Nils Eingrüber, W. Korres, U. Löhnert, K. Schneider
{"title":"Investigation of the ENVI-met model sensitivity to different wind direction forcing data in a heterogeneous urban environment","authors":"Nils Eingrüber, W. Korres, U. Löhnert, K. Schneider","doi":"10.5194/asr-20-65-2023","DOIUrl":null,"url":null,"abstract":"Abstract. As the frequency of extreme heat events in cities is\nsignificantly increasing due to climate change, the implementation of\nadaptation measures is important for urban planning. Microclimate modelling\napproaches enable scenario analyses and evaluations of adaptation\npotentials. An ENVI-met microclimate model was setup for a heterogeneous\nurban study area in Cologne/Germany characterized by closed building\nstructures in the eastern part and an urban park area in the western part.\nThe goal of this paper is to evaluate the model sensitivity and performance\nto different wind direction forcing and demonstrate the importance of\naccurate wind forcing data for precise microclimate modelling evaluated with\nsensor measurements. To this end, we compared simulated air temperatures at\n3 m height level using measured wind direction forcing data with simulated\nair temperatures using constant wind direction forcing from west, north,\neast and south direction. All other forcing data like wind speed were kept\nexactly the same as in the reference run. This sensitivity study was\nperformed for a warm summer day in 2022. The model results of all five model\nruns (reference plus four scenarios) were compared to microclimatological\nmeasurements derived from one station of a dense meteorological sensor\nnetwork located in the study area using the simulated mean air temperatures.\nWe found significant temperature differences between the four sensitivity\ntests and the reference run as well as to the sensor measurements.\nTemperature differences between the reference run and the measurements were\nsmall and a high statistical model fit could be determined (Nash Sutcliffe\nModel Efficiency Coefficient/NSE = 0.91). The four model runs with\nconstant wind directions showed significantly larger differences to\nmeasurement data and a worse statistical correlation between simulated and\nobserved data (NSE between 0.62 and 0.15). For constant west winds, cooler\nair temperatures and higher wind speeds were found in the urban park and in\nthe streets and courtyards east of the park. Constant east wind causes\nwarmer air temperatures in the urban park area and lower wind speeds in the\nstreet canyons and inner courtyards. This shows that cooling effects in\nadjacent building blocks due to the greened urban park largely depend on the\nwind direction. The sensitivity tests show that the wind direction effect\ncan result in local air temperature differences of up to 4 K on\naverage. These results shows that even on summer days with low wind speeds,\naccurate wind direction data is highly relevant for accurate air temperature\nsimulation. This finding can have important implications for urban planning\nand the design of green infrastructures in cities, e. g. for the design of\nfresh air corridors.\n","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"74 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Science and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/asr-20-65-2023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. As the frequency of extreme heat events in cities is
significantly increasing due to climate change, the implementation of
adaptation measures is important for urban planning. Microclimate modelling
approaches enable scenario analyses and evaluations of adaptation
potentials. An ENVI-met microclimate model was setup for a heterogeneous
urban study area in Cologne/Germany characterized by closed building
structures in the eastern part and an urban park area in the western part.
The goal of this paper is to evaluate the model sensitivity and performance
to different wind direction forcing and demonstrate the importance of
accurate wind forcing data for precise microclimate modelling evaluated with
sensor measurements. To this end, we compared simulated air temperatures at
3 m height level using measured wind direction forcing data with simulated
air temperatures using constant wind direction forcing from west, north,
east and south direction. All other forcing data like wind speed were kept
exactly the same as in the reference run. This sensitivity study was
performed for a warm summer day in 2022. The model results of all five model
runs (reference plus four scenarios) were compared to microclimatological
measurements derived from one station of a dense meteorological sensor
network located in the study area using the simulated mean air temperatures.
We found significant temperature differences between the four sensitivity
tests and the reference run as well as to the sensor measurements.
Temperature differences between the reference run and the measurements were
small and a high statistical model fit could be determined (Nash Sutcliffe
Model Efficiency Coefficient/NSE = 0.91). The four model runs with
constant wind directions showed significantly larger differences to
measurement data and a worse statistical correlation between simulated and
observed data (NSE between 0.62 and 0.15). For constant west winds, cooler
air temperatures and higher wind speeds were found in the urban park and in
the streets and courtyards east of the park. Constant east wind causes
warmer air temperatures in the urban park area and lower wind speeds in the
street canyons and inner courtyards. This shows that cooling effects in
adjacent building blocks due to the greened urban park largely depend on the
wind direction. The sensitivity tests show that the wind direction effect
can result in local air temperature differences of up to 4 K on
average. These results shows that even on summer days with low wind speeds,
accurate wind direction data is highly relevant for accurate air temperature
simulation. This finding can have important implications for urban planning
and the design of green infrastructures in cities, e. g. for the design of
fresh air corridors.