Journal
JOURNAL OF CLIMATE
Volume 27, Issue 1, Pages 41-56Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-13-00169.1
Keywords
Extratropical cyclones; Shortwave radiation; Climate models; Clouds
Categories
Funding
- Joint DECC/Defra Met Office Hadley Centre Climate Programme [GA01101]
- European Union [GA01101]
- European Union via the EU Cloud Intercomparison and Process Study Evaluation project (EUCLIPSE) [244067]
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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. The authors study the role of clouds on 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. The authors composite daily data around cyclone centers in the latitude band between 40 degrees and 70 degrees S during the summer. They use cloud property estimates from satellite to classify clouds into different regimes, which allow them 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. The authors use information from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to investigate in more detail the properties of the midlevel 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 midlevel regime is the main contributor to reflected shortwave radiation biases. CALIPSO data show that the midlevel cloud regime is dominated by two main cloud types: cloud with tops actually at midlevel 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.
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