Methodological choices influencing uncertainties andinformation loss in research on climate adaptation of buildings
Authors: Gaarder Jørn Emil , Hygen Hans Olav , Kvande Tore 
Published: June 2022

&lt;p&gt;Adapting buildings to a changing climate has become an increasingly popular topic of research. A&lt;br&gt;critical tool for evaluating the proposed adaptation measures, is simulation models of future climatic&lt;br&gt;strains. Using future climate scenarios introduces uncertainties into the study conclusions, as they&lt;br&gt;are based on complex socio-economic and meteorological models and predict consequences far into&lt;br&gt;the future. Accounting for, and treatment of, these uncertainties are paramount for the quality of&lt;br&gt;the results. We have mapped the methodology used for calculating the climate strains in building&lt;br&gt;simulation models in 132 studies within the topic of building adaptation measures from the past 7&lt;br&gt;years. In particular, the treatment of climate-model induced uncertainties and presentation of their&lt;br&gt;influence on the final results have been mapped.&lt;/p&gt;&lt;p&gt;In order to quantify the uncertainties introduced by climate-modelling in some way, the calculated&lt;br&gt;climatic strains need to be based on more than one strain of climate-models, to root out the&lt;br&gt;variations, biases, and deviations in the chosen model. The studies presenting the most&lt;br&gt;comprehensive evaluation of climate related uncertainties produced means and standard deviations&lt;br&gt;for all used-GCM-RCM chains and evaluated the variations. The methods for downscaling and bias-&lt;br&gt;correcting were well-documented in these studies, providing a transparent presentation of the&lt;br&gt;underlying uncertainties. Producing such results is work-demanding and probabilistic results may be&lt;br&gt;more challenging to present in a clear way. However, presenting an analysis of the uncertainties&lt;br&gt;greatly increases the quality and credibility of the results, and even more importantly it reminds the&lt;br&gt;reader that assessments of complex systems far into the future are not deterministic in nature.&lt;/p&gt;&lt;p&gt;The different kinds of uncertainties introduced from climate-modelling found in the study selection&lt;br&gt;have been characterized and structured by level of uncertainty and source of uncertainty in this&lt;br&gt;paper, as well as how they are dealt with in principle. Further, a flow chart of how information loss&lt;br&gt;increases progressively through methodological choices along the way from emission scenario to&lt;br&gt;result presentation have been mapped and structured, as a tool for addressing the climate-&lt;br&gt;modelling-specific uncertainties in such studies. A frequent conclusion in studies calculating and&lt;br&gt;analyzing the uncertainties was that this should not be omitted, as it was found to have a great&lt;br&gt;impact on the results. By careful description of the methods, by calculating and carrying quantified&lt;br&gt;uncertainties from the climate-model to the results, and by evaluating the validity of the results, the&lt;br&gt;reader of such studies will certainly be reminded of the uncertain nature of the future.&lt;/p&gt;