Community Climate System Model Version Research Articles

The CCSM4 Ocean Component

The ocean component of the Community Climate System Model version 4 (CCSM4) is described, and its solutions from the twentieth-century (20C) simulations are documented in comparison with observations and those of CCSM3. The improvements to the ocean model physical processes include new parameterizations to represent previously missing physics and modifications of existing parameterizations to incorporate recent new developments. In comparison with CCSM3, the new solutions show some significant improvements that can be attributed to these model changes. These include a better equatorial current structure, a sharper thermocline, and elimination of the cold bias of the equatorial cold tongue all in the Pacific Ocean; reduced sea surface temperature (SST) and salinity biases along the North Atlantic Current path; and much smaller potential temperature and salinity biases in the near-surface Pacific Ocean. Other improvements include a global-mean SST that is more consistent with the present-day observations due to a different spinup procedure from that used in CCSM3. Despite these improvements, many of the biases present in CCSM3 still exist in CCSM4. A major concern continues to be the substantial heat content loss in the ocean during the preindustrial control simulation from which the 20C cases start. This heat loss largely reflects the top of the atmospheric model heat loss rate in the coupled system, and it essentially determines the abyssal ocean potential temperature biases in the 20C simulations. There is also a deep salty bias in all basins. As a result of this latter bias in the deep North Atlantic, the parameterized overflow waters cannot penetrate much deeper than in CCSM3.

Estimating future global per capita water availability based on changes in climate and population

Human populations are profoundly affected by water stress, or the lack of sufficient per capita available freshwater. Water stress can result from overuse of available freshwater resources or from a reduction in the amount of available water due to decreases in rainfall and stored water supplies. Analyzing the interrelationship between human populations and water availability is complicated by the uncertainties associated with climate change projections and population projections. We present a simple methodology developed to integrate disparate climate and population data sources and develop first-order per capita water availability projections at the global scale. Simulations from the coupled land–ocean–atmosphere Community Climate System Model version 3 (CCSM3) forced with a range of hypothetical greenhouse gas emissions scenarios are used to project grid-based changes in precipitation minus evapotranspiration as proxies for changes in runoff, or fresh water supply. Population growth changes, according to Intergovernmental Panel on Climate Change (IPCC) storylines, are used as proxies for changes in fresh water demand by 2025, 2050 and 2100. These freshwater supply and demand projections are then combined to yield estimates of per capita water availability aggregated by watershed and political unit. Results suggest that important insights might be extracted from the use of the process developed here, notably including the identification of the globe's most vulnerable regions in need of more detailed analysis and the relative importance of population growth versus climate change in altering future freshwater supplies. However, these are only exemplary insights and, as such, could be considered hypotheses that should be rigorously tested with multiple climate models, multiple observational climate datasets, and more comprehensive population change storylines.

Improved Madden–Julian Oscillations with Improved Physics: The Impact of Modified Convection Parameterizations

Abstract Two modifications are made to the deep convection parameterization in the NCAR Community Climate System Model, version 3 (CCSM3): a dilute plume approximation and an implementation of the convective momentum transport (CMT). These changes lead to significant improvement in the simulated Madden–Julian oscillations (MJOs). With the dilute plume approximation, temperature and convective heating perturbations become more positively correlated. Consequently, more available potential energy is generated and the intraseasonal variability (ISV) becomes stronger. The organization of ISV is also improved, which is manifest in coherent structures between different MJO phases and an improved simulation of the eastward propagation of MJOs with a reasonable eastward speed. The improved propagation can be attributed to a better simulation of the low-level zonal winds due to the inclusion of CMT. The authors posit that the large-scale zonal winds are akin to a selective conveyor belt that facilitates the organization of ISVs into highly coherent structures, which are important features of observed MJOs. The conclusions are supported by two supplementary experiments, which include the dilute plume approximation and CMT separately.

Potential flaws of interdecadal changes over eastern China around the early 1990s in the National Centers for Environmental Prediction‐National Center for Atmospheric Research reanalyses

This study compares interdecadal changes in tropospheric temperature and geopotential height over eastern China in four reanalyses and upper air radiosonde (UAR) observations. It is found that the tropospheric temperature and geopotential height over eastern China during the period 1992–2000 were systematically lower in the National Centers for Environmental Prediction (NCEP)‐National Center for Atmospheric Research (NCAR) reanalysis‐1 and the NCEP‐Department of Energy reanalysis‐2 compared to the UAR observations. Accordingly, the tropospheric temperature and geopotential height over eastern China in the NCEP reanalyses showed a pronounced interdecadal decrease around 1992, while this decrease was not significant in the UAR observations, the 40 year European Centre for Medium‐Range Weather Forecasts (ERA‐40) reanalysis, and the 25 year Japanese Meteorological Agency (JRA‐25) reanalysis. The overestimated interdecadal change in the NCEP reanalyses may lead to an inconsistent variation between tropospheric and surface climates. When summer surface air temperature increases (decreases) over southern China, summer tropospheric temperature over eastern China generally increases (decreases) in the ERA‐40, JRA‐25, and UAR data sets, which is physically supported by the NCAR Community Climate System Model version 3. However, this link between the troposphere and surface is not observed in the two NCEP reanalyses. The interdecadal bias in tropospheric temperature after 1992 in the NCEP reanalyses is possibly related to an operational change in the bias correction tables since 1992.

Climate Sensitivity of the Community Climate System Model, Version 4

Equilibrium climate sensitivity of the Community Climate System Model, version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. This study uses the radiative kernel technique to show that, from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude and the shortwave cloud feedback increases. These two warming effects are partially canceled by cooling because of slight decreases in the global mean water vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed layer, slab-ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab-ocean model version for both CCSM3 and CCSM4. The authors argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.

Climate System Response to External Forcings and Climate Change Projections in CCSM4

Results are presented from experiments performed with the Community Climate System Model, version 4 (CCSM4) for the Coupled Model Intercomparison Project phase 5 (CMIP5). These include multiple ensemble members of twentieth-century climate with anthropogenic and natural forcings as well as single-forcing runs, sensitivity experiments with sulfate aerosol forcing, twenty-first-century representative concentration pathway (RCP) mitigation scenarios, and extensions for those scenarios beyond 2100–2300. Equilibrium climate sensitivity of CCSM4 is 3.20°C, and the transient climate response is 1.73°C. Global surface temperatures averaged for the last 20 years of the twenty-first century compared to the 1986–2005 reference period for six-member ensembles from CCSM4 are +0.85°, +1.64°, +2.09°, and +3.53°C for RCP2.6, RCP4.5, RCP6.0, and RCP8.5, respectively. The ocean meridional overturning circulation (MOC) in the Atlantic, which weakens during the twentieth century in the model, nearly recovers to early twentieth-century values in RCP2.6, partially recovers in RCP4.5 and RCP6, and does not recover by 2100 in RCP8.5. Heat wave intensity is projected to increase almost everywhere in CCSM4 in a future warmer climate, with the magnitude of the increase proportional to the forcing. Precipitation intensity is also projected to increase, with dry days increasing in most subtropical areas. For future climate, there is almost no summer sea ice left in the Arctic in the high RCP8.5 scenario by 2100, but in the low RCP2.6 scenario there is substantial sea ice remaining in summer at the end of the century.

Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.

Contrasts between Urban and Rural Climate in CCSM4 CMIP5 Climate Change Scenarios

A new parameterization of urban areas in the Community Climate System Model version 4 (CCSM4) allows for simulation of temperature in cities where most of the global population lives. CCSM4 Coupled Model Intercomparison Project phase 5 (CMIP5) simulations [Representative Concentration Pathway (RCP) 2.6, 4.5, and 8.5] are analyzed to examine how urban and rural areas might respond differently to changes in climate. The urban heat island (UHI), defined as the urban minus rural air temperature, is used as a metric. The average UHI at the end of the twenty-first century is similar to present day in RCP2.6 and RCP4.5, but decreases in RCP8.5. Both the daytime and nocturnal UHIs decrease in RCP8.5, but the decrease in the daytime UHI is larger and more uniform across regions and seasons than in the nocturnal UHI. This is caused by changes in evaporation that warm the rural surface more than the urban. There is significant spatial and seasonal variability in the response of the nocturnal UHI caused mainly by changes in the rural surface. In Europe, the response to climate change of rural leaf–stem area in summer and clouds and rural soil moisture in winter explains the majority of this variability. Climate change increases the number of warm nights in urban areas substantially more than in rural areas. These results provide evidence that urban and rural areas respond differently to climate change. Thus, the unique aspects of the urban environment should be considered when making climate change projections, particularly since the global population is becoming increasingly urbanized.

Tropical Atlantic Biases in CCSM4

This paper focuses on diagnosing biases in the seasonal climate of the tropical Atlantic in the twentieth-century simulation of the Community Climate System Model, version 4 (CCSM4). The biases appear in both atmospheric and oceanic components. Mean sea level pressure is erroneously high by a few millibars in the subtropical highs and erroneously low in the polar lows (similar to CCSM3). As a result, surface winds in the tropics are ~1 m s−1 too strong. Excess winds cause excess cooling and depressed SSTs north of the equator. However, south of the equator SST is erroneously high due to the presence of additional warming effects. The region of highest SST bias is close to southern Africa near the mean latitude of the Angola–Benguela Front (ABF). Comparison of CCSM4 to ocean simulations of various resolutions suggests that insufficient horizontal resolution leads to the insufficient northward transport of cool water along this coast and an erroneous southward stretching of the ABF. A similar problem arises in the coupled model if the atmospheric component produces alongshore winds that are too weak. Erroneously warm coastal SSTs spread westward through a combination of advection and positive air–sea feedback involving marine stratocumulus clouds. This study thus highlights three aspects to improve to reduce bias in coupled simulations of the tropical Atlantic: 1) large-scale atmospheric pressure fields; 2) the parameterization of stratocumulus clouds; and 3) the processes, including winds and ocean model resolution, that lead to errors in seasonal SST along southwestern Africa. Improvements of the latter require horizontal resolution much finer than the 1° currently used in many climate models.

An Investigation of the Initial Development of the Double-ITCZ Warm SST Biases in the CCSM

Abstract This paper investigates the initial development of the double ITCZ in the Community Climate System Model version 3 (CCSM3) in the central Pacific. Starting from a resting initial condition of the ocean in January, the model developed a warm bias of sea surface temperature (SST) in the central Pacific from 5°S to 10°S in the first three months. This initial bias is caused by excessive surface shortwave radiation that is also present in the stand-alone atmospheric model. The initial bias is further amplified by biases in both surface latent heat flux and horizontal heat transport in the upper ocean. These biases are caused by the responses of surface winds to SST bias and the thermocline structure to surface wind curls. This study also showed that the warming biases in surface solar radiation and latent heat fluxes are seasonally offset by cooling biases from reduced solar radiation after the austral summer due to cloud responses and in the austral fall due to enhanced evaporation when the maximum SST is closest to the equator. The warming biases from the dynamic heat transport by ocean currents however stay throughout all seasons once they are developed, which are eventually balanced by enhanced energy exchange and penetration of solar radiation below the mixed layer. It was also shown that the equatorial cold tongue develops after the warm biases in the south-central Pacific, and the overestimation of surface shortwave radiation recurs in the austral summer in each year. The results provide a case study on the physical processes leading to the development of the double ITCZ. Applicability of the results in other models is discussed.

The Madden–Julian Oscillation in CCSM4

Abstract This study assesses the ability of the Community Climate System Model, version 4 (CCSM4) to represent the Madden–Julian oscillation (MJO), the dominant mode of intraseasonal variability in the tropical atmosphere. The U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group’s prescribed diagnostic tests are used to evaluate the model’s mean state, variance, and wavenumber–frequency characteristics in a 20-yr simulation of the intraseasonal variability in zonal winds at 850 hPa (U850) and 200 hPa (U200), and outgoing longwave radiation (OLR). Unlike its predecessor, CCSM4 reproduces a number of aspects of MJO behavior more realistically. The CCSM4 produces coherent, broadbanded, and energetic patterns in eastward-propagating intraseasonal zonal winds and OLR in the tropical Indian and Pacific Oceans that are generally consistent with MJO characteristics. Strong peaks occur in power spectra and coherence spectra with periods between 20 and 100 days and zonal wavenumbers between 1 and 3. Model MJOs, however, tend to be more broadbanded in frequency than in observations. Broad-scale patterns, as revealed in combined EOFs of U850, U200, and OLR, are remarkably consistent with observations and indicate that large-scale convergence–convection coupling occurs in the simulated MJO. Relations between MJO in the model and its concurrence with other climate states are also explored. MJO activity (defined as the percentage of time the MJO index exceeds 1.5) is enhanced during El Niño events compared to La Niña events, both in the model and observations. MJO activity is increased during periods of anomalously strong negative meridional wind shear in the Asian monsoon region and also during strong negative Indian Ocean zonal mode states, in both the model and observations.

Predictability of the Atlantic Overturning Circulation and Associated Surface Patterns in Two CCSM3 Climate Change Ensemble Experiments

Abstract Predictability of the Atlantic meridional overturning circulation (AMOC) and associated oceanic and atmospheric fields on decadal time scales in the Community Climate System Model, version 3 (CCSM3) at T42 resolution is quantified with a 700-yr control run and two 40-member “perfect model” climate change experiments. After taking into account both the mean and spread about the mean of the forecast distributions and allowing for the possibility of time-evolving modes, the natural variability of the AMOC is found to be predictable for about a decade; beyond that range the forced predictability resulting from greenhouse gas forcing becomes dominant. The upper 500-m temperature in the North Atlantic is even more predictable than the AMOC by several years. This predictability is associated with subsurface and sea surface temperature (SST) anomalies that propagate in an anticlockwise direction along the subpolar gyre and tend to be prominent during the 10 yr following peaks in the amplitude of AMOC anomalies. Predictability in the North Atlantic SST mainly resides in the ensemble mean signals after three to four forecast years. Analysis suggests that in the CCSM3 the subpolar gyre SST anomalies associated with the AMOC variability can influence the atmosphere and produce surface climate predictability that goes beyond the ENSO time scale. However, the resulting initial-value predictability in the atmosphere is very weak.

Evaluation of IPCC Models’ Performance in Simulating Late-Twentieth-Century Climatologies and Weather Patterns over North America

Abstract The authors analyze the performance of 22 Intergovernmental Panel on Climate Change (IPCC) global climate models (GCMs) over all of North America and its western subregion using several different evaluation metrics. They assess the model skill in simulating climatologies of several climate variables and the skill in simulating the daily synoptic patterns. The evaluation is performed by comparing the model output with the North American Regional Reanalysis (NARR) over the period 1980–99. One set of metrics, based on root-mean-square errors and variance ratios, compares modeled versus the NARR mean annual cycle and interannual variability. Based on these measures the three top performing models are the ECHAM5–Max Planck Institute Ocean Model (MPI-OM), the third climate configuration of the Met Office Unified Model (HadCM3), and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled General Circulation Model, version 3.1 [CGCM3.1(T47)]. Models that perform well over all North America also perform well over its western subregion. However, the model ranking is sensitive to the choice of climate variable. For another evaluation measure the method of self-organizing maps was applied to classify the characteristic daily patterns of sea level pressure over the region. The evaluation consists of correlating the frequencies of these patterns, as generated in GCMs, with the frequencies in the NARR over the baseline period. Most of the models are successful in simulating the frequencies of daily anomaly patterns from the 20-yr-average daily pattern. However, very few GCMs are able to reproduce the occurrences of characteristic daily weather patterns in the NARR on seasonal basis over the baseline period. In terms of relative performance, the three top performing models are the Meteorological Research Institute (MRI) CGCM2.3.2, ECHAM5–MPI-OM, and the Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2(hires)]. The model skill in simulating daily synoptic patterns is not strongly linked to the skill in simulating the climatologies of selected variables. Despite the large scatter of model performance across all the metrics, some models consistently rank high [e.g., ECHAM5–MPI-OM and MIROC3.2(medres)]. Likewise, some models consistently rank low [e.g., the Community Climate System Model, version 3 (CCSM3) and the Goddard Institute for Space Studies Model E-R (GISS-ER)] independently of the evaluation measures, domain size, and climate variable of interest.

Response to Increasing Southern Hemisphere Winds in CCSM4

Results from two perturbation experiments using the Community Climate System Model version 4 where the Southern Hemisphere zonal wind stress is increased are described. It is shown that the ocean response is in accord with experiments using much-higher-resolution ocean models that do not use an eddy parameterization. The key to obtaining an appropriate response in the coarse-resolution climate model is to specify a variable coefficient in the Gent and McWilliams eddy parameterization, rather than a constant value. This result contrasts with several recent papers that have suggested that coarse-resolution climate models cannot obtain an appropriate response.

Factors Influencing Simulated Changes in Future Arctic Cloudiness

Abstract This study diagnoses the changes in Arctic clouds simulated by the Community Climate System Model version 3 (CCSM3) in a transient 2 × CO2 simulation. Four experiments—one fully coupled and three with prescribed SSTs and/or sea ice cover—are used to identify the mechanisms responsible for the projected cloud changes. The target simulation uses a T42 version of the CCSM3, in which the atmosphere is coupled to a dynamical ocean with mobile sea ice. This simulation is approximated by a T42 atmosphere-only integration using CCSM3’s atmospheric component [the Community Atmosphere Model version 3 (CAM3)] forced at its lower boundary with the changes in both SSTs and sea ice concentration from CCSM3’s 2 × CO2 run. The authors decompose the combined effect of the higher SSTs and reduced sea ice concentration on the Arctic cloud response in this experiment by running two additional CAM3 simulations: one forced with modern SSTs and the projected sea ice cover changes in CCSM3 and the other forced with modern sea ice coverage and the projected changes in SSTs in CCSM3. The results suggest that future increases in Arctic cloudiness simulated by CCSM3 are mostly attributable to two separate processes. Low cloud gains are primarily initiated locally by enhanced evaporation within the Arctic due to reduced sea ice, whereas cloud increases at middle and high levels are mostly driven remotely via greater meridional moisture transport from lower latitudes in a more humid global atmosphere. The enhanced low cloudiness attributable to sea ice loss causes large increases in cloud radiative forcing during the coldest months and therefore promotes even greater surface warming. Because CCSM3’s Arctic cloud response to greenhouse forcing is similar to other GCMs, the driving mechanisms identified here may be applicable to other models and could help to advance our understanding of likely changes in the vertical structure of polar clouds.

Decadal Variability of Asian–Australian Monsoon–ENSO–TBO Relationships

Abstract A set of dynamically coupled ocean–atmosphere mechanisms has previously been proposed for the Asia–Pacific tropics to produce a dominant biennial component of interannual variability [the tropospheric biennial oscillation (TBO)]. Namely, a strong Asian–Australian monsoon is often associated with negative SST anomalies in the equatorial eastern Pacific and a negative Indian Ocean dipole in northern fall between the strong Indian monsoon and strong Australian monsoon, and tends to be followed by a weak monsoon and positive SST anomalies in the Pacific the following year and so on. These connections are communicated through the large-scale east–west (Walker) circulation that involves the full depth of the troposphere. However, the Asia–Pacific climate system is characterized by intermittent decadal fluctuations whereby the TBO during some time periods is more pronounced than others. Observations and models are analyzed to identify processes that make the system less biennial at certain times due to one or some combination of the following:increased latitudinal extent of Pacific trade winds and wider cold tongue;warmer tropical Pacific compared to tropical Indian Ocean that weakens trade winds and reduces coupling strength;eastward shift of the Walker circulation;reduced interannual variability of Pacific and/or Indian Ocean SSTs. Decadal time-scale SST variability associated with the interdecadal Pacific oscillation (IPO) has been shown to alter the TBO over the Indo-Pacific region by contributing changes in either some or all of the four factors listed above. Analysis of a multicentury control run of the Community Climate System Model, version 4 (CCSM4), shows that this decadal modulation of interannual variability is transferred via the Walker circulation to the Asian–Australian monsoon region, thus affecting the TBO and monsoon–Pacific connections. Understanding these processes is important to be able to evaluate decadal predictions and longer-term climate change in the Asia–Pacific region.

Climate change impact on meteorological, agricultural, and hydrological drought in central Illinois

This paper investigates the impact of climate change on drought by addressing two questions: (1) How reliable is the assessment of climate change impact on drought based on state‐of‐the‐art climate change projections and downscaling techniques? and (2) Will the impact be at the same level from meteorological, agricultural, and hydrologic perspectives? Regional climate change projections based on dynamical downscaling through regional climate models (RCMs) are used to assess drought frequency, intensity, and duration, and the impact propagation from meteorological to agricultural to hydrological systems. The impact on a meteorological drought index (standardized precipitation index, SPI) is first assessed on the basis of daily climate inputs from RCMs driven by three general circulation models (GCMs). Two periods and two emission scenarios, i.e., 1991–2000 and 2091–2100 under B1 and A1Fi for Parallel Climate Model (PCM), 1990–1999 and 2090–2099 under A1B and A1Fi for Community Climate System Model, version 3.0 (CCSM3), 1980–1989 and 2090–2099 under B2 and A2 for Hadley Centre CGCM (HadCM3), are undertaken and dynamically downscaled through the RCMs. The climate projections are fed to a calibrated hydro‐agronomic model at the watershed scale in Central Illinois, and agricultural drought indexed by the standardized soil water index (SSWI) and hydrological drought by the standardized runoff index (SRI) and crop yield impacts are assessed. SSWI, in particular with extreme droughts, is more sensitive to climate change than either SPI or SRI. The climate change impact on drought in terms of intensity, frequency, and duration grows from meteorological to agricultural to hydrological drought, especially for CCSM3‐RCM. Significant changes of SSWI and SRI are found because of the temperature increase and precipitation decrease during the crop season, as well as the nonlinear hydrological response to precipitation and temperature change.

Probabilistic Projections of Climate Change over China under the SRES A1B Scenario Using 28 AOGCMs

Probabilistic projection of climate change consists of formulating the climate change information in a probabilistic manner at either global or regional scale. This can produce useful results for studies of the impact of climate change impact and change mitigation. In the present study, a simple yet effective approach is proposed with the purpose of producing probabilistic results of climate change over China for the middle and end of the twenty-first century under the Special Report on Emissions Scenarios A1B (SRES A1B) emission scenario. Data from 28 coupled atmosphere–ocean general circulation models (AOGCMs) are used. The methodology consists of ranking the 28 models, based on their ability to simulate climate over China in terms of two model evaluation metrics. Different weights were then given to the models according to their performances in present-day climate. Results of the evaluation for the current climate show that five models that have relatively higher resolutions—namely, the Istituto Nazionale di Geofisica e Vulcanologia ECHAM4 (INGV ECHAM4), the third climate configuration of the Met Office Unified Model (UKMO HadCM3), the CSIRO Mark version 3.5 (Mk3.5), the NCAR Community Climate System Model, version 3 (CCSM3), and the Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2 (hires)]—perform better than others over China. Their corresponding weights (normalized to 1) are 0.289, 0.096, 0.058, 0.048, and 0.044, respectively. Under the A1B scenario, surface air temperature is projected to increase significantly for both the middle and end of the twenty-first century, with larger magnitude over the north and in winter. There are also significant increases in rainfall in the twenty-first century under the A1B scenario, especially for the period 2070–99. As far as the interannual variability is concerned, the most striking feature is that there are high probabilities for the future intensification of interannual variability of precipitation over most of China in both winter and summer. For instance, over the Yangtze–Huai River basin (28°–35°N, 105°–120°E), there is a 60% probability of increased interannual standard deviation of precipitation by 20% in summer, which is much higher than that of the mean precipitation. In general there are small differences between weighted and unweighted projections, but the uncertainties in the projected changes are reduced to some extent after weighting.

Evaluation of the HOMME Dynamical Core in the Aquaplanet Configuration of NCAR CAM4: Rainfall

Abstract The NCAR Community Climate System Model, version 4 (CCSM4), includes a new dynamical core option based on NCAR’s High-Order Method Modeling Environment (HOMME). HOMME is a petascale-capable high-order element-based conservative dynamical core developed on the cubed-sphere grid. Initial simulations have been completed in an aquaplanet configuration of the Community Atmosphere Model, version 4 (CAM4), the atmospheric component of CCSM4. The authors examined the results of this simulation and assessed its fidelity in simulating rainfall, which is one of the most important components of the earth’s climate system. For this they compared the results from two other dynamical cores of CAM4: the finite volume (FV) and Eulerian (EUL). Instantaneous features of rainfall in HOMME are similar to FV and EUL. Similar to EUL and FV, HOMME simulates a single-peak intertropical convergence zone (ITCZ) over the equator. The strength of the ITCZ is found to be almost the same in HOMME and EUL but more in FV. It is observed that in HOMME and EUL, there is higher surface evaporation, which supplies more moisture to the deep tropics and gives more rainfall over the ITCZ. The altitude of maximum precipitation is found to be at almost the same level in all three dynamical cores. The eastward propagation of rainfall bands is organized and more prominent in FV and HOMME than in EUL. The phase speed of the eastward propagation in HOMME is found to be higher than in FV. The results show that, in general, the rainfall simulated by HOMME falls in a regime between that of FV and EUL. Hence, they conclude that the key aspects of rainfall simulation with HOMME falls into an acceptable range, as compared to the existing dynamical cores used in the model.

Seasonal Variations of Climate Feedbacks in the NCAR CCSM3

Abstract This study investigates the annual cycle of radiative contributions to global climate feedbacks. A partial radiative perturbation (PRP) technique is used to diagnose monthly radiative perturbations at the top of atmosphere (TOA) due to CO2 forcing; surface temperature response; and water vapor, cloud, lapse rate, and surface albedo feedbacks using NCAR Community Climate System Model, version 3 (CCSM3) output from a Special Report on Emissions Scenarios (SRES) A1B emissions-scenario-forced climate simulation. The seasonal global mean longwave TOA radiative feedback was found to be minimal. However, the global mean shortwave (SW) TOA cloud and surface albedo radiative perturbations exhibit large seasonality. The largest contributions to the negative SW cloud feedback occur during summer in each hemisphere, marking the largest differences with previous results. Results suggest that intermodel spread in climate sensitivity may occur, partially from cloud and surface albedo feedback seasonality differences. Further, links between the climate feedback and surface temperature response seasonality are investigated, showing a strong relationship between the seasonal climate feedback distribution and the seasonal surface temperature response.