Performance of Three Reanalysis Precipitation Datasets over the Qinling-Daba Mountains, Eastern Fringe of Tibetan Plateau, China
Evaluation of different reanalysis precipitation datasets is of great importance to understanding the hydrological processes and water resource management practice in the Qinling-Daba Mountains (QDM), located at the eastern fringe of the Tibetan Plateau. Although the evaluation of satellite precipit...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2019/7698171 |
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| Summary: | Evaluation of different reanalysis precipitation datasets is of great importance to understanding the hydrological processes and water resource management practice in the Qinling-Daba Mountains (QDM), located at the eastern fringe of the Tibetan Plateau. Although the evaluation of satellite precipitation data in this region has been performed, another kind of popular precipitation product-reanalysis dataset has not been assessed in depth. Three popular reanalysis precipitation datasets, including ERA-Interim Reanalysis of European Centre for Medium Forecasts (ERA-Interim), Japanese 55-year Reanalysis (JRA-55), and National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis-1 (NCEP/NCAR-1) were evaluated against rain gauge data over the Qinling-Daba Mountains from 2000 to 2014 on monthly, seasonal, and annual scales. Different statistical measures based on the Correlation Coefficient (CC), relative BIAS (BIAS), Root-Mean-Square Error (RMSE), and Mean Absolute Error (MAE) were adopted to determine the performance of the above reanalysis datasets. Results show that ERA-Interim and JRA-55 have good performance on a monthly scale and annual scale. However, the NCEP/NCAR-1 has the least BIAS with the observed precipitation in annual scale in QDM. All reanalysis datasets performed better in spring, summer, and autumn than in winter. The advantages of involving more precipitation observation stations was probably the main reason of the different performance of three precipitation reanalysis products, and the benefit of a four-dimensional variational analysis model over a three-dimensional variational analysis model may be another reason. The evaluation suggested that ERA-Interim is more suitable for study the precipitation and water cycles in the QDM. |
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| ISSN: | 1687-9309 1687-9317 |