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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Systematic Bias in the Prediction of Warm-Rain Hydrometeors in the WDM6 Microphysics Scheme and Modifications
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Systematic Bias in the Prediction of Warm-Rain Hydrometeors in the WDM6 Microphysics Scheme and Modifications

机译:Systematic Bias in the Prediction of Warm-Rain Hydrometeors in the WDM6 Microphysics Scheme and Modifications

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摘要

Modifications are made to the calculation of warm-rain hydrometeor number concentrations of the Weather Research and Forecasting double-moment six-class (WDM6) microphysics scheme. These modifications are related with cloud condensation nuclei activation, cloud droplet evaporation, and snow and graupel melting. The effects of the modifications are tested in a North China heavy rain event (Case01) as well as a short-duration rain event in Hebei Province of China (Case02). The results show that the WDM6 scheme underestimates the cloud mixing ratios (Qc) and number concentrations (Nc), while it overestimates the rain mixing ratios (Qr) and number concentrations (Nr). Meanwhile, the WDM6 scheme overestimates the mass mean diameter of cloud droplets (Dmc) and underestimates that of raindrops (Dmr). Through microphysical budget analysis, it is found that the inappropriate calculations of cloud condensation nuclei activation and cloud evaporation are responsible for the underestimation of Nc and larger Dmc. The overestimation of the autoconversion rate resulting from larger Dmc plays a decisive role in the overestimation of Qr and Nr, as well as in the underestimation of Qc. The overestimation of raindrops produced by the melting of snow and graupel is another reason for higher Qr and Nr. By comparing with the airborne observations in Case02, it is found that the Nc and Dmc simulation are notably improved with the direct modifications of Nc. The Nr simulation is closer to the observation after the melting of snow and graupel are modified.

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