Tuning of length-scale and observation-error for radar data assimilation using four dimensional variational (4D-Var) method

被引:7
作者
Choi, Yonghan [1 ,2 ]
Cha, Dong-Hyun [1 ]
Kim, Joowan [3 ]
机构
[1] Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, 50 UNIST Gil, Ulsan 44919, South Korea
[2] Natl Ctr Atmospher Res, Mesoscale & Microscale Meteorol Lab, Boulder, CO 80307 USA
[3] Kongju Natl Univ, Dept Atmospher Sci, Gongju, South Korea
来源
ATMOSPHERIC SCIENCE LETTERS | 2017年 / 18卷 / 11期
关键词
length-scale tuning; observation-error tuning; radar data assimilation; 4D-Var; BACKGROUND-ERROR; KOREAN PENINSULA; SYSTEM; DIAGNOSIS; STATISTICS; FIELDS; IMPACT;
D O I
10.1002/asl.787
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The effects of tuning of length-scale and observation-error on heavy rainfall forecasts are investigated. Length scale and observation error are tuned based on observation minus background (O - B) covariances and theoretically expected cost function values, respectively. Tuned length scale and observation error are applied to radar data assimilation using the Four Dimensional Variational (4D-Var) method. Length-scale tuning leads to improved Quantitative Precipitation Forecast (QPF) skill for heavy precipitation, better analyses, and reduced errors of wind, temperature, humidity, and hydrometeor forecasts. The effects of observation-error tuning are not as significant as those of length-scale tuning, and they are limited to improvements in QPF skill. This is because tuned observation errors are close to pre-assumed values. Proper tuning of length-scale and observation-error is essential for radar data assimilation using the 4D-Var method.
引用
收藏
页码:441 / 448
页数:8
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