Fine precipitation time variation characteristic space analysis method

A feature space and analysis method technology, applied in special data processing applications, complex mathematical operations, instruments, etc., can solve problems such as large differences in precipitation spatial information, complex precipitation gradients, and limited distribution of precipitation stations, so as to improve accuracy and reliable data The effect of supporting and refining water resource management

Pending Publication Date: 2022-04-05
青海省水文水资源测报中心
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Problems solved by technology

As a result, there is a large difference in the spatial information of precipitation in the face of different precipitation satellite remote sensing data.
[0006] 2. The time variation characteristics of existing precipitation data are mostly analyzed using station data
However, for areas with large spatial variation of precipitation, such as mountainous areas affected by orographic rain, the precipitation gradient is relatively

Method used

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  • Fine precipitation time variation characteristic space analysis method
  • Fine precipitation time variation characteristic space analysis method
  • Fine precipitation time variation characteristic space analysis method

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Effect test

Embodiment 1

[0113] In this case, the CMORPH CRT and Trmm 3B43 data from January 1998 to December 2017 were used to integrate precipitation and precipitation downscaling data from 73 precipitation stations, SPOT NDVI data, and SRTM3 DEM data in the Qilian Mountains area, and the 1998 data in the Qilian Mountains area were obtained. Monthly precipitation data at 0.5km resolution from January to December 2017. The effectiveness of the downscaling method was verified using the coefficient of determination, coefficient of variation, and root mean square error. It is found that the downscaling results are greatly improved compared with the original data. The results are shown in the table below:

[0114]

[0115] Using downscaling to analyze the trend, volatility, and intra-annual distribution changes in the Qilian Mountains, the spatial distribution of the 20-year precipitation temporal variation characteristics in the Qilian Mountains from 1998 to 2017 was obtained.

[0116] The present ...

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Abstract

The invention discloses a refined precipitation time variation characteristic space analysis method. The method comprises the following steps: respectively carrying out preprocessing operation on satellite precipitation data and ground station observation precipitation data; carrying out statistical downscaling by adopting a quadratic multiple regression equation; performing error correction on the two downscaling data by using the site data pair; fusing the two kinds of downscaling data; carrying out precipitation secondary gridding; and analyzing trend, volatility and annual distribution change of precipitation grid points. Compared with a traditional method for obtaining precipitation time variation characteristic space distribution, the method can obtain more effective and fine precipitation space distribution conditions.

Description

technical field [0001] The invention relates to a spatial distribution analysis technique for time variation characteristics of precipitation data, in particular to a refined precipitation time variation characteristic space analysis method based on multi-source data. Background technique [0002] Climate factors are an important basis for human survival and development, and also an important factor affecting social and economic development. As one of the important sources of surface water and groundwater resources, precipitation plays an important role in terrestrial water cycle and ecosystem evolution. However, precipitation is affected by many factors such as region, topography, and underlying surface, and its temporal and spatial distribution is relatively complex. Over the past half century, almost all regions of the world have experienced warming, and the continuous rise in temperature has led to accelerated global and regional water cycles. The temporal and spatial ...

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Application Information

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IPC IPC(8): G06F16/2458G06F17/18G06Q50/06
Inventor 王岗李其江杜嘉妮蔡宜晴时璐胡海静刘希胜闵敏南措吉张珊珊
Owner 青海省水文水资源测报中心
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