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Downscaling method of trmm satellite rainfall data based on m5‑localr

A rainfall data and downscaling technology, which is applied in the direction of electrical digital data processing, special data processing applications, measuring devices, etc., can solve problems such as inability to improve accuracy, and achieve the effect of improving spatial resolution

Active Publication Date: 2017-12-26
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, current researchers believe that the use of multi-factor downscaling algorithms cannot improve the accuracy, and the accuracy of multi-factors will be lower than that of a single factor.

Method used

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  • Downscaling method of trmm satellite rainfall data based on m5‑localr
  • Downscaling method of trmm satellite rainfall data based on m5‑localr
  • Downscaling method of trmm satellite rainfall data based on m5‑localr

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Embodiment 1

[0026] In this embodiment, geographically weighted regression is used for downscaling prediction, and the specific steps are as follows:

[0027] The Tibet region was selected as the research area, and the monthly rainfall in the wet season (May-October) of 2003-2009 was predicted and studied, and finally the monthly rainfall distribution map with a spatial resolution of 1km was obtained.

[0028] Step 1) Data acquisition: Obtain TRMM meteorological satellite remote sensing image data, MODIS satellite remote sensing image data and ASTER GDEM satellite remote sensing image data in the Tibet region, and collect daily rainfall observations at ground observation stations in the Tibet region; the MODIS satellite remote sensing image data The data includes MOD11A2 data product and MOD13A2 data product. Among them: the spatial resolution of the TRMM meteorological satellite remote sensing image data is 0.25°×0.25°, and the time resolution is 3 hours; the spatial resolution of the AST...

Embodiment 2

[0039] In this embodiment, the M5-LocalR method is selected for regression modeling, and the specific steps are:

[0040] In this embodiment, geographically weighted regression is used for downscaling prediction, and the specific steps are as follows:

[0041] The Tibet region was selected as the research area, and the monthly rainfall in the wet season (May-October) of 2003-2009 was predicted and studied, and finally the monthly rainfall distribution map with a spatial resolution of 1km was obtained.

[0042] Step 1) Data acquisition: Obtain TRMM meteorological satellite remote sensing image data, MODIS satellite remote sensing image data and ASTER GDEM satellite remote sensing image data in the Tibet region, and collect daily rainfall observations at ground observation stations in the Tibet region; MODIS satellite remote sensing Image data includes MOD11A2 data products and MOD13A2 data products. Among them: the spatial resolution of the TRMM meteorological satellite remote...

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Abstract

The invention discloses a downscaling method for TRMM satellite rainfall data based on M5‑LocalR. The invention adopts the idea of ​​M5‑LocalR regression, and fully utilizes multiple environmental stress factors with high spatial resolution to improve the spatial resolution of the product. First, the 1km environmental variable factors such as vegetation index, digital elevation model, daytime surface temperature, nighttime surface temperature, topographic humidity index, slope, slope aspect, slope length and slope are aggregated and calculated to 25km, as independent variables, corresponding to The TRMM data with a resolution of 25 km was used as the dependent variable, and the M5-LocalR method was used to model, and the intercept of the regression modeling equation with a spatial resolution of 1 km and the slope parameters corresponding to each environmental factor variable were predicted, and the 1 km TRMM rainfall value was obtained through calculation. The downscaling results based on the M5-LocalR model are significantly better than the downscaling results based on the conventional regression model.

Description

technical field [0001] The invention relates to a method for downscaling TRMM rainfall data, in particular to a method for downscaling TRMM satellite rainfall data based on M5-LocalR. technical background [0002] Rainfall plays an important role in the fields of hydrology, meteorology, ecology, and agricultural research, especially an important part of the conservation of matter-energy exchange. Surface observation station is a widely used means of rainfall measurement, and has the characteristics of high precision and mature technology. However, the rainfall monitored by surface observation stations only represents the precipitation conditions at a certain distance from the surface observation stations and surrounding areas, so it is difficult to describe the characteristics of large-scale rainfall distribution, especially in plateau areas where the network density of surface observation stations is sparse. The satellite remote sensing technology can provide rainfall data...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00G01W1/10
Inventor 史舟马自强刘用吕志强
Owner ZHEJIANG UNIV
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