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A Window Sliding GPM Data Correction Method Considering Spatial Distribution

A technology of spatial distribution and window, applied in geographic information database, structured data retrieval, database design/maintenance, etc., to reduce the correction error

Active Publication Date: 2022-04-22
CHINA INST OF WATER RESOURCES & HYDROPOWER RES
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] The object of the present invention is to provide a kind of window sliding GPM data correction method that considers spatial distribution, thus solve the foregoing problems existing in the prior art

Method used

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  • A Window Sliding GPM Data Correction Method Considering Spatial Distribution
  • A Window Sliding GPM Data Correction Method Considering Spatial Distribution
  • A Window Sliding GPM Data Correction Method Considering Spatial Distribution

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Embodiment 1

[0037] Such as figure 1 As shown, in this embodiment, a kind of window sliding GPM data correction method considering spatial distribution is provided, comprising the following steps,

[0038] S1. Preprocessing satellite raster data and ground station data;

[0039] S2. According to the preprocessed satellite raster data and ground station data, an initial window is set;

[0040] S3. Correcting the satellite grid data in the initial window, moving the initial window to correct all the satellite grid data in turn;

[0041] S4. Evaluate the correction result.

[0042] In this embodiment, the correction method mainly includes four parts, which are data preprocessing, initial window setting, satellite raster data correction, and correction result evaluation. The following four parts are described in detail respectively.

[0043] 1. Data preprocessing

[0044] This part corresponds to step S1, and step S1 specifically includes the following content, see figure 2 ,

[0045] P...

Embodiment 2

[0103] In this embodiment, the Northwest region (the longitude range is 73 degrees east longitude to 123 degrees east longitude, and the latitude range is 37 degrees north latitude to 50 degrees north latitude) is used as the research area of ​​the embodiment, and the ground observation site data is used to correct the satellite raster data (GPMIMERG Final Run), illustrates the effectiveness of the present invention.

[0104] A total of 178 ground observation stations in Northwest China were used in the study, and their spatial distribution is as follows: Figure 6 shown. First, use the measured precipitation data of 128 ground stations to correct and train the satellite raster data in July 2018 to obtain the corrected raster data, and then use the measured data of the remaining 50 ground observation stations to verify and evaluate the correction results , the results are shown in Table 1. Contour maps are drawn for the results in Table 1, as shown in Figure 7, (a) is the con...

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Abstract

The invention discloses a window sliding GPM data correction method considering spatial distribution, comprising the following steps: S1, preprocessing satellite grid data and ground station data; S2, according to the preprocessed satellite grid data and ground station data data, setting an initial window; S3, correcting the satellite raster data in the initial window, and moving the initial window to correct all the satellite raster data in turn; S4, evaluating the correction results. The advantage is that it can take into account the temporal and spatial distribution characteristics of satellite precipitation data, use the actual precipitation data measured by ground stations as a reference, and perform local corrections on satellite raster data to reduce the correction error and make the correction results have relatively high accuracy.

Description

technical field [0001] The invention relates to the technical field of satellite precipitation data correction, in particular to a window sliding GPM data correction method considering spatial distribution. Background technique [0002] The existing technology is satellite precipitation data fusion technology, and the methods used can be divided into two categories: global and local. Among them, global fusion methods include average deviation correction method, linear regression method, dual-kernel smoothing method, etc.; local fusion methods mainly include co-kriging, geographically weighted regression, Bayesian fusion, etc. However, for satellite precipitation data with low accuracy and errors, direct fusion may not only fail to improve product quality, but will introduce greater errors, making it difficult to guarantee the reliability of the results. In addition, common satellite precipitation data fusion techniques usually do not take into account the differences in the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/21G06F16/29
CPCG06F16/21G06F16/29
Inventor 杨明祥南林江刘珂董宁澎王贺佳
Owner CHINA INST OF WATER RESOURCES & HYDROPOWER RES