Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates

• Published in: Renewable energy Vol. 55; pp. 514 - 524
• Main Authors: Jentsch, Mark F., James, Patrick A.B., Bourikas, Leonidas, Bahaj, AbuBakr S.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01-07-2013; Elsevier
• Subjects: Applied sciences; Climate; Climate change; Climatology; Computer simulation; data collection; emissions; Energy; Exact sciences and technology; General Circulation Models; meteorological data; Natural energy; Offices; prediction; RCM; Simulation weather data; solar energy; temperature; Weather; Weather data generation tool; Weather data morphing; United Kingdom; Weather data morphing; Climate change; Simulation weather data; Weather data generation tool; Dynamical climatology; Weather; Energy consumption; Climate; Renewable energy; Simulation; Buildings
• ISSN: 0960-1481; 1879-0682; 1879-0682
• DOI: 10.1016/j.renene.2012.12.049

Building performance and solar energy system simulations are typically undertaken with standardised weather files which do not generally consider future climate predictions. This paper investigates the generation of climate change adapted simulation weather data for locations worldwide from readily available data sets. An approach is presented for ‘morphing’ existing EnergyPlus/ESP-r Weather (EPW) data with UK Met Office Hadley Centre general circulation model (GCM) predictions for a ‘medium–high’ emissions scenario (A2). It was found that, for the United Kingdom (UK), the GCM ‘morphed’ data shows a smoothing effect relative to data generated from the corresponding regional climate model (RCM) outputs. This is confirmed by building performance simulations of a naturally ventilated UK office building which highlight a consistent temperature distribution profile between GCM and RCM ‘morphed’ data, yet with a shift in the distribution. It is demonstrated that, until more detailed RCM data becomes available globally, ‘morphing’ with GCM data can be considered as a viable interim approach to generating climate change adapted weather data.
► GCM outputs are used to generate climate change adapted simulation weather data. ► Underlying data uncertainties/limitations of the generation method are discussed. ► Using GCM data for transformation smooths weather profiles relative to RCM data. ► Climate model grid resolution impacts on building performance simulation results. ► Until RCM data becomes widely available, GCM data can be considered as appropriate.