Weather and Applied Climate

Comparison of downscaling methods for TRMM 3B43 precipitation data in the Qinghai Lake Basin and its surrounding areas

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  • 1. College of Geography Science, Qinghai Normal University, Xining 810008, Qinghai, China
    2. Key Laboratory of Tibetan Plateau Land Surface Processes and Ecological Conservation (Ministry of Education), Qinghai Normal University, Xining 810008, Qinghai, China
    3. Academy of Plateau Science and Sustainability, People’s Government of Qinghai Province and Beijing Normal University, Xining 810008, Qinghai, China

Received date: 2022-04-16

  Revised date: 2022-09-07

  Online published: 2023-01-17

Abstract

Using multiple linear regression (MLR), principal component stepwise regression (PCSR), and Kriging, the TRMM 3B43 precipitation data in the Qinghai Lake Basin and surrounding areas with a resolution of 0.25° were downscaled to a resolution of 0.01°. The measured precipitation data of 20 meteorological stations in the study area were selected, and the correlation coefficient, root mean square error, and relative deviation (Bias) were used to evaluate the downscaling results. Downscaling methods for the study area. The results show a consistent spatial distribution of precipitation in the study area based on TRMM and the three downscaling methods. The annual average precipitation and the three seasons of spring, summer, and autumn are all high in the north, low in the west and northwest, and winter precipitation. The performance was high in the south and northwest and low in the middle. With increased altitude, the precipitation in the study area showed an overall trend of first increasing and then decreasing with 3800 meters as the boundary. The results of the accuracy evaluation show that the Kriging accuracy on the annual scale has the best performance. On the spatial scale, the TRMM and the three downscale data have the best accuracy in the eastern region. On the quarterly scale, the data precision is PCSR > Kriging > TRMM > MLR. On the monthly scale, the PCSR data accuracy is the best. The effect of altitude on the TRMM and the three downscaling data in the study area is small. However, with increasing altitude, the remote sensing data gradually underestimates the precipitation phenomenon, which may be due to the underestimation of precipitation and convection during microwave precipitation rate inversion underestimation of precipitation. From the comprehensive precipitation spatial distribution consistency analysis and precision evaluation, it is considered that PCSR is the most suitable downscaling method for TRMM 3B43 precipitation data in the Qinghai Lake Basin and surrounding areas.

Cite this article

LI Yankun,GAO Liming,ZHANG Lele,WU Xueqing,LIU Xuanchen,QI Wen . Comparison of downscaling methods for TRMM 3B43 precipitation data in the Qinghai Lake Basin and its surrounding areas[J]. Arid Zone Research, 2022 , 39(6) : 1706 -1716 . DOI: 10.13866/j.azr.2022.06.02

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