An Improved Parameterization for Simulating Arctic Cloud Amount in the CCSM3 Climate Model

Steve Vavrus Center for Climatic Research, University of Wisconsin—Madison, Madison, Wisconsin

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Duane Waliser Water and Carbon Cycles Group, Jet Propulsion Laboratory, Pasadena, California

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Abstract

A simple alternative parameterization for predicting cloud fraction in the Community Climate System Model, version 3 (CCSM3) global climate model is presented. This formula, dubbed “freeezedry,” is designed to alleviate the bias of excessive low clouds during polar winter by reducing the cloud amount under very dry conditions. During winter, freezedry decreases the low cloud amount over the coldest regions in high latitudes by over 50% locally and more than 30% averaged across the Arctic. The cloud reduction causes an Arctic-wide drop of 15 W m−2 in surface cloud radiative forcing (CRF) during winter and about a 50% decrease in mean annual Arctic CRF. Consequently, wintertime surface temperatures fall by up to 4 K on land and 2–8 K over the Arctic Ocean, thus significantly reducing the model’s pronounced warm bias. Freezedry also affects CCSM3’s sensitivity to greenhouse forcing. In a transient-CO2 experiment, the model version with freezedry warms up to 20% less in the North Polar and South Polar regions (1.5- and 0.5-K-smaller warming, respectively). Paradoxically, the muted high-latitude response occurs despite a much larger increase in cloud amount with freezedry during nonsummer months (when clouds warm the surface), apparently because of the colder modern reference climate. While improving the polar climate simulation in CCSM3, freezedry has virtually no influence outside of very cold regions and has already been implemented in another climate model, the Global Environmental and Ecological Simulation of Ecological Systems, version 1 (GENESIS1). Furthermore, the simplicity of this parameterization allows it to be readily incorporated into other GCMs, many of which also suffer from excessive wintertime polar cloudiness.

Corresponding author address: Steve Vavrus, Center for Climatic Research, University of Wisconsin—Madison, 1225 W. Dayton Street, Madison, WI 53706. Email: sjvavrus@wisc.edu

Abstract

A simple alternative parameterization for predicting cloud fraction in the Community Climate System Model, version 3 (CCSM3) global climate model is presented. This formula, dubbed “freeezedry,” is designed to alleviate the bias of excessive low clouds during polar winter by reducing the cloud amount under very dry conditions. During winter, freezedry decreases the low cloud amount over the coldest regions in high latitudes by over 50% locally and more than 30% averaged across the Arctic. The cloud reduction causes an Arctic-wide drop of 15 W m−2 in surface cloud radiative forcing (CRF) during winter and about a 50% decrease in mean annual Arctic CRF. Consequently, wintertime surface temperatures fall by up to 4 K on land and 2–8 K over the Arctic Ocean, thus significantly reducing the model’s pronounced warm bias. Freezedry also affects CCSM3’s sensitivity to greenhouse forcing. In a transient-CO2 experiment, the model version with freezedry warms up to 20% less in the North Polar and South Polar regions (1.5- and 0.5-K-smaller warming, respectively). Paradoxically, the muted high-latitude response occurs despite a much larger increase in cloud amount with freezedry during nonsummer months (when clouds warm the surface), apparently because of the colder modern reference climate. While improving the polar climate simulation in CCSM3, freezedry has virtually no influence outside of very cold regions and has already been implemented in another climate model, the Global Environmental and Ecological Simulation of Ecological Systems, version 1 (GENESIS1). Furthermore, the simplicity of this parameterization allows it to be readily incorporated into other GCMs, many of which also suffer from excessive wintertime polar cloudiness.

Corresponding author address: Steve Vavrus, Center for Climatic Research, University of Wisconsin—Madison, 1225 W. Dayton Street, Madison, WI 53706. Email: sjvavrus@wisc.edu

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