Variational data assimilation of sea surface height into a regional storm surge model: Benefits and limitations

Byrne, David; Horsburgh, Kevin ORCID: https://orcid.org/0000-0003-4803-9919; Williams, Jane. 2021 Variational data assimilation of sea surface height into a regional storm surge model: Benefits and limitations. Journal of Operational Oceanography, 14. 1-14. https://doi.org/10.1080/1755876X.2021.1884405

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Abstract/Summary

Storm surges are coastal sea-level variations caused by meteorological conditions. It is vital that they are forecasted accurately to reduce the potential for financial damage and loss of life. In this study, we investigate how effectively the variational assimilation of sparse sea level observations from tide gauges can be used for operational forecasting in the North Sea. Novel data assimilation ideas are considered and evaluated: a new shortest-path method for generating improved distance-based correlations in the presence of coastal boundaries and an adaptive error covariance model. An assimilation setup is validated by removing selections of tide gauges from the assimilation procedure for a North Sea case study. These experiments show widespread improvements in RMSE and correlations, reaching up to 16 cm and 0.7 (respectively) at some locations. Simulated forecast experiments show RMSE improvements of up to 5 cm for the first 24 h of forecasting, which is useful operationally. Beyond 24 h, improvements quickly diminish however. Using the setup based on the shortest path algorithm shows little difference when compared to a simpler Euclidean method at most locations. Analysis of this event shows that improvements due to data assimilation are bounded and relatively short lived.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1080/1755876X.2021.1884405
ISSN:	1755-876X
Date made live:	01 Mar 2021 13:40 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/529769

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