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Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

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  • 1 Delft University of Technology, Delft, Netherlands, and King Abdullah University of Science and Technology, Thuwal, Saudia Arabia
  • | 2 Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas
  • | 3 International Research Institute of Stavanger, Bergen, Norway
  • | 4 Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas
  • | 5 King Abdullah University of Science and Technology, Thuwal, Saudia Arabia
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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.

Corresponding author address: M. U. Altaf, Department of Applied Mathematics, Delft University of Technology, Mekelweg 4, Delft, 2628CD, Netherlands. E-mail: m.u.altaf@tudelft.nl

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.

Corresponding author address: M. U. Altaf, Department of Applied Mathematics, Delft University of Technology, Mekelweg 4, Delft, 2628CD, Netherlands. E-mail: m.u.altaf@tudelft.nl
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