Improved mesoscopic meteorological modelling of the urban climate for building physics applications
Open access
Date
2023-12Type
- Conference Paper
ETH Bibliography
yes
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Abstract
A meteorological mesoscale model is used to predict the local urban climate at 250 m resolution. The authors propose a hybrid machine learning approach to improve the prediction accuracy and remove simulation bias. Two case studies are presented to show the improvements of the simulation accuracy. Based on the hybrid model results, using cooling degree hours is proposed as an insightful time-dependent index to map local hotspots and assess the difference of cooling loads between rural and urban environments. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000647653Publication status
publishedExternal links
Editor
Book title
Proceedings of NSB 2023: 13th Nordic Symposium on Building PhysicsJournal / series
Journal of Physics: Conference SeriesVolume
Pages / Article No.
Publisher
IOP PublishingEvent
Organisational unit
03806 - Carmeliet, Jan / Carmeliet, Jan
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ETH Bibliography
yes
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