Improving short-range ensemble Kalman storm surge forecasting using robust adaptive inflation

Journal article (2013)
Department
Applied Mathematics (EEMCS) (TU Delft)
Copyright: © 2013 American Meteorological Society
DOI: https://doi.org/doi:10.1175/MWR-D-12-00310.1
More Info
expand_more

Published Date

31-08-2013

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Source:

Monthly weather review, 141 (8), 2013

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Applied Mathematics

Abstract

This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H? filter. By design, an H? filter is more robust than the common Kalman filter in the sense that the estimation error in the H? filter has, in general, a finite growth rate with respect to the uncertainties in assimilation. The computational hydrodynamical model used in this study is the Advanced Circulation (ADCIRC) model. The authors assimilate data obtained from Hurricanes Katrina and Ike as test cases. The results clearly show that the H?-based SEIK filter provides more accurate short-range forecasts of storm surge compared to recently reported data assimilation results resulting from the standard SEIK filter.