Regional assessment of the parameter‐dependent performance of CAM4 in simulating tropical clouds

Zhang, Yuying; Xie, Shaocheng; Covey, Curt; Lucas, D. D.; Gleckler, P. J.; Klein, Stephen A.; Tannahill, J.; Doutriaux, Charles; Klein, Richard

doi:10.1029/2012gl052184

Cited by 33 publications

(42 citation statements)

References 21 publications

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“…We use CF from the GCM simulator-oriented ISCCP cloud product (Pincus et al 2012;Zhang et al 2012) and CALIPSO-GOCCP datasets. ISCCP provides CF in 7 pressure layers and 6 optical thickness categories.…”

Section: A Observational Datamentioning

confidence: 99%

On the Relationships between Subtropical Clouds and Meteorology in Observations and CMIP3 and CMIP5 Models*

Myers

Norris

2015

Journal of Climate

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Climate models' simulation of clouds over the eastern subtropical oceans contributes to large uncertainties in projected cloud feedback to global warming. Here, interannual relationships of cloud radiative effect and cloud fraction to meteorological variables are examined in observations and in models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively). In observations, cooler sea surface temperature, a stronger estimated temperature inversion, and colder horizontal surface temperature advection are each associated with larger low-level cloud fraction and increased reflected shortwave radiation. A moister free troposphere and weaker subsidence are each associated with larger midand high-level cloud fraction and offsetting components of shortwave and longwave cloud radiative effect. It is found that a larger percentage of CMIP5 than CMIP3 models simulate the wrong sign or magnitude of the relationship of shortwave cloud radiative effect to sea surface temperature and estimated inversion strength. Furthermore, most models fail to produce the sign of the relationship between shortwave cloud radiative effect and temperature advection. These deficiencies are mostly, but not exclusively, attributable to errors in the relationship between low-level cloud fraction and meteorology. Poor model performance also arises due to errors in the response of mid-and high-level cloud fraction to variations in meteorology. Models exhibiting relationships closest to observations tend to project less solar reflection by clouds in the late twenty-first century and have higher climate sensitivities than poorer-performing models. Nevertheless, the intermodel spread of climate sensitivity is large even among these realistic models.

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Section: A Observational Datamentioning

confidence: 99%

On the Relationships between Subtropical Clouds and Meteorology in Observations and CMIP3 and CMIP5 Models*

Myers

Norris

2015

Journal of Climate

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“…The ERA-Interim data begin in 1979 and extend to the present. For the ISCCP data, we use two derived data products: 1) the top-of-the-atmosphere radiative fluxes (ISCCP-FD; Zhang et al 2004) and 2) the simulatororiented ISCCP cloud product produced for the Cloud Feedback Model Intercomparison Project (CFMIP; http://climserv.ipsl.polytechnique.fr/cfmip-obs/; Pincus et al 2012;Zhang et al 2012). …”

Section: A Datamentioning

confidence: 99%

Southern Hemisphere Cloud–Dynamics Biases in CMIP5 Models and Their Implications for Climate Projections

Grise

Polvani

2014

Journal of Climate

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This study quantifies cloud-radiative anomalies associated with interannual variability in the latitude of the Southern Hemisphere (SH) midlatitude eddy-driven jet, in 20 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Two distinct model types are found. In the first class of models (type I models), total cloud fraction is reduced at SH midlatitudes as the jet moves poleward, contributing to enhanced shortwave radiative warming. In the second class of models (type II models), this dynamically induced cloud radiative warming effect is largely absent. Type I and type II models have distinct deficiencies in their representation of observed Southern Ocean clouds, but comparison with two independent satellite datasets indicates that the cloud-dynamics behavior of type II models is more realistic.Because the SH midlatitude jet shifts poleward in response to CO 2 forcing, the cloud-dynamics biases uncovered from interannual variability are directly relevant for climate change projections. In CMIP5 model experiments with abruptly quadrupled atmospheric CO 2 concentrations, the global-mean surface temperature initially warms more in type I models, even though their equilibrium climate sensitivity is not significantly larger. In type I models, this larger initial warming is linked to the rapid adjustment of the circulation and clouds to CO 2 forcing in the SH, where a nearly instantaneous poleward shift of the midlatitude jet is accompanied by a reduction in the reflection of solar radiation by clouds. In type II models, the SH jet also shifts rapidly poleward with CO 2 quadrupling, but it is not accompanied by cloud radiative warming anomalies, resulting in a smaller initial globalmean surface temperature warming.

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“…We used the 2.5° × 2.5° monthly means of the ISCCP-D1 cloud amounts, segregated by cloud-top pressure and cloud optical thickness (Pincus et al 2012;Zhang et al 2012). In this study, the ISCCP low-plusmiddle cloud amounts with optical thickness > 3.6, corrected with the random-overlap assumption, were defined as "the LSC amount".…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Relationships between Subtropical Marine Low Stratiform Cloudiness and Estimated Inversion Strength in CMIP5 Models Using the Satellite Simulator Package COSP

Koshiro¹,

Shiotani

Kawai³

et al. 2018

SOLA

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Using the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) outputs, subtropical marine low stratiform cloud (LSC) amounts simulated in 12 Coupled Model Intercomparison Project phase 5 (CMIP5) models are robustly evaluated in terms of the relationship with the estimated inversion strength (EIS). The International Satellite Cloud Climatology Project (ISCCP) low-plus-middle cloud amounts with optical thickness > 3.6, corrected with the random-overlap assumption, are defined as the LSC amount. Although EISs are well-simulated in all the models, more than half of the models show weaker responses of the LSC amount to EIS (2%−3% K −1 ) than the observations (~4.5% K −1 ), and some models even show negative responses. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud amounts and layered EISs reveal that most models simulate inversion levels lower than observed, and that the vertical structure of LSCs has a key role for improvement in the modeled relationships.(Citation: Koshiro, T., M. Shiotani, H. Kawai, and S. Yukimoto, 2018: Evaluation of relationships between subtropical marine low stratiform cloudiness and estimated inversion strength in CMIP5 models using the satellite simulator package COSP.

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Regional assessment of the parameter‐dependent performance of CAM4 in simulating tropical clouds

Cited by 33 publications

References 21 publications

On the Relationships between Subtropical Clouds and Meteorology in Observations and CMIP3 and CMIP5 Models*

On the Relationships between Subtropical Clouds and Meteorology in Observations and CMIP3 and CMIP5 Models*

Southern Hemisphere Cloud–Dynamics Biases in CMIP5 Models and Their Implications for Climate Projections

Evaluation of Relationships between Subtropical Marine Low Stratiform Cloudiness and Estimated Inversion Strength in CMIP5 Models Using the Satellite Simulator Package COSP

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