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Climate change projections for building energy simulation studies: a CORDEX-based methodological approach to manage uncertainties

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  • Tanea Coronato

    (CONICET - UNR, Instituto de Física Rosario (IFIR)
    Facultad de Ciencias Exactas, Ingeniería y Agrimensura (FCEIA)
    CNRS – IRD – CONICET – UBA, Institut Franco-Argentin d’Estudes sur le Climat et ses Impacts (IRL IFAECI))

  • Pablo G. Zaninelli

    (CNRS – IRD – CONICET – UBA, Institut Franco-Argentin d’Estudes sur le Climat et ses Impacts (IRL IFAECI)
    IGEO, CSIC-Universidad Complutense de Madrid
    Facultad de Ciencias Astronómicas y Geofísicas)

  • Rita Abalone

    (CONICET - UNR, Instituto de Física Rosario (IFIR)
    Facultad de Ciencias Exactas, Ingeniería y Agrimensura (FCEIA))

  • Andrea F. Carril

    (CNRS – IRD – CONICET – UBA, Institut Franco-Argentin d’Estudes sur le Climat et ses Impacts (IRL IFAECI)
    UBA - CONICET, Centro de Investigaciones del Mar y la Atmósfera (CIMA))

Abstract

We propose a comprehensive methodological approach to address uncertainties in building energy simulation (BES) studies within a climate change context. Drawing upon expertise from the climate community, our approach aims to improve the reliability of climate-dependent BES for sustainable building design studies. The methodology focuses on creating weather files that accurately retain the climate variability from CORDEX high-frequency climate data, and performing multiple BES (conducted with climatologies from various climate models and emissions scenarios) while removing the climate models biases. The robustness of the results is assessed through statistical analysis, and an uncertainty range is attributed to future energy demand estimations. This approach is illustrated using a representative prototype of a social house located in central-eastern Argentina. The evaluation specifically focuses on assessing the influence of climate change projections on cooling and heating energy demand. We systematically assessed uncertainties related to climate scenarios, seasonality, and building design sensitivity. Our exercise highlight that uncertainty levels rise with higher emissions scenarios. Within our case study, the cooling (heating) energy demand exhibits substantial variations, ranging from 27-37 (303-330) MJ/m² in a moderate emissions context to 51-70 (266-326) MJ/m² in a high emissions scenario. Notably, improvements in building efficiency correlate with reduced uncertainty and, in the context of higher emissions, the projected energy demand can range between 24-37 (201-243) MJ/m². Finally, a discussion is provided on the added value of the proposed methodology compared to solely utilizing a single climate projection file in BES, when uncertainties within climate projections remain unassessed.

Suggested Citation

  • Tanea Coronato & Pablo G. Zaninelli & Rita Abalone & Andrea F. Carril, 2024. "Climate change projections for building energy simulation studies: a CORDEX-based methodological approach to manage uncertainties," Climatic Change, Springer, vol. 177(3), pages 1-22, March.
    • Handle: RePEc:spr:climat:v:177:y:2024:i:3:d:10.1007_s10584-024-03710-9
    DOI: 10.1007/s10584-024-03710-9
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    References listed on IDEAS

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    1. Jentsch, Mark F. & James, Patrick A.B. & Bourikas, Leonidas & Bahaj, AbuBakr S., 2013. "Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates," Renewable Energy, Elsevier, vol. 55(C), pages 514-524.
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    4. Nik, Vahid M., 2016. "Making energy simulation easier for future climate – Synthesizing typical and extreme weather data sets out of regional climate models (RCMs)," Applied Energy, Elsevier, vol. 177(C), pages 204-226.
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