Impacts of Representative Weather Data Type on Hygrothermal Simulations for Future Climate
Nik, Vahid M. LU
(2026)
6th Central European Symposium on Building Physics, CESBP 2025
In Lecture Notes in Civil Engineering
795 LNCE.
p.152-163
- Abstract
Synthesizing representative weather data sets that reflect both typical and extreme conditions is essential for reliable hygrothermal simulations, especially when considering future climates, which involve significant uncertainties. In this study, multiple representative weather data sets are generated using various methods, broadly categorized based on picking the representative months using variables reflecting the outdoor temperature, moisture or rain conditions. The performance of each method is evaluated by conducting hygrothermal simulations of a prefabricated wood-frame wall, using both the original long-term weather data and the synthesized representative data sets. A comparison of different outdoor weather variables and wall... (More)
Synthesizing representative weather data sets that reflect both typical and extreme conditions is essential for reliable hygrothermal simulations, especially when considering future climates, which involve significant uncertainties. In this study, multiple representative weather data sets are generated using various methods, broadly categorized based on picking the representative months using variables reflecting the outdoor temperature, moisture or rain conditions. The performance of each method is evaluated by conducting hygrothermal simulations of a prefabricated wood-frame wall, using both the original long-term weather data and the synthesized representative data sets. A comparison of different outdoor weather variables and wall characteristics is carried out, examining both average and extreme conditions. The results indicate that the representative data sets based on outdoor dry-bulb temperature (TDY, ECY, and EWY) can effectively capture the characteristics and variability of the long-term dataset.
(Less)
- author
- Nik, Vahid M.
LU
- organization
- publishing date
- 2026
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Climate change, Extreme Weather, Hygrothermal Simulation, Typical Weather, Weather Data
- host publication
- Proceedings of CESBP 2025 - 6th Central European Symposium on Building Physics - Volume 1
- series title
- Lecture Notes in Civil Engineering
- editor
- Nagy, Balázs and Szalay, Zsuzsa
- volume
- 795 LNCE
- pages
- 12 pages
- publisher
- Springer Science and Business Media B.V.
- conference name
- 6th Central European Symposium on Building Physics, CESBP 2025
- conference location
- Budapest, Hungary
- conference dates
- 2025-09-11 - 2025-09-13
- external identifiers
-
- scopus:105029422441
- ISSN
- 2366-2557
- 2366-2565
- ISBN
- 9783032140104
- DOI
- 10.1007/978-3-032-14011-1_13
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
- id
- 041bf3c7-9ed3-435e-8a36-593634e0e248
- date added to LUP
- 2026-05-05 16:19:52
- date last changed
- 2026-05-19 17:15:05
@inproceedings{041bf3c7-9ed3-435e-8a36-593634e0e248,
abstract = {{<p>Synthesizing representative weather data sets that reflect both typical and extreme conditions is essential for reliable hygrothermal simulations, especially when considering future climates, which involve significant uncertainties. In this study, multiple representative weather data sets are generated using various methods, broadly categorized based on picking the representative months using variables reflecting the outdoor temperature, moisture or rain conditions. The performance of each method is evaluated by conducting hygrothermal simulations of a prefabricated wood-frame wall, using both the original long-term weather data and the synthesized representative data sets. A comparison of different outdoor weather variables and wall characteristics is carried out, examining both average and extreme conditions. The results indicate that the representative data sets based on outdoor dry-bulb temperature (TDY, ECY, and EWY) can effectively capture the characteristics and variability of the long-term dataset.</p>}},
author = {{Nik, Vahid M.}},
booktitle = {{Proceedings of CESBP 2025 - 6th Central European Symposium on Building Physics - Volume 1}},
editor = {{Nagy, Balázs and Szalay, Zsuzsa}},
isbn = {{9783032140104}},
issn = {{2366-2557}},
keywords = {{Climate change; Extreme Weather; Hygrothermal Simulation; Typical Weather; Weather Data}},
language = {{eng}},
pages = {{152--163}},
publisher = {{Springer Science and Business Media B.V.}},
series = {{Lecture Notes in Civil Engineering}},
title = {{Impacts of Representative Weather Data Type on Hygrothermal Simulations for Future Climate}},
url = {{http://dx.doi.org/10.1007/978-3-032-14011-1_13}},
doi = {{10.1007/978-3-032-14011-1_13}},
volume = {{795 LNCE}},
year = {{2026}},
}