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Assimilation of MWHS radiance data from the FY-3B satellite with the WRF Hybrid-3DVAR system for the forecasting of binary typhoons

作者:重点实验室  发布时间:2016/09/08 15:59:43  浏览量:

Article

Assimilation of MWHS radiance data from the FY-3B satellite with the WRF Hybrid-3DVAR system for the forecasting of binary typhoons

Journal of Advances in Modeling Earth Systems

Xu Dongmei; Min Jinzhong; Shen Feifei; Ban Junmei; Chen Peng

Abstract

Chan-hom and Linfa were binary typhoons that occurred in the western North Pacific in 2015. In this study, the impacts of FY-3B satellite Microwave Humidity Sounder (MWHS) radiance observations on the analyses and forecasts of Linfa and Chan-hom are assessed. The regional Weather Research and Forecasting model and its data assimilation (DA) systems, using three-dimensional variational (3DVAR) and Hybrid (ensemble/3DVAR) methods are used. Assimilation of the FY-3B MWHS data using the 3DVAR method slightly improves the descriptive wind and temperature fields. Positive impacts on the specific humidity forecasts, for levels higher than 850 hPa, are also obvious. 3DVAR adjusts the typhoons' initial positions and their dynamic structures favorably, yielding better tracks, intensities, and precipitation forecasts, compared to the experiment run without MWHS data (control). With the Hybrid method, the water vapor information from the MWHS data better improve the analyses through multivariable correlations with the flow-dependent background error. The Hybrid method further improves the track, intensities, and precipitation forecasts. For Typhoon Linfa, with the coexistence of Typhoon Chan-hom, the Hybrid method provides a more descriptive background error covariance matrix, than using 3DVAR. Experiments on multiple binary typhoon cases are also provided to further validate the robustness of the results on the FY-3B satellite MWHS radiance data assimilation.

Xu D, Min J, Shen F, et al. Assimilation of MWHS radiance data from the FY‐3B satellite with the WRF Hybrid‐3DVAR system for the forecasting of binary typhoons[J]. Journal of Advances in Modeling Earth Systems, 2016, 8(2).

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