Back to Search Start Over

Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves

Authors :
Anaïs Machard
Agnese Salvati
Mamak P. Tootkaboni
Abhishek Gaur
Jiwei Zou
Liangzhu Leon Wang
Fuad Baba
Hua Ge
Facundo Bre
Emmanuel Bozonnet
Vincenzo Corrado
Xuan Luo
Ronnen Levinson
Sang Hoon Lee
Tianzhen Hong
Marcello Salles Olinger
Rayner Maurício e Silva Machado
Emeli Lalesca Aparecida da Guarda
Rodolfo Kirch Veiga
Roberto Lamberts
Afshin Afshari
Delphine Ramon
Hoang Ngoc Dung Ngo
Abantika Sengupta
Hilde Breesch
Nicolas Heijmans
Jade Deltour
Xavier Kuborn
Sana Sayadi
Bin Qian
Chen Zhang
Ramin Rahif
Shady Attia
Philipp Stern
Peter Holzer
Source :
Scientific Data, Vol 11, Iss 1, Pp 1-21 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essential climate elements needed to undertake building simulations. The datasets contain typical and extreme weather years in the EnergyPlus weather file (EPW) format and multiyear projections in comma-separated value (CSV) format for three periods: historical (2001–2020), future mid-term (2041–2060), and future long-term (2081–2100). The datasets were generated from projections of one regional climate model, which were bias-corrected using multiyear observational data for each city. The methodology used makes the datasets among the first to incorporate complex changes in the future climate for the frequency, duration, and magnitude of extreme temperatures. These datasets, created within the IEA EBC Annex 80 “Resilient Cooling for Buildings”, are ready to be used for different types of building adaptation and resilience studies to climate change and heatwaves.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20524463
Volume :
11
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
edsdoj.1542278a14f544229436ea7bc08fca42
Document Type :
article
Full Text :
https://doi.org/10.1038/s41597-024-03319-8