Synchronization of Radar Observations with Multi-Scale Storm Tracking

被引:4
作者
Yang Hongping [1 ]
Zhang, Jian [2 ,3 ]
Langston, Carrie [2 ,3 ]
机构
[1] China Meteorol Adm, Wuhan Inst Heavy Rain, Wuhan 430074, Peoples R China
[2] Univ Oklahoma, Cooperat Inst Mesoscale Meteorol Studies, Norman, OK USA
[3] NOAA, Natl Severe Storms Lab, OAR, Norman, OK 73069 USA
关键词
synchronization; radar; multi-scale storm tracking; DETECTION ALGORITHM; PART I; RAINFALL ESTIMATION; REAL-TIME; WSR-88D; PREDICTION; IDENTIFICATION; REFLECTIVITY;
D O I
10.1007/s00376-009-0078-0
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The 3-D radar reflectivity data has become increasingly important for use in data assimilation towards convective scale numerical weather prediction as well as next generation precipitation estimation. Typically, reflectivity data from multiple radars are objectively analyzed and mosaiced onto a regional 3-D Cartesian grid prior to being assimilated into the models. One of the scientific issues associated with the mosaic of multi-radar observations is the synchronization of all the observations. Since radar data is usually rapidly updated (similar to every 5-10 min), it is common in current multi-radar mosaic techniques to combine multiple radar' observations within a time window by assuming that the storms are steady within the window. The assumption holds well for slow evolving precipitation systems, but for fast evolving convective storms, this assumption may be violated and the mosaic of radar observations at different times may result in inaccurate storm structure depictions. This study investigates the impact of synchronization on storm structures in multiple radar data analyses using a multi-scale storm tracking algorithm.
引用
收藏
页码:78 / 86
页数:9
相关论文
共 32 条
[1]  
Anagnostou EN, 1999, J ATMOS OCEAN TECH, V16, P189, DOI 10.1175/1520-0426(1999)016<0189:RTRREP>2.0.CO
[2]  
2
[3]  
Brewster KA, 2003, MON WEATHER REV, V131, P480, DOI 10.1175/1520-0493(2003)131<0480:PCDAAA>2.0.CO
[4]  
2
[5]  
Fulton RA, 1998, WEATHER FORECAST, V13, P377, DOI 10.1175/1520-0434(1998)013<0377:TWRA>2.0.CO
[6]  
2
[7]  
Gao JD, 2004, J ATMOS OCEAN TECH, V21, P457, DOI 10.1175/1520-0426(2004)021<0457:ATVDAM>2.0.CO
[8]  
2
[9]  
Golding B.W., 1998, METEOROL APPL, V5, P1, DOI [10.1017/S1350482798000577, DOI 10.1017/S1350482798000577]
[10]   3DVAR and cloud analysis with WSR-88D level-II data for the prediction of the Fort Worth, Texas, Tornadic thunderstorms. Part I: Cloud analysis and its impact [J].
Hu, M ;
Xue, M ;
Brewster, K .
MONTHLY WEATHER REVIEW, 2006, 134 (02) :675-698