Long-term analysis of gauge-adjusted radar rainfall accumulations at European scale

TL;DR

This study evaluates the quality of high-resolution European radar rainfall data (OPERA) over 2015-2017, demonstrating that bias adjustment improves accuracy and supports flash flood detection.

Contribution

It introduces a simple bias adjustment method for radar rainfall data and assesses its effectiveness over multiple years at a continental scale.

Findings

Bias adjustment improves rainfall estimation accuracy.

OPERA data quality has gradually improved over the years.

Enhanced data quality benefits flash flood detection efforts.

Abstract

Monitoring continental precipitation over Europe with high resolution (2 km, 15 minutes) has been possible since the operational production of the OPERA composites from the European weather radar networks. The OPERA data are the essential input to a hazard assessment tool for identifying localized rainfall-induced flash floods at European scale, and their quality determines the performance of the tool. This paper analyses the OPERA data quality during the warm seasons of 2015-2017 by comparing the estimated rainfall accumulations with the SYNOP rain gauge records over Europe. To compensate the OPERA underestimation, a simple spatially-variable bias adjustment method has been applied. The long-term comparison between the OPERA and gauge point daily rainfall accumulations at the gauge locations shows the benefit of the bias adjustment. Additionally, the daily monitoring shows gradual improvement of the OPERA data year by year. The impact of the quality of the OPERA data for effective flash flood identification is demonstrated for the case of the flash floods that occurred from 29 May to 3 June 2016 in central Europe.