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

页码：441 / 448

页数：8

共 29 条

[21] Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave [J].