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Why use spectral (bin) microphysics to simulate precipitating systems?

 

 

Barry Lynn, Alexander Khain, and Jimy Dudhia

Department of the Atmospheric Sciences, The Hebrew University of Jerusalem

And National Center for Atmospheric Research

 

Abstract 

Forecast of the rate, duration, amount and spatial distribution of precipitation remains a difficult problem for current high-resolution weather prediction mesoscale models. These models use, as a rule, bulk-parameterization schemes for the description of cloud microphysics. In these schemes, the size distributions of raindrops and ice particles are preset (e.g., they might use the Marshall-Palmer distribution). This simplification allows one to reduce a complex equation system for microphysical processes to a few equations for mass contents (or mass contents and number concentrations).  This  makes the schemes computationally efficient, but also introduces errors in the description of microphysical mechanisms that are responsible for formation of precipitation. We will present several examples of such errors.

A more precise description of microphysical processes is referred to as spectral (bin) microphysics (SBM).  This takes into account factors influencing drop spectrum formation (e.g., atmospheric aerosols) that are  required for improved simulation of precipitation formation. SBM is based on solving an equation system for size distribution functions that includes water drops, ice particles, and atmospheric aerosols. Each size distribution is described by several tens of bins representing particles of certain mass, bulk density and shape. This method is more time consuming as compared to bulk-parameterization schemes, but the use of PC cluster technology makes possible the use of the SBM in a three-dimensional simulation environment as a potent tool for microphysical research.

We implemented SBM (developed by the Hebrew University of Jerusalem) into the three-dimensional mesoscale model known as MM5. The MM5-SBM was used to simulate a rain event over Florida on 27 July 1991. This event was accompanied be a squall-line formation. It is shown that the MM5-SBM reproduces precipitation rate, rain amounts and location, radar reflectivity, and cloud structure better than bulk parameterizations currently implemented in MM5.

Possible applications of the first mesoscale model with spectral (bin) microphysics are discussed.

 

 

 

 

Thursday, September 2, 2004, 3:30 PM

Refreshments 3:15 PM

NCAR-Foothills Laboratory

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