Assimilation of radar observations with En3DVAR at cloud-resolving scale for the prediction of Typhoon Saomai

Shen Feifei; Xu Dongmei; Min Jinzhong; Zhang Bing; Li Chao

doi:10.3969/j.issn.0253-4193.2018.05.005

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Article Navigation > Haiyang Xuebao > 2018 > 40(5): 48-61

Shen Feifei, Xu Dongmei, Min Jinzhong, Zhang Bing, Li Chao. Assimilation of radar observations with En3DVAR at cloud-resolving scale for the prediction of Typhoon Saomai[J]. Haiyang Xuebao, 2018, 40(5): 48-61. doi: 10.3969/j.issn.0253-4193.2018.05.005

Citation:

Shen Feifei, Xu Dongmei, Min Jinzhong, Zhang Bing, Li Chao. Assimilation of radar observations with En3DVAR at cloud-resolving scale for the prediction of Typhoon Saomai[J]. Haiyang Xuebao, 2018, 40(5): 48-61. doi: 10.3969/j.issn.0253-4193.2018.05.005

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Assimilation of radar observations with En3DVAR at cloud-resolving scale for the prediction of Typhoon Saomai

doi: 10.3969/j.issn.0253-4193.2018.05.005

1.
Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China
2.
Jiangsu Research Institute of Meteorological Science, Nanjing 210009, China
3.
Nantong Meteorological Bureau, Jiangsu Province, Nantong 226018, China

Received Date: 2017-09-10
Rev Recd Date: 2017-12-10

Abstract

Abstract

The impacts of assimilation of radar radial velocity data (Vr) using ensemble-variational (En3DVAR) data assimilation system based on the Weather Research and Forecasting model (WRF) data assimilation system (WRFDA) for the application of analyses and forecasts for Typhoon Saomai (2006) are investigated. The Vr data at 30-min intervals are assimilated into the WRF model at a cloud-resolving scale using the three-dimensional variational data assimilation (3DVAR) and En3DVAR respectively, over a 3 hour before its landfall. The root-mean-square errors of the Vr data by the En3DVAR were smaller than those by the 3DVAR for Typhoon Saomai. Experiments showed that such improvements were due to the use of the flow-dependent ensemble covariance provided by En3DVAR system. Positive temperature increments are found in Hybrid-En3DVAR experiments, indicating a warming of the inner core with a more realistic thermal structure throughout the depth of the hurricane. In contrast, 3DVAR experiment produces much weaker and smoother increments with negative values at the vortex center at lower levels. In additional, it was found that the En3DVAR, using the flow-dependent covariance that gave the hurricane-specific error covariance estimates, was able to systematically adjust the position of the hurricane during the assimilation whereas the 3DVAR was not. Overall, the analysis and forecasts of the En3DVAR scheme are superior to the 3DVAR scheme assimilating the same Vr Observations.
- radar radial velocity,
- data assimilation,
- En3DVAR,
- numerical simulation

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References(35)

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