improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system
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2016
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Abstract
A comprehensive aerosol–cloud–precipitation interaction (ACI) scheme has been
developed under a China Meteorological Administration (CMA) chemical weather modeling
system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified
Atmospheric Chemistry Environment). Calculated by a sectional aerosol activation scheme based on the information of size and
mass from CUACE and the thermal-dynamic and humid states from the weather
model GRAPES at each time step, the cloud condensation nuclei (CCN) are interactively fed
online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme – WDM6) and a convective
parameterization to drive cloud physics and precipitation formation
processes. The modeling system has been applied to study the ACI for
January 2013 when several persistent haze-fog events and eight precipitation
events occurred.
The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.
The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.
| Reference Key |
zhou2016atmosphericimproving
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|---|---|
| Authors | ;C. Zhou;X. Zhang;S. Gong;Y. Wang;M. Xue |
| Journal | Journal of agricultural and food chemistry |
| Year | 2016 |
| DOI |
10.5194/acp-16-145-2016
|
| URL | |
| Keywords |
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