{"title":"Climatologically Aided Mapping of Daily Precipitation and Temperature","authors":"Richard D. Hunter, R. Meentemeyer","doi":"10.1175/JAM2295.1","DOIUrl":null,"url":null,"abstract":"Abstract Accurately mapped meteorological data are an essential component for hydrologic and ecological research conducted at broad scales. A simple yet effective method for mapping daily weather conditions across heterogeneous landscapes is described and assessed. Daily weather data recorded at point locations are integrated with long-term-average climate maps to reconstruct spatially explicit estimates of daily precipitation and temperature extrema. The method uses ordinary kriging to interpolate base station data spatially into fields of approximately 2-km grain size. The fields are subsequently adjusted by 30-yr-average climate maps [Parameter-Elevation Regression on Independent Slopes Model (PRISM)], which incorporate adiabatic lapse rates, orographic effects, coastal proximity, and other environmental factors. The accuracy assessment evaluated an interpolation-only approach and the new method by comparing predicted and observed values from an independent validation dataset. The results of the accura...","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"1 1","pages":"1501-1510"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"114","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Meteorology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1175/JAM2295.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 114
Abstract
Abstract Accurately mapped meteorological data are an essential component for hydrologic and ecological research conducted at broad scales. A simple yet effective method for mapping daily weather conditions across heterogeneous landscapes is described and assessed. Daily weather data recorded at point locations are integrated with long-term-average climate maps to reconstruct spatially explicit estimates of daily precipitation and temperature extrema. The method uses ordinary kriging to interpolate base station data spatially into fields of approximately 2-km grain size. The fields are subsequently adjusted by 30-yr-average climate maps [Parameter-Elevation Regression on Independent Slopes Model (PRISM)], which incorporate adiabatic lapse rates, orographic effects, coastal proximity, and other environmental factors. The accuracy assessment evaluated an interpolation-only approach and the new method by comparing predicted and observed values from an independent validation dataset. The results of the accura...