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Advances in Meteorology Volume 2018 ,2018-11-11
GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts
Research Article
Wei Cheng 1 , 2 Youping Xu 1 , 2 Zhiwu Deng 2 Chunli Gu 2
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DOI:10.1155/2018/1376235
Received 2018-08-06, accepted for publication 2018-10-02, Published 2018-10-02
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摘要

Based on the Backward Four-Dimensional Variational Data Assimilation (Backward-4DVar) system with the Advanced Regional Eta-coordinate Model (AREM), which is capable of assimilating radio occultation data, a heavy rainfall case study is performed using GPS radio occultation (GPS RO) data and routine GTS data on July 5, 2007. The case study results indicate that the use of radio occultation data after quality control can improve the quality of the analysis to be similar to that of the observations and, thus, have a positive effect when improving 24-hour rainfall forecasts. Batch tests for 119 days from May to August during the flood season in 2009 show that only the use of GPS RO data can make positive improvements in both 24-hour and 48-hour regional rainfall forecasts and obtain a better B score for 24-hour forecasts and better TS score for 48-hour forecasts. When using radio occultation refractivity data and conventional radiosonde data, the results indicate that radio occultation refractivity data can achieve a better performance for 48-hour forecasts of light rain and heavy rain.

授权许可

Copyright © 2018 Wei Cheng et al. 2018
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

图表

The distribution of GPS RO data in the case study (assimilation time window from 18 UTC on July 3, 2007, to 00 UTC on July 4, 2007) [12].

Comparison of different initial values and occultation refractivity observations in the middle-upper troposphere (a) and middle-lower troposphere (b) ○ represents actual occultation observations (OBS), • stands for the reference control test (CTRL), □ represents the nonquality control scheme (REF_NQC), and ■ represents the quality control scheme (REF_QC).

Comparison of different initial values and occultation refractivity observations in the middle-upper troposphere (a) and middle-lower troposphere (b) ○ represents actual occultation observations (OBS), • stands for the reference control test (CTRL), □ represents the nonquality control scheme (REF_NQC), and ■ represents the quality control scheme (REF_QC).

24-hour cumulative precipitation forecast difference between the quality control plan (REF_QC) and nonquality control plan (REF_NQC) (Figure 3a; unit: mm) and the difference in the initial values of the data assimilation analysis (Figure 3b: 700 hPa; Figure 3c: 500 hPa). The contour represents geopotential height increments (unit: GPM). The arrow vectors represent wind speed increments in m/s.

24-hour cumulative precipitation forecast difference between the quality control plan (REF_QC) and nonquality control plan (REF_NQC) (Figure 3a; unit: mm) and the difference in the initial values of the data assimilation analysis (Figure 3b: 700 hPa; Figure 3c: 500 hPa). The contour represents geopotential height increments (unit: GPM). The arrow vectors represent wind speed increments in m/s.

24-hour cumulative precipitation forecast difference between the quality control plan (REF_QC) and nonquality control plan (REF_NQC) (Figure 3a; unit: mm) and the difference in the initial values of the data assimilation analysis (Figure 3b: 700 hPa; Figure 3c: 500 hPa). The contour represents geopotential height increments (unit: GPM). The arrow vectors represent wind speed increments in m/s.

Comparison of the (a) TS score and (b) B score for 24-hour cumulative precipitation across several schemes from May 4, 2009, to August 30, 2009.

Comparison of the (a) TS score and (b) B score for 24-hour cumulative precipitation across several schemes from May 4, 2009, to August 30, 2009.

Comparison of the (a) TS score and (b) B score for 48-hour cumulative precipitation across several schemes from May 4, 2009, to August 30, 2009.

Comparison of the (a) TS score and (b) B score for 48-hour cumulative precipitation across several schemes from May 4, 2009, to August 30, 2009.

Comparison of the 24-hour cumulative precipitation (a) TS scores and (b) B scores for several schemes from May 4, 2009, to August 30, 2009.

Comparison of the 24-hour cumulative precipitation (a) TS scores and (b) B scores for several schemes from May 4, 2009, to August 30, 2009.

Comparison of the 48-hour cumulative precipitation (a) TS scores and (b) B scores for several schemes from May 4, 2009, to August 30, 2009.

Comparison of the 48-hour cumulative precipitation (a) TS scores and (b) B scores for several schemes from May 4, 2009, to August 30, 2009.

通讯作者

Wei Cheng.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China, cas.cn;Institute of Applied Meteorology, Beijing 100029, China.chengw@mail.iap.ac.cn

推荐引用方式

Wei Cheng,Youping Xu,Zhiwu Deng,Chunli Gu. GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts. Advances in Meteorology ,Vol.2018(2018)

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