GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts
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...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2018/1376235 |
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| author | Wei Cheng Youping Xu Zhiwu Deng Chunli Gu |
| author_facet | Wei Cheng Youping Xu Zhiwu Deng Chunli Gu |
| author_sort | Wei Cheng |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9d904e217bf04e70a9e3c33889c112c3 |
| institution | OA Journals |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-9d904e217bf04e70a9e3c33889c112c32025-08-20T02:20:30ZengWileyAdvances in Meteorology1687-93091687-93172018-01-01201810.1155/2018/13762351376235GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood ForecastsWei Cheng0Youping Xu1Zhiwu Deng2Chunli Gu3State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, ChinaState Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, ChinaInstitute of Applied Meteorology, Beijing 100029, ChinaInstitute of Applied Meteorology, Beijing 100029, ChinaBased 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.http://dx.doi.org/10.1155/2018/1376235 |
| spellingShingle | 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 |
| title | GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts |
| title_full | GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts |
| title_fullStr | GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts |
| title_full_unstemmed | GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts |
| title_short | GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts |
| title_sort | gps radio occultation data assimilation in the arem regional numerical weather prediction model for flood forecasts |
| url | http://dx.doi.org/10.1155/2018/1376235 |
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