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Deviation analysis of reanalysis data in boundary layer in summer over Tibetan Plateau and its simulation correction
MA Minjin, CHEN Yue, KANG Guoqiang, ZHAO Zhenzhu, HUANG Wanlong, TAN Changrong, DING Fan
Journal of Arid Meteorology    2022, 40 (1): 95-107.   DOI: 10.11755/j.issn.1006-7639(2022)-01-0095
Abstract433)   HTML7)    PDF(pc) (6173KB)(1672)       Save

The thermal and dynamic processes of the convective boundary layer over the Tibetan Plateau (TP) have an important impact on weather and climate of the downstream region and even the entire East Asia region. This paper uses a summer case of 2017 as an example to analyze the applicability of three sets of reanalysis data including ERA-Interim, JRA-55 and MERRA-2 in the study of the boundary layer over the TP, and further uses the constraints of the numerical model physical framework to correct its analysis error. In the summer of 2017, the variation of air temperature and dew point temperature were presented well through the three sets of reanalysis data in the boundary layer over the southeastern TP, while the reproducibility of the horizontal wind field was very poor, and the reanalysis data with better applicability over the TP during the study period was ERA-Interim. The results from the 12 parameterization scheme combinations selected in this paper were compared by the dispersion degree of the horizontal wind field error, improvements of the simulations in clear skies and moderate rain were significant. Therefore, for the simulated critical physical quantity (the horizontal wind field), the combination of Betts-Miller-Janjic, WSM6 and ACM2 scheme was the most locally applicable in the study area. The wind field in the reanalysis data could describe the summer boundary layer development over the TP more closely after adjustment using simulation results. It was proved that the model parameterization scheme could reduce its deviation of seasonal distribution in the plateau area, which had certain guiding significance for subsequent research and application.

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