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Evento
BHS-YHS Gotta catch'em all October 2025 Episode
Abstract: Weather radar provides essential information about rainfall in space and time, needed for applications (e.g. flood risk assessment), yet radar products are prone to errors that can lead to significant underestimation or omission of rainfall in extreme conditions. This study investigates how often weather radar misses rainfall using a stochastic simulation framework that generates synthetic true rainfall events and applies a parametrised radar error model.
The results demonstrate systematic impacts on rainfall distributions: non-zero rainfall marginals become more peaked with reduced extremes, while spatial inconsistencies give rise to rainfall shadows defined as areas where significant rainfall is lost even after correction methods. Analysis shows that 90% of simulated radar images exhibit at least 1% rainfall shadowing, and in 50% of cases more than 45 km of significant rainfall is lost. These findings highlight the scale and complexity of radar errors, their implications for hydrological applications, and the challenges of quality control. Future research will explore enhanced estimation methods, radar-gauge merging, machine learning approaches, and probabilistic techniques to improve radar rainfall reliability.
About our Presenter: Amy Green is a Research Associate in the Water Group at Newcastle University, specialising in climate science and hydrology. Her research focuses on the quantification and prediction of hydrological extremes, with an emphasis on improving understanding of extreme rainfall in a changing climate. Her current work on the IMPETUS4CHANGE project (Horizon Europe), where her work involves validating climate model outputs through the application of hazard indices, with a particular focus on extreme precipitation. Previously, she was a researcher on the PYRAMID project (NERC), developing a novel platform for dynamic, near real-time flood risk assessment by integrating novel and hidden data sources in a digital twin framework. Amy completed her PhD at Newcastle University in 2022, titled improving radar rainfall estimation for flood risk using Monte Carlo ensemble simulation. Prior to this she obtained an MMathStat degree, during which she investigated extreme wind speeds for the nuclear industry, which developed her passion for environmental extremes.
In addition to her research, she is actively engaged in the hydrological community. She is the Early Career Representative and a trustee for the British Hydrological Society and is also strongly committed to the communication of science, with experience in organising conferences and developing innovative approaches to the visualisation of complex datasets, including interactive dashboards and Shiny applications. Her research interests include weather radar, hydrological extremes, statistical modelling, gridded rainfall products and better open-access data and coding practices.
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UbicaciónMicrosoft Teams
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