Statistical characterization of rainfall fields based upon a 12-year high-resolution radar archive of Belgium

Abstract

Spatial and temporal variability of rainfall input plays a critical role on the performance of the urban runoff simulations. For this reason, urban hydrological application demands accurate products of high-resolution and high-quality rainfall estimates, which use and understanding become critical for more robust models.In this study, the spatial and temporal characteristics of rainfall in Belgium are analyzed at fine scales. This is done by constructing a conceptual rain storm model using historical long-term radar data archive. This application involved the use of a state-of-the-art tracking algorithm, developed by Muñoz et al. (2018), to associate the spatial and temporal variations in rain storms and cells This algorithm enables better handling of high-resolution details and is capable of extracting rainfall objects/entities across various scales. Through tracking and conceptualizing these storm entities, spatial and temporal rainfall properties, such as geometric features, intensities, velocity, rainfall types or spatial patterns, can be extracted and analyzed. To accomplish this, twelve years of continuous high-resolution radar data are utilized in this work. The resulting analysis of the spatial and temporal characteristics of rainfall radar data is intended to set the ground for the future applications. More specifically, it can be used to refine and improve the existing long-term spatial rainfall generators, such as that the one implemented by Willems' in 2001.