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Intercomparison of reanalysis products during extreme flood and drought events: evaluation over the major river basins of Africa
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<p>Data availability and accuracy is predominantly an issue for building hydrological applications, particularly in data-scare regions, like Africa. This is further one of the challenges that hinders understanding the climate variability and its subsequent extreme flood and drought events. Forcing data from different sources, e.g., satellite sensors, in-situ observations, or reanalysis products, are required to derive hydrological models. Reanalysis products have recently become an alternative tool of meteorological data given their long record at various temporal and spatial scales. The overarching goal of this study is to evaluate the primary forcing data for hydrological models; precipitation, as produced by six different reanalysis data (JRA55, 20CRv3, ERA5, ERA-20C, MERRA, NCEP/NCAR). We here focused our evaluation on the major river basins in Africa during a 15-year period spanning from 2001 to 2015. The five major river basins include the Nile River, Congo River, Zambezi River, Orange River, and Niger River basins. Our evaluation method is summarized as follows: Firstly, precipitation data is compared with the gridded gauged data, e.g., CHIRPS for precipitation. Secondly, statistical indices, including categorical and continuous statistical metrics, will be used to assess the accuracy of reanalysis products over each of the major basins. Finally, we present the intercomparison of reanalysis products for extreme events including floods and droughts. The results from our evaluation will pinpoint the skill of reanalysis products and thus benefit the future development of hydrological modeling over the river basins in Africa.</p>
Title: Intercomparison of reanalysis products during extreme flood and drought events: evaluation over the major river basins of Africa
Description:
<p>Data availability and accuracy is predominantly an issue for building hydrological applications, particularly in data-scare regions, like Africa.
This is further one of the challenges that hinders understanding the climate variability and its subsequent extreme flood and drought events.
Forcing data from different sources, e.
g.
, satellite sensors, in-situ observations, or reanalysis products, are required to derive hydrological models.
Reanalysis products have recently become an alternative tool of meteorological data given their long record at various temporal and spatial scales.
The overarching goal of this study is to evaluate the primary forcing data for hydrological models; precipitation, as produced by six different reanalysis data (JRA55, 20CRv3, ERA5, ERA-20C, MERRA, NCEP/NCAR).
We here focused our evaluation on the major river basins in Africa during a 15-year period spanning from 2001 to 2015.
The five major river basins include the Nile River, Congo River, Zambezi River, Orange River, and Niger River basins.
Our evaluation method is summarized as follows: Firstly, precipitation data is compared with the gridded gauged data, e.
g.
, CHIRPS for precipitation.
Secondly, statistical indices, including categorical and continuous statistical metrics, will be used to assess the accuracy of reanalysis products over each of the major basins.
Finally, we present the intercomparison of reanalysis products for extreme events including floods and droughts.
The results from our evaluation will pinpoint the skill of reanalysis products and thus benefit the future development of hydrological modeling over the river basins in Africa.
</p>.
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