The use of geographically weighted regression for the relationship among extreme climate indices in China
type: Item
instance of: scholarly article
title: The use of geographically weighted regression for the relationship among extreme climate indices in China
zbMATH Open document ID: 1264.86016
DOI: 10.1155/2012/369539
author: Chunhong Wang
author: Xiao-Dong Yan
author: Jiang-She Zhang
published in: Mathematical Problems in Engineering
publication date: 2013-06-11T00:00:00Z
review text: Summary: The changing frequency of extreme climate events generally has profound impacts on our living environment and decision-makers. Based on the daily temperature and precipitation data collected from 753 stations in China during 1961-2005, the geographically weighted regression (GWR) model is used to investigate the relationship between the index of frequency of extreme precipitation (FEP) and other climate extreme indices including frequency of warm days (FWD), frequency of warm nights (FWN), frequency of cold days (FCD), and frequency of cold nights (FCN). Assisted by some statistical tests, it is found that the regression relationship has significant spatial nonstationarity and the influence of each explanatory variable (namely, FWD, FWN, FCD, and FCN) on FEP also exhibits significant spatial inconsistency. Furthermore, some meaningful regional characteristics for the relationship between the studied extreme climate indices are obtained.
Mathematics Subject Classification ID: 86A32
zbMATH DE Number: 6173228
Wikidata QID: Q58911494
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/369539
OpenAlex ID: W2014106265
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description: scientific article; zbMATH DE number 6173228