Satellite precipitation product space downscaling method based on water balance principle

Abstract

The invention relates to the technical field of satellite remote sensing data processing, in particular to a satellite precipitation product space downscaling method based on a water balance principle, which comprises the steps of precipitation correlation factor earth surface soil moisture data set generation, precipitation estimation model construction based on the water balance principle, and satellite precipitation product space downscaling. S3, applying a water balance relational expression to high-resolution soil moisture and vegetation factors to obtain a GPM which is not subjected to residual error correction and has the spatial resolution of 1km, interpolating 10km fitting residual error data to the spatial resolution of 1km by applying a weight Kriging interpolation method, and superposing the data obtained in the S3. Seamless high-spatial-resolution (1km) soil moisture data and vegetation factors NDVI are introduced in the downscaling method, excessive regression parameters are not introduced, the scale effect and regression redundancy among excessive data are avoided, a fitting relation is constructed based on a water balance equation, and large-area high-spatial-resolution rainfall data acquisition is achieved.

Description

technical field [0001] The invention relates to the technical field of satellite remote sensing data processing, in particular to a space downscaling method for satellite precipitation products based on the principle of water balance. Background technique [0002] With the continuous development of satellite remote sensing technology, because satellite precipitation products can provide continuous large-area coverage and long-term spatial coverage products, they are an important source of precipitation data for hydrological research in data-scarce areas, making up for ground stations and The lack of weather radar observations has been widely used in research in the fields of hydrology, ecology and climate change. [0003] These satellite precipitation products all have a common problem, that is, the spatial resolution is very low, generally ranging from several kilometers to tens of kilometers, which limits their application in related research. The spatial downscaling metho...

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Problems solved by technology

[0003]These satellite precipitation products all have a common problem, that is, the spatial resolution is very low, generally ranging from several kilometers to tens of kilometers, which limits their use in Applications in related research, the spatial downscaling method of satellite precipitation products is one of the effective means to improve the spatial resolution of satellite precipitation products. The selection of downscaling-related factors in many downscaling methods is mostly based on terrain factors and vegetation factors. These factors are related to precipitation The relationship between them is not an immediate response, and there is a certain degree of delay. The method is mainly based on statistical significance and lacks physical significance. The resolution (25km) is rarely considered as a key factor in the downscaling process of satellite precipitation products, and due to the large uncertainty in the occurrence of daily precipitation in the region, most downscaling methods only focus on the monthly and annual time scales , the accuracy is generally unsatisfactory on the diurnal scale

Moreover, the geographically weighted regression method in downscaling in the prior art is only a statistical method and does not involve physical meaning, and due to the scale effect, too many auxiliary regression factors are introduced, and the relationship between the downscaling regression factor used in the downscaling process and the precipitation The response effect is not immediately reflected. When calculating the optimal weight of each satellite in the high-resolution grid where the precipitation measurement site is located, it depends on the number of ground measurement sites. The interpolation weight process only contains mathematical meaning, and the interpolation has a great influence. Uncertainty

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