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The simulation of Arctic clouds and their influence on the winter surface temperature in present-day climate in the CMIP3 multi-model dataset
Stockholm University, Faculty of Science, Department of Meteorology .
Stockholm University, Faculty of Science, Department of Meteorology .
2011 (English)In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 36, no 3-4, 623-635 p.Article in journal (Refereed) Published
Abstract [en]

We investigate the influence of clouds on the surface energy budget and surface temperature in the sea-ice covered parts of the ocean north of the Arctic circle in present-day climate in nine global climate models participating in the Coupled Model Intercomparison Project phase 3, CMIP3. Monthly mean simulated surface skin temperature, radiative fluxes and cloud parameters are evaluated using retrievals from the extended AVHHR Polar Pathfinder (APP-x) product. We analyzed the annual cycle but the main focus is on the winter, in which large parts of the region experience polar night. We find a smaller across-model spread as well as better agreement with observations during summer than during winter in the simulated climatological annual cycles of total cloudiness and surface skin temperature. The across-model spread in liquid and ice water paths is substantial during the whole year. These results qualitatively agree with earlier studies on the present-day Arctic climate in GCMs. The climatological ensemble model mean annual cycle of surface cloud forcing shows good agreement with observations in summer. However, during winter the insulating effect of clouds tends to be underestimated in models. During winter, most of the models as well as the observations show higher monthly mean total cloud fractions, associated with larger positive surface cloud forcing. Most models also show good correlation between the surface cloud forcing and the vertically integrated ice and liquid cloud condensate. The wintertime ensemble model mean total cloud fraction (69%) shows excellent agreement with observations. The across-model spread in the winter mean cloudiness is substantial (36-94%) however and several models significantly underestimate the cloud liquid water content. If the two models not showing any relationship between cloudiness and surface cloud forcing are disregarded, a tentative across-model relation exists, in such a way that models that simulate large winter mean cloudiness also show larger surface cloud forcing. Even though the across-model spread in wintertime surface cloud forcing is large, no clear relation to the surface temperature is found. This indicates that other processes, not explicitly cloud related, are important for the simulated across-model spread in surface temperature.

Place, publisher, year, edition, pages
2011. Vol. 36, no 3-4, 623-635 p.
Keyword [en]
GCM, Arctic clouds, CRF, CMIP3, APP-x, Surface energy budget
National Category
Meteorology and Atmospheric Sciences
URN: urn:nbn:se:su:diva-67484DOI: 10.1007/s00382-010-0758-6ISI: 000286937100016OAI: diva2:470588
authorCount :2Available from: 2011-12-29 Created: 2011-12-28 Last updated: 2011-12-29Bibliographically approved

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Karlsson, JohannesSvensson, Gunilla
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