Fine precipitation time variation characteristic space analysis method

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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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 complex, and the distribution of precipitation stations in mountainous areas is limited due to conditions, so it is difficult to obtain accurate spatial distribution of precipitation temporal variation characteristics through interpolation

The spatial distribution resolution of time variation features obtained through satellite remote sensing data is low, which is difficult to meet the needs of refined water resource management.

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