Tag: clouds

Cloud biases over the Southern Ocean in current climate models

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Poor simulation of clouds may be the main reason why current climate models show sea-surface temperature biases over the Southern Ocean. This in turn could have implications for assessing the plausibility of modelled cloud feedbacks in this region under climate change. A new paper led by my colleague Alejandro Bodas-Salcedo – which has just been published as an early online release in the Journal of Climate – looks at the simulation of clouds over the Southern Ocean in the current generation of climate models. The abstract and citation are below, the paper can be accessed here.

Current climate models generally reflect too little solar radiation over the Southern Ocean, which may be the leading cause of the prevalent sea-surface temperature biases in climate models. We study the role of clouds the radiation biases in atmosphere-only simulations of the Cloud Feedback Model Intercomparison Project phase 2 (CFMIP2), as clouds have a leading role in controlling the solar radiation absorbed at those latitudes. We composite daily data around cyclone centres in the latitude band between 40°S and 70°S during the summer. We use cloud property estimates from satellite to classify clouds into different regimes, which allows us to relate the cloud regimes and their associated radiative biases to the meteorological conditions in which they occur. The cloud regimes are defined using cloud properties retrieved using passive sensors, and may suffer from the errors associated with this type of retrievals. We use information from the CALIPSO lidar to investigate in more detail the properties of the ‘mid-level’ cloud regime. Most of the model biases occur in the cold air side of the cyclone composite, and the cyclone composite accounts for most of the climatological error in that latitudinal band. The ‘mid-level’ regime is the main contributor to reflected shortwave radiation biases. CALIPSO data show that the ‘mid-level’ cloud regime is dominated by two main cloud types; cloud with tops actually at mid-level, and low-level cloud. Improving the simulation of these cloud types should help reduce the biases in the simulation of the solar radiation budget in the Southern Ocean in climate models.

Bodas-Salcedo, A., K.D. Williams, M.A. Ringer et al., 2013, Origins of the solar radiation biases over the Southern Ocean in CFMIP2 models, J. Climate, doi: http://dx.doi.org/10.1175/JCLI-D-13-00169.1

The seasonal variation of cloud regimes in CMIP5 models

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A new paper led by my colleague Yoko Tsushima has just been published online in Climate Dynamics. The paper uses a clustering method to compare the latest CMIP5 models with satellite observations of clouds – the example above shows maps of the observed and model-simulated deep convective cloud cluster in the tropics for January and July. The focus of the paper is on how well the models are able to represent the seasonal cycle of such cloud regimes and whether these comparisons can provide us with a useful metric to assess model performance. The abstract and citation are below, the full paper is here.

An extended cloud-clustering method to assess the seasonal variation of clouds is applied to five CMIP5 models. The seasonal variation of the total cloud radiative effect (CRE) is dominated by variations in the relative frequency of occurrence of the different cloud regimes. Seasonal variations of the CRE within the individual regimes contribute much less. This is the case for both observations, models and model errors. The error in the seasonal variation of cloud regimes, and its breakdown into mean amplitude and time varying components, are quantified with a new metric. The seasonal variation of the CRE of the cloud regimes is relatively well simulated by the models in the tropics, but less well in the extra-tropics. The stratocumulus regime has the largest seasonal variation of shortwave CRE in the tropics, despite having a small magnitude in the climatological mean. Most of the models capture the temporal variation of the CRE reasonably well, with the main differences between models coming from the variation in amplitude. In the extra-tropics, most models fail to correctly represent both the amplitude and time variation of the CRE of congestus, frontal and stratocumulus regimes. The annual mean climatology of the CRE and its amplitude in the seasonal variation are both underestimated for the anvil regime in the tropics, the cirrus regime and the congestus regime in the extra-tropics. The models in this study that best capture the seasonal variation of the cloud regimes tend to have higher climate sensitivities.

Tsushima, Y., M.A. Ringer, M.J. Webb, K.D. Williams, 2012, Quantitative evaluation of the seasonal variations in climate model cloud regimes, Climate Dynamics, doi: 10.1007/ s00382-012-1609-4