Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386216115> ?p ?o ?g. }
- W4386216115 endingPage "116984" @default.
- W4386216115 startingPage "116984" @default.
- W4386216115 abstract "Robust spatio-temporal delineation of extreme climate events and accurate identification of areas that are impacted by an event is a prerequisite for identifying population-level and health-related risks. In prior research, attributes such as temperature and humidity have often been linearly assigned to the population of the study unit from the closest weather station. This could result in inaccurate event delineation and biased assessment of extreme heat exposure. We have developed a spatio-temporal model to dynamically delineate boundaries for Extreme Heat Events (EHE) across space and over time, using a relative measure of Apparent Temperature (AT). Our surface interpolation approach offers a higher spatio-temporal resolution compared to the standard nearest-station (NS) assignment method. We show that the proposed approach can provide at least 80.8 percent improvement in identification of areas and populations impacted by EHEs. This improvement in average adjusts the misclassification of about one million Californians per day of an extreme event, who would be either unidentified or misidentified under EHEs between 2017 and 2021." @default.
- W4386216115 created "2023-08-29" @default.
- W4386216115 creator A5006237435 @default.
- W4386216115 creator A5019061611 @default.
- W4386216115 creator A5032780472 @default.
- W4386216115 creator A5071182540 @default.
- W4386216115 date "2023-11-01" @default.
- W4386216115 modified "2023-09-28" @default.
- W4386216115 title "Spatio-temporal interpolation and delineation of extreme heat events in California between 2017 and 2021" @default.
- W4386216115 cites W1980780720 @default.
- W4386216115 cites W1982444207 @default.
- W4386216115 cites W1996417111 @default.
- W4386216115 cites W2007933340 @default.
- W4386216115 cites W2010296010 @default.
- W4386216115 cites W2011094999 @default.
- W4386216115 cites W2018146898 @default.
- W4386216115 cites W2031353019 @default.
- W4386216115 cites W2041285331 @default.
- W4386216115 cites W2047007042 @default.
- W4386216115 cites W2058120680 @default.
- W4386216115 cites W2059195846 @default.
- W4386216115 cites W2062479245 @default.
- W4386216115 cites W2079361870 @default.
- W4386216115 cites W2082780011 @default.
- W4386216115 cites W2084672768 @default.
- W4386216115 cites W2089046918 @default.
- W4386216115 cites W2093087376 @default.
- W4386216115 cites W2099468086 @default.
- W4386216115 cites W2100189428 @default.
- W4386216115 cites W2112776483 @default.
- W4386216115 cites W2144540813 @default.
- W4386216115 cites W2162775913 @default.
- W4386216115 cites W2174288345 @default.
- W4386216115 cites W2178059220 @default.
- W4386216115 cites W2201097253 @default.
- W4386216115 cites W2217979645 @default.
- W4386216115 cites W2302501749 @default.
- W4386216115 cites W2402348462 @default.
- W4386216115 cites W2501262125 @default.
- W4386216115 cites W2517252399 @default.
- W4386216115 cites W2587111568 @default.
- W4386216115 cites W2740986094 @default.
- W4386216115 cites W2759208587 @default.
- W4386216115 cites W2795891908 @default.
- W4386216115 cites W2804233742 @default.
- W4386216115 cites W2884440806 @default.
- W4386216115 cites W2891755699 @default.
- W4386216115 cites W2898260065 @default.
- W4386216115 cites W2903028269 @default.
- W4386216115 cites W2904006770 @default.
- W4386216115 cites W2910751597 @default.
- W4386216115 cites W2964646732 @default.
- W4386216115 cites W2999144726 @default.
- W4386216115 cites W3000487909 @default.
- W4386216115 cites W3004794249 @default.
- W4386216115 cites W3006860009 @default.
- W4386216115 cites W3147113984 @default.
- W4386216115 cites W3155639816 @default.
- W4386216115 cites W3158567675 @default.
- W4386216115 cites W3205971907 @default.
- W4386216115 cites W4205344245 @default.
- W4386216115 cites W4213446586 @default.
- W4386216115 cites W4221002889 @default.
- W4386216115 cites W4307402605 @default.
- W4386216115 doi "https://doi.org/10.1016/j.envres.2023.116984" @default.
- W4386216115 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37648196" @default.
- W4386216115 hasPublicationYear "2023" @default.
- W4386216115 type Work @default.
- W4386216115 citedByCount "0" @default.
- W4386216115 crossrefType "journal-article" @default.
- W4386216115 hasAuthorship W4386216115A5006237435 @default.
- W4386216115 hasAuthorship W4386216115A5019061611 @default.
- W4386216115 hasAuthorship W4386216115A5032780472 @default.
- W4386216115 hasAuthorship W4386216115A5071182540 @default.
- W4386216115 hasBestOaLocation W43862161151 @default.
- W4386216115 hasConcept C104114177 @default.
- W4386216115 hasConcept C116834253 @default.
- W4386216115 hasConcept C121332964 @default.
- W4386216115 hasConcept C127313418 @default.
- W4386216115 hasConcept C132651083 @default.
- W4386216115 hasConcept C137800194 @default.
- W4386216115 hasConcept C144024400 @default.
- W4386216115 hasConcept C149923435 @default.
- W4386216115 hasConcept C153294291 @default.
- W4386216115 hasConcept C154945302 @default.
- W4386216115 hasConcept C18903297 @default.
- W4386216115 hasConcept C205537798 @default.
- W4386216115 hasConcept C205649164 @default.
- W4386216115 hasConcept C2779662365 @default.
- W4386216115 hasConcept C2908525100 @default.
- W4386216115 hasConcept C2908647359 @default.
- W4386216115 hasConcept C2993190167 @default.
- W4386216115 hasConcept C39432304 @default.
- W4386216115 hasConcept C41008148 @default.
- W4386216115 hasConcept C49204034 @default.
- W4386216115 hasConcept C54005896 @default.
- W4386216115 hasConcept C62520636 @default.
- W4386216115 hasConcept C86803240 @default.