A Comparative Analysis of Different Future Weather Data for Building Energy Performance Simulation
1
Department of Energy, Politecnico di Torino, 10129 Turin, Italy
2
ENEA, Via Anguillarese 301, 00123 Rome, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Steven McNulty
Climate 2021, 9(2), 37; https://doi.org/10.3390/cli9020037
Received: 2 February 2021
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Revised: 17 February 2021
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Accepted: 19 February 2021
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Published: 23 February 2021
(This article belongs to the Special Issue The Built Environment in a Changing Climate: Interactions, Challenges and Perspectives)
The building energy performance pattern is predicted to be shifted in the future due to climate change. To analyze this phenomenon, there is an urgent need for reliable and robust future weather datasets. Several ways for estimating future climate projection and creating weather files exist. This paper attempts to comparatively analyze three tools for generating future weather datasets based on statistical downscaling (WeatherShift, Meteonorm, and CCWorldWeatherGen) with one based on dynamical downscaling (a future-typical meteorological year, created using a high-quality reginal climate model). Four weather datasets for the city of Rome are generated and applied to the energy simulation of a mono family house and an apartment block as representative building types of Italian residential building stock. The results show that morphed weather files have a relatively similar operation in predicting the future comfort and energy performance of the buildings. In addition, discrepancy between them and the dynamical downscaled weather file is revealed. The analysis shows that this comes not only from using different approaches for creating future weather datasets but also by the building type. Therefore, for finding climate resilient solutions for buildings, care should be taken in using different methods for developing future weather datasets, and regional and localized analysis becomes vital.
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Keywords:
climate change; future weather data; building energy performance; thermal comfort; statistical downscaling of climate models; dynamical downscaling of climate models
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MDPI and ACS Style
P.Tootkaboni, M.; Ballarini, I.; Zinzi, M.; Corrado, V. A Comparative Analysis of Different Future Weather Data for Building Energy Performance Simulation. Climate 2021, 9, 37. https://doi.org/10.3390/cli9020037
AMA Style
P.Tootkaboni M, Ballarini I, Zinzi M, Corrado V. A Comparative Analysis of Different Future Weather Data for Building Energy Performance Simulation. Climate. 2021; 9(2):37. https://doi.org/10.3390/cli9020037
Chicago/Turabian StyleP.Tootkaboni, Mamak, Ilaria Ballarini, Michele Zinzi, and Vincenzo Corrado. 2021. "A Comparative Analysis of Different Future Weather Data for Building Energy Performance Simulation" Climate 9, no. 2: 37. https://doi.org/10.3390/cli9020037
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