A Screening Method for Predictors of Statistical Downscaling Models

A technology of predictors and screening methods, applied in forecasting, calculation, data processing applications, etc., can solve problems such as mining useful information, affecting prediction accuracy, not considering the influence of adjacent grids, etc., to reduce uncertainty and improve accuracy Effect

Active Publication Date: 2022-01-18
CHINA THREE GORGES UNIV +1
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AI Technical Summary

Problems solved by technology

The traditional factor selection only considers the influence of the factors of the grid where the station is located on the forecast, but does not consider the influence of adjacent grids on its selection. This does not fully mine the useful information, and affects the prediction to a certain extent. accuracy

Method used

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  • A Screening Method for Predictors of Statistical Downscaling Models
  • A Screening Method for Predictors of Statistical Downscaling Models
  • A Screening Method for Predictors of Statistical Downscaling Models

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Embodiment Construction

[0057] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0058] Such as figure 1 , a method for screening statistical downscaling model predictors, comprising the following steps:

[0059] Step 1, establish the location relationship map of the basin meteorological stations and grids;

[0060] Step 2. Deduce the correlation between the measured precipitation, temperature and other forecasts of each station and the atmospheric circulation factor of the reanalysis data, including the correlation with the grid where the meteorological station is located and the correlation with the surrounding grids. According to the set correlation The coefficient threshold selects the appropriate factor;

[0061] Step 3, analyze the changes in the certainty coefficient of the rate-period judgment standard under the three scales of month, season and year;

[0062] Step 4: Analyze and test the model according to different scal...

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Abstract

The invention involves a screening method of a statistical reduction standard model forecasting factor, including the following steps: step 1, establish a location relationship diagram of the watershed meteorological site and grid; step 2, push the forecast volume and re -analysis of the predictions such as precipitation, temperature and temperature of each site.The correlation between data atmospheric circulation factor, including the correlation with the grid where the meteorological site is located, and the correlation with the surrounding grid, select suitable factor according to the set correlation threshold;At the three standards of seasonal and annual standards, the regular determination standard determines the change of sexual coefficient; step 4, analyze and test the model according to the different scale and different selection factor methods of step 3.

Description

technical field [0001] The invention relates to a method for screening predictors, in particular to a method for screening statistical downscaling model predictors. Background technique [0002] Affected by global climate change, the climatic and hydrological processes around the world have undergone significant changes in the past half a century, leading to an increase in extreme events such as precipitation and temperature in many regions (or basins), frequent floods, lakes, etc. Phenomena such as water body shrinkage intensified. In this context, it is urgent to study the quantitative changes of climate and predict future climate change. Generally rely on the climate variables provided by the Global Climate Model (GCM), that is, to combine the climate variables output by the Global Climate Model with the environmental response model (such as: hydrological model) to assess the impact of environmental factors (such as: runoff) on climate change the response to. The outpu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/10
Inventor 郭家力张静文程雄戴凌全
Owner CHINA THREE GORGES UNIV
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