Mohamed Saadi, C. Furusho‐Percot, Alexandre Belleflamme, S. Trömel, S. Kollet, R. Reinoso-Rondinel
{"title":"2021年7月德国极端洪水事件的三个基于雷达降水临近预报的比较","authors":"Mohamed Saadi, C. Furusho‐Percot, Alexandre Belleflamme, S. Trömel, S. Kollet, R. Reinoso-Rondinel","doi":"10.1175/jhm-d-22-0121.1","DOIUrl":null,"url":null,"abstract":"\nQuantitative precipitation nowcasts (QPN) can improve the accuracy of flood forecasts especially for lead times up to 12 hours, but their evaluation depends on a variety of factors, namely the choice of the hydrological model and the benchmark. We tested three precipitation nowcasting techniques based on radar observations for the disastrous mid-July 2021 event in seven German catchments (140-1670 km2). Two deterministic (advection-based and S-PROG) and one probabilistic (STEPS) QPN with maximum lead time of 3 h were used as input to two hydrological models: a physically-based, 3D-distributed model (ParFlowCLM) and a conceptual, lumped model (GR4H). We quantified the hydrological added value of QPN compared to hydrological persistence and zero-precipitation nowcasts as benchmarks. For the 14 July 2021 event, we obtained the following key results: (1) According to the quality of the forecasted hydrographs, exploiting QPN improved the lead times by up to 4 h (8 h) compared to adopting zero-precipitation nowcasts (hydrological persistence) as a benchmark. Using a skill-based approach, obtained improvements were up to 7-12 h depending on the benchmark. (2) The three QPN techniques obtained similar performances regardless of the applied hydrological model. (3) Using zero-precipitation nowcasts instead of hydrological persistence as benchmark reduced the added value of QPN. These results highlight the need for combining a skill-based approach with an analysis of the quality of forecasted hydrographs to rigorously estimate the added value of QPN.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Comparison of three radar-based precipitation nowcasts for the extreme July 2021 flooding event in Germany\",\"authors\":\"Mohamed Saadi, C. Furusho‐Percot, Alexandre Belleflamme, S. Trömel, S. Kollet, R. Reinoso-Rondinel\",\"doi\":\"10.1175/jhm-d-22-0121.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nQuantitative precipitation nowcasts (QPN) can improve the accuracy of flood forecasts especially for lead times up to 12 hours, but their evaluation depends on a variety of factors, namely the choice of the hydrological model and the benchmark. We tested three precipitation nowcasting techniques based on radar observations for the disastrous mid-July 2021 event in seven German catchments (140-1670 km2). Two deterministic (advection-based and S-PROG) and one probabilistic (STEPS) QPN with maximum lead time of 3 h were used as input to two hydrological models: a physically-based, 3D-distributed model (ParFlowCLM) and a conceptual, lumped model (GR4H). We quantified the hydrological added value of QPN compared to hydrological persistence and zero-precipitation nowcasts as benchmarks. For the 14 July 2021 event, we obtained the following key results: (1) According to the quality of the forecasted hydrographs, exploiting QPN improved the lead times by up to 4 h (8 h) compared to adopting zero-precipitation nowcasts (hydrological persistence) as a benchmark. Using a skill-based approach, obtained improvements were up to 7-12 h depending on the benchmark. (2) The three QPN techniques obtained similar performances regardless of the applied hydrological model. (3) Using zero-precipitation nowcasts instead of hydrological persistence as benchmark reduced the added value of QPN. These results highlight the need for combining a skill-based approach with an analysis of the quality of forecasted hydrographs to rigorously estimate the added value of QPN.\",\"PeriodicalId\":15962,\"journal\":{\"name\":\"Journal of Hydrometeorology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hydrometeorology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1175/jhm-d-22-0121.1\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrometeorology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/jhm-d-22-0121.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Comparison of three radar-based precipitation nowcasts for the extreme July 2021 flooding event in Germany
Quantitative precipitation nowcasts (QPN) can improve the accuracy of flood forecasts especially for lead times up to 12 hours, but their evaluation depends on a variety of factors, namely the choice of the hydrological model and the benchmark. We tested three precipitation nowcasting techniques based on radar observations for the disastrous mid-July 2021 event in seven German catchments (140-1670 km2). Two deterministic (advection-based and S-PROG) and one probabilistic (STEPS) QPN with maximum lead time of 3 h were used as input to two hydrological models: a physically-based, 3D-distributed model (ParFlowCLM) and a conceptual, lumped model (GR4H). We quantified the hydrological added value of QPN compared to hydrological persistence and zero-precipitation nowcasts as benchmarks. For the 14 July 2021 event, we obtained the following key results: (1) According to the quality of the forecasted hydrographs, exploiting QPN improved the lead times by up to 4 h (8 h) compared to adopting zero-precipitation nowcasts (hydrological persistence) as a benchmark. Using a skill-based approach, obtained improvements were up to 7-12 h depending on the benchmark. (2) The three QPN techniques obtained similar performances regardless of the applied hydrological model. (3) Using zero-precipitation nowcasts instead of hydrological persistence as benchmark reduced the added value of QPN. These results highlight the need for combining a skill-based approach with an analysis of the quality of forecasted hydrographs to rigorously estimate the added value of QPN.
期刊介绍:
The Journal of Hydrometeorology (JHM) (ISSN: 1525-755X; eISSN: 1525-7541) publishes research on modeling, observing, and forecasting processes related to fluxes and storage of water and energy, including interactions with the boundary layer and lower atmosphere, and processes related to precipitation, radiation, and other meteorological inputs.