EconPapers    
Economics at your fingertips  
 

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

Mark F. Jentsch, Patrick A.B. James, Leonidas Bourikas and AbuBakr S. Bahaj

Renewable Energy, 2013, vol. 55, issue C, 514-524

Abstract: 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.

Keywords: Climate change; Simulation weather data; Weather data morphing; Weather data generation tool (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (48)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148113000232
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:55:y:2013:i:c:p:514-524

DOI: 10.1016/j.renene.2012.12.049

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:renene:v:55:y:2013:i:c:p:514-524