Impact of a Diagnostic Pressure Equation Constraint on Tornadic Supercell Thunderstorm Forecasts Initialized Using 3DVAR Radar Data Assimilation

被引:1
|
作者
Ge, Guoqing [1 ]
Gao, Jidong [2 ]
Xue, Ming [1 ,3 ]
机构
[1] Univ Oklahoma, Ctr Anal & Predict Storms, Norman, OK 73072 USA
[2] Natl Severe Storms Lab, Norman, OK 73072 USA
[3] Univ Oklahoma, Sch Meteorol, Norman, OK 73072 USA
关键词
ENSEMBLE KALMAN FILTER; PREDICTION SYSTEM ARPS; NONHYDROSTATIC ATMOSPHERIC SIMULATION; VARIATIONAL STATISTICAL-ANALYSIS; MULTICASE COMPARATIVE-ASSESSMENT; LOW-LEVEL WIND; PART II; MICROPHYSICAL RETRIEVAL; RECURSIVE FILTERS; NUMERICAL ASPECTS;
D O I
10.1155/2013/947874
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A diagnostic pressure equation constraint has been incorporated into a storm-scale three-dimensional variational (3DVAR) data assimilation system. This diagnostic pressure equation constraint (DPEC) is aimed to improve dynamic consistency among different model variables so as to produce better data assimilation results and improve the subsequent forecasts. Ge et al. (2012) described the development of DPEC and testing of it with idealized experiments. DPEC was also applied to a real supercell case, but only radial velocity was assimilated. In this paper, DPEC is further applied to two real tornadic supercell thunderstorm cases, where both radial velocity and radar reflectivity data are assimilated. The impact of DPEC on radar data assimilation is examined mainly based on the storm forecasts. It is found that the experiments using DPEC generally predict higher low-level vertical vorticity than the experiments not using DPEC near the time of observed tornadoes. Therefore, it is concluded that the use of DPEC improves the forecast of mesocyclone rotation within supercell thunderstorms. The experiments using different weighting coefficients generate similar results. This suggests that DPEC is not very sensitive to the weighting coefficients.
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页数:12
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