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.
| Original language | English |
|---|---|
| Article number | 297 |
| Number of pages | 18 |
| Journal | Geosciences |
| Volume | 8 |
| Issue number | 8 |
| Early online date | 7 Aug 2018 |
| DOIs | |
| Publication status | Published - Aug 2018 |
Research Groups and Themes
- Water and Environmental Engineering
Keywords
- Flow forecast
- Nowcasting
- Probabilistic forecasts
- Radar ensembles