocean dynamical cooling throughout the equatorial Pacific. The combined anomalous ocean dynamical plus radiative heating from CO2 is balanced by different processes in the western and eastern basins: Cloud cover feedbacks and evaporation balance the heating over the warm pool, while increased cooling by ocean vertical heat transport balances the warming over the cold tongue. This increased cooling by vertical ocean heat transport arises from increased near-surface thermal stratification, despite a reduction in vertical velocity. The stratification response is found to be a permanent feature of the equilibrium climate potentially linked to both thermodynamical and dynamical changes within the equatorial Pacific. Briefly stated, ocean dynamical changes act to reduce (enhance) the net heating in the east (west). This explains why the models simulate enhanced equatorial warming, rather than El Niño–like warming, in response to a weaker Walker circulation. To conclude, the implications for detecting these signals in the modern observational record are discussed.

The roles of zonal and meridional wind stress and of surface heat flux in the seasonal cycle of sea surface temperature (SST) are examined with a primitive equation (PE) model of the tropical Pacific Ocean. While a variety of previous numerical and observational studies have examined the seasonal cycle of SST in the eastern tropical Pacific, it is noteworthy that different mechanisms have been invoked as primary in each case and different conclusions have been reached regarding the relative importance of the various components of surface forcing. Here, we perform a series of numerical experiments in which different components of the surface forcing are eliminated and the resulting upper ocean variability is compared with that of the climatological experiment. The model used for these experiments reproduces a realistic climatological seasonal cycle, in which SST emerges as an independent quantity. We find that the different cases all produce qualitatively reasonable seasonal cycles of SST, though only the most complete model is also able to reproduce the seasonal cycle of near surface currents, tropical instability waves (TIWs), and net surface heat fluxes consistent with historical observations. These results indicate that simply reproducing a qualitatively accurate seasonal cycle of SST does not necessarily allow meaningful conclusions to be made about the relative importance of the different components of surface forcing. The results described here also suggest that a model simulation must at least reproduce all the documented near surface kinematic features of the equatorial Pacific cold tongue region reasonably well, before accurate inferences can be made from model experiments. This provides useful guidelines to current efforts to develop and evaluate more complex fully coupled air-sea models and shows that results for simple or intermediate ocean models that do not have this level of fidelity to the observations will be difficult to interpret.

Coordinated Ocean-ice Reference Experiments (COREs) are presented as a tool to explore the behaviour of global ocean-ice models under forcing from a common atmospheric dataset. We highlight issues arising when designing coupled global ocean and sea ice experiments, such as difficulties formulating a consistent forcing methodology and experimental protocol. Particular focus is given to the hydrological forcing, the details of which are key to realizing simulations with stable meridional overturning circulations. The atmospheric forcing from [Large, W., Yeager, S., 2004. Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies. NCAR Technical Note: NCAR/TN-460+STR. CGD Division of the National Center for Atmospheric Research] was developed for coupled-ocean and sea ice models. We found it to be suitable for our purposes, even though its evaluation originally focussed more on the ocean than on the sea-ice. Simulations with this atmospheric forcing are presented from seven global ocean-ice models using the CORE-I design (repeating annual cycle of atmospheric forcing for 500 years). These simulations test the hypothesis that global ocean-ice models run under the same atmospheric state produce qualitatively similar simulations. The validity of this hypothesis is shown to depend on the chosen diagnostic. The CORE simulations provide feedback to the fidelity of the atmospheric forcing and model configuration, with identification of biases promoting avenues for forcing dataset and/or model development.

The role of the penetration length scale of shortwave radiation into the surface ocean and its impact on tropical Pacific variability is investigated with a fully coupled ocean, atmosphere, land and ice model. Previous work has shown that removal of all ocean color results in a system that tends strongly towards an El Niño state. Results from a suite of surface chlorophyll perturbation experiments show that the mean state and variability of the tropical Pacific is highly sensitive to the concentration and distribution of ocean chlorophyll. Setting the near-oligotrophic regions to contain optically pure water warms the mean state and suppresses variability in the western tropical Pacific. Doing the same above the shadow zones of the tropical Pacific also warms the mean state but enhances the variability. It is shown that increasing penetration can both deepen the pycnocline (which tends to damp El Niño) while shifting the mean circulation so that the wind response to temperature changes is altered. Depending on what region is involved this change in the wind stress can either strengthen or weaken ENSO variability.

A control simulation of the GFDL CM2.1 global coupled GCM, run for 2000 years with its atmospheric composition, solar irradiance, and land cover held fixed at 1860 values, exhibits strong interdecadal and intercentennial modulation of its ENSO behavior. To the extent that such modulation is realistic, it could attach large uncertainties to ENSO metrics diagnosed from centennial and shorter records – with important implications for historical and paleo records, climate projections, and model assessment and intercomparison. Analysis of the wait times between ENSO warm events suggests that such slow modulation need not require multidecadal memory; it can arise simply from Poisson statistics applied to ENSO's interannual time scale and seasonal phase-locking.

Determining how El Niño and its impacts may change over the next 10 to 100 years remains a difficult scientific challenge. Ocean–atmosphere coupled general circulation models (CGCMs) are routinely used both to analyze El Niño mechanisms and teleconnections and to predict its evolution on a broad range of time scales, from seasonal to centennial. The ability to simulate El Niño as an emergent property of these models has largely improved over the last few years. Nevertheless, the diversity of model simulations of present-day El Niño indicates current limitations in our ability to model this climate phenomenon and to anticipate changes in its characteristics. A review of the several factors that contribute to this diversity, as well as potential means to improve the simulation of El Niño, is presented.

We present a correlation study of time-varying multivariate volumetric data sets. In most scientific disciplines, to test hypotheses and discover insights, scientists are interested in looking for connections among different variables, or among different spatial locations within a data field. In response, we propose a suite of techniques to analyze the correlations in time-varying multivariate data. Various temporal curves are utilized to organize the data and capture the temporal behaviors. To reveal patterns and find connections, we perform data clustering and segmentation using the kmeans clustering and graph partitioning algorithms. We study the correlation structure of a single or a pair of variables using pointwise correlation coefficients and canonical correlation analysis. We demonstrate our approach using results on time-varying multivariate climate data sets.

Global atmospheric transport in a climate subject to a substantial weakening of the Atlantic thermohaline circulation (THC) is studied by using climatological Green’s functions of the mass conservation equation for a conserved, passive tracer. Two sets of Green’s functions for the perturbed climate and for the present climate are evaluated from 11-year atmospheric trajectory calculations, based on 3-D winds simulated by GFDL’s newly developed global coupled ocean–atmosphere model (CM2.1). The Green’s function analysis reveals pronounced effects of the climate change on the atmospheric transport, including seasonally modified Hadley circulation with a stronger Northern Hemisphere cell in DJF and a weaker Southern Hemisphere cell in JJA. A weakened THC is also found to enhance mass exchange rates through mixing barriers between the tropics and the two extratropical zones. The response in the tropics is not zonally symmetric. The 3-D Green’s function analysis of the effect of THC weakening on transport in the tropical Pacific shows a modified Hadley cell in the eastern Pacific, confirming the results of our previous studies, and a weakening (strengthening) of the upward and eastward motion to the south (north) of the Equator in the western Pacific in the perturbed climate as compared to the present climate.

A conundrum exists regarding whether the sea-surface temperatures decreased or increased over the southern Caribbean and the western Tropical Atlantic region during the Younger Dryas when the North Atlantic cooled substantially and the Atlantic thermohaline circulation was weakened significantly. Despite the proximity of core locations, some proxy reconstructions record a surface cooling, while others indicate a warming. We suggest that this seemingly paradoxical finding may, at least partially, be attributed to the competing physical processes that result in opposing signs of temperature change in the region in response to weakened North Atlantic meridional overturning circulation. Our coupled ocean-atmosphere model experiments indicate that the temperature response over the southern Caribbean and Western Tropical Atlantic regions is complex and can vary considerably in small spatial scales, depending on the nature of physical processes that dominate.

²³⁰Th-dated oxygen isotope records of stalagmites from Sanbao Cave, China, characterize Asian Monsoon (AM) precipitation through the ends of the third- and fourthmost recent ice ages. As a result, AM records for the past four glacial terminations can now be precisely correlated with those from ice cores and marine sediments, establishing the timing and sequence of major events. In all four cases, observations are consistent with a classic Northern Hemisphere summer insolation intensity trigger for an initial retreat of northern ice sheets. Meltwater and icebergs entering the North Atlantic alter oceanic and atmospheric circulation and associated fluxes of heat and carbon, causing increases in atmospheric CO₂ and Antarctic temperatures that drive the termination in the Southern Hemisphere. Increasing CO₂ and summer insolation drive recession of northern ice sheets, with probable positive feedbacks between sea level and CO₂.

Previous work has suggested that the strength and latitudinal position of the Southern Hemisphere (SH) mid-latitude westerly winds has an important impact on climate and the Atlantic Meridional Overturning Circulation (AMOC). We probe this hypothesis by conducting ensembles of experiments using the GFDL CM2.1 coupled ocean-atmosphere model with altered SH wind stress. We find, consistent with previous work, that enhanced (reduced) and poleward (equatorward) displaced SH westerly winds lead to an AMOC intensification (weakening). While the AMOC takes more than a century to respond fully to the altered SH winds, initial effects in the North Atlantic can occur within a few decades. The AMOC changes generate SST and surface air temperature responses in the North Atlantic and adjacent continental regions. In the Southern Hemisphere, the atmosphere responds to the altered ocean circulation with a further strengthening and poleward movement of the SH winds, thereby constituting a modest positive feedback.

This study examines the impact of projected changes (A1B “marker” scenario) in emissions of four short-lived air pollutants (ozone, black carbon, organic carbon, and sulfate) on future climate. Through year 2030, simulated climate is only weakly dependent on the projected levels of short-lived air pollutants, primarily the result of a near cancellation of their global net radiative forcing. However, by year 2100, the projected decrease in sulfate aerosol (driven by a 65% reduction in global sulfur dioxide emissions) and the projected increase in black carbon aerosol (driven by a 100% increase in its global emissions) contribute a significant portion of the simulated A1B surface air warming relative to the year 2000: 0.2°C (Southern Hemisphere), 0.4°C globally, 0.6°C (Northern Hemisphere), 1.5–3°C (wintertime Arctic), and 1.5–2°C (∼40% of the total) in the summertime United States. These projected changes are also responsible for a significant decrease in central United States late summer root zone soil water and precipitation. By year 2100, changes in short-lived air pollutants produce a global average increase in radiative forcing of ∼1 W/m²; over east Asia it exceeds 5 W/m². However, the resulting regional patterns of surface temperature warming do not follow the regional patterns of changes in short-lived species emissions, tropospheric loadings, or radiative forcing (global pattern correlation coefficient of −0.172). Rather, the regional patterns of warming from short-lived species are similar to the patterns for well-mixed greenhouse gases (global pattern correlation coefficient of 0.8) with the strongest warming occurring over the summer continental United States, Mediterranean Sea, and southern Europe and over the winter Arctic.

In this study, an estimate of the expected number of Atlantic tropical cyclones (TCs) that were missed by the observing system in the presatellite era (between 1878 and 1965) is developed. The significance of trends in both number and duration since 1878 is assessed and these results are related to estimated changes in sea surface temperature (SST) over the “main development region” (“MDR”). The sensitivity of the estimate of missed TCs to underlying assumptions is examined. According to the base case adjustment used in this study, the annual number of TCs has exhibited multidecadal variability that has strongly covaried with multidecadal variations in MDR SST, as has been noted previously. However, the linear trend in TC counts (1878–2006) is notably smaller than the linear trend in MDR SST, when both time series are normalized to have the same variance in their 5-yr running mean series. Using the base case adjustment for missed TCs leads to an 1878–2006 trend in the number of TCs that is weakly positive, though not statistically significant, with p ~ 0.2. The estimated trend for 1900–2006 is highly significant (+~ 4.2 storms century⁻¹) according to the results of this study. The 1900–2006 trend is strongly influenced by a minimum in 1910–30, perhaps artificially enhancing significance, whereas the 1878–2006 trend depends critically on high values in the late 1800s, where uncertainties are larger than during the 1900s. The trend in average TC duration (1878–2006) is negative and highly significant. Thus, the evidence for a significant increase in Atlantic storm activity over the most recent 125 yr is mixed, even though MDR SST has warmed significantly. The decreasing duration result is unexpected and merits additional exploration; duration statistics are more uncertain than those of storm counts. As TC formation, development, and track depend on a number of environmental factors, of which regional SST is only one, much work remains to be done to clarify the relationship between anthropogenic climate warming, the large-scale tropical environment, and Atlantic TC activity.

The interpretation of model precipitation output (e.g., as a gridpoint estimate versus as an areal mean) has a large impact on the evaluation and comparison of simulated daily extreme rainfall indices from climate models. It is first argued that interpretation as a gridpoint estimate (i.e., corresponding to station data) is incorrect. The impacts of this interpretation versus the areal mean interpretation in the context of rainfall extremes are then illustrated. A high-resolution (0.25° × 0.25° grid) daily observed precipitation dataset for the United States [from Climate Prediction Center (CPC)] is used as idealized perfect model gridded data. Both 30-yr return levels of daily precipitation (P₃₀) and a simple daily intensity index are substantially reduced in these data when estimated at coarser resolution compared to the estimation at finer resolution. The reduction of P₃₀ averaged over the conterminous United States is about 9%, 15%, 28%, 33%, and 43% when the data were first interpolated to 0.5° × 0.5°, 1° × 1°, 2° × 2°, 3° × 3°, and 4° × 4° grid boxes, respectively, before the calculation of extremes. The differences resulting from the point estimate versus areal mean interpretation are sensitive to both the data grid size and to the particular extreme rainfall index analyzed. The differences are not as sensitive to the magnitude and regional distribution of the indices. Almost all Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) models underestimate U.S. mean P₃₀ if it is compared directly with P₃₀ estimated from the high-resolution CPC daily rainfall observation. On the other hand, if CPC daily data are first interpolated to various model resolutions before calculating the P₃₀ (a more correct procedure in our view), about half of the models show good agreement with observations while most of the remaining models tend to overestimate the mean intensity of heavy rainfall events. A further implication of interpreting model precipitation output as an areal mean is that use of either simple multimodel ensemble averages of extreme rainfall or of intermodel variability measures of extreme rainfall to assess the common characteristics and range of uncertainties in current climate models is not appropriate if simulated extreme rainfall is analyzed at a model’s native resolution. Owing to the large sensitivity to the assumption used, the authors recommend that for analysis of precipitation extremes, investigators interpret model precipitation output as an area average as opposed to a point estimate and then ensure that various analysis steps remain consistent with that interpretation.

In this chapter, we revisit two recent studies performed at the Geophysical Fluid Dynamics Laboratory (GFDL), with a focus on issues relevant to tropical cyclones and climate change. The first study was a model-based assessment of twentieth-century regional surface temperature trends. The tropical Atlantic Main Development Region (MDR) for hurricane activity was found to have warmed by several tenths of a degree Celsius over the twentieth century. Coupled model historical simulations using current best estimates of radiative forcing suggest that the century-scale warming trend in the MDR may contain a significant contribution from anthropogenic forcing, including increases in atmospheric greenhouse gas concentrations. The results further suggest that the low-frequency variability in the MDR, apart from the trend, may contain substantial contributions from both radiative forcing (natural and anthropogenic) and internally generated climate variability. The second study used the GFDL huyrricane model, in an idealized setting, to simulate the impact of a pronounced CO2-induced warming on hurricane intensities and precipitation. A 1.75°C warming increases the intensities of hurricanes in the model by 5.8% in terms of surface wind speeds, 14% in terms of central pressure fall, or about one half category on the Saffir-Simpson Hurricane Scale. A revised storm-core accumulated (six-hour) rainfall measure shows a 21.6% increase under high CO2 conditions. Our simulated storm intensities are substantially less sensitive to sea surface temperature (SST) changes than recently reported historical observational trends are - a difference we are not able to completely reconcile at this time.

Increasing sea surface temperatures in the tropical Atlantic Ocean and measures of Atlantic hurricane activity have been reported to be strongly correlated since at least 1950 (refs 1, 2, 3, 4, 5), raising concerns that future greenhouse-gas-induced warming6 could lead to pronounced increases in hurricane activity. Models that explicitly simulate hurricanes are needed to study the influence of warming ocean temperatures on Atlantic hurricane activity, complementing empirical approaches. Our regional climate model of the Atlantic basin reproduces the observed rise in hurricane counts between 1980 and 2006, along with much of the interannual variability, when forced with observed sea surface temperatures and atmospheric conditions7. Here we assess, in our model system7, the changes in large-scale climate that are projected to occur by the end of the twenty-first century by an ensemble of global climate models8, and find that Atlantic hurricane and tropical storm frequencies are reduced. At the same time, near-storm rainfall rates increase substantially. Our results do not support the notion of large increasing trends in either tropical storm or hurricane frequency driven by increases in atmospheric greenhouse-gas concentrations.

Leading hypotheses for abrupt climate changes are focused on the ocean response to a freshening of surface waters in the north Atlantic. The degree to which such a freshening affects the deep, slow thermohaline, rather than the shallow, swift, wind-driven circulations of the ocean, and hence the degree to which that freshening affects climate in high rather than low latitudes, differ from model to model, depending on factors such as the treatment of diffusive processes in the oceans. Many comprehensive climate models are biased and confine the influence mainly to the thermohaline circulation and northern climates. Simulations of paleoclimates can provide valuable tests for the models, but only some of those climates provide sufficiently stringent tests to determine which models are realistic.

We explore the predictability of the sea surface temperature anomalies associated with the Indian Ocean Dipole/Zonal Mode (IODZM) at a three-season lead, within the Geophysical Fluid Dynamics Laboratory (GFDL) coupled general circulation model (CGCM). In both control simulations and retrospective forecasts of the 1990's in the CGCM, we find that the occurrence of some IODZM events is preconditioned by oceanic conditions and potentially predictable three seasons in advance, while other IODZM events appear to be triggered by weather noise and have low predictability. The results highlight the necessity for future studies to distinguish periods when the IODZM is more or less predictable and search for its precursory pattern in the ocean.

A common practice in the design of forecast models for ENSO is to couple ocean general circulation models to simple atmospheric models. Therefore, by construction these models (known as hybrid ENSO models) do not resolve various kinds of atmospheric variability [e.g., the Madden–Julian oscillation (MJO) and westerly wind bursts] that are often regarded as “unwanted noise.” In this work the sensitivity of three hybrid ENSO models to this unresolved atmospheric variability is studied. The hybrid coupled models were tuned to be asymptotically stable and the magnitude, and spatial and temporal structure of the unresolved variability was extracted from observations. The results suggest that this neglected variability can add an important piece of realism and forecast skill to the hybrid models. The models were found to respond linearly to the low-frequency part of the neglected atmospheric variability, in agreement with previous findings with intermediate models. While the wind anomalies associated with the MJO typically explain a small fraction of the unresolved variability, a large fraction of the interannual variability can be excited by this forcing. A large correlation was found between interannual anomalies of Kelvin waves forced by the intraseasonal MJO and the Kelvin waves forced by the low-frequency part of the MJO. That is, in years when the MJO tends to be more active it also produces a larger low-frequency contribution, which can then resonate with the large-scale coupled system. Other kinds of atmospheric variability not related to the MJO can also produce interannual anomalies in the hybrid models. However, when projected on the characteristics of Kelvin waves, no clear correlation between its low-frequency content and its intraseasonal activity was found. This suggests that understanding the mechanisms by which the intraseasonal MJO interacts with the ocean to modulate its low-frequency content may help to better to predict ENSO variability.

Alternative interpretations of the relationship between sea surface temperature and hurricane activity imply vastly different future Atlantic hurricane activity.

The potential for sea ice-albedo feedback to give rise to nonlinear climate change in the Arctic Ocean defined as a nonlinear relationship between polar and global temperature change or, equivalently, a time-varying polar amplification is explored in IPCC AR4 climate models. Five models supplying SRES A1B ensembles for the 21st century are examined and very linear relationships are found between polar and global temperatures (indicating linear Arctic Ocean climate change), and between polar temperature and albedo (the potential source of nonlinearity). Two of the climate models have Arctic Ocean simulations that become annually sea ice-free under the stronger CO₂ increase to quadrupling forcing. Both of these runs show increases in polar amplification at polar temperatures above -5°C and one exhibits heat budget changes that are consisten with the small ice cap instability of simple energy balance models. Both models show linear warming up to a polar temperature of -5° well above the disappearance of their September ice covers at about -9°C. Below -5°C, surface albedo decreases smoothly as reductions move, progressively, to earlier parts of the sunlit period. Atmospheric heat transport exerts a strong cooling effect during the transition to annually ice-free conditions. Specialized experiments with atmosphere and coupled models show that the main damping mechanism for sea ice region surface temperature is reduced upward heat flux through the adjacent ice-free oceans resulting in reduced atmospheric heat transport into the region.

Impacts of convective momentum transport (CMT) on tropical Pacific climate are examined, using an atmospheric (AGCM) and coupled GCM (CGCM) from Seoul National University. The CMT scheme affects the surface mainly via a convection-compensating atmospheric subsidence which conveys momentum downward through most of the troposphere. AGCM simulations—with SSTs prescribed from climatological and El Nino Southern Oscillation (ENSO) conditions—show substantial changes in circulation when CMT is added, such as an eastward shift of the climatological trade winds and west Pacific convection. The CMT also alters the ENSO wind anomalies by shifting them eastward and widening them meridionally, despite only subtle changes in the precipitation anomaly patterns. During ENSO, CMT affects the low-level winds mainly via the anomalous convection acting on the climatological westerly wind shear over the central Pacific—so that an eastward shift of convection transfers more westerly momentum toward the surface than would occur without CMT. By altering the low-level circulation, the CMT further alters the precipitation, which in turn feeds back on the CMT. In the CGCM, CMT affects the simulated climatology by shifting the mean convection and trade winds eastward and warming the equatorial SST; the ENSO period and amplitude also increase. In contrast to the AGCM simulations, CMT substantially alters the El Nino precipitation anomaly patterns in the CGCM. Also discussed are possible impacts of the CMT-induced changes in climatology on the simulated ENSO.

Abrupt changes in the African monsoon can have pronounced socioeconomic impacts on many West African countries. Evidence for both prolonged humid periods and monsoon failures have been identified throughout the late Pleistocene and early Holocene epochs1, 2. In particular, drought conditions in West Africa have occurred during periods of reduced North Atlantic thermohaline circulation, such as the Younger Dryas cold event1. Here, we use an ocean–atmosphere general circulation model to examine the link between oceanographic changes in the North Atlantic Ocean and changes in the strength of the African monsoon. Our simulations show that when North Atlantic thermohaline circulation is substantially weakened, the flow of the subsurface North Brazil Current reverses. This leads to decreased upper tropical ocean stratification and warmer sea surface temperatures in the equatorial South Atlantic Ocean, and consequently reduces African summer monsoonal winds and rainfall over West Africa. This mechanism is in agreement with reconstructions of past climate. We therefore suggest that the interaction between thermohaline circulation in the North Atlantic Ocean and wind-driven currents in the tropical Atlantic Ocean contributes to the rapidity of African monsoon transitions during abrupt climate change events.

Satellite altimeter data shows a weakening of the North Atlantic subpolar gyre during the 1990s, which is thought as an indicator of a slowdown of the Atlantic meridional overturning circulation (AMOC). However, whether the recent slowing subpolar gyre is a decadal variation or a long-term trend remains unclear. Here I show that altimeter data is highly correlated with instrumental subsurface ocean temperature data in the North Atlantic, and both show opposite signs between the subpolar gyre and the Gulf Stream path. Such a dipole pattern is a distinctive fingerprint of AMOC variability, as shown for the first time by a 1000-year coupled ocean-atmosphere model simulation. The results suggest that, contrary to previous interpretations, the recent slowdown of the subpolar gyre is a part of a multidecadal variation and suggests a strengthening of the AMOC. The ongoing satellite and subsurface temperature measurements could be used to monitor future AMOC variations sensitively.

The impact of the penetration length scale of shortwave radiation into the surface ocean is investigated with a fully coupled ocean, atmosphere, land and ice model. Oceanic shortwave radiation penetration is assumed to depend on the chlorophyll concentration. As chlorophyll concentrations increase the distribution of shortwave heating becomes shallower. This change in heat distribution impacts mixed-layer depth. This study shows that removing all chlorophyll from the ocean results in a system that tends strongly towards an El Niño state—suggesting that chlorophyll is implicated in maintenance of the Pacific cold tongue. The regions most responsible for this response are located off-equator and correspond to the oligotrophic gyres. Results from a suite of surface chlorophyll perturbation experiments suggest a potential positive feedback between chlorophyll concentration and a non-local coupled response in the fully coupled ocean-atmosphere system.

While the Northern Hemisphere mean surface temperature has clearly warmed over the 20th century due in large part to increasing greenhouse gases, this warming has not been monotonic. The departures from steady warming on multidecadal timescales might be associated in part with radiative forcing, especially solar irradiance, volcanoes, and anthropogenic aerosols. It is also possible that internal oceanic variability explains a part of this variation. We report here on simulations with a climate model in which the Atlantic Ocean is constrained to produce multidecadal fluctuations similar to observations by redistributing heat within the Atlantic, with other oceans left free to adjust to these Atlantic perturbations. The model generates multidecadal variability in Northern Hemisphere mean temperatures similar in phase and magnitude to detrended observations. The results suggest that variability in the Atlantic is a viable explanation for a portion of the multidecadal variability in the Northern Hemisphere mean temperature record.

A coordinated set of global coupled climate model [atmosphere–ocean general circulation model (AOGCM)] experiments for twentieth- and twenty-first-century climate, as well as several climate change commitment and other experiments, was run by 16 modeling groups from 11 countries with 23 models for assessment in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Since the assessment was completed, output from another model has been added to the dataset, so the participation is now 17 groups from 12 countries with 24 models. This effort, as well as the subsequent analysis phase, was organized by the World Climate Research Programme (WCRP) Climate Variability and Predictability (CLIVAR) Working Group on Coupled Models (WGCM) Climate Simulation Panel, and constitutes the third phase of the Coupled Model Intercomparison Project (CMIP3). The dataset is called the WCRP CMIP3 multimodel dataset, and represents the largest and most comprehensive international global coupled climate model experiment and multimodel analysis effort ever attempted. As of March 2007, the Program for Climate Model Diagnostics and Intercomparison (PCMDI) has collected, archived, and served roughly 32 TB of model data. With oversight from the panel, the multimodel data were made openly available from PCMDI for analysis and academic applications. Over 171 TB of data had been downloaded among the more than 1000 registered users to date. Over 200 journal articles, based in part on the dataset, have been published so far. Though initially aimed at the IPCC AR4, this unique and valuable resource will continue to be maintained for at least the next several years. Never before has such an extensive set of climate model simulations been made available to the international climate science community for study. The ready access to the multimodel dataset opens up these types of model analyses to researchers, including students, who previously could not obtain state-of-the-art climate model output, and thus represents a new era in climate change research. As a direct consequence, these ongoing studies are increasing the body of knowledge regarding our understanding of how the climate system currently works, and how it may change in the future.

Some aspects of multidecadal Atlantic climate variability, and its impact on regional and hemispheric scale climate, are reviewed. Observational analyses have documented distinct patterns of Atlantic variability with decadal (8-12 years) and multidecadal (30-80 years) time scales. Numerical models have succeeded in capturing some aspects of this observed variability, but much work remains to understand the mechanisms of the observed variability. The impacts of the variability — particularly on the multidecadal time scale — are striking, including modulation of African and Indian summer monsoon rainfall, summer climate over North America and Europe, and a potential influence on Atlantic hurricane activity. Some of the observed variability, particularly in recent decades, is likely influenced by changing radiative forcings, of both anthropogenic and natural origin. This poses an important challenge for the detection, attribution and prediction of climate change.

Past studies have suggested that increasing atmospheric CO₂ will lead to a substantial reduction of soil moisture during summer in the extratropics. We revisit this topic using a new climate model developed at NOAA's Geophysical Fluid Dynamics Laboratory. The new model has a horizontal resolution of 2.5° longitude by 2.0° latitude, with 24 vertical levels, and has both a diurnal and seasonal cycle of insolation. The model incorporates substantially updated physics relative to previous versions. Results from earlier studies showed, among other things, an increase in wintertime rainfall over most mid-latitude continental regions when CO₂ is doubled, an earlier snowmelt season and onset of springtime evaporation, and a higher ratio of evaporation to precipitation in summer. These factors led to large-scale increases in soil moisture in winter and decreases in summer in mid-latitude in doubled-CO₂ experiments. The new model shows similar results, and the processes discussed above are important in this model as well. In addition, we find that changes in atmospheric circulation play an important role in regional hydrologic changes. Additional experiments have been run to probe the causes of the circulation changes. These simulations show that global scale sea surface temperature increases caused by the CO₂ doubling explain the majority of the atmospheric circulation changes, while positive feedbacks from the land surface have a secondary impact. These results highlight the importance of global scale sea surface temperature changes for future regional hydrology changes.

In this paper, we found that the Atlantic Multidecadal Oscillation (AMO) can contribute to the Pacific Decadal Oscillation (PDO), especially the component of the PDO that is linearly independent of El Niño and the Southern Oscillation (ENSO), i.e. the North Pacific Multidecadal Oscillation (NPMO), and the associated Pacific/North America (PNA) pattern. Using a hybrid version of the GFDL CM2.1 climate model, we show that the AMO provides a source of multidecadal variability to the North Pacific, and needs to be considered along with other forcings for North Pacific climate change. The lagged North Pacific response to the North Atlantic forcing is through atmospheric teleconnections and reinforced by oceanic dynamics and positive air-sea feedback over the North Pacific. The results indicate that a North Pacific regime shift, opposite to the 1976–77 shift, might occur now a decade after the switch of the observed AMO to a positive phase around 1995.

Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory’s climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation.

Episodes of mass coral bleaching around the world in recent decades have been attributed to periods of anomalously warm ocean temperatures. In 2005, the sea surface temperature (SST) anomaly in the tropical North Atlantic that may have contributed to the strong hurricane season caused widespread coral bleaching in the Eastern Caribbean. Here, we use two global climate models   to evaluate the contribution of natural climate variability and anthropogenic forcing to the thermal stress that caused the 2005 coral bleaching event. Historical temperature data and simulations for the 1870–2000 period show that the observed warming in the region is unlikely to be due to unforced climate variability alone. Simulation of background climate variability suggests that anthropogenic warming may have increased the probability of occurrence of significant thermal stress events for corals in this region by an order of magnitude. Under scenarios of future greenhouse gas emissions, mass coral bleaching in the Eastern Caribbean may become a biannual event in 20–30 years. However, if corals and their symbionts can adapt by 1–1.5°C, such mass bleaching events may not begin to recur at potentially harmful intervals until the latter half of the century. The delay could enable more time to alter the path of greenhouse gas emissions, although long-term "committed warming" even after stabilization of atmospheric CO₂ levels may still represent an additional long-term threat to corals.

Following Hurricane Katrina and the parade of storms that affected the conterminous United States in 2004–2005, the apparent recent increase in intense hurricane activity in the Atlantic basin, and the reported increases in recent decades in some hurricane intensity and duration measures in several basins have received considerable attention. An important ongoing avenue of investigation in the climate and meteorology research communities is to determine the relative roles of anthropogenic forcing (i.e., global warming) and natural variability in producing the observed recent increases in hurricane frequency in the Atlantic, as well as the reported increases of tropical cyclone activity measures in several other ocean basins. A survey of the existing literature shows that many types of data have been used to describe hurricane intensity, and not all records are of sufficient length to reliably identify historical trends. Additionally, there are concerns among researchers about possible effects of data inhomogeneities on the reported trends. Much of the current debate has focused on the relative roles of sea-surface temperatures or large-scale potential intensity versus the role of other environmental factors such as vertical wind shear in causing observed changes in hurricane statistics. Significantly more research – from observations, theory, and modeling – is needed to resolve the current debate around global warming and hurricanes.

Extending the meteorological record back in time can offer critical data for assessing tropical cyclone-climate links. While paleotempestology, the study of ancient storms, can provide a more realistic view of past ‘worst case scenarios’, future environmental conditions may have no analogues in the paleoclimate record. The primary value in paleotempestology proxy records arises from their ability to quantify climate–tropical cyclone interactions by sampling tropical cyclone activity during pre-historic periods with a wider range of different climates. New paleotempestology proxies are just beginning to be applied, encouraging new collaboration between the paleo and tropical cyclone dynamics communities. The aim of this paper is to point out some paths toward closer coordination by outlining target needs of the tropical cyclone theory and modelling community and potential contributions of the paleotempestology community. We review recent advances in paleotempestology, summarize the range of types and quality of paleodata generation, and identify future research opportunities for paleotempestology, tropical cyclone dynamics and climate change impacts and attribution communities.

In this study, a new modeling framework for simulating Atlantic hurricane activity is introduced. The model is an 18-km-grid nonhydrostatic regional model, run over observed specified SSTs and nudged toward observed time-varying large-scale atmospheric conditions (Atlantic domain wavenumbers 0–2) derived from the National Centers for Environmental Prediction (NCEP) reanalyses. Using this “perfect large-scale model” approach for 27 recent August–October seasons (1980–2006), it is found that the model successfully reproduces the observed multidecadal increase in numbers of Atlantic hurricanes and several other tropical cyclone (TC) indices over this period. The correlation of simulated versus observed hurricane activity by year varies from 0.87 for basin-wide hurricane counts to 0.41 for U.S. landfalling hurricanes. For tropical storm count, accumulated cyclone energy, and TC power dissipation indices the correlation is 0.75, for major hurricanes the correlation is 0.69, and for U.S. landfalling tropical storms, the correlation is 0.57. The model occasionally simulates hurricanes intensities of up to category 4 (942 mb) in terms of central pressure, although the surface winds (< 47 m s^-1 ) do not exceed category-2 intensity. On interannual time scales, the model reproduces the observed ENSO-Atlantic hurricane covariation reasonably well. Some notable aspects of the highly contrasting 2005 and 2006 seasons are well reproduced, although the simulated activity during the 2006 core season was excessive. The authors conclude that the model appears to be a useful tool for exploring mechanisms of hurricane variability in the Atlantic (e.g., shear versus potential intensity contributions). The model may be capable of making useful simulations/projections of pre-1980 or twentieth-century Atlantic hurricane activity. However, the reliability of these projections will depend on obtaining reliable large-scale atmospheric and SST conditions from sources external to the model.

Base flow recession information is helpful for regional estimation of low-flow characteristics. However, analyses that exploit such information generally require a continuous record of streamf low at the estimation site to characterize base flow recession. Here we propose a simple method for characterizing base flow recession at low-flow partial record stream gauges (i.e., sites with very few streamflow measurements under low-streamflow conditions), and we use that characterization as the basis for a practical new approach to low-flow regression. In a case study the introduction of a base flow recession time constant, estimated from a single pair of strategically timed streamflow measurements, approximately halves the root-mean-square estimation error relative to that of a conventional drainage area regression. Additional streamflow measurements can be used to reduce the error further.

To facilitate estimation of streamflow characteristics at an ungauged site, hydrologists often define a region of influence containing gauged sites hydrologically similar to the estimation site. This region can be defined either in geographic space or in the space of the variables that are used to predict streamflow (predictor variables). These approaches are complementary, and a combination of the two may be superior to either. Here we propose a hybrid region-of-influence (HRoI) regression method that combines the two approaches. The new method was applied with streamflow records from 1,091 gauges in the southeastern United States to estimate the 50-year peak flow (Q50). The HRoI approach yielded lower root-mean-square estimation errors and produced fewer extreme errors than either the predictor-variable or geographic region-of-influence approaches. It is concluded, for Q50 in the study region, that similarity with respect to the basin characteristics considered (area, slope, and annual precipitation) is important, but incomplete, and that the consideration of geographic proximity of stations provides a useful surrogate for characteristics that are not included in the analysis. http://dx.doi.org/10.1061/(ASCE)1084-0699(2007)12:6(585)

The impacts of a freshening of surface waters in high latitudes on the deep, slow, thermohaline circulation have received enormous attention, especially the possibility of a shutdown in the meridional overturning that involves sinking of surface waters in the northern Atlantic Ocean. A recent study by Federov,et al. has drawn attention to the effects of a freshening on the other main component of the oceanic circulation—the swift, shallow, wind-driven circulation that varies on decadal time scales and is closely associated with the ventilated thermocline. That circulation, too, involves meridional overturning, but its variations and critical transitions affect mainly the Tropics. A surface freshening in mid- to high latitudes can deepen the equatorial thermocline to such a degree that temperatures along the equator become as warm in the eastern part of the basin as they are in the west, the tropical zonal sea surface temperature gradient virtually disappears, and permanently warm conditions prevail in the Tropics. In a model that has both the wind driven and thermohaline components of the circulation, which factors determine the relative effects of a freshening on the two components and its impact on climate? Studies with an idealized ocean general circulation model find that vertical diffusivity is one of the critical parameters that affect the relative strength of the two circulation components and hence their response to a freshening. The spatial structure of the freshening and imposed meridional temperature gradients are other important factors.

The impacts of the Indonesian Throughflow (ITF) on the tropical Indo–Pacific climate, particularly on the character of interannual variability, are explored using a coupled general circulation model (CGCM). A pair of CGCM experiments—a control experiment with an open ITF and a perturbation experiment in which the ITF is artificially closed—is integrated for 200 model years, with the 1990 values of trace gases. The closure of the ITF results in changes to the mean oceanic and atmospheric conditions throughout the tropical Indo–Pacific domain as follows: surface temperatures in the eastern tropical Pacific (Indian) Ocean warm (cool), the near-equatorial Pacific (Indian) thermocline flattens (shoals), Indo–Pacific warm-pool precipitation shifts eastward, and there are relaxed trade winds over the tropical Pacific and anomalous surface easterlies over the equatorial Indian Ocean. The character of the oceanic changes is similar to that described by ocean-only model experiments, though the amplitude of many features in the tropical Indo–Pacific is amplified in the CGCM experiments. In addition to the mean-state changes, the character of tropical Indo–Pacific interannual variability is substantially modified. Interannual variability in the equatorial Pacific and the eastern tropical Indian Ocean is substantially intensified by the closure of the ITF. In addition to becoming more energetic, El Niño–Southern Oscillation (ENSO) exhibits a shorter time scale of variability and becomes more skewed toward its warm phase (stronger and more frequent warm events). The structure of warm ENSO events changes; the anomalies of sea surface temperature (SST), precipitation, and surface westerly winds are shifted to the east and the meridional extent of surface westerly anomalies is larger. In the eastern tropical Indian Ocean, the interannual SST variability off the coast of Java–Sumatra is noticeably amplified by the occurrence of much stronger cooling events. Closing the ITF shoals the eastern tropical Indian Ocean thermocline, which results in stronger cooling events through enhanced atmosphere–thermocline coupled feedbacks. Changes to the interannual variability caused by the ITF closure rectify into mean-state changes in tropical Indo–Pacific conditions. The modified Indo–Pacific interannual variability projects onto the mean-state differences between the ITF open and closed scenarios, rectifying into mean-state differences. These results suggest that CGCMs need to reasonably simulate the ITF in order to successfully represent not just the mean climate, but its variations as well.

Two global ocean analyses from 1993 to 2001 have been generated by the Global Modeling and Assimilation Office (GMAO) and Geophysical Fluid Dynamics Laboratory (GFDL), as part of the Ocean Data Assimilation for Seasonal-to-Interannual Prediction (ODASI) consortium efforts. The ocean general circulation models (OGCM) and assimilation methods in the analyses are different, but the forcing and observations are the same as designed for ODASI experiments. Global expendable bathythermograph and Tropical Atmosphere Ocean (TAO) temperature profile observations are assimilated. The GMAO analysis also assimilates synthetic salinity profiles based on climatological T–S relationships from observations (denoted "TS scheme"). The quality of the two ocean analyses in the tropical Pacific is examined here. Questions such as the following are addressed: How do different assimilation methods impact the analyses, including ancillary fields such as salinity and currents? Is there a significant difference in interpretation of the variability from different analyses? How does the treatment of salinity impact the analyses? Both GMAO and GFDL analyses reproduce the time mean and variability of the temperature field compared with assimilated TAO temperature data, taking into account the natural variability and representation errors of the assimilated temperature observations. Surface zonal currents at 15 m from the two analyses generally agree with observed climatology. Zonal current profiles from the analyses capture the intensity and variability of the Equatorial Undercurrent (EUC) displayed in the independent acoustic Doppler current profiler data at three TAO moorings across the equatorial Pacific basin. Compared with independent data from TAO servicing cruises, the results show that 1) temperature errors are reduced below the thermocline in both analyses; 2) salinity errors are considerably reduced below the thermocline in the GMAO analysis; and 3) errors in zonal currents from both analyses are comparable. To discern the impact of the forcing and salinity treatment, a sensitivity study is undertaken with the GMAO assimilation system. Additional analyses are produced with a different forcing dataset, and another scheme to modify the salinity field is tested. This second scheme updates salinity at the time of temperature assimilation based on model T–S relationships (denoted "T scheme"). The results show that both assimilated field (i.e., temperature) and fields that are not directly observed (i.e., salinity and currents) are impacted. Forcing appears to have more impact near the surface (above the core of the EUC), while the salinity treatment is more important below the surface that is directly influenced by forcing. Overall, the TS scheme is more efective than the T scheme in correcting model bias in salinity and improving the current structure. Zonal currents from the GMAO control run where no data are assimilated are as good as the best analysis.

The interannual variability of the Indian Ocean, with particular focus on the Indian Ocean dipole/zonal mode (IODZM), is investigated in a 250-yr simulation of the GFDL coupled global general circulation model (CGCM). The CGCM successfully reproduces many fundamental characteristics of the climate system of the Indian Ocean. The character of the IODZM is explored, as are relationships between positive IODZM and El Niño events, through a composite analysis. The IODZM events in the CGCM grow through feedbacks between heat-content anomalies and SST-related atmospheric anomalies, particularly in the eastern tropical Indian Ocean. The composite IODZM events that co-occur with El Niño have stronger anomalies and a sharper east–west SSTA contrast than those that occur without El Niño. IODZM events, whether or not they occur with El Niño, are preceded by distinctive Indo-Pacific warm pool anomaly patterns in boreal spring: in the central Indian Ocean easterly surface winds, and in the western equatorial Pacific an eastward shift of deep convection, westerly surface winds, and warm sea surface temperature. However, delayed onsets of the anomaly patterns (e.g., boreal summer) are often not followed by IODZM events. The same anomaly patterns often precede El Niño, suggesting that the warm pool conditions favorable for both IODZM and El Niño are similar. Given that IODZM events can occur without El Niño, it is proposed that the observed IODZM–El Niño relation arises because the IODZM and El Niño are both large-scale phenomena in which variations of the Indo-Pacific warm pool deep convection plays a central role. Yet each phenomenon has its own dynamics and life cycle, allowing each to develop without the other. The CGCM integration also shows substantial decadal modulation of the occurrence of IODZM events, which is found to be not in phase with that of El Niño events. There is a weak, though significant, negative correlation between the two. Moreover, the statistical relationship between the IODZM and El Niño displays strong decadal variability.

A fully coupled data assimilation (CDA) system, consisting of an ensemble filter applied to the Geophysical Fluid Dynamics Laboratory’s global fully coupled climate model (CM2), has been developed to facilitate the detection and prediction of seasonal-to-multidecadal climate variability and climate trends. The assimilation provides a self-consistent, temporally continuous estimate of the coupled model state and its uncertainty, in the form of discrete ensemble members, which can be used directly to initialize probabilistic climate forecasts. Here, the CDA is evaluated using a series of perfect model experiments, in which a particular twentieth-century simulation—with temporally varying greenhouse gas and natural aerosol radiative forcings—serves as a “truth” from which observations are drawn, according to the actual ocean observing network for the twentieth century. These observations are then assimilated into a coupled model ensemble that is subjected only to preindustrial forcings. By examining how well this analysis ensemble reproduces the “truth,” the skill of the analysis system in recovering anthropogenically forced trends and natural climate variability is assessed, given the historical observing network. The assimilation successfully reconstructs the twentieth-century ocean heat content variability and trends in most locations. The experiments highlight the importance of maintaining key physical relationships among model fields, which are associated with water masses in the ocean and geostrophy in the atmosphere. For example, when only oceanic temperatures are assimilated, the ocean analysis is greatly improved by incorporating the temperature–salinity covariance provided by the analysis ensemble. Interestingly, wind observations are more helpful than atmospheric temperature observations for constructing the structure of the tropical atmosphere; the opposite holds for the extratropical atmosphere. The experiments indicate that the Atlantic meridional overturning circulation is difficult to constrain using the twentieth-century observational network, but there is hope that additional observations—including those from the newly deployed Argo profiles—may lessen this problem in the twenty-first century. The challenges for data assimilation of model systematic biases and evolving observing systems are discussed.

A consistent weakening and poleward expansion of the Hadley circulation is diagnosed in the climate change simulations of the IPCC AR4 project. Associated with this widening is a poleward expansion of the subtropical dry zone. Simple scaling analysis supports the notion that the poleward extent of the Hadley cell is set by the location where the thermally driven jet first becomes baroclinically unstable. The expansion of the Hadley cell is caused by an increase in the subtropical static stability, which pushes poleward the baroclinic instability zone and hence the outer boundary of the Hadley cell.

How anthropogenic climate change will affect hydroclimate in the arid regions of southwestern North America has implications for the allocation of water resources and the course of regional development. Here we show that there is a broad consensus among climate models that this region will dry in the 21st century and that the transition to a more arid climate should already be under way. If these models are correct, the levels of aridity of the recent multiyear drought or the Dust Bowl and the 1950s droughts will become the new climatology of the American Southwest within a time frame of years to decades.

To help understand possible impacts of anthropogenic greenhouse warming on hurricane activity, we assess model-projected changes in large-scale environmental factors tied to variations in hurricane statistics. This study focuses on vertical wind shear (Vs) over the tropical Atlantic during hurricane season, the increase of which has been historically associated with diminished hurricane activity and intensity. A suite of state-of-the-art global climate model experiments is used to project changes in Vs over the 21st century. Substantial increases in tropical Atlantic and East Pacific shear are robust features of these experiments, and are shown to be connected to the model-projected decrease in the Pacific Walker circulation. The relative changes in shear are found to be comparable to those of other large-scale environmental parameters associated with Atlantic hurricane activity. The influence of these Vs changes should be incorporated into projections of long-term hurricane activity.

An integrated in situ Indian Ocean observing system (IndOOS) is simulated using a high-resolution ocean general circulation model (OGCM) with daily mean forcing, including an estimate of subdaily oceanic variability derived from observations. The inclusion of subdaily noise is fundamental to the results; in the mixed layer it is parameterized as Gaussian noise with an rms of 0.1°C; below the mixed layer a Gaussian interface displacement with an rms of 7 m is used. The focus of this assessment is on the ability of an IndOOS—comprising a 3° × 3° Argo profiling float array, a series of frequently repeated XBT lines, and an array of moored buoys—to observe the interannual and subseasonal variability of subsurface Indian Ocean temperature. The simulated IndOOS captures much of the OGCM interannual subsurface temperature variability. A fully deployed Argo array with 10-day sampling interval is able to capture a significant part of the Indian Ocean interannual temperature variability; a 5-day sampling interval degrades its ability to capture variability. The proposed moored buoy array and frequently repeated XBT lines provide complementary information in key regions, particularly the Java/Sumatra and Somali upwelling and equatorial regions. Since the subdaily noise is of the same order as the subseasonal signal and since much of the variability is submonthly, a 5-day sampling interval does not drastically enhance the ability of Argo to capture the OGCM subseasonal variability. However, as sampling intervals are decreased, there is enhanced divergence of the Argo floats, diminished ability to quality control data, and a decreased lifetime of the floats; these factors argue against attempting to resolve subseasonal variability with Argo by shortening the sampling interval. A moored array is essential to capturing the subseasonal and near-equatorial variability in the model, and the proposed moored buoy locations span the region of strong subseasonal variability. On the whole, the proposed IndOOS significantly enhances the ability to capture both interannual and subseasonal variability in the Indian Ocean.

This study examines the response of the tropical atmospheric and oceanic circulation to increasing greenhouse gases using a coordinated set of twenty-first-century climate model experiments performed for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The strength of the atmospheric overturning circulation decreases as the climate warms in all IPCC AR4 models, in a manner consistent with the thermodynamic scaling arguments of Held and Soden. The weakening occurs preferentially in the zonally asymmetric (i.e., Walker) rather than zonal-mean (i.e., Hadley) component of the tropical circulation and is shown to induce substantial changes to the thermal structure and circulation of the tropical oceans. Evidence suggests that the overall circulation weakens by decreasing the frequency of strong updrafts and increasing the frequency of weak updrafts, although the robustness of this behavior across all models cannot be confirmed because of the lack of data. As the climate warms, changes in both the atmospheric and ocean circulation over the tropical Pacific Ocean resemble “El Niño–like” conditions; however, the mechanisms are shown to be distinct from those of El Niño and are reproduced in both mixed layer and full ocean dynamics coupled climate models. The character of the Indian Ocean response to global warming resembles that of Indian Ocean dipole mode events. The consensus of model results presented here is also consistent with recently detected changes in sea level pressure since the mid–nineteenth century.

The response of tropical cyclone activity to global warming is widely debated. It is often assumed that warmer sea surface temperatures provide a more favourable environment for the development and intensification of tropical cyclones, but cyclone genesis and intensity are also affected by the vertical thermodynamic properties of the atmosphere. Here we use climate models and observational reconstructions to explore the relationship between changes in sea surface temperature and tropical cyclone 'potential intensity'—a measure that provides an upper bound on cyclone intensity and can also reflect the likelihood of cyclone development. We find that changes in local sea surface temperature are inadequate for characterizing even the sign of changes in potential intensity, but that long-term changes in potential intensity are closely related to the regional structure of warming; regions that warm more than the tropical average are characterized by increased potential intensity, and vice versa. We use this relationship to reconstruct changes in potential intensity over the twentieth century from observational reconstructions of sea surface temperature. We find that, even though tropical Atlantic sea surface temperatures are currently at a historical high, Atlantic potential intensity probably peaked in the 1930s and 1950s, and recent values are near the historical average. Our results indicate that—per unit local sea surface temperature change—the response of tropical cyclone activity to natural climate variations, which tend to involve localized changes in sea surface temperature, may be larger than the response to the more uniform patterns of greenhouse-gas-induced warming.

Westerly wind bursts (WWBs) in the equatorial Pacific are known to play a significant role in the development of El Niño events. They have typically been treated as a purely stochastic external forcing of ENSO. Recent observations, however, show that WWB characteristics depend upon the large-scale SST field. The consequences of such a WWB modulation by SST are examined using an ocean general circulation model coupled to a statistical atmosphere model (i.e., a hybrid coupled model). An explicit WWB component is added to the model with guidance from a 23-yr observational record. The WWB parameterization scheme is constructed such that the likelihood of WWB occurrence increases as the western Pacific warm pool extends: a “semistochastic” formulation, which has both deterministic and stochastic elements. The location of the WWBs is parameterized to migrate with the edge of the warm pool. It is found that modulation of WWBs by SST strongly affects the characteristics of ENSO. In particular, coupled feedbacks between SST and WWBs may be sufficient to transfer the system from a damped regime to one with self-sustained oscillations. Modulated WWBs also play a role in the irregular timing of warm episodes and the asymmetry in the size of warm and cold events in this ENSO model. Parameterizing the modulation of WWBs by an increase of the linear air–sea coupling coefficient seems to miss important dynamical processes, and a purely stochastic representation of WWBs elicits only a weak ocean response. Based upon this evidence, it is proposed that WWBs may need to be treated as an internal part of the coupled ENSO system, and that the detailed knowledge of wind burst dynamics may be necessary to explain the characteristics of ENSO.

Since the upper ocean takes up much of the heat added to the earth system by anthropogenic global warming, one would expect that global warming would lead to an increase in stratification and a decrease in the ventilation of the ocean interior. However, multiple simulations in global coupled climate models using an ideal age tracer which is set to zero in the mixed layer and ages at 1 yr/yr outside this layer show that the intermediate depths in the low latitudes, Northwest Atlantic, and parts of the Arctic Ocean become younger under global warming. This paper reconciles these apparently contradictory trends, showing that the decreases result from changes in the relative contributions of old deep waters and younger surface waters. Implications for the tropical oxygen minimum zones, which play a critical role in global biogeochemical cycling are considered in detail.

In this paper for the first time I show that the multidecadal variations of observed tropical North Atlantic (TNA) sea surface temperature (SST) are strongly anticorrelated with those of the observed TNA subsurface ocean temperature, with long-term trends removed. I further show that the anticorrelated change between the TNA surface and subsurface temperature is a distinctive signature of the Atlantic meridional overturning circulation (AMOC) variations, using water-hosing experiments with the GFDL state-of-art coupled climate model (CM2.1). External radiative forced simulations with the same model do not provide a significant relationship between the TNA surface and subsurface temperature variations. The observed detrended multidecadal TNA subsurface temperature anomaly may be taken as a proxy for the AMOC variability. Various mechanisms proposed for the multidecadal TNA SST variations, which are crucial for multidecadal variations of Atlantic hurricane activities, should take into account the observed anticorrelation between the TNA surface and subsurface temperature variations.

Paleoclimate records from glacial Indian and Pacific oceans sediments document millennial-scale fluctuations of subsurface dissolved oxygen levels and denitrification coherent with North Atlantic temperature oscillations. Yet the mechanism of this teleconnection between the remote ocean basins remains elusive. Here we present model simulations of the oxygen and nitrogen cycles that explain how changes in deepwater subduction in the North Atlantic can cause large and synchronous variations of oxygen minimum zones throughout the Northern Hemisphere of the Indian and Pacific oceans, consistent with the paleoclimate records. Cold periods in the North Atlantic are associated with reduced nutrient delivery to the upper Indo-Pacific oceans, thereby decreasing productivity. Reduced export production diminishes subsurface respiration of organic matter leading to higher oxygen concentrations and less denitrification. This effect of reduced oxygen consumption dominates at low latitudes. At high latitudes in the Southern Ocean and North Pacific, increased mixed layer depths and steepening of isopycnals improve ocean ventilation and oxygen supply to the subsurface. Atmospheric teleconnections through changes in wind-driven ocean circulation modify this basin-scale pattern regionally. These results suggest that changes in the Atlantic Ocean circulation, similar to those projected by climate models to possibly occur in the centuries to come because of anthropogenic climate warming, can have large effects on marine ecosystems and biogeochemical cycles even in remote areas.

The mechanisms affecting the path of the depth-integrated North Atlantic western boundary current and the formation of the northern recirculation gyre are investigated using a hierarchy of models, namely, a robust diagnostic model, a prognostic model using a global 1° ocean general circulation model coupled to a two-dimensional atmospheric energy balance model with a hydrological cycle, a simple numerical barotropic model, and an analytic model. The results herein suggest that the path of this boundary current and the formation of the northern recirculation gyre are sensitive to both the magnitude of lateral viscosity and the strength of the deep western boundary current (DWBC). In particular, it is shown that bottom vortex stretching induced by a downslope DWBC near the south of the Grand Banks leads to the formation of a cyclonic northern recirulation gyre and keeps the path of the depth-integrated western boundary current downstream of Cape Hatteras separated from the North American coast. Both south of the Grand Banks and at the crossover region of the DWBC and Gulf Stream, the downslope DWBC induces strong bottom downwelling over the steep continental slope, and the magnitude of the bottom downwelling is locally stronger than surface Ekman pumping velocity, providing strong positive vorticity through bottom vortex stretching effects. The bottom vortex-stretching effect is also present in an extensive area in the North Atlantic, and the contribution to the North Atlantic subpolar and subtropical gyres is on the same order as the local surface wind stress curl. Analytic solutions show that the bottom vortex stretching is important near the western boundary only when the continental slope is wider than the Munk frictional layer scale.