环境科学
气候学
空间变异性
气象学
空气温度
大气科学
地理
地质学
统计
数学
作者
Olli Saranko,Juuso Suomi,Antti‐Ilari Partanen,Carl Fortelius,Carlos Gonzales‐Inca,Jukka Käyhkö
标识
DOI:10.1175/jamc-d-23-0149.1
摘要
Abstract 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 to 31 July 2018 in the City of Turku, Finland, to study their performance in urban areas and surrounding rural areas. The 2 am (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 variability during heatwaves. Observed temperatures were collected from 74 sites, representing both rural and urban environments. Both models were able to reproduce the spatial night-time 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.
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