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Geosciences 2018, 8(8), 297; https://doi.org/10.3390/geosciences8080297

Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications

Department of Civil Engineering, University of Bristol, Bristol BS8 1TR, UK
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Received: 31 May 2018 / Revised: 27 July 2018 / Accepted: 30 July 2018 / Published: 7 August 2018
(This article belongs to the Special Issue Hydrology of Urban Catchments)
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Abstract

Radar rainfall forecasting is of major importance to predict flows in the sewer system to enhance early flood warning systems in urban areas. In this context, reducing radar rainfall estimation uncertainties can improve rainfall forecasts. This study utilises an ensemble generator that assesses radar rainfall uncertainties based on historical rain gauge data as ground truth. The ensemble generator is used to produce probabilistic radar rainfall forecasts (radar ensembles). The radar rainfall forecast ensembles are compared against a stochastic ensemble generator. The rainfall forecasts are used to predict sewer flows in a small urban area in the north of England using an Infoworks CS model. Uncertainties in radar rainfall forecasts are assessed using relative operating characteristic (ROC) curves, and the results showed that the radar ensembles overperform the stochastic ensemble generator in the first hour of the forecasts. The forecast predictability is however rapidly lost after 30 min lead-time. This implies that knowledge of the statistical properties of the radar rainfall errors can help to produce more meaningful radar rainfall forecast ensembles. View Full-Text
Keywords: nowcasting; flow forecast; radar ensembles; probabilistic forecasts nowcasting; flow forecast; radar ensembles; probabilistic forecasts
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Codo, M.; Rico-Ramirez, M.A. Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications. Geosciences 2018, 8, 297.

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