The influence of the meteorological forcing data on the reconstructions of historical storms in the Black Sea

TL;DR

This study evaluates how different meteorological data sources affect the accuracy of historical storm reconstructions in the Black Sea, emphasizing the importance of high-resolution data for reliable coastal hazard assessments.

Contribution

It demonstrates the impact of meteorological forcing data resolution on storm reconstructions and recommends dynamical downscaling for improved accuracy in coastal storm modeling.

Findings

ERA Interim and ERA40 are valuable but limited in resolution.

High-resolution dynamical downscaling improves storm reconstruction accuracy.

Simulations of two historical storms showed significant differences based on data source.

Abstract

The present article is a study of the applicability of different sources of meteorological forcing for the coastal wave and storm surge models, which provide the operational marine forecasts for the coastal early warning systems (EWS) and are used for reconstructions of historical storms. The reconstruction of historical storms is one of the approaches to the natural coastal hazard vulnerability assessment. We evaluate the importance of the input meteorological information for the mentioned types of coastal models. For two well documented historical storms, that caused significant damages along the Bulgarian coast we simulate the significant wave heights and sea level change, using SWAN wave model and a storm surge model. The wind and mean sea level pressure fields, which are used in the present study, are extracted from the ERA Interim reanalysis of the European Center for Medium range Forecasts (ECMWF) and from the output of the high resolution limited area numerical weather prediction model ALADIN. The overall conclusion is that for the successful historical storms reconstructions ERA Interim and ERA40 reanalysis are valuable source of meteorological forcing, but due to their limitations in terms of spatial and temporal resolution, it is recommended to produce a higher spatial and temporal resolution meteorological fields, using dynamical downscaling of the reanalyzed data.