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Tono Dam of West Africa. Wehbe et al. (2019) addressed the potential of WRF-Hydro in the short-term hydrological and meteorological predictions in an extreme weather event in an arid region of the United Arab Emirates. Furthermore, Lin et al. (2018) implemented a vector-based river network into the WRF-Hydro to enhance the flood discharge simulation in a hurricane storm event. Arnault et al. (2019) developed a joint soil–vegetation–atmospheric water tagging procedure with WRF-Hydro to assess
Tono Dam of West Africa. Wehbe et al. (2019) addressed the potential of WRF-Hydro in the short-term hydrological and meteorological predictions in an extreme weather event in an arid region of the United Arab Emirates. Furthermore, Lin et al. (2018) implemented a vector-based river network into the WRF-Hydro to enhance the flood discharge simulation in a hurricane storm event. Arnault et al. (2019) developed a joint soil–vegetation–atmospheric water tagging procedure with WRF-Hydro to assess
the performance of PDIR-Now in capturing the seasonal cycle of precipitation, based on monthly precipitation, with GPCP 1DD precipitation being used as a baseline for evaluation. We carry out the analysis at two regions with distinct rainfall seasonal cycles. The first region (location 1) is a rectangular region bounded by the latitudes (1°–6°N) and the longitudes (16°–21°E). This region lies at the northwestern part of the Congo River basin with elevation in the range of 0–700 m above sea level
the performance of PDIR-Now in capturing the seasonal cycle of precipitation, based on monthly precipitation, with GPCP 1DD precipitation being used as a baseline for evaluation. We carry out the analysis at two regions with distinct rainfall seasonal cycles. The first region (location 1) is a rectangular region bounded by the latitudes (1°–6°N) and the longitudes (16°–21°E). This region lies at the northwestern part of the Congo River basin with elevation in the range of 0–700 m above sea level
summer, TE is dominantly from north or west, with very broad distributions in some regions, reflecting the large variety of precipitation causes in this season ( Kunkel et al. 2012 ). Southwest (California, Lower Colorado, Rio Grande): Here, TE is dominantly from south or southwest in winter. This reflects precipitation events due to atmospheric rivers that convey moisture from the Pacific Ocean during this season ( Gershunov et al. 2017 ). In the summer when conditions are relatively drier in most
summer, TE is dominantly from north or west, with very broad distributions in some regions, reflecting the large variety of precipitation causes in this season ( Kunkel et al. 2012 ). Southwest (California, Lower Colorado, Rio Grande): Here, TE is dominantly from south or southwest in winter. This reflects precipitation events due to atmospheric rivers that convey moisture from the Pacific Ocean during this season ( Gershunov et al. 2017 ). In the summer when conditions are relatively drier in most
flash flooding, geomorphological parameters were derived from the National Elevation Dataset (NED; http://ned.usgs.gov/ ) digital elevation model (DEM) across the CONUS. To ensure compatibility between DEM-based flow accumulations and the actual river network, flow accumulation and direction was extracted by delineating basins with USGS stations, and the National Hydrography Dataset (NHD; http://nhd.usgs.gov/ ) was used to resample the 30-m DEM to a 1-km grid. The geomorphologic parameters for
flash flooding, geomorphological parameters were derived from the National Elevation Dataset (NED; http://ned.usgs.gov/ ) digital elevation model (DEM) across the CONUS. To ensure compatibility between DEM-based flow accumulations and the actual river network, flow accumulation and direction was extracted by delineating basins with USGS stations, and the National Hydrography Dataset (NHD; http://nhd.usgs.gov/ ) was used to resample the 30-m DEM to a 1-km grid. The geomorphologic parameters for
improve GPM IMERG precipitation product over the Brahmaputra river basin . Forecasting , 2 , 248 – 266 , https://doi.org/10.3390/forecast2030014 . Boukabara , S. A. , and Coauthors , 2011 : MiRS: An all-weather 1DVAR satellite data assimilation and retrieval system . IEEE Trans. Geosci. Remote Sens. , 49 , 3249 – 3272 , https://doi.org/10.1109/TGRS.2011.2158438 . Boukabara , S. A. , V. Krasnopolsky , J. Q. Stewart , E. S. Maddy , N. Shahroudi , and R. N. Hoffman , 2019
improve GPM IMERG precipitation product over the Brahmaputra river basin . Forecasting , 2 , 248 – 266 , https://doi.org/10.3390/forecast2030014 . Boukabara , S. A. , and Coauthors , 2011 : MiRS: An all-weather 1DVAR satellite data assimilation and retrieval system . IEEE Trans. Geosci. Remote Sens. , 49 , 3249 – 3272 , https://doi.org/10.1109/TGRS.2011.2158438 . Boukabara , S. A. , V. Krasnopolsky , J. Q. Stewart , E. S. Maddy , N. Shahroudi , and R. N. Hoffman , 2019
.1175/JHM-D-15-0094.1 Mahoney , K. , and Coauthors , 2016 : Understanding the role of atmospheric rivers in heavy precipitation in the southeast United States . Mon. Wea. Rev. , 144 , 1617 – 1632 , https://doi.org/10.1175/MWR-D-15-0279.1 . 10.1175/MWR-D-15-0279.1 Matsui , T. , and Coauthors , 2014 : Introducing multisensor satellite radiance-based evaluation for regional Earth System modeling . J. Geophys. Res. Atmos. , 119 , 8450 – 8475 , https://doi.org/10.1002/2013JD021424 . 10
.1175/JHM-D-15-0094.1 Mahoney , K. , and Coauthors , 2016 : Understanding the role of atmospheric rivers in heavy precipitation in the southeast United States . Mon. Wea. Rev. , 144 , 1617 – 1632 , https://doi.org/10.1175/MWR-D-15-0279.1 . 10.1175/MWR-D-15-0279.1 Matsui , T. , and Coauthors , 2014 : Introducing multisensor satellite radiance-based evaluation for regional Earth System modeling . J. Geophys. Res. Atmos. , 119 , 8450 – 8475 , https://doi.org/10.1002/2013JD021424 . 10
generation of precipitation fraction at high resolution with a multiscale constraint from satellite observations . Quart. J. Roy. Meteor. Soc. , 144 , 176 – 190 , https://doi.org/10.1002/qj.3314 . 10.1002/qj.3314 Haberlandt , U. , and C. Gattke , 2004 : Spatial interpolation vs. simulation of precipitation for rainfall-runoff modelling—A case study in the Lippe River basin. Hydrology: Science and practice for the 21st century: Proceedings of the British Hydrological Society International
generation of precipitation fraction at high resolution with a multiscale constraint from satellite observations . Quart. J. Roy. Meteor. Soc. , 144 , 176 – 190 , https://doi.org/10.1002/qj.3314 . 10.1002/qj.3314 Haberlandt , U. , and C. Gattke , 2004 : Spatial interpolation vs. simulation of precipitation for rainfall-runoff modelling—A case study in the Lippe River basin. Hydrology: Science and practice for the 21st century: Proceedings of the British Hydrological Society International
PMW products are in agreement with the findings of past studies and require better understanding of the ice content in heavy precipitation events ( Petković and Kummerow 2015 ; Derin et al. 2018 ). The West Coast region reports the highest HSS values across all surfaces in the range 0.3–0.5 mm h −1 , indicating higher IM-F ability to delineate moderate rainfall in this region. A detailed performance analysis of PMW retrievals of specific West Coast precipitation events such as atmospheric rivers
PMW products are in agreement with the findings of past studies and require better understanding of the ice content in heavy precipitation events ( Petković and Kummerow 2015 ; Derin et al. 2018 ). The West Coast region reports the highest HSS values across all surfaces in the range 0.3–0.5 mm h −1 , indicating higher IM-F ability to delineate moderate rainfall in this region. A detailed performance analysis of PMW retrievals of specific West Coast precipitation events such as atmospheric rivers
