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Advances in atmospheric sciences, 2017-04, Vol.34 (4), p.441-455
2017
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Autor(en) / Beteiligte
Titel
Performance of RegCM4 over Major River Basins in China
Ist Teil von
  • Advances in atmospheric sciences, 2017-04, Vol.34 (4), p.441-455
Ort / Verlag
Beijing: Science Press
Erscheinungsjahr
2017
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • A long-term simulation for the period 1990–2010 is conducted with the latest version of the International Centre for Theoretical Physics' Regional Climate Model(RegCM4), driven by ERA-Interim boundary conditions at a grid spacing of 25 km. The Community Land Model(CLM) is used to describe land surface processes, with updates in the surface parameters,including the land cover and surface emissivity. The simulation is compared against observations to evaluate the model performance in reproducing the present day climatology and interannual variability over the 10 main river basins in China,with focus on surface air temperature and precipitation. Temperature and precipitation from the ERA-Interim reanalysis are also considered in the model assessment. Results show that the model reproduces the present day climatology over China and its main river basins, with better performances in June–July–August compared to December–January–February(DJF).In DJF, we find a warm bias at high latitudes, underestimated precipitation in the south, and overestimated precipitation in the north. The model in general captures the observed interannual variability, with greater skill for temperature. We also find an underestimation of heavy precipitation events in eastern China, and an underestimation of consecutive dry days in northern China and the Tibetan Plateau. Similar biases for both mean climatology and extremes are found in the ERA-Interim reanalysis, indicating the difficulties for climate models in simulating extreme monsoon climate events over East Asia.
Sprache
Englisch
Identifikatoren
ISSN: 0256-1530
eISSN: 1861-9533
DOI: 10.1007/s00376-016-6179-7
Titel-ID: cdi_wanfang_journals_dqkxjz_e201704002

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