Couldrey, Matthew P., Jonathan M Gregory, Xiao Dong, Oluwayemi Garuba, Helmuth Haak, Aixue Hu, and William J Hurlin, et al., April 2023: Greenhouse-gas forced changes in the Atlantic meridional overturning circulation and related worldwide sea-level change. Climate Dynamics, 60, DOI:10.1007/s00382-022-06386-y2003-2039. Abstract
The effect of anthropogenic climate change in the ocean is challenging to project because atmosphere-ocean general circulation models (AOGCMs) respond differently to forcing. This study focuses on changes in the Atlantic Meridional Overturning Circulation (AMOC), ocean heat content (ΔOHC), and the spatial pattern of ocean dynamic sea level (Δζ). We analyse experiments following the FAFMIP protocol, in which AOGCMs are forced at the ocean surface with standardised heat, freshwater and momentum flux perturbations, typical of those produced by doubling CO2. Using two new heat-flux-forced experiments, we find that the AMOC weakening is mainly caused by and linearly related to the North Atlantic heat flux perturbation, and further weakened by a positive coupled heat flux feedback. The quantitative relationships are model-dependent, but few models show significant AMOC change due to freshwater or momentum forcing, or to heat flux forcing outside the North Atlantic. AMOC decline causes warming at the South Atlantic-Southern Ocean interface. It does not strongly affect the global-mean vertical distribution of ΔOHC, which is dominated by the Southern Ocean. AMOC decline strongly affects Δζ in the North Atlantic, with smaller effects in the Southern Ocean and North Pacific. The ensemble-mean Δζ and ΔOHC patterns are mostly attributable to the heat added by the flux perturbation, with smaller effects from ocean heat and salinity redistribution. The ensemble spread, on the other hand, is largely due to redistribution, with pronounced disagreement among the AOGCMs.
Because of a spring predictability barrier, the seasonal forecast skill of Arctic summer sea ice is limited by the availability of melt-season sea ice thickness (SIT) observations. The first year-round SIT observations, retrieved from CryoSat-2 from 2011 to 2020, are assimilated into the GFDL ocean–sea ice model. The model's SIT anomaly field is brought into significantly better agreement with the observations, particularly in the Central Arctic. Although the short observational period makes forecast assessment challenging, we find that the addition of May–August SIT assimilation improves September local sea ice concentration (SIC) and extent forecasts similarly to SIC-only assimilation. Although most regional forecasts are improved by SIT assimilation, the Chukchi Sea forecasts are degraded. This degradation is likely due to the introduction of negative correlations between September SIC and earlier SIT introduced by SIT assimilation, contrary to the increased correlations found in other regions.
We use two coupled climate models, GFDL-CM4 and GFDL-ESM4, to investigate the physical response of the Southern Ocean to changes in surface wind stress, Antarctic meltwater, and the combined forcing of the two in a pre-industrial control simulation. The meltwater cools the ocean surface in all regions except the Weddell Sea, where the wind stress warms the near-surface layer. The limited sensitivity of the Weddell Sea surface layer to the meltwater is due to the spatial distribution of the meltwater fluxes, regional bathymetry, and large-scale circulation patterns. The meltwater forcing dominates the Antarctic shelf response and the models yield strikingly different responses along West Antarctica. The disagreement is attributable to the mean-state representation and meltwater-driven acceleration of the Antarctic Slope Current (ASC). In CM4, the meltwater is efficiently trapped on the shelf by a well resolved, strong, and accelerating ASC which isolates the West Antarctic shelf from warm offshore waters, leading to strong subsurface cooling. In ESM4, a weaker and diffuse ASC allows more meltwater to escape to the open ocean, the West Antarctic shelf does not become isolated, and instead strong subsurface warming occurs. The CM4 results suggest a possible negative feedback mechanism that acts to limit future melting, while the ESM4 results suggest a possible positive feedback mechanism that acts to accelerate melt. Our results demonstrate the strong influence the ASC has on governing changes along the shelf, highlighting the importance of coupling interactive ice sheet models to ocean models that can resolve these dynamical processes.
Research over the past decade has demonstrated that dynamical forecast systems can skillfully predict pan-Arctic sea ice extent (SIE) on the seasonal time scale; however, there have been fewer assessments of prediction skill on user-relevant spatial scales. In this work, we evaluate regional Arctic SIE predictions made with the Forecast-Oriented Low Ocean Resolution (FLOR) and Seamless System for Prediction and Earth System Research (SPEAR_MED) dynamical seasonal forecast systems developed at the NOAA/Geophysical Fluid Dynamics Laboratory. Compared to FLOR, we find that the recently developed SPEAR_MED system displays improved skill in predicting regional detrended SIE anomalies, partially owing to improvements in sea ice concentration (SIC) and thickness (SIT) initial conditions. In both systems, winter SIE is skillfully predicted up to 11 months in advance, whereas summer minimum SIE predictions are limited by the Arctic spring predictability barrier, with typical skill horizons of roughly 4 months. We construct a parsimonious set of simple statistical prediction models to investigate the mechanisms of sea ice predictability in these systems. Three distinct predictability regimes are identified: a summer regime dominated by SIE and SIT anomaly persistence; a winter regime dominated by SIE and upper-ocean heat content (uOHC) anomaly persistence; and a combined regime in the Chukchi Sea, characterized by a trade-off between uOHC-based and SIT-based predictability that occurs as the sea ice edge position evolves seasonally. The combination of regional SIE, SIT, and uOHC predictors is able to reproduce the SIE skill of the dynamical models in nearly all regions, suggesting that these statistical predictors provide a stringent skill benchmark for assessing seasonal sea ice prediction systems.
The continuing decline of the summertime sea ice cover has reduced the sea ice path that must be traversed to Arctic destinations and through the Arctic between the Atlantic and Pacific Oceans, stimulating interest in trans–Arctic Ocean routes. Seasonal prediction of the sea ice cover along these routes could support the increasing summertime ship traffic taking advantage of recent low ice conditions. We introduce the minimum Arctic sea ice path (MIP) between Atlantic and Pacific Oceans as a shipping-relevant metric that is amenable to multidecadal hindcast evaluation. We show, using 1992–2017 retrospective predictions, that bias correction is necessary for the GFDL Seamless System for Prediction and Earth System Research (SPEAR) forecast system to improve upon damped persistence seasonal forecasts of summertime daily MIP between the Atlantic and Pacific Oceans both east and west of Greenland, corresponding roughly to the Northeast and Northwest Passages. Without bias correction, only the Northwest Passage MIP forecasts have lower error than a damped persistence forecast. Using the forecast ensemble spread to estimate a lower bound on forecast error, we find large opportunities for forecast error reduction, especially at lead times of less than 2 months. Most of the potential improvement remains after linear removal of climatological and trend biases, suggesting that significant error reduction might come from improved initialization and simulation of subannual variability. Using a different passive microwave sea ice dataset for calculating error than was used for data assimilation increases the raw forecast errors but not the trend anomaly forecast errors.
The current GFDL seasonal prediction system, the Seamless System for Prediction and Earth System Research (SPEAR), has shown skillful prediction of Arctic sea ice extent with atmosphere and ocean constrained by observations. In this study we present improvements in subseasonal and seasonal predictions of Arctic sea ice by directly assimilating sea ice observations. The sea ice initial conditions from a data assimilation (DA) system that assimilates satellite sea ice concentration (SIC) observations are used to produce a set of reforecast experiments (IceDA) starting from the first day of each month from 1992 to 2017. Our evaluation of daily sea ice extent prediction skill concludes that the SPEAR system generally outperforms the anomaly persistence forecast at lead times beyond 1 month. We primarily focus our analysis on daily gridcell-level sea ice fields. SIC DA improves prediction skill of SIC forecasts prominently in the June-, July-, August-, and September-initialized reforecasts. We evaluate two additional user-oriented metrics: the ice-free probability (IFP) and ice-free date (IFD). IFP is the probability of a grid cell experiencing ice-free conditions in a given year, and IFD is the first date on which a grid cell is ice free. A combined analysis of IFP and IFD demonstrates that the SPEAR model can make skillful predictions of local ice melt as early as May, with modest improvements from SIC DA.
Compared to the Arctic, seasonal predictions of Antarctic sea ice have received relatively little attention. In this work, we utilize three coupled dynamical prediction systems developed at the Geophysical Fluid Dynamics Laboratory to assess the seasonal prediction skill and predictability of Antarctic sea ice. These systems, based on the FLOR, SPEAR_LO, and SPEAR_MED dynamical models, differ in their coupled model components, initialization techniques, atmospheric resolution, and model biases. Using suites of retrospective initialized seasonal predictions spanning 1992–2018, we investigate the role of these factors in determining Antarctic sea ice prediction skill and examine the mechanisms of regional sea ice predictability. We find that each system is capable of skillfully predicting regional Antarctic sea ice extent (SIE) with skill that exceeds a persistence forecast. Winter SIE is skillfully predicted 11 months in advance in the Weddell, Amundsen/Bellingshausen, Indian, and west Pacific sectors, whereas winter skill is notably lower in the Ross sector. Zonally advected upper-ocean heat content anomalies are found to provide the crucial source of prediction skill for the winter sea ice edge position. The recently developed SPEAR systems are more skillful than FLOR for summer sea ice predictions, owing to improvements in sea ice concentration and sea ice thickness initialization. Summer Weddell SIE is skillfully predicted up to 9 months in advance in SPEAR_MED, due to the persistence and drift of initialized sea ice thickness anomalies from the previous winter. Overall, these results suggest a promising potential for providing operational Antarctic sea ice predictions on seasonal time scales.
The current GFDL seasonal prediction system achieved retrospective sea ice extent (SIE) skill without direct sea ice data assimilation. Here we develop sea ice data assimilation, shown to be a key source of skill for seasonal sea ice predictions, in GFDL’s next-generation prediction system, the Seamless System for Prediction and Earth System Research (SPEAR). Satellite sea ice concentration (SIC) observations are assimilated into the GFDL Sea Ice Simulator version 2 (SIS2) using the ensemble adjustment Kalman filter (EAKF). Sea ice physics is perturbed to form an ensemble of ice–ocean members with atmospheric forcing from the JRA-55 reanalysis. Assimilation is performed every 5 days from 1982 to 2017 and the evaluation is conducted at pan-Arctic and regional scales over the same period. To mitigate an assimilation overshoot problem and improve the analysis, sea surface temperatures (SSTs) are restored to the daily Optimum Interpolation Sea Surface Temperature version 2 (OISSTv2). The combination of SIC assimilation and SST restoring reduces analysis errors to the observational error level (~10%) from up to 3 times larger than this (~30%) in the free-running model. Sensitivity experiments show that the choice of assimilation localization half-width (190 km) is near optimal and that SIC analysis errors can be further reduced slightly either by reducing the observational error or by increasing the assimilation frequency from every 5 days to daily. A lagged-correlation analysis suggests substantial prediction skill improvements from SIC initialization at lead times of less than 2 months.
We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous‐generation coupled ESM2‐carbon and CM3‐chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land‐atmosphere‐ocean cycling of CO2, dust and iron, and interactive ocean‐atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.
GFDL's new CM4.0 climate model has high transient and equilibrium climate sensitivities near the middle of the upper half of CMIP5 models. The CMIP5 models have been criticized for excessive sensitivity based on observations of present‐day warming and heat uptake and estimates of radiative forcing. An ensemble of historical simulations with CM4.0 produces warming and heat uptake that are consistent with these observations under forcing that is at the middle of the assessed distribution. Energy budget‐based methods for estimating sensitivities based on these quantities underestimate CM4.0's sensitivities when applied to its historical simulations. However, we argue using a simple attribution procedure that CM4.0's warming evolution indicates excessive transient sensitivity to greenhouse gases. This excessive sensitivity is offset prior to recent decades by excessive response to aerosol and land use changes.
We describe GFDL's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the pre‐industrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top‐of‐atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño‐Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasi‐periodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.
Meltwater from the Antarctic Ice Sheet is projected to cause up to one metre of sea-level rise by 2100 under the highest greenhouse gas concentration trajectory (RCP8.5) considered by the Intergovernmental Panel on Climate Change (IPCC). However, the effects of meltwater from the ice sheets and ice shelves of Antarctica are not included in the widely used CMIP5 climate models, which introduces bias into IPCC climate projections. Here we assess a large ensemble simulation of the CMIP5 model ‘GFDL ESM2M’ that accounts for RCP8.5-projected Antarctic Ice Sheet meltwater. We find that, relative to the standard RCP8.5 scenario, accounting for meltwater delays the exceedance of the maximum global-mean atmospheric warming targets of 1.5 and 2 degrees Celsius by more than a decade, enhances drying of the Southern Hemisphere and reduces drying of the Northern Hemisphere, increases the formation of Antarctic sea ice (consistent with recent observations of increasing Antarctic sea-ice area) and warms the subsurface ocean around the Antarctic coast. Moreover, the meltwater-induced subsurface ocean warming could lead to further ice-sheet and ice-shelf melting through a positive feedback mechanism, highlighting the importance of including meltwater effects in simulations of future climate.
Day, J J., Steffen Tietsche, Matthew Collins, William J Hurlin, Masao Ishii, S P E Keeley, D Matei, and Rym Msadek, et al., June 2016: The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set. Geoscientific Model Development, DOI:10.5194/gmd-9-2255-2016. Abstract
Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other
Gregory, Jonathan M., N Bouttes-Mauhourat, Stephen M Griffies, Helmuth Haak, William J Hurlin, J H Jungclaus, M Kelley, W G Lee, J Marshall, Anastasia Romanou, Oleg A Saenko, Detlef Stammer, and Michael Winton, November 2016: The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) contribution to CMIP6: Investigation of sea-level and ocean climate change in response to CO2 forcing. Geoscientific Model Development, 9(11), DOI:10.5194/gmd-9-3993-2016. Abstract
The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) aims to investigate the spread in simulations of sea-level and ocean climate change in response to CO2 forcing by atmosphere-ocean general circulation models (AOGCMs). It is particularly motivated by the uncertainties in projections of ocean heat uptake, global-mean sea-level rise due to thermal expansion and the geographical patterns of sea-level change due to ocean density and circulation change. FAFMIP has three tier-1 experiments, in which prescribed surface flux perturbations of momentum, heat and freshwater respectively are applied to the ocean in separate AOGCM simulations. All other conditions are as in the pre-industrial control. The prescribed fields are typical of pattern and magnitude of changes in these fluxes projected by AOGCMs for doubled CO2 concentration. Five groups have tested the experimental design with existing AOGCMs. Their results show diversity in the pattern and magnitude of changes, with some common qualitative features. Heat and water flux perturbation cause the dipole in sea-level change in the North Atlantic, while momentum and heat flux perturbation cause the gradient across the Antarctic Circumpolar Current. The Atlantic Meridional Overturning Circulation (AMOC) declines in response to the heat flux perturbation, and there is a strong positive feedback on this effect due to the consequent cooling of sea surface temperature in the North Atlantic, which enhances the local heat input to the ocean. The momentum and water flux perturbations do not substantially affect the AMOC. Heat is taken up largely as a passive tracer in the Southern Ocean, which is the region of greatest heat input, but elsewhere heat is actively redistributed towards lower latitude. Future analysis of these and other phenomena with the wider range of CMIP6 FAFMIP AOGCMs will benefit from new diagnostics of temperature and salinity tendencies, which will enable investigation of the model spread in behaviour in terms of physical processes as formulated in the models.
Tietsche, Steffen, J J Day, Virginie Guemas, William J Hurlin, S P E Keeley, D Matei, and Rym Msadek, et al., February 2014: Seasonal to interannual Arctic sea-ice predictability in current GCMs. Geophysical Research Letters, 41(3), DOI:10.1002/2013GL058755. Abstract
We establish the first inter-model comparison of seasonal to interannual predictability of present-day Arctic climate by performing coordinated sets of idealized ensemble predictions with four state-of-the-art global climate models. For Arctic sea-ice extent and volume, there is potential predictive skill for lead times of up to three years, and potential prediction errors have similar growth rates and magnitudes across the models. Spatial patterns of potential prediction errors differ substantially between the models, but some features are robust. Sea-ice concentration errors are largest in the marginal ice zone, and in winter they are almost zero away from the ice edge. Sea-ice thickness errors are amplified along the coasts of the Arctic Ocean, an effect that is dominated by sea-ice advection. These results give an upper bound on the ability of current global climate models to predict important aspects of Arctic climate.
We investigate the influence of ocean component resolution on simulation of climate sensitivity using variants of the GFDL CM2.5 climate model incorporating eddy-resolving (1/10o) and eddy-parameterizing (1o) ocean resolutions. Two parameterization configurations of the coarse-resolution model are used yielding a three-model suite with significant variation in the transient climate response (TCR). The variation of TCR in this suite and in an enhanced group of 10 GFDL models is found to be strongly associated with the control climate Atlantic meridional overturning circulation (AMOC) magnitude and its decline under forcing. We find it is the AMOC behavior rather than resolution per se that accounts for most of the TCR differences. A smaller difference in TCR stems from the eddy-resolving model having more Southern Ocean surface warming than the coarse models.
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.
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.
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.
We study the reaction of a global ocean–sea ice model to an increase of fresh water input into the northern North Atlantic under different surface boundary conditions, ranging from simple restoring of surface salinity to the use of an energy balance model (EBM) for the atmosphere. The anomalous fresh water flux is distributed around Greenland, reflecting increased melting of the Greenland ice sheet and increasing fresh water export from the Arctic Ocean. Depending on the type of surface boundary condition, the large circulation reacts with a slow-down of overturning and gyre circulations. Restoring of the total or mean surface salinity prevents a large scale redistribution of the salinity field that is apparent under mixed boundary conditions and with the EBM. The control run under mixed boundary conditions exhibits large and unrealistic oscillations of the meridional overturning. Although the reaction to the fresh water flux anomaly is similar to the response with the EBM, mixed boundary conditions must thus be considered unreliable. With the EBM, the waters in the deep western boundary current initially become saltier and a new fresh water mass forms in the north-eastern North Atlantic in response to the fresh water flux anomaly around Greenland. After an accumulation period of several decades duration, this new North East Atlantic Intermediate Water spreads towards the western boundary and opens a new southward pathway at intermediate depths along the western boundary for the fresh waters of high northern latitudes.
The current generation of coupled climate models run at the Geophysical Fluid Dynamics Laboratory (GFDL) as part of the Climate Change Science Program contains ocean components that differ in almost every respect from those contained in previous generations of GFDL climate models. This paper summarizes the new physical features of the models and examines the simulations that they produce. Of the two new coupled climate model versions 2.1 (CM2.1) and 2.0 (CM2.0), the CM2.1 model represents a major improvement over CM2.0 in most of the major oceanic features examined, with strikingly lower drifts in hydrographic fields such as temperature and salinity, more realistic ventilation of the deep ocean, and currents that are closer to their observed values. Regional analysis of the differences between the models highlights the importance of wind stress in determining the circulation, particularly in the Southern Ocean. At present, major errors in both models are associated with Northern Hemisphere Mode Waters and outflows from overflows, particularly the Mediterranean Sea and Red Sea.
Stouffer, Ronald J., Keith W Dixon, Michael J Spelman, William J Hurlin, Jianjun Yin, Jonathan M Gregory, A J Weaver, M Eby, G M Flato, D Y Robitaille, H Hasumi, A Oka, Aixue Hu, J H Jungclaus, I V Kamenkovich, A Levermann, M Montoya, S Murakami, S Nawrath, W R Peltier, G Vettoretti, A P Sokolov, and S L Weber, 2006: Investigating the Causes of the Response of the Thermohaline Circulation to Past and Future Climate Changes. Journal of Climate, 19(8), DOI:10.1175/JCLI3689.11. Abstract
The Atlantic thermohaline circulation (THC) is an important part of the earth's climate system. Previous research has shown large uncertainties in simulating future changes in this critical system. The simulated THC response to idealized freshwater perturbations and the associated climate changes have been intercompared as an activity of World Climate Research Program (WCRP) Coupled Model Intercomparison Project/Paleo-Modeling Intercomparison Project (CMIP/PMIP) committees. This intercomparison among models ranging from the earth system models of intermediate complexity (EMICs) to the fully coupled atmosphere–ocean general circulation models (AOGCMs) seeks to document and improve understanding of the causes of the wide variations in the modeled THC response. The robustness of particular simulation features has been evaluated across the model results. In response to 0.1-Sv (1 Sv 106 m3 s−1) freshwater input in the northern North Atlantic, the multimodel ensemble mean THC weakens by 30% after 100 yr. All models simulate some weakening of the THC, but no model simulates a complete shutdown of the THC. The multimodel ensemble indicates that the surface air temperature could present a complex anomaly pattern with cooling south of Greenland and warming over the Barents and Nordic Seas. The Atlantic ITCZ tends to shift southward. In response to 1.0-Sv freshwater input, the THC switches off rapidly in all model simulations. A large cooling occurs over the North Atlantic. The annual mean Atlantic ITCZ moves into the Southern Hemisphere. Models disagree in terms of the reversibility of the THC after its shutdown. In general, the EMICs and AOGCMs obtain similar THC responses and climate changes with more pronounced and sharper patterns in the AOGCMs.
Philander, S G., and William J Hurlin, 1988: The heat budget of the tropical Pacific Ocean in a simulation of the 1982-83 El Niño. Journal of Physical Oceanography, 18(6), 926-931. Abstract PDF
The heat budget of a model that realistically simulates the 1982-83 El Niño indicates that the enormous changes in the winds during that event failed to disrupt the usual seasonal variations in meridional heat transport. Cross-equatorial transport towards the winter hemisphere continued as in a regular seasonal cycle. The key factor was the continued seasonal migrations of the ITCZ during El Niño. In early 1983 the ITCZ strayed farther south than usual and remained near the equator longer than usual thus causing an increase in the northward heat transport. This, together with an increase in the evaporative heat loss because of higher sea surface temperatures, resulted in a large loss of heat from the band of latitudes approximately 12°N - 12°S during El Niño.
A general circulation model of the tropical Pacific Ocean, which realistically simulates El Niño of 1982-83, has been used to determine how different initial conditions affect the model. Given arbitrary initial conditions (not in equilibrium with the wind) the model takes almost a year to return to a state in which the currents and density gradients are in equilibrium with the winds. Errors in the absolute value of the temperature persist far longer, however, indicating that accurate density data are essential initial conditions. If the correct density field is specified initially, but no information is provided about the currents, then the model recovers the currents within an inertial period, except for the eastern equatorial region. That region is affected by equatorial Kelvin waves which are excited because the model is initially in an unbalanced state. The currents associated with these waves are relatively modest and do not affect the density field significantly. Because of the large zonal scale of the thermal field in the tropical Pacific, three or four high resolution meridional density sections appear adequate for the initialization of the model. This result, however, takes into account neither the energetic waves, with a scale of 1000 km, that are associated with instabilities of the equatorial currents nor other high frequency fluctuations in the ocean.
Philander, S G., William J Hurlin, and A D Siegel, 1987: Simulation of the seasonal cycle of the tropical Pacific Ocean. Journal of Physical Oceanography, 17(11), 1986-2002. Abstract PDF
In a general circulation model of the tropical Pacific Ocean forced with climatological seasonally varying winds, equatorial upwelling and downwelling in adjacent latitudes play central roles in closing the oceanic circulation. The transport of the eastward North Equatorial Countercurrent decreases in a downstream direction because fluid is lost to downwelling into the thermocline where there is equatorward motion. Although this fluid converges onto the Equatorial Undercurrent, the latter's transport decreases because of equatorial upwelling. The upwelling, on the other hand, enhances the transport of the westward South Equatorial Current. Seasonally, the Countercurrent and South Equatorial Current are intense during the Northern Hemisphere summer and fall, at which time the thermocline has pronounced trough near 3°N and a ridge near 10°N, and are weak in the spring when latitudinal thermal gradients are small and when the southeast trades are relatively weak. These variations are out of phase with those of the Equatorial Undercurrent, which is most intense in the spring.
The seasonal changes are associated with considerable variations in the meridional heat transport, especially across 9°N. The heat transport is always towards the winter hemisphere. During the northern winter, Ekman drift in the central Pacific affects the northward transport of warm surface waters. During the northern summer, when the ITCZ is near 9°N and the winds there are weak, the Ekman drift across 9°N is small. The relatively steady southward flow of warm surface waters across 9°N in the far western Pacific now contributes significantly to the southward heat transport. Seasonally there is both this meridional and a zonal redistribution of warm surface waters in the upper tropical Pacific Ocean. The zonal redistribution, from west to east, contributes to high sea surface temperatures in the east in April when the Equatorial Undercurrent surges eastward and attains its highest speed and transport during the period of weak southwest tradewinds. Increased heat flux across the ocean surface at this time also contributes to the warming of the upper equatorial ocean. Seasonal wind variations west of the dateline have little effect on the eastern tropical Pacific in the model.
In general circulation models of the seasonal cycle, westward propagating waves, with an approximate wavelength of 1000 km and period of 3 to 4 weeks, in the western equatorial Atlantic and eastern equatorial Pacific derive their energy from the kinetic and potential energy of the mean flow. There is intense downwelling the cold crests of the wave and upwelling in the warm troughs. The local meridional heat flux associated with the waves is of the order of 100 W m-2, but their contribution to the net heat transport across the equator is small. The waves are highly nonstationary in time and inhomogenous in space.
