The Analysis and Prediction of the 8-9 May 2007 Oklahoma Tornadic Mesoscale Convective System by Assimilating WSR-88D and CASA Radar Data Using 3DVAR

被引:87
|
作者
Schenkman, Alexander D. [1 ,2 ]
Xue, Ming [1 ,2 ]
Shapiro, Alan [1 ,2 ]
Brewster, Keith [2 ]
Gao, Jidong [2 ]
机构
[1] Univ Oklahoma, Sch Meteorol, Norman, OK 73072 USA
[2] Univ Oklahoma, Ctr Anal & Predict Storms, Norman, OK 73072 USA
基金
美国国家科学基金会;
关键词
ENSEMBLE KALMAN FILTER; NONHYDROSTATIC ATMOSPHERIC SIMULATION; SINGLE-DOPPLER OBSERVATIONS; OBJECT-BASED VERIFICATION; MODEL INITIAL FIELDS; LEVEL-II DATA; PART II; MICROPHYSICAL RETRIEVAL; PRECIPITATION FORECASTS; SUPERCELL THUNDERSTORM;
D O I
10.1175/2010MWR3336.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The Advanced Regional Prediction System (ARPS) model is employed to perform high-resolution numerical simulations of a mesoscale convective system and associated cyclonic line-end vortex (LEV) that spawned several tornadoes in central Oklahoma on 8-9 May 2007. The simulation uses a 1000 km 3 1000 km domain with 2-km horizontal grid spacing. The ARPS three-dimensional variational data assimilation (3DVAR) is used to assimilate a variety of data types. All experiments assimilate routine surface and upper-air observations as well as wind profiler and Oklahoma Mesonet data over a 1-h assimilation window. A subset of experiments assimilates radar data. Cloud and hydrometeor fields as well as in-cloud temperature are adjusted based on radar reflectivity data through the ARPS complex cloud analysis procedure. Radar data are assimilated from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network as well as from the Engineering Research Center for Collaborative and Adaptive Sensing of the Atmosphere ( CASA) network of four X-band Doppler radars. Three-hour forecasts are launched at the end of the assimilation window. The structure and evolution of the forecast MCS and LEV are markedly better throughout the forecast period in experiments in which radar data are assimilated. The assimilation of CASA radar data in addition to WSR-88D data increases the structural detail of the modeled squall line and MCS at the end of the assimilation window, which appears to yield a slightly better forecast track of the LEV.
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页码:224 / 246
页数:23
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