Cloud-Layer Overlap Characteristics Derived from Long-Term Cloud Radar Data

Gerald G. Mace Department of Meteorology, University Of Utah, Salt Lake City, Utah

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Sally Benson-Troth Department of Meteorology, University Of Utah, Salt Lake City, Utah

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Abstract

Assumptions regarding the vertical overlap characteristics of horizontal cloudy layers have been shown to be important to both the radiation transfer and the cloud microphysics that are predicted in general circulation models. Certain reasonable assumptions regarding cloud-layer overlap have been applied in models up to now where vertically continuous cloudy layers were assumed to overlap maximally leading to a minimum in cloud cover, and layers separated by noncloudy layers were assumed to overlap randomly. However, these assumptions have not been systematically evaluated with a comprehensive dataset that can resolve simultaneously occurring cloud layers. Presented here is an analysis of cloud-layer overlap characteristics derived from 103 months of cloud radar data collected by continuously operating millimeter-wavelength instruments deployed at the Atmospheric Radiation Measurement (ARM) sites in the Tropics, middle latitudes, and the Arctic. Using an approach recently proposed by Hogan and Illingworth, it is shown that an assumption of random overlap for layers separated by noncloudy layers is supported by observations. However, that the overlap characteristics of vertically continuous layers cannot be considered maximal is also shown. Indeed, vertically continuous cloudy layers do not appear to lend themselves to a simple overlap assumption. Therefore, to avoid significant biases in diagnosed cloud cover, the overlap properties of these layers in models will need to be parameterized. It is shown that the cloud-layer overlap characteristics in the middle latitudes do appear to be a strong function of season, suggesting that an overlap parameterization in terms of cloud system type may be possible.

Corresponding author address: Dr. Gerald Mace, Department of Meteorology, University of Utah, 135 South 1450 East, Rm 819 (819 WBB), Salt Lake City, UT 84112-0110. Email: mace@met.utah.edu

Abstract

Assumptions regarding the vertical overlap characteristics of horizontal cloudy layers have been shown to be important to both the radiation transfer and the cloud microphysics that are predicted in general circulation models. Certain reasonable assumptions regarding cloud-layer overlap have been applied in models up to now where vertically continuous cloudy layers were assumed to overlap maximally leading to a minimum in cloud cover, and layers separated by noncloudy layers were assumed to overlap randomly. However, these assumptions have not been systematically evaluated with a comprehensive dataset that can resolve simultaneously occurring cloud layers. Presented here is an analysis of cloud-layer overlap characteristics derived from 103 months of cloud radar data collected by continuously operating millimeter-wavelength instruments deployed at the Atmospheric Radiation Measurement (ARM) sites in the Tropics, middle latitudes, and the Arctic. Using an approach recently proposed by Hogan and Illingworth, it is shown that an assumption of random overlap for layers separated by noncloudy layers is supported by observations. However, that the overlap characteristics of vertically continuous layers cannot be considered maximal is also shown. Indeed, vertically continuous cloudy layers do not appear to lend themselves to a simple overlap assumption. Therefore, to avoid significant biases in diagnosed cloud cover, the overlap properties of these layers in models will need to be parameterized. It is shown that the cloud-layer overlap characteristics in the middle latitudes do appear to be a strong function of season, suggesting that an overlap parameterization in terms of cloud system type may be possible.

Corresponding author address: Dr. Gerald Mace, Department of Meteorology, University of Utah, 135 South 1450 East, Rm 819 (819 WBB), Salt Lake City, UT 84112-0110. Email: mace@met.utah.edu

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