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.
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.
In this two-part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part I, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode – with prescribed sea surface temperatures (SSTs) and sea ice distribution – is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top-of-atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part II, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.
In Part II of this two-part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part I. Part II provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.
Dogar, Muhammad M., Georgiy Stenchikov, Sergey Osipov, Bruce Wyman, and Ming Zhao, August 2017: Sensitivity of the Regional Climate in the Middle East and North Africa to Volcanic perturbations. Journal of Geophysical Research: Atmospheres, 122(15), DOI:10.1002/2017JD026783. Abstract
The Middle East and North Africa (MENA) regional climate appears to be extremely sensitive to volcanic eruptions. Winter cooling after the 1991 Pinatubo eruption far exceeded the mean hemispheric temperature anomaly, even causing snowfall in Israel. To better understand MENA climate variability, the climate responses to the El Chichón and Pinatubo volcanic eruptions are analyzed using observations, NOAA/NCEP Climate Forecast System Reanalysis, and output from the Geophysical Fluid Dynamics Laboratory's High-Resolution Atmospheric Model (HiRAM). A multiple regression analysis both for the observations and the model output is performed on seasonal summer and winter composites to separate out the contributions from climate trends, El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian summer monsoon and volcanic aerosols. Strong regional temperature and precipitation responses over the MENA region are found in both winter and summer. The model and the observations both show that a positive NAO amplifies the MENA volcanic winter cooling. In boreal summer, the patterns of changing temperature and precipitation suggest a weakening and southward shift of the Intertropical Convergence Zone, caused by volcanic surface cooling and weakening of the Indian and West African monsoons. The model captures the main features of the climate response; however, it underestimates the total cooling, especially in winter, and exhibits a different spatial pattern of the NAO climate response in MENA compared to the observations. The conducted analysis sheds light on the internal mechanisms of MENA climate variability and helps to selectively diagnose the model deficiencies.
Balaji, V, Rusty Benson, Bruce Wyman, and Isaac M Held, October 2016: Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework. Geoscientific Model Development, 9(10), DOI:10.5194/gmd-9-3605-2016. Abstract
Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by.
We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath.
We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models.
We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.
Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the inter-model spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, we use a developmental version of the next generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the CMIP5 model ensemble. We demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere/land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and our current inability to find a clear observational constraint that favors one version of our model over the others, the implications of this ability to engineer climate sensitivity needs to be considered when estimating the uncertainty in climate projections.
CLUBB (Cloud Layers Unified by Binormals) is a higher-order closure (HOC) method with an assumed joint probability density function (PDF) for the subgrid variations in vertical velocity, temperature, and moisture. CLUBB has been implemented in the GFDL climate model AM3-CLUBB and successfully unifies the treatment of shallow convection, resolved clouds, and planetary boundary layer (PBL). In this study, we further explore the possibility for CLUBB to unify the deep convection in a new configuration referred as AM3-CLUBB+. AM3-CLUBB+ simulations with prescribed sea surface temperature are discussed. Cloud, radiation, and precipitation fields compare favorably with observations and reanalyses. AM3-CLUBB+ successfully captures the transition from stratocumulus to deep convection and the modulated response of liquid water path to aerosols. Simulations of tropical variability and the Madden-Julian oscillation (MJO) are also improved. Deficiencies include excessive tropical water vapor and insufficient ice clouds in the mid-latitudes.
Flannaghan, Thomas J., Stephan Fueglistaler, Isaac M Held, S Po-Chedley, Bruce Wyman, and Ming Zhao, December 2014: Tropical temperature trends in Atmospheric General Circulation Model simulations and the impact of uncertainties in observed SSTs. Journal of Geophysical Research: Atmospheres, 119(23), DOI:10.1002/2014JD022365. Abstract
The comparison of trends in various climate indices in observations and models is of fundamental importance for judging the credibility of climate projections. Tropical tropospheric temperature trends have attracted particular attention as this comparison may suggest a model deficiency [Santer et al., 2005; Christy et al., 2007, 2010; Fu et al., 2011; Thorne et al., 2011]. One can think of this problem as composed of two parts: one focused on tropical surface temperature trends and the associated issues related to forcing, feedbacks, and ocean heat uptake; and a second part focusing on connections between surface and tropospheric temperatures and the vertical profile of trends in temperature. Here, we focus on the atmospheric component of the problem. We show that two ensembles of GFDL HiRAM model runs (similar results are shown for NCAR's CAM4 model) with different commonly used prescribed sea surface temperatures (SSTs), namely the HadISST1 and ‘Hurrell’ data sets, have a difference in upper tropical tropospheric temperature trends (~0.1 K/decade at 300 hPa for the period 1984-2008) that is about a factor 3 larger than expected from moist adiabatic scaling of the tropical average SST trend difference. We show that this surprisingly large discrepancy in temperature trends is a consequence of SST trend differences being largest in regions of deep convection. Further, trends, and the degree of agreement with observations, not only depend on SST data set and the particular atmospheric temperature data set, but also on the period chosen for comparison. Due to the large impact on atmospheric temperatures, these systematic uncertainties in SSTs need to be resolved before the fidelity of climate models’ tropical temperature trend profiles can be assessed.
Maloney, Eric, Suzana J Camargo, E K M Chang, B A Colle, R Fu, K L Geil, Qi Hu, Xianan Jiang, Nathaniel C Johnson, K B Karnauskas, J L Kinter, Ben P Kirtman, Sanjiv Kumar, B Langenbrunner, K Lombardo, L Long, A Mariotti, J E Meyerson, K Mo, J David Neelin, Zaitao Pan, Richard Seager, Yolande L Serra, A Seth, Justin Sheffield, J Stroeve, J Thibeault, Shang-Ping Xie, Chunzai Wang, Bruce Wyman, and Ming Zhao, March 2014: North American Climate in CMIP5 Experiments: Part III: Assessment of 21st Century Projections. Journal of Climate, 27(6), DOI:10.1175/JCLI-D-13-00273.1. Abstract
In Part 3 of a three-part study on North American climate in Coupled Model Intercomparison project (CMIP5) models, we examine projections of 21st century climate in the RCP8.5 emission experiments. This paper summarizes and synthesizes results from several coordinated studies by the authors. Aspects of North American climate change that are examined include changes in continental-scale temperature and the hydrologic cycle, extremes events, and storm tracks, as well as regional manifestations of these climate variables. We also examine changes in eastern north Pacific and north Atlantic tropical cyclone activity and North American intraseasonal to decadal variability, including changes in teleconnections to other regions of the globe.
Projected changes are generally consistent with those previously published for CMIP3, although CMIP5 model projections differ importantly from those of CMIP3 in some aspects, including CMIP5 model agreement on increased central California precipitation. The paper also highlights uncertainties and limitations based on current results as priorities for further research. Although many projected changes in North American climate are consistent across CMIP5 models, substantial intermodel disagreement exists in other aspects. Areas of disagreement include projections of changes in snow water equivalent on a regional basis, summer Arctic sea ice extent, the magnitude and sign of regional precipitation changes, extreme heat events across the Northern U.S., and Atlantic and east Pacific tropical cyclone activity.
Many prior studies clearly document episodic Asian pollution in the western U.S.
free troposphere. Here, we examine the mechanisms involved in the transport of Asian
pollution plumes into western U.S. surface air through an integrated analysis of in situ
and satellite measurements in May–June 2010 with a new global high-resolution
(50 50 km2) chemistry-climate model (GFDL AM3). We find that AM3 with
full stratosphere-troposphere chemistry nudged to reanalysis winds successfully
reproduces observed sharp ozone gradients above California, including the interleaving
and mixing of Asian pollution and stratospheric air associated with complex interactions of
midlatitude cyclone air streams. Asian pollution descends isentropically behind cold fronts;
at 800 hPa a maximum enhancement to ozone occurs over the southwestern U.S.,
including the densely populated Los Angeles Basin. During strong episodes, Asian
emissions can contribute 8–15 ppbv ozone in the model on days when observed daily
maximum 8-h average ozone (MDA8 O3) exceeds 60 ppbv. We find that in the absence
of Asian anthropogenic emissions, 20% of MDA8 O3 exceedances of 60 ppbv in the model
would not have occurred in the southwestern USA. For a 75 ppbv threshold, that
statistic increases to 53%. Our analysis indicates the potential for Asian emissions to
contribute to high-O3 episodes over the high-elevation western USA, with implications
for attaining more stringent ozone standards in this region. We further demonstrate a
proof-of-concept approach using satellite CO column measurements as a qualitative early
warning indicator to forecast Asian ozone pollution events in the western U.S. with
lead times of 1–3 days.
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.
Held, Isaac M., Ming Zhao, and Bruce Wyman, January 2007: Dynamic radiative-convective equilibria using GCM column physics. Journal of the Atmospheric Sciences, 64(1), 228-238. Abstract PDF
The behavior of a GCM column physics package in a nonrotating, doubly periodic, homogeneous setting with prescribed SSTs is examined. This radiative–convective framework is proposed as a useful tool for studying some of the interactions between convection and larger-scale dynamics and the effects of differing modeling assumptions on convective organization and cloud feedbacks.
For the column physics utilized here, from the Geophysical Fluid Dynamics Laboratory (GFDL) AM2 model, many of the properties of the homogeneous, nonrotating model are closely tied to the fraction of precipitation that is large-scale, rather than convective. Significant large-scale precipitation appears above a critical temperature and then increases with further increases in temperature. The amount of large-scale precipitation is a function of horizontal resolution and can also be controlled by modifying the convection scheme, as is illustrated here by modifying assumptions concerning entrainment into convective plumes. Significant similarities are found between the behavior of the homogeneous model and that of the Tropics of the parent GCM when ocean temperatures are increased and when the convection scheme is modified.
The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved.
Two versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2° latitude × 2.5° longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1° in latitude and longitude, with meridional resolution equatorward of 30° becoming progressively finer, such that the meridional resolution is 1/3° at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments.
The control simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic.
Both models have been used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO2. The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/).
Manuscript received 8 December 2004, in final form 18 March 2005
Anderson, Jeffrey L., Bruce Wyman, Shaoqing Zhang, and T Hoar, August 2005: Assimilation of surface pressure observations using an ensemble filter in an idealized global atmospheric prediction system. Journal of the Atmospheric Sciences, 62(8), DOI:10.1175/JAS3510.1. Abstract
An ensemble filter data assimilation system is tested in a perfect model setting using a low resolution Held-Suarez configuration of an atmospheric GCM. The assimilation system is able to reconstruct details of the model's state at all levels when only observations of surface pressure (PS) are available. The impacts of varying the spatial density and temporal frequency of PS observations are examined. The error of the ensemble mean assimilation prior estimate appears to saturate at some point as the number of PS observations available once every 24 h is increased. However, increasing the frequency with which PS observations are available from a fixed network of 1800 randomly located stations results in an apparently unbounded decrease in the assimilation's prior error for both PS and all other model state variables. The error reduces smoothly as a function of observation frequency except for a band with observation periods around 4 h. Assimilated states are found to display enhanced amplitude high-frequency gravity wave oscillations when observations are taken once every few hours, and this adversely impacts the assimilation quality. Assimilations of only surface temperature and only surface wind components are also examined.
The results indicate that, in a perfect model context, ensemble filters are able to extract surprising amounts of information from observations of only a small portion of a model's spatial domain. This suggests that most of the remaining challenges for ensemble filter assimilation are confined to problems such as model error, observation representativeness error, and unknown instrument error characteristics that are outside the scope of perfect model experiments. While it is dangerous to extrapolate from these simple experiments to operational atmospheric assimilation, the resulrts also suggest that exploring the frequency with which observations are used for assimilation may lead to significant enhancements to assimilated state estimates.
for climate research developed at the Geophysical Fluid Dynamics Laboratory (GFDL) are presented. The atmosphere model, known as AM2, includes a new gridpoint dynamical core, a prognostic cloud scheme, and a multispecies aerosol climatology, as well as components from previous models used at GFDL. The land model, known as LM2, includes soil sensible and latent heat storage, groundwater storage, and stomatal resistance. The performance of the coupled model AM2–LM2 is evaluated with a series of prescribed sea surface temperature (SST) simulations. Particular focus is given to the model's climatology and the characteristics of interannual variability related to E1 Niño– Southern Oscillation (ENSO).
One AM2–LM2 integration was performed according to the prescriptions of the second Atmospheric Model Intercomparison Project (AMIP II) and data were submitted to the Program for Climate Model Diagnosis and Intercomparison (PCMDI). Particular strengths of AM2–LM2, as judged by comparison to other models participating in AMIP II, include its circulation and distributions of precipitation. Prominent problems of AM2– LM2 include a cold bias to surface and tropospheric temperatures, weak tropical cyclone activity, and weak tropical intraseasonal activity associated with the Madden–Julian oscillation.
An ensemble of 10 AM2–LM2 integrations with observed SSTs for the second half of the twentieth century permits a statistically reliable assessment of the model's response to ENSO. In general, AM2–LM2 produces a realistic simulation of the anomalies in tropical precipitation and extratropical circulation that are associated with ENSO.
Wyman, Bruce, 1996: A comparison of the sigma and eta vertical coordinate In Research Activities in Atmospheric and Oceanic Modelling, CAS/JSC Working Group on Numerical Experimentation, Report No. 23 WMO/TD No. 734, World Meteorological Organization, 3.42-3.43.
Wyman, Bruce, 1996: A step-mountain coordinate general circulation model: Description and validation of medium-range forecasts. Monthly Weather Review, 124(1), 102-121. Abstract PDF
The step-mountain or eta vertical coordinate has been a proposed solution for eliminating the numerical errors encountered when calculating the pressure gradient force along sloping surfaces. The main objectives of this paper are to describe the development of a global general circulation model using the eta coordinate and to verify the capabilities of the model for medium-range forecasts. First, the treatment of the polar boundary and the polar filtering are presented. To verify the polar treatment, numerical results using the shallow-water equations are presented. Second, various physical parameterizations are incorporated into the multilevel eta coordinate model. Model integrations for several January cases are presented to validate the model.
The similarity of the eta coordinate formulation to the terrain-following sigma coordinate allows the model to be run using either vertical coordinate. Thus, model comparisons are performed with the eta and sigma coordinate versions of the general circulation model, keeping the same physical parameterizations. Additional comparisons are made with a sigma coordinate spectral model.
As a validation of the model, 10-day integrations are made from four observed initial conditions at several horizontal resolutions. At relatively low resolution, forecast results slightly favor the spectral and sigma coordinate models. However, at higher resolution, forecast skill scores for the eta coordinate model are indistinguishable from those of the sigma models. Additional results are presented to demonstrate the advantages the advantages of the eta coordinate near steep topography and the potential deficiency of the eta coordinate in connection with the surface boundary layer treatment.
Pierrehumbert, R T., and Bruce Wyman, 1985: Upstream effects of mesoscale mountains. Journal of the Atmospheric Sciences, 42(10), 977-1003. Abstract PDF
The Alpine Experiment (ALPEX) has revealed that low-level air is typically diverted around the Alps without reaching the mountaintop. In pursuit of an understanding of the physical basis of this phenomenon and of its generality, we have explored the characteristics of orographic blocking of a rotating continuously stratified fluid, as revealed in a simple model problem retaining full nonlinear and transient effects. Hydrostatic dynamics is assumed, and the obstacleis taken to be an infinitely long ridge with height h(x). The key questions treated are the strength of the upstream deceleration of cross-mountain flow and the length scale over which the decelerated region extends. By means of scale analysis, the controlling parameters are found to be the Rossby number Ro = U/fL and the Froude number Fr = Nhm/U, where U is the speed of the oncoming flow, f is the Coriolis parameter, L the mountain half-width, N the Brunt Väisälä frequency, and hm is the maximum mountain height. The scale analysis also determines the qualitative dependence of the strength of the blocking on Ro and Fr; these predictions were confirmed and made quantitative via extensive numerical simulation.
In the nonrotating limit, Fr is the sole parameter. In this case, it is found that for sufficiently large Fr a decelerated layer of fluid forms near the obstacle and propagates arbitrarily far upstream with time, in a manner similar to that familiar in one-layer hydraulic theory. The upstream influence requires neither downstream lee wave trains nor vertical confinement by a rigid lid; rather, the upstream modes appear to be generated by wave breaking above the lee slope of the mountain. For a Gaussian mountain profile, wave breaking and upstream influence set in near Fr = 0.75; low-level flow upstream of the mountain is decelerated to rest for Fr > 1.5. In the rotating case, the decelerated zone does not propagate infinitely far. Instead, it attains a maximum extent on the order of the radius of deformation Nhm/f before retreating toward the mountain. The upstream scales remaining after a long time has passed are also discussed.
The theory accounts for a number of aspects of the ALPEX data, as well as for features seen in earlier observations of barrier winds elsewhere. It appears though that the sharp transition between flow over and flow around found in certain ALPEX vertical soundings obtained from aircraft cannot be explained in terms of inviscid theory. It is conjectured that the sharp division is due to low-level convective mixing.
