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Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
2013 (English)In: Renewable energy, ISSN 0960-1481, Vol. 55, no 0, 514-524 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2013. Vol. 55, no 0, 514-524 p.
Keyword [en]
Climate change, Simulation weather data, Weather data morphing, Weather data generation tool
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:uu:diva-222367DOI: 10.1016/j.renene.2012.12.049OAI: oai:DiVA.org:uu-222367DiVA: diva2:711582
Available from: 2014-04-10 Created: 2014-04-10 Last updated: 2014-04-10

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Publisher's full texthttp://www.sciencedirect.com/science/article/pii/S0960148113000232
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