Method of using high-resolution terrain and meteorology factors for multi-source precipitation fusion

Abstract

The invention discloses a method of using high-resolution terrain and meteorology factors for multi-source precipitation fusion. The method comprises the steps of: extracting DEM grid data of a targetwatershed, and obtaining a mask file of the watershed; calculating a slope, an aspect, surface roughness and a to-shoreline distance of the target watershed by the DEM grid data of the target watershed; extracting wind speed data of the watershed according to the mask file; using the mask file to extract satellite precipitation data of the watershed; carrying out downscaling on original satelliteprecipitation to obtain satellite precipitation of Rkm; calculating deviation of satellite precipitation after downscaling and actually measured site precipitation; using a geographically weighted regression model to calculate precipitation deviation of Rkm grids; and obtaining an Rkm fusion precipitation product. According to the method, site data and the satellite precipitation product are fused, downscaling is carried out on the satellite precipitation, the high-time / space-resolution precipitation product is obtained, conversion of precipitation data from points to a surface can be realized, and data support is provided for an input of a refined hydrological model.

Description

technical field [0001] The invention belongs to the technical field of hydrology and meteorology, and in particular relates to a multi-source precipitation fusion method using high-resolution terrain and meteorological factors. Background technique [0002] China is a country with frequent flood disasters, and hydrological model is an important means to solve flood disasters. Precipitation is the most critical input source of hydrological models, and the accuracy and timeliness of precipitation directly affect the accuracy and reliability of simulation results. [0003] At present, the methods of obtaining precipitation data mainly include ground observation, satellite and radar quantitative precipitation estimation, and model quantitative precipitation forecasting. For a long time, the routine observation of precipitation has mainly relied on the observation stations deployed on the surface, and the limited observation results represent the real precipitation within tens o...

AI Technical Summary

Problems solved by technology

Satellite quantitative precipitation estimation has the advantages of wide coverage and relatively continuous observation time. However, due to the limitations of remote sensing detection instruments and inversion algorithms, satellite precipitation products have low spatial resolution and relatively low accuracy, and the inversion ability for solid precipitation is very poor. limited

[0004] Fusion of station data and satellite radar precipitation has become an effective way to improve precipitation products. At present, there are many methods of precipitation fusion, such as: optimal interpolation, Kalman filter, particle filter, Bayesian estimation, probability density and other methods, none of which are involved Downscaling to Satellite Precipitation

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