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DU Junkai, JIA Yangwen, LI Xiaoxing, NIU Cunwen, LIU Huan, QIU Yaqin. Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data[J]. Advances in Water Science, 2019, 30(1): 1-13. doi: 10.14042/j.cnki.32.1309.2019.01.001
Citation: DU Junkai, JIA Yangwen, LI Xiaoxing, NIU Cunwen, LIU Huan, QIU Yaqin. Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data[J]. Advances in Water Science, 2019, 30(1): 1-13. doi: 10.14042/j.cnki.32.1309.2019.01.001

Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data

doi: 10.14042/j.cnki.32.1309.2019.01.001
  • Received Date: 2018-08-21
  • Publish Date: 2019-02-25
  • A comprehensive understanding of the spatial and temporal distribution of precipitation in mountain areas is of great significance for improving the simulation accuracy of regional water cycle processes,as well as the level of water management. In view of the fact that there is a severe lack of ground monitoring in high altitude areas,as well as the disadvantage of downscaling of satellite precipitation products by a single method,this study selects the Taihang Mountain as the research region and establishes a downscaling correction model. The model consists of the validation module and the downscaling module,which includes the multiple linear regression,the partial least squares regression,and the geographically weighted regression. Using the model,the original TRMM data is scaled from 0.25° to 0.05°. The distribution of the wet and dry seasons and the vertical distribution of the annual and monthly precipitation of the "pixel-catchment-region" are analyzed on the basis of the evaluation and optimization of the downscaling results. The research results are as follows: ① The geographically weighted regression is the most effective,reducing the root mean square error and average relative deviation of the corrected and gauged precipitation series,as well as improving the coefficient of determination. The partial least squares regression can reduce the two errors,but it cannot improve the determination coefficient. The multiple linear regression cannot improve any of the three indicators. ② The precipitation on the east and south slopes on the windward side of the summer monsoon is generally higher than 500 mm,while that on the west and north slopes on the leeward side is lower. The zones of the maximum annual precipitation are located in the southeast slope at an altitude of 1 300—1 500 m. ③ The precipitation from July to September accounts for 58.7% of the entire year;the ratio of precipitation in the dry and wet season is 1∶18;and the ratio in each catchment ranges from 1∶13 to 1∶25. ④ The variations of wind direction of the monsoon affect the moving track of the precipitation center,and the vertical zonality is more complicated in the windward than in the leeward.
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Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data

doi: 10.14042/j.cnki.32.1309.2019.01.001

Abstract: A comprehensive understanding of the spatial and temporal distribution of precipitation in mountain areas is of great significance for improving the simulation accuracy of regional water cycle processes,as well as the level of water management. In view of the fact that there is a severe lack of ground monitoring in high altitude areas,as well as the disadvantage of downscaling of satellite precipitation products by a single method,this study selects the Taihang Mountain as the research region and establishes a downscaling correction model. The model consists of the validation module and the downscaling module,which includes the multiple linear regression,the partial least squares regression,and the geographically weighted regression. Using the model,the original TRMM data is scaled from 0.25° to 0.05°. The distribution of the wet and dry seasons and the vertical distribution of the annual and monthly precipitation of the "pixel-catchment-region" are analyzed on the basis of the evaluation and optimization of the downscaling results. The research results are as follows: ① The geographically weighted regression is the most effective,reducing the root mean square error and average relative deviation of the corrected and gauged precipitation series,as well as improving the coefficient of determination. The partial least squares regression can reduce the two errors,but it cannot improve the determination coefficient. The multiple linear regression cannot improve any of the three indicators. ② The precipitation on the east and south slopes on the windward side of the summer monsoon is generally higher than 500 mm,while that on the west and north slopes on the leeward side is lower. The zones of the maximum annual precipitation are located in the southeast slope at an altitude of 1 300—1 500 m. ③ The precipitation from July to September accounts for 58.7% of the entire year;the ratio of precipitation in the dry and wet season is 1∶18;and the ratio in each catchment ranges from 1∶13 to 1∶25. ④ The variations of wind direction of the monsoon affect the moving track of the precipitation center,and the vertical zonality is more complicated in the windward than in the leeward.

DU Junkai, JIA Yangwen, LI Xiaoxing, NIU Cunwen, LIU Huan, QIU Yaqin. Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data[J]. Advances in Water Science, 2019, 30(1): 1-13. doi: 10.14042/j.cnki.32.1309.2019.01.001
Citation: DU Junkai, JIA Yangwen, LI Xiaoxing, NIU Cunwen, LIU Huan, QIU Yaqin. Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data[J]. Advances in Water Science, 2019, 30(1): 1-13. doi: 10.14042/j.cnki.32.1309.2019.01.001

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