Urban flood modelling using probabilistic radar rainfall ensembles (URFLOODPRE)

The quantitative measurement and forecasting of precipitation is crucial for predicting and mitigating the effects of flood-producing storms. In recent years the UK has experienced devastating flooding events such as Boscastle in 2004, Carlisle in 2005, Tewksbury in 2007, the Morpeth floods in 2008, and the Cumbria floods in 2009. The main goal in flood forecasting is to provide reliable information to the general public, local authorities, and emergency services under the threat of potential flooding. Although significant progress has been made in the measurement and forecasting of precipitation using weather radars and numerical weather prediction models, there is a need to improve the estimation and forecasting of precipitation during extreme rainfall events in particular, not only for flood prediction in large rural catchments but also for applications in urban hydrology. Real-time flood forecasting systems for flood prediction and warning in urban areas require measurements and forecasts of precipitation with high spatial and temporal resolutions. Weather radar systems are able to provide such measurements, but unfortunately radar rainfall estimations are affected by different sources of error. These errors have been difficult to quantify and traditionally ignored when producing radar-based precipitation forecasts for urban flood forecasting. Accurate, reliable and timely quantitative precipitation forecasting is an important and challenging task that it is now crucial for the reduction of hazard and the preservation of life and property in large urban areas in the probability of flooding. The aim of this research is to develop a probabilistic urban flood forecasting system that integrates information from radar and Numerical Weather Prediction (NWP) models for the real-time prediction and management of severe storms affecting urban areas.

Impact Plan With the prospect of the severe effects due to climate change over the next couple of centuries, the way in which we manage the impact of extreme storms - unpredictably occurring in different climate zones all around the world - is now crucial for the reduction of hazard and the preservation of life and property in large urban areas. This problem is world-wide and relevant to all Member States of the European Union, as well as major/mega cities in the developing world. This proposal will target a novel technique to provide uncertainty information in radar rainfall estimations to improve quantitative precipitation forecasting, beyond the current state-of-the-art, for the real-time prediction and management of severe storms in urban areas. Non-academic beneficiaries According to the Pitt review, during 2007 there were over 200 floods worldwide, which affected more than 180 million people. The most expensive of all these events was the summer floods in the UK, which is estimated to have cost over 3 billion in insurance payouts, 13 people lost their lives and approximately 48,000 houses and 7300 businesses were flooded1. Efficient methods of flood prediction allow valuable time for safe evacuation and relocation of the population. By having a robust system in place, although the flood cannot be prevented, authorities will be provided with reliable data to allow them to make informed decisions. The outputs of the proposed research work will have an indirect benefit to the society by improving the quality of life through better forecasting. The immediate beneficiaries of this research are UK organisations such as the Environment Agency, and the Met Office, which ultimately are the responsible to issue warnings in the possibility of flooding. Working together with the end users and using their input will shape the direction of the proposed research and will contribute to the overall objectives of this project. The engagement with the end users will be carried out by holding 2 research workshops at the University of Bristol. Routes and resources for dissemination The PI will provide leadership for the project and will be the responsible for monitoring impact. For instance, under the FRMRC1 project, the PI developed an algorithm using artificial intelligence techniques to classify non-meteorological echoes using polarimetric radar precipitation measurements, and implemented his algorithm into the Met Office (MO) radar data processing system. The MO is currently in the process of upgrading all UK radars to polarimetric systems and the algorithm developed by the PI under the FRMRC1 project will be very valuable for real-time removal of non-meteorological echoes in weather radar rainfall estimation. Equally, the new algorithms developed under this new project will be provided to the MO so that they can be used operationally. The dissemination of results to the end users and scientific community will be done through the publication of results in refereed international journals and conferences, as well as reports and presentations, which will be made publicly available online at the PI's current web-site at the University of Bristol. The information will be available on this web-site even after the grant has finished. Additional mechanisms for communication to beneficiaries include presentations at International conferences listed under the section 'justification of the resources', and presentations at the proposed research workshops. This project will deliver a highly trained post-doctoral professional in the areas of flood forecasting and quantitative precipitation estimation and forecasting with radar. This will help to the shortage of skilled people in the areas of weather radar and flood risk in the UK. Such expertise directly benefits the UK. 1Pitt, M (2008), The Pitt Review - Learning Lessons from the 2007 Summer Floods, Cabinet Office.