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Building Adaptation Measures Using Future Climate Scenarios—A Scoping Review of Uncertainty Treatment and Communication

Author(s): ORCID
ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 6, v. 13
Page(s): 1460
DOI: 10.3390/buildings13061460
Abstract:

The global climate is changing. Predicting the impacts this will have on buildings is the first step in the process of finding suitable building adaptation measures. Future climate adaptation of buildings and infrastructure is a growing field of research, relying on both socio-economical and meteorological research for input values to the simulation models. Models producing hourly future weather data rely on global climate models which are based on emission scenarios made from assumptions of future political, social, and economic developments. Accounting for the uncertainties from these underlying models as much as possible, and communicating the uncertainties in the results, is obviously paramount for reliable conclusions from the building simulation models. This paper is a scoping review, investigating how 132 studies treat and communicate the string of uncertainties from underlying models connected to future weather file generation in the scientific literature on building adaptation research. The findings suggest that climate-model-induced uncertainties are often under-communicated, due to either insufficient analysis or neglect. The studies that included the most comprehensive analyses of the uncertainties frequently concluded that treatment of these is important for the reliability of the results, and neglecting this could lead to misleading conclusions.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10731754
  • Published on:
    21/06/2023
  • Last updated on:
    07/08/2023
 
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