scholarly journals Improved Representation of Marine Stratocumulus Cloud Shortwave Radiative Properties in the CMIP5 Climate Models

2014 ◽  
Vol 27 (16) ◽  
pp. 6175-6188 ◽  
Author(s):  
Anders Engström ◽  
Frida A.-M. Bender ◽  
Johannes Karlsson

Abstract The radiative properties of subtropical marine stratocumulus clouds are investigated in an ensemble of current-generation global climate models from phase 5 of the Climate Model Intercomparison Project (CMIP5). Using a previously documented method for determining regional mean cloud albedo, the authors find a closer agreement with observations in the CMIP5 models as compared to the previous generation of models (phase 3 of CMIP). The multimodel average indicates regional mean, monthly mean cloud albedos ranging from 0.32 to 0.5 among 26 models and five regions, to be compared with satellite observations that indicate a range from 0.32 to 0.39 for the same five regions. The intermodel spread in cloud fraction gives rise to a spread in albedo. Within models, there is a tendency for large cloud fraction to be related to low cloud albedo and vice versa, a relationship that dampens the intermodel variability in total albedo. The intramodel variability in albedo, for a given cloud fraction, is found to be up to twice as large in magnitude in models as in satellite observations. The reason for this larger variability in models is not settled, but possible contributing factors may be imperfect representation in the models of cloud type distribution or of sensitivity to meteorological variability or aerosols. Changes in aerosol loading are found to be the likely cause of an increase in cloud albedo over time. The radiative effect of such a scene brightening in marine stratocumulus cloud regions, from preindustrial times to present day, is estimated to be up to −1 W m−2 for the global ocean, but there are no observations to verify this number.

2018 ◽  
Vol 32 (1) ◽  
pp. 195-212 ◽  
Author(s):  
Sicheng He ◽  
Jing Yang ◽  
Qing Bao ◽  
Lei Wang ◽  
Bin Wang

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.


2011 ◽  
Vol 50 (10) ◽  
pp. 2139-2148 ◽  
Author(s):  
Frida A.-M. Bender ◽  
Robert J. Charlson ◽  
Annica M. L. Ekman ◽  
Louise V. Leahy

AbstractPlanetary albedo—the reflectivity for solar radiation—is of singular importance in determining the amount of solar energy taken in by the Earth–atmosphere system. Modeling albedo, and specifically cloud albedo, correctly is crucial for realistic climate simulations. A method is presented herein by which regional cloud albedo can be quantified from the relation between total albedo and cloud fraction, which in observations is found to be approximately linear on a monthly mean scale. This analysis is based primarily on the combination of cloud fraction data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and albedo data from the Clouds and the Earth’s Radiant Energy System (CERES), but the results presented are also supported by the combination of cloud fraction and proxy albedo data from satelliteborne lidar [Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)]. These data are measured and derived completely independently from the CERES–MODIS data. Applied to low-level marine stratiform clouds in three regions (off the coasts of South America, Africa, and North America), the analysis reveals regionally uniform monthly mean cloud albedos, indicating that the variation in cloud shortwave radiative properties is small on this scale. A coherent picture of low “effective” cloud albedo emerges, in the range from 0.35 to 0.42, on the basis of data from CERES and MODIS. In its simplicity, the method presented appears to be useful as a diagnostic tool and as a constraint on climate models. To demonstrate this, the same method is applied to cloud fraction and albedo output from several current-generation climate models [from the Coupled Model Intercomparison Project, phase 3 (CMIP3), archive]. Although the multimodel mean cloud albedo estimates agree to within 20% with the satellite-based estimates for the three focus regions, model-based estimates of cloud albedo are found to display much larger variability than do the observations, within individual models as well as between models.


2016 ◽  
Vol 29 (10) ◽  
pp. 3559-3587 ◽  
Author(s):  
Frida A.-M. Bender ◽  
Anders Engström ◽  
Johannes Karlsson

Abstract This study focuses on the radiative properties of five subtropical marine stratocumulus cloud regions, on monthly mean scale. Through examination of the relation between total albedo and cloud fraction, and its variability and relation to other parameters, some of the factors controlling the reflectivity, or albedo, of the clouds in these regions are investigated. It is found that the main part of the variability in albedo at a given cloud fraction can be related to temporal rather than spatial variability, indicating spatial homogeneity in cloud radiative properties in the studied regions. This is seen most clearly in satellite observations but also appears in an ensemble of climate models. Further comparison between satellite data and output from climate models shows that there is good agreement with respect to the role of liquid water path, the parameter that can be assumed to be the primary source of variability in cloud reflectivity for a given cloud fraction. On the other hand, the influence of aerosol loading on cloud albedo differs between models and observations. The cloud-albedo effect, or cloud brightening caused by aerosol through its coupling to cloud droplet number concentration and droplet size, is found not to dominate in the satellite observations on monthly mean scale, as it appears to do on this scale in the climate models. The disagreement between models and observations is particularly strong in regions with frequent occurrence of absorbing aerosols above clouds, where satellite data, in contrast to the climate models, indicate a scene darkening with increasing aerosol loading.


2017 ◽  
Vol 30 (11) ◽  
pp. 4131-4147 ◽  
Author(s):  
Frida A.-M. Bender ◽  
Anders Engström ◽  
Robert Wood ◽  
Robert J. Charlson

Abstract The hemispheric symmetry of albedo and its contributing factors in satellite observations and global climate models is evaluated. The analysis is performed on the annual mean time scale, on which a bimodality in the joint distribution of albedo and cloud fraction is evident, resulting from tropical and subtropical clouds and midlatitude clouds, respectively. Hemispheric albedo symmetry is not found in individual ocean-only latitude bands; comparing the Northern and Southern Hemisphere (NH and SH), regional mean albedo is higher in the NH tropics and lower in the NH subtropics and midlatitudes than in the SH counterparts. This follows the hemispheric asymmetry of cloud fraction. In midlatitudes and tropics the hemispheric asymmetry in cloud albedo also contributes to the asymmetry in total albedo, whereas in the subtropics the cloud albedo is more hemispherically symmetric. According to the observations, cloud contributions to compensation for higher clear-sky albedo in the NH come primarily from cloud albedo in midlatitudes and cloud amount in the subtropics. Current-generation climate models diverge in their representation of these relationships, but common features of the model–data comparison include weaker-than-observed asymmetry in cloud fraction and cloud albedo in the tropics, weaker or reversed cloud fraction asymmetry in the subtropics, and agreement with observed cloud albedo asymmetry in the midlatitudes. Models on average reproduce the NH–SH asymmetry in total albedo over the 60°S–60°N ocean but show higher occurrence of brighter clouds in the SH compared to observations. The albedo bias in both hemispheres is reinforced by overestimated clear-sky albedo in the models.


2020 ◽  
Vol 33 (14) ◽  
pp. 5885-5903 ◽  
Author(s):  
Elinor R. Martin ◽  
Cameron R. Homeyer ◽  
Roarke A. McKinzie ◽  
Kevin M. McCarthy ◽  
Tao Xian

AbstractChanges in tropical width can have important consequences in sectors including ecosystems, agriculture, and health. Observations suggest tropical expansion over the past 30 years although studies have not agreed on the magnitude of this change. Climate model projections have also indicated an expansion and show similar uncertainty in its magnitude. This study utilizes an objective, longitudinally varying, tropopause break method to define the extent of the tropics at upper levels. The location of the tropopause break is associated with enhanced stratosphere–troposphere exchange and thus its structure influences the chemical composition of the stratosphere. The method shows regional variations in the width of the upper-level tropics in the past and future. Four modern reanalyses show significant contraction of the tropics over the eastern Pacific between 1981 and 2015, and slight but significant expansion in other regions. The east Pacific narrowing contributes to zonal mean narrowing, contradicting prior work, and is attributed to the use of monthly and zonal mean data in prior studies. Six global climate models perform well in representing the climatological location of the tropical boundary. Future projections show a spread in the width trend (from ~0.5° decade−1 of narrowing to ~0.4° decade−1 of widening), with a narrowing projected across the east Pacific and Northern Hemisphere Americas. This study illustrates that this objective tropopause break method that uses instantaneous data and does not require zonal averaging is appropriate for identifying upper-level tropical width trends and the break location is connected with local and regional changes in precipitation.


2017 ◽  
Vol 30 (8) ◽  
pp. 2867-2884 ◽  
Author(s):  
Ross D. Dixon ◽  
Anne Sophie Daloz ◽  
Daniel J. Vimont ◽  
Michela Biasutti

Representing the West African monsoon (WAM) is a major challenge in climate modeling because of the complex interaction between local and large-scale mechanisms. This study focuses on the representation of a key aspect of West African climate, namely the Saharan heat low (SHL), in 22 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel dataset. Comparison of the CMIP5 simulations with reanalyses shows large biases in the strength and location of the mean SHL. CMIP5 models tend to develop weaker climatological heat lows than the reanalyses and place them too far southwest. Models that place the climatological heat low farther to the north produce more mean precipitation across the Sahel, while models that place the heat low farther to the east produce stronger African easterly wave (AEW) activity. These mean-state biases are seen in model ensembles with both coupled and fixed sea surface temperatures (SSTs). The importance of SSTs on West African climate variability is well documented, but this research suggests SSTs are secondary to atmospheric biases for understanding the climatological SHL bias. SHL biases are correlated across the models to local radiative terms, large-scale tropical precipitation, and large-scale pressure and wind across the Atlantic, suggesting that local mechanisms that control the SHL may be connected to climate model biases at a much larger scale.


2020 ◽  
Author(s):  
Reinhard Schiemann ◽  
Panos Athanasiadis ◽  
David Barriopedro ◽  
Francisco Doblas-Reyes ◽  
Katja Lohmann ◽  
...  

Abstract. Global Climate Models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations, and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and in winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 32 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 19 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 km to 20 km grid spacing, in the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer, and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.


2020 ◽  
Vol 1 (1) ◽  
pp. 277-292 ◽  
Author(s):  
Reinhard Schiemann ◽  
Panos Athanasiadis ◽  
David Barriopedro ◽  
Francisco Doblas-Reyes ◽  
Katja Lohmann ◽  
...  

Abstract. Global climate models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA – PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and during winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 33 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 18 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 to 20 km grid spacing, in most of the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.


2012 ◽  
Vol 5 (1) ◽  
pp. 425-458 ◽  
Author(s):  
M. A. Chamberlain ◽  
C. Sun ◽  
R. J. Matear ◽  
M. Feng ◽  
S. J. Phipps

Abstract. At present, global climate models used to project changes in climate do not resolve mesoscale ocean features such as boundary currents and eddies. These missing features may be important to realistically project the marine impacts of climate change. Here we present a framework for dynamically downscaling coarse climate change projections utilising a global ocean model that resolves these features in the Australian region. The downscaling model used here is ocean-only. The ocean feedback on the air-sea fluxes is explored by restoring to surface temperature and salinity, as well as a calculated feedback to wind stress. These feedback approximations do not replace the need for fully coupled models, but they allow us to assess the sensitivity of the ocean in downscaled climate change simulations. Significant differences are found in sea surface temperature, salinity, stratification and transport between the downscaled projections and those of the climate model. While the magnitude of the climate change differences may vary with the feedback parameterisation used, the patterns of the climate change differences are consistent and develop rapidly indicating they are mostly independent of feedback that ocean differences may have on the air-sea fluxes. Until such a time when it is feasible to regularly run a global climate model with eddy resolution, our framework for ocean climate change downscaling provides an attractive way to explore how climate change may affect the mesoscale ocean environment.


2013 ◽  
Vol 26 (22) ◽  
pp. 9077-9089 ◽  
Author(s):  
Sophie C. Lewis ◽  
David J. Karoly

Abstract Diurnal temperature range (DTR) is a useful index of climatic change in addition to mean temperature changes. Observational records indicate that DTR has decreased over the last 50 yr because of differential changes in minimum and maximum temperatures. However, modeled changes in DTR in previous climate model simulations of this period are smaller than those observed, primarily because of an overestimate of changes in maximum temperatures. This present study examines DTR trends using the latest generation of global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and utilizes the novel CMIP5 detection and attribution experimental design of variously forced historical simulations (natural-only, greenhouse gas–only, and all anthropogenic and natural forcings). Comparison of observed and modeled changes in DTR over the period of 1951–2005 again reveals that global DTR trends are lower in model simulations than observed across the 27-member multimodel ensemble analyzed here. Modeled DTR trends are similar for both experiments incorporating all forcings and for the historical experiment with greenhouse gases only, while no DTR trend is discernible in the naturally forced historical experiment. The persistent underestimate of DTR changes in this latest multimodel evaluation appears to be related to ubiquitous model deficiencies in cloud cover and land surface processes that impact the accurate simulation of regional minimum or maximum temperatures changes observed during this period. Different model processes are likely responsible for subdued simulated DTR trends over the various analyzed regions.


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