Short-range prediction of a heavy precipitation event by assimilating Chinese CINRAD-SA radar reflectivity data using complex cloud analysis |
| |
Authors: | C Sheng S Gao M Xue |
| |
Institution: | (1) Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China;(2) Shandong Provincial Meteorological Center, Jinan, Shandong, China;(3) School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA;(4) Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma, USA |
| |
Abstract: | Summary With the ARPS (Advanced Regional Prediction System) Data Analysis System (ADAS) and its complex cloud analysis scheme, the
reflectivity data from a Chinese CINRAD-SA Doppler radar are used to analyze 3D cloud and hydrometeor fields and in-cloud
temperature and moisture. Forecast experiments starting from such initial conditions are performed for a northern China heavy
rainfall event to examine the impact of the reflectivity data and other conventional observations on short-range precipitation
forecast.
The full 3D cloud analysis mitigates the commonly known spin-up problem with precipitation forecast, resulting a significant
improvement in precipitation forecast in the first 4 to 5 hours. In such a case, the position, timing and amount of precipitation
are all accurately predicted. When the cloud analysis is used without in-cloud temperature adjustment, only the forecast of
light precipitation within the first hour is improved.
Additional analysis of surface and upper-air observations on the native ARPS grid, using the 1 degree real-time NCEP AVN analysis
as the background, helps improve the location and intensity of rainfall forecasting slightly. Hourly accumulated rainfall
estimated from radar reflectivity data is found to be less accurate than the model predicted precipitation when full cloud
analysis is used. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|