scholarly journals Stratocumulus Clouds in Southeastern Pacific Simulated by Eight CMIP5–CFMIP Global Climate Models

2014 ◽  
Vol 27 (8) ◽  
pp. 3000-3022 ◽  
Author(s):  
Jia-Lin Lin ◽  
Taotao Qian ◽  
Toshiaki Shinoda
Keyword(s):  
Cloud Cover ◽  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Temperature Structure ◽  
Model Intercomparison ◽  
Stratocumulus Clouds ◽  
Intercomparison Project

Abstract This study examines the stratocumulus clouds and associated cloud feedback in the southeast Pacific (SEP) simulated by eight global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and Cloud Feedback Model Intercomparison Project (CFMIP) using long-term observations of clouds, radiative fluxes, cloud radiative forcing (CRF), sea surface temperature (SST), and large-scale atmosphere environment. The results show that the state-of-the-art global climate models still have significant difficulty in simulating the SEP stratocumulus clouds and associated cloud feedback. Comparing with observations, the models tend to simulate significantly less cloud cover, higher cloud top, and a variety of unrealistic cloud albedo. The insufficient cloud cover leads to overly weak shortwave CRF and net CRF. Only two of the eight models capture the observed positive cloud feedback at subannual to decadal time scales. The cloud and radiation biases in the models are associated with 1) model biases in large-scale temperature structure including the lack of temperature inversion, insufficient lower troposphere stability (LTS), and insufficient reduction of LTS with local SST warming, and 2) improper model physics, especially insufficient increase of low cloud cover associated with larger LTS. The two models that arguably do best at simulating the stratocumulus clouds and associated cloud feedback are the only ones using cloud-top radiative cooling to drive boundary layer turbulence.

scholarly journals Large-scale features and evaluation of the PMIP4-CMIP6 <i>midHolocene</i> simulations

2020 ◽  
Vol 16 (5) ◽  
pp. 1847-1872 ◽  
Author(s):  
Chris M. Brierley ◽  
Anni Zhao ◽  
Sandy P. Harrison ◽  
Pascale Braconnot ◽  
Charles J. R. Williams ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Current Phase ◽  
Model Intercomparison ◽  
Global Mean Temperature ◽  
Intercomparison Project

Abstract. The mid-Holocene (6000 years ago) is a standard time period for the evaluation of the simulated response of global climate models using palaeoclimate reconstructions. The latest mid-Holocene simulations are a palaeoclimate entry card for the Palaeoclimate Model Intercomparison Project (PMIP4) component of the current phase of the Coupled Model Intercomparison Project (CMIP6) – hereafter referred to as PMIP4-CMIP6. Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the Northern Hemisphere and associated shifts in tropical rainfall. Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of −0.3 K, which is −0.2 K cooler than the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe, and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on the hydrological cycle, feedback strength, and potentially climate sensitivity.

scholarly journals Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations

2020 ◽  
Author(s):  
Chris Brierley ◽  
Anni Zhao ◽  
Sandy Harrison ◽  
Pascale Braconnot ◽  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Model Complexity ◽  
Current Phase ◽  
Model Intercomparison ◽  
Global Mean Temperature ◽  
Intercomparison Project

&lt;p&gt;The mid-Holocene (6,000 years ago) is a standard experiment for the evaluation of the simulated response of global climate models using paleoclimate reconstructions. The latest mid-Holocene simulations are a contribution by the Palaeoclimate Model Intercomparison Project (PMIP4) to the current phase of the Coupled Model Intercomparison Project (CMIP6). Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the northern hemisphere and associated shifts in tropical rainfall. &amp;#160;Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of -0.3 K, which is -0.2 K cooler that the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Neither this difference nor the improvement in model complexity and resolution seems to improve the realism of the simulations. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on climate sensitivity and feedback strength.&lt;/p&gt;

scholarly journals Large-scale features and evaluation of the PMIP4-CMIP6 <i>midHolocene</i> simulations

2020 ◽  
Author(s):  
Chris M. Brierley ◽  
Anni Zhao ◽  
Sandy P. Harrison ◽  
Pascale Braconnot ◽  
Charles J. R. Williams ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Model Complexity ◽  
Current Phase ◽  
Model Intercomparison ◽  
Global Mean Temperature ◽  
Intercomparison Project

Abstract. The mid-Holocene (6000 years ago) is a standard experiment for the evaluation of the simulated response of global climate models using paleoclimate reconstructions. The latest mid-Holocene simulations are a contribution by the Palaeoclimate Model Intercomparison Project (PMIP4) to the current phase of the Coupled Model Intercomparison Project (CMIP6). Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the northern hemisphere and associated shifts in tropical rainfall. Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of −0.3 K, which is −0.2 K cooler that the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Neither this difference nor the improvement in model complexity and resolution seems to improve the realism of the simulations. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on climate sensitivity and feedback strength.

scholarly journals European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)

2020 ◽  
Vol 13 (11) ◽  
pp. 5485-5506
Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  
Jesús Fernández ◽  
Silje L. Sørland ◽  
Roman Brogli ◽  
...  
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Daily Precipitation ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Grid Spacing ◽  
Intercomparison Project ◽  
Horizontal Grid

Abstract. In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale.

Simulation of subtropical marine stratocumulus clouds in convection-resolving models

2020 ◽  
Author(s):  
Christoph Heim ◽  
Laureline Hentgen ◽  
Nikolina Ban ◽  
Christoph Schär
Keyword(s):  
Cloud Cover ◽  
Large Scale ◽  
Climate Models ◽  
Inversion Layer ◽  
Heat Fluxes ◽  
Global Climate Models ◽  
The Other ◽  
Limited Area ◽  
Stratocumulus Clouds ◽  
The Mean

&lt;p&gt;Even though the complexity and resolution of global climate models (GCMs) has increased over the last decades, the inter-model spread of equilibrium climate sensitivity has not narrowed. The representation of subtropical low-level clouds and their associated radiative feedbacks in climate models still poses a major challenge. A fundamental problem underlying the simulation of such clouds is their multiscale nature. On the one hand, current GCMs allow to capture the large-scale processes but are too coarse to represent the mesoscale and microscale dynamical processes governing their formation and dissipation. On the other hand, large eddy simulations (LES) resolving the micro scale are bound to small domains and thus lack a robust representation of the large-scale flow and the mesoscale organisation of the clouds. Convection-resolving models (CRMs) are an attractive compromise between the former two since they allow for simulations at much higher resolution than in conventional GCMs and on larger domains than in LES.&lt;/p&gt;&lt;p&gt;Here we analyse how CRMs simulate stratocumulus decks and investigate causes for inter-model differences. We consider a set of ten CRMs (nine GCMs that are run at convection-resolving resolution during a short time period as part of the pioneering DYAMOND initiative, and the limited area model COSMO run by ourselves) used to simulate stratocumulus clouds over the South-East Atlantic during a 40 day period. The simulations cover a range of horizontal grid spacings between 5 and 1 km.&lt;/p&gt;&lt;p&gt;We find pronounced differences in the mean cloud cover among the analysed CRMs. In comparison to observed radiation (CERES), most of them underestimate cloud cover, in particular the low-lying stratus decks close to the African coast. Nevertheless, the simulated mesoscale cloud organisation is realistic and similar in the set of CRMs, with few exceptions showing organisation on larger scales than in the other models. In general, the simulated cloud field appears to be more sensitive to the model choice than to the horizontal resolution.&lt;/p&gt;&lt;p&gt;Despite the differences in the cloud cover, most models capture the subtropical inversion and its spatial structure relatively well. Therefore, differences in the inversion strengths do not suffice to explain variability in the simulated cloud cover fraction between models. However, we find a relation between the mean height of the stratocumulus layer (or inversion layer) and its cloud cover fraction: Models with higher inversions tend to simulate a higher cloud cover fraction, bringing them closer to observations. Similarly, stronger vertical mixing within the boundary layer and enhanced surface latent heat fluxes appear to be related to higher cloud cover. Such relations may help to determine the physical processes responsible for the differences among CRMs in the simulated stratocumulus field.&lt;/p&gt;

Model Uncertainty in Cloud–Circulation Coupling, and Cloud-Radiative Response to Increasing CO2, Linked to Biases in Climatological Circulation

2018 ◽  
Vol 31 (24) ◽  
pp. 10013-10020
Author(s):  
Bernard R. Lipat ◽  
Aiko Voigt ◽  
George Tselioudis ◽  
Lorenzo M. Polvani
Keyword(s):  
Model Uncertainty ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Hadley Cell ◽  
Temperature Structure ◽  
Climatological Circulation

Recent analyses of global climate models suggest that uncertainty in the coupling between midlatitude clouds and the atmospheric circulation contributes to uncertainty in climate sensitivity. However, the reasons behind model differences in the cloud–circulation coupling have remained unclear. Here, we use a global climate model in an idealized aquaplanet setup to show that the Southern Hemisphere climatological circulation, which in many models is biased equatorward, contributes to the model differences in the cloud–circulation coupling. For the same poleward shift of the Hadley cell (HC) edge, models with narrower climatological HCs exhibit stronger midlatitude cloud-induced shortwave warming than models with wider climatological HCs. This cloud-induced radiative warming results predominantly from a subsidence warming that decreases cloud fraction and is stronger for narrower HCs because of a larger meridional gradient in the vertical velocity. A comparison of our aquaplanet results with comprehensive climate models suggests that about half of the model uncertainty in the midlatitude cloud–circulation coupling stems from this impact of the circulation on the large-scale temperature structure of the atmosphere, and thus could be removed by improving the climatological circulation in models. This illustrates how understanding of large-scale dynamics can help reduce uncertainty in clouds and their response to climate change.

scholarly journals Characterizing and Understanding Cloud Ice and Radiation Budget Biases in Global Climate Models and Reanalysis

2016 ◽  
Vol 56 ◽  
pp. 13.1-13.20 ◽  
Author(s):  
J.-L. F. Li ◽  
D. E. Waliser ◽  
G. Stephens ◽  
Seungwon Lee
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Convective Core ◽  
Intercomparison Project ◽  
Annual Means ◽  
Cloud Ice ◽  
Ice Water

Abstract The authors present an observationally based evaluation of the vertically resolved cloud ice water content (CIWC) and vertically integrated cloud ice water path (CIWP) as well as radiative shortwave flux downward at the surface (RSDS), reflected shortwave (RSUT), and radiative longwave flux upward at top of atmosphere (RLUT) of present-day global climate models (GCMs), notably twentieth-century simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), and compare these results to those of the third phase of the Coupled Model Intercomparison Project (CMIP3) and two recent reanalyses. Three different CloudSat and/or Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined ice water products and two methods are used to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate can be obtained for model evaluations. The results show that, for annual mean CIWC and CIWP, there are factors of 2–10 (either over- or underestimate) in the differences between observations and models for a majority of the GCMs and for a number of regions. Most of the GCMs in CMIP3 and CMIP5 significantly underestimate the total ice water mass because models only consider suspended cloud mass, ignoring falling and convective core cloud mass. For the annual means of RSDS, RLUT, and RSUT, a majority of the models have significant regional biases ranging from −30 to 30 W m−2. Based on these biases in the annual means, there is virtually no progress in the simulation fidelity of RSDS, RLUT, and RSUT fluxes from CMIP3 to CMIP5, even though there is about a 50% bias reduction improvement of global annual mean CIWP from CMIP3 to CMIP5. It is concluded that at least a part of these persistent biases stem from the common GCM practice of ignoring the effects of precipitating and/or convective core ice and liquid in their radiation calculations.

scholarly journals Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution

2020 ◽  
Vol 1 (1) ◽  
pp. 277-292 ◽  
Author(s):  
Reinhard Schiemann ◽  
Panos Athanasiadis ◽  
David Barriopedro ◽  
Francisco Doblas-Reyes ◽  
Katja Lohmann ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Development ◽  
Global Climate Models ◽  
Assessment Model ◽  
Climate Simulation ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Intercomparison Project

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.

scholarly journals European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)

2021 ◽  
Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Daily Precipitation ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Grid Spacing ◽  
Intercomparison Project ◽  
Horizontal Grid

&lt;p&gt;In this study, we evaluate a set of high-resolution (25&amp;#8211;50&amp;#8201;km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12&amp;#8211;50&amp;#8201;km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50&amp;#8201;km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events.&lt;/p&gt;&lt;p&gt;The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12&amp;#8201;km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50&amp;#8201;km scale.&lt;/p&gt;

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