Comparison of Physically Based and Empirical Modeling of Nighttime Spatial Temperature Variability during a Heatwave in and around a City

dc.contributor.authorSaranko, Olli
dc.contributor.authorSuomi, Juuso
dc.contributor.authorPartanen, Antti-Ilari
dc.contributor.authorFortelius, Carl
dc.contributor.authorGonzales-Inca, Carlos
dc.contributor.authorKäyhkö, Jukka
dc.contributor.organizationfi=maantiede|en=Geography |
dc.contributor.organization-code1.2.246.10.2458963.20.17647764921
dc.converis.publication-id458653512
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/458653512
dc.date.accessioned2026-01-21T13:44:24Z
dc.date.available2026-01-21T13:44:24Z
dc.description.abstract<p>The numerical weather prediction model HARMONIE-AROME and a multiple linear regression model (referred to in this article as the TURCLIM model after the local climate observation network) were used to model surface air temperature for 25–31 July 2018 in the City of Turku, Finland, to study their performance in urban areas and surrounding rural areas. The 0200 LT (local standard time) temperatures modeled by the HARMONIE-AROME and TURCLIM models were compared to each other and against the observed temperatures to find the model best suited for modeling the urban heat island effect and other spatial temperature variabilities during heatwaves. Observed temperatures were collected from 74 sites, representing both rural and urban environments. Both models were able to reproduce the spatial nighttime temperature variation. However, HARMONIE-AROME modeled temperatures were systematically warmer than the observed temperatures in stable conditions. Spatial differences between the models were mostly related to the physiographic characteristics: for the urban areas, HARMONIE-AROME modeled on average 1.4°C higher temperatures than the TURCLIM model, while for other land-cover types, the average difference was 0.51°C at maximum. The TURCLIM model performed well when the explanatory variables were able to incorporate enough information on the surrounding physiography. Respectively, systematic cold or warm bias occurred in the areas in which the thermophysically relevant physiography was lacking or was only partly captured by the model.<br></p>
dc.format.pagerange1053
dc.format.pagerange1074
dc.identifier.eissn1558-8432
dc.identifier.jour-issn1558-8432
dc.identifier.olddbid213306
dc.identifier.oldhandle10024/196324
dc.identifier.urihttps://www.utupub.fi/handle/11111/55176
dc.identifier.urlhttp://doi.org/10.1175/jamc-d-23-0149.1
dc.identifier.urnURN:NBN:fi-fe2025082786853
dc.language.isoen
dc.okm.affiliatedauthorSuomi, Juuso
dc.okm.affiliatedauthorGonzales Inca, Carlos
dc.okm.affiliatedauthorKäyhkö, Jukka
dc.okm.discipline1171 Geosciencesen_GB
dc.okm.discipline1171 Geotieteetfi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherAmerican Meteorological Society
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.doi10.1175/JAMC-D-23-0149.1
dc.relation.ispartofjournalJournal of Applied Meteorology and Climatology
dc.relation.issue10
dc.relation.volume63
dc.source.identifierhttps://www.utupub.fi/handle/10024/196324
dc.titleComparison of Physically Based and Empirical Modeling of Nighttime Spatial Temperature Variability during a Heatwave in and around a City
dc.year.issued2024

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