Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Downscaling Calibration Model Based on Spatial Multiple Correlation Disassembly Algorithm

A technology of multiple correlation and correction models, applied in the field of statistical downscaling, can solve the problems of large error, high uncertainty, and inability to guarantee the spatial correlation of downscaling results, etc., and achieve the effect of improving simulation accuracy

Active Publication Date: 2020-06-16
HOHAI UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However (some) predictors and predictor variables may not have a clear physical correlation; and when the correlation between predictors and predictor variables is weak, the error of the downscaling results will be large, and there is a high uncertainty; this downscaling method by introducing multiple predictors may “contaminate” the downscaling results of the predictor variables
In addition, the commonly used statistical downscaling methods can generally only achieve downscaling of a single site, and cannot guarantee the spatial correlation of the downscaling results of each site in the region

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Downscaling Calibration Model Based on Spatial Multiple Correlation Disassembly Algorithm
  • Downscaling Calibration Model Based on Spatial Multiple Correlation Disassembly Algorithm
  • Downscaling Calibration Model Based on Spatial Multiple Correlation Disassembly Algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0034] Such as figure 1 as shown,

[0035] Step 1: Data acquisition, including 1) Obtaining the daily rainfall grid data from 1961 to 2004 under different climate models in the source area of ​​the Yellow River from the IPCC official website X t =(x 1,t ,x 2,t ,...,x m,t ), m is the number of grids, and t is the time; 2) Collect the daily measured rainfall data Y from 1961 to 2004 at each station in the source area of ​​the Yellow River t =(y 1,t ,y 2,t ,...,y n,t ), n is the number of stations. The base period (1961-2004) is divided into two periods: the rate period (1961-1994) and the verification period (1995-2004), and the downscaling precipitation simulation performance of the clim...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a dimension reduction and correction model based on a spacial multi-correlation solution set algorithm. The processing method of the model comprises the steps of (1) obtainingdata, wherein the data includes a climate pattern grid data series Xt = (x1, t, x2, t, ..., xm, t) and actual measurement data series Yt= (y1, t, y2, t, ..., yn, t) of each site, m refers to the number of the grids, t refers to time and n refers to the number of the sites; (2) constructing the dimension reduction and correction model based on the spacial multi-correlation solution set algorithm: Y= B + AX + epsilon (epsilon - N (0, sigma 2)), wherein A and B are used for reflecting a related structural relationship between the grid data and the actual measurement data of the sites, and the sigma is a standardized independent random vector; (3) adopting a particle swarm optimization algorithm to figure out the solutions to the coefficient matrix A and the coefficient matrix B in an equation(1). The dimension reduction and correction model based on the spacial multi-correlation solution set algorithm has the advantage of increasing the simulation precision.

Description

technical field [0001] The invention relates to a downscaling correction model based on a spatial multiple correlation solution set algorithm, and belongs to the technical field of statistical downscaling. Background technique [0002] According to the specific information of global climate models, the spatial resolution of the models is low, and most of them are above 1.5°×1.5°. If the model data is directly used in the study of the impact of climate change on hydrology and water resources, it will definitely bring about large errors, and the results will have high uncertainty. In order to study the future climate change in the region, the climate model should be downscaled. [0003] Common downscaling methods include dynamic downscaling, statistical downscaling, and interpolation downscaling. The statistical downscaling method is simple, flexible, easy to implement, and has been widely used in practice. At present, the commonly used statistical downscaling methods (such ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20
Inventor 梁忠民肖章玲胡义明李彬权王军
Owner HOHAI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products