Accelerating the EnKF spinup for typhoon assimilation and prediction

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Title:	Accelerating the EnKF spinup for typhoon assimilation and prediction
Authors:	楊舒芝;Yang, Shu-Chih;Kalnay, Eugenia;Miyoshi, Takemasa
Contributors:	地球科學學院大氣科學學系
Keywords:	Cold;Data assimilation;Data collection;Earth, ocean, space;Environmental conditions;Exact sciences and technology;External geophysics;Meteorology;Problems;Storms, hurricanes, tornadoes, thunderstorms;Studies;Tropical cyclones;Typhoons;Weather analysis and prediction
Date:	2012-08-01
Issue Date:	2026-04-21 13:36:09 (UTC+8)
Publisher:	American Meteorological Society;Boston, MA: American Meteorological Society
Abstract:	摘要： AbstractA mesoscale ensemble Kalman filter (EnKF) for a regional model is often initialized from global analysis products and with initial ensemble perturbations constructed based on the background error covariance used in the three-dimensional variational data assimilation (3DVar) system. Because of the lack of proper mesoscale information, a long spinup period of typically a few days is required for the regional EnKF to reach its asymptotic level of accuracy, and thus, the impact of observations is limited during the EnKF spinup. For the case of typhoon assimilation, such spinup usually corresponds to the stages of generation and development of tropical cyclones, when observations are important but limited over open waters. To improve the analysis quality during the spinup, the “running in place” (RIP) method is implemented within the framework of the local ensemble transform Kalman filter (LETKF) coupled with the Weather Research and Forecasting model (WRF). Results from observing system simulation experiments (OSSEs) for a specific typhoon show that the RIP method is able to accelerate the analysis adjustment of the dynamical structures of the typhoon during the LETKF spinup, and improves both the accuracy of the mean state and the structure of the ensemble-based error covariance. These advantages of the RIP method are found not only in the inner-core structure of the typhoon but also identified in the environmental conditions. As a result, the LETKF-RIP analysis leads to better typhoon prediction, particularly in terms of both track and intensity. 出版者： Boston, MA: American Meteorological Society 出版日期： 2012-08-01 出處： Weather and Forecasting, 2012-08, Vol.27 (4), p.878-897 資源來源： Agricultural & Environmental Science Collection 版權： 2015 INIST-CNRS 版權： Copyright American Meteorological Society Aug 2012 識別號： ISSN: 0882-8156 識別號： EISSN: 1520-0434 識別號： DOI: 10.1175/waf-d-11-00153.1 識別號： CODEN: WEFOE3
Appears in Collections:	[Department of Atmospheric Sciences] journal & Dissertation

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