caa a22 4500 467937575 CHVBK 20180406153001.0 cr unu---uuuuu 170328e20061101xx s 000 0 eng 10.1007/s00703-005-0177-0 doi (NATIONALLICENCE)springer-10.1007/s00703-005-0177-0 Short-range prediction of a heavy precipitation event by assimilating Chinese CINRAD-SA radar reflectivity data using complex cloud analysis [Elektronische Daten] [C. Sheng, S. Gao, M. Xue] 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. Springer-Verlag, 2006 Sheng C. Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China aut Gao S. Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China aut Xue M. School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA aut Meteorology and Atmospheric Physics Springer-Verlag 94/1-4(2006-11-01), 167-183 0177-7971 94:1-4<167 2006 94 703 https://doi.org/10.1007/s00703-005-0177-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00703-005-0177-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sheng C. Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China aut NATIONALLICENCE 700 1- Gao S. Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China aut NATIONALLICENCE 700 1- Xue M. School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA aut NATIONALLICENCE 773 0- Meteorology and Atmospheric Physics Springer-Verlag 94/1-4(2006-11-01), 167-183 0177-7971 94:1-4<167 2006 94 703 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer