Session 4

A set of 103 surface-water flooding events in the UK over the period 2015 – 2021 has been identified using impact reports from a variety of sources. For inclusion, flooding impacts had to meet basic severity criteria (broadly comprising internal flooding of multiple properties, or disruption to key infrastructure such as hospitals) and the flooding had to be associated with deep, moist convection (assessed by analysis of radar data in conjunction with the flood reports). The synoptic-scale, mesoscale and storm-scale environments of the identified events were explored using ERA5 reanalysis data, radar data and surface meso-analysis, the latter incorporating bias-corrected observations from a network of home automatic weather stations. One of the main findings is that surface-water flooding events in the UK often occurred in environments of relatively weak vertical wind shear (median effective bulk wind difference = 12.8 knots) and small buoyant instability (median MUCAPE = 561 J kg^-1), though a few cases exhibited much larger vertical wind shear and CAPE. Mesoscale features such as convergence lines were often important in focussing repeated convection initiation over a small area. In this presentation, results of the work will be described in more detail, and some conclusions drawn about the typical characteristics of surface-water-flood-producing storms in the UK.

How to cite: Clark, M.: Characteristics and environments of flash-flood-producing storms in the UK, 11th European Conference on Severe Storms, Bucharest, Romania, 8–12 May 2023, ECSS2023-68, https://doi.org/10.5194/ecss2023-68, 2023.

Deep summertime convection associated with heavy rain and flooding endangers life and property. Radar derived quantitative precipitation estimates (QPE) play an important role as input for hydrological models and flash flood warnings. QPE is also one of the key inputs for nowcasting applications and seamless forecasting products as developed by the SINFONY (Seamless INtegrated FOrecastiNg sYstem)-project of Deutscher Wetterdienst (DWD).

Currently, the QPE at the DWD follows a hydrometeor-based approach, where reflectivity-rainfall rate relationships are selected depending on the results of a hydrometeor classification scheme. Each solid hydrometeor, such as hail, graupel or snow, has its own reflectivity-rainfall rate relationship, while the liquid phase also includes a proxy for convective or stratiform rain depending on the gradient in the reflectivity field.

According to literature, dual-polarimetric radar moments can directly be used to derive QPE. Gorgucci et al., 1994 showed an improvement in rain rate by combining the radar reflectivity and the differential reflectivity (ZDR) to derive the QPE. Chen et al., 2021 favored a combination of reflectivity and the specific differential phase (KDP) to estimate rain rates for the German C-Band radars. While heavy precipitation attenuates the reflectivity and thus leads to an underestimation of QPE, KDP is immune to attenuation. 

We compare these two methods to the current operational algorithm and perform a verification with ground stations (ombrometer) based on hourly precipitation accumulations. The analysis will focus on a case study of the flooding event in Germany in July 2021 and might extent to a full convective season. First results show an improvement in QPE when KDP is used for stronger liquid precipitation. 

References
•    Chen et al., 2021: Assessing the benefits of specific attenuation for quantitative precipitation estimation with a C-band radar network, Journal of Hydrometeorology, 22, 2617–2631.
•    Gorgucci et al., 1994: A robust estimator of rainfall rate using differential reflectivity, Journal of Atmospheric & Oceanic Technology, 11, 586-592

How to cite: Gottschalk, M. and Hengstebeck, T.: Using dual-polarimetric radar moments to improve the precipitation estimate over Germany, 11th European Conference on Severe Storms, Bucharest, Romania, 8–12 May 2023, ECSS2023-97, https://doi.org/10.5194/ecss2023-97, 2023.

Warnings of extreme precipitation averaged over a small area and during a short duration are needed by people and the public services to ensure their safety. For these localized extreme events, accurate statistics can be derived from radar-based precipitation estimation using a regional analysis. This method has already been applied for rainfall averaged over a square of 1 km by Goudenhoofdt, Delobbe and Willems (2017). The extreme statistics can then be combined in realtime with precipitation estimation or nowcasting to provide relevant warnings. For this purpose web and smartphone applications can be developed to let the user define areas, durations and return periods of interest. Additional parameters could be added in the framework of a probabilistic approach.

In the first step of this project, we need to perform the extreme value analysis. The quality of a 10-year radar rainfall product for extreme events will be analyzed by comparison with independent rain gauge measurements. The principles of the regional frequency analysis will be presented together with the underlying hypothesis on the rainfall process. The statistical method will be tested using rectangles with different length, width and orientation. This will allow to analyze the impact of these parameters on the extreme precipitation statistics. Eventually the possibility to extent the method to any given small area will be discussed.

How to cite: Goudenhoofdt, E.: Radar-based extreme rainfall analysis for small areas, 11th European Conference on Severe Storms, Bucharest, Romania, 8–12 May 2023, ECSS2023-152, https://doi.org/10.5194/ecss2023-152, 2023.