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- W4322009874 abstract "Accurate predictions of heavy and intense rainfall are vital for impact-based forecasting that can be essential for mitigating the significant damage and loss of life across the globe. However, producing reliable forecasts capable of capturing the rainfall values is challenging in complex mountain terrain due to the forecast uncertainty and computational cost especially in data-scarce regions. Central Asia is one of these regions, where extreme rainfall leads to flash floods, landslides and debris flows in the mountains and foothills. The risk of these events increases with global warming, and the early warning systems based on reliable forecasts are particularly important to manage the risk in the region and adapt to climate change.In this study, we have evaluated and compared the skills of two probabilistic forecasts developed by the European Centre for Medium-Range Weather Forecasts (ECMWF): standard Ensemble Forecasts (ENS) which consists of an ensemble of 51 members and ecPoint Rainfall produced by statistical post-processing of the ENS and delivers probabilistic forecasts of rainfall totals for points within a model gridbox (18 km resolution) that can be particularly useful in the mountains. Skills of both forecasts were assessed in relation to the forecast of debris flows in Central Asia.Both forecast products were verified against SYNOP (surface synoptic observations) data for stations over Central Asia, mainly for the debris flow season (March-October) in 2022. In this case, two popular verification methods were used: Brier Score and Receiver Operating Characteristics (ROC) diagram for the exceedance of precipitation thresholds of 1 mm, 10 mm and 25 mm.Verification trials over the 2022 debris flow season in Central Asia show that the performance of ecPoint Rainfall depending on the forecast lead-time can be a good proxy for the range of point rainfall values to define the warning areas of debris flow risk over the study area. The ecPoint Rainfall is recommended for the operational application of heavy rainfall leading to debris flow formation which can support impact-orientated forecasting and early warning systems in Central Asia." @default.
- W4322009874 created "2023-02-26" @default.
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- W4322009874 date "2023-05-15" @default.
- W4322009874 modified "2023-09-29" @default.
- W4322009874 title "Debris flows risk assessment for Central Asia by application of Global Ensemble Output and Post-processed Precipitation" @default.
- W4322009874 doi "https://doi.org/10.5194/egusphere-egu23-13338" @default.
- W4322009874 hasPublicationYear "2023" @default.
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