Several climate models have been developed and used to forecast the effects of the climate changes, however the variability of results due to different models lead to a significant uncertainty on the estimation of the building energy use for the next century. In this context, the paper analyses this uncertainty and combines different climate models in order to improve the robustness of energy consumption predictions. The data of the climate models were then used to generate hourly weather files for the future period 2020-2099 and energy simulations for a case study located in Palermo (Italy) were performed. Results show a wide variability among all models (either alone or combined with our data-fusion method), with a mean variability of about 18% of the cooling energy requirements considering the RCP4.5 scenario. This reinforces the need for a more detailed validation and alternative climate change models for building simulation.

Giovanni Tumminia, F.G. (2020). A New Approach to Model the Effect of Climate Change on the Building Sector: a Climate Models Data Fusion. In E.F. V. Corrado (a cura di), Proceedings of Building Simulation 2019: 16th IBPSA Conference (pp. 4762-4769) [10.26868/25222708.2019.210243].

A New Approach to Model the Effect of Climate Change on the Building Sector: a Climate Models Data Fusion

Francesco Guarino;Daniele Croce;Sonia Longo;Ilenia Tinnirello;Maurizio Cellura
2020

Abstract

Several climate models have been developed and used to forecast the effects of the climate changes, however the variability of results due to different models lead to a significant uncertainty on the estimation of the building energy use for the next century. In this context, the paper analyses this uncertainty and combines different climate models in order to improve the robustness of energy consumption predictions. The data of the climate models were then used to generate hourly weather files for the future period 2020-2099 and energy simulations for a case study located in Palermo (Italy) were performed. Results show a wide variability among all models (either alone or combined with our data-fusion method), with a mean variability of about 18% of the cooling energy requirements considering the RCP4.5 scenario. This reinforces the need for a more detailed validation and alternative climate change models for building simulation.
Settore ING-IND/11 - Fisica Tecnica Ambientale
Settore ING-INF/03 - Telecomunicazioni
978-1-7750520-1-2
Giovanni Tumminia, F.G. (2020). A New Approach to Model the Effect of Climate Change on the Building Sector: a Climate Models Data Fusion. In E.F. V. Corrado (a cura di), Proceedings of Building Simulation 2019: 16th IBPSA Conference (pp. 4762-4769) [10.26868/25222708.2019.210243].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/426543
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