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Simulating urban climate at sub‐kilometre scale for representing the intra‐urban variability of Zurich, Switzerland
Author(s) -
Mussetti Gianluca,
Brunner Dominik,
Allegrini Jonas,
Wicki Andreas,
Schubert Sebastian,
Carmeliet Jan
Publication year - 2020
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.6221
Subject(s) - mesoscale meteorology , environmental science , urban heat island , climatology , meteorology , wind speed , urban climate , scale (ratio) , climate model , spatial ecology , downscaling , climate change , atmospheric sciences , geography , urban planning , geology , cartography , precipitation , ecology , oceanography , biology
In the face of an increasing number of urban climate modelling studies performed at sub‐kilometre resolution, systematic investigations of the performance of high‐resolution urban climate simulations and their dependency on spatial resolution are still very sparse. This study investigates the impact of the scale of representation of the urban area on the urban climate simulation with a multi‐layer urban canopy model (UCM) integrated in a mesoscale numerical weather prediction model for different sub‐kilometre resolutions. The potential of using such a model system for representing the intra‐urban climate variability is explored. The weather and climate model COSMO in Climate Mode (CCLM), coupled with the multi‐layer UCM Double‐Canyon effect parameterization (CCLM‐DCEP), was used at increasing resolution from 1 km to 250 m grid spacing to simulate the pronounced heat wave event of June–July 2015 over the city of Zurich, Switzerland. Air temperature and wind speed measurements from a network of urban stations as well as surface temperatures (STs) from Landsat 7 imagery have been used to evaluate the model results. CCLM‐DCEP showed good performance against observed air temperature, ST, and wind speed in the urban area. The model performance did not change significantly with model resolution and a performance improvement with model resolution was not found. Small‐scale features such as urban parks and large railway areas started to be resolved at sub‐kilometre grid spacing. At the finest model resolution (250 m), a spatial variability in air temperature of up to 2 K and wind speed of up to 1.5 m/s was found within the grid cell of the coarsest resolution grid (1 km). CCLM‐DCEP showed the potential to represent the urban climate at the neighbourhood scale when used at high (sub‐kilometre) resolution, which is needed to support applications such as urban planning, building energy use and urban air quality.