Optimal Localization for Ensemble Kalman Filter Systems

Journal of the Meteorological Society of Japan. Ser. II

África PERIÁÑEZ¹  Hendrik REICH¹  Roland POTTHAST¹ 

[1] Deutscher Wetterdienst, Data Assimilation Unit, Offenbach, Germany

关键词: ensemble Kalman filter;    localization;    adaptive methods;   

DOI  :  10.2151/jmsj.2014-605

学科分类：大气科学

来源: Meteorological Society of Japan

【 摘 要 】

 In ensemble Kalman filter methods, localization is applied for both avoiding the spurious correlations of distant observations and increasing the effective size of the ensemble space. The procedure is essential in order to provide quality assimilation in large systems; however a severe localization can cause imbalances that impact negatively on the accuracy of the analysis. We want to understand the fundamental properties of localized ensemble methods and to investigate an optimal localization expression which minimizes the analysis error. The novel analytical expression derived in this work depends on the observation error, the density of measurements, and the approximation error, i.e., the error that comes from working in the ensemble space. The mathematical results are tested with two numerical simulations using a toy model. We demonstrate that observations with different observation error or density need different localization length scales.

【 授权许可】

Unknown