Abstract
In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.
Highlights
Meteorological data like temperature, wind speed, and solar radiation are essential input for characterising buildings’ thermal performance
Using assimilated data-sources has several advantages, e.g., making it possible to supplement low-cost air temperature observations, that are relatively common to measure on-site, with other weather variables that are more difficult to capture or predict in a simple way. Such as solar irradiance data from services built on remote sensing of sky conditions, or wind speed estimations from numerical weather prediction (NWP)-models in forecast or reanalysis-mode
We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service
Summary
Meteorological data like temperature, wind speed, and solar radiation are essential input for characterising buildings’ thermal performance These elements are measured locally using a well-maintained weather station near the building site or on the building itself. Using assimilated data-sources has several advantages, e.g., making it possible to supplement low-cost air temperature observations, that are relatively common to measure on-site, with other weather variables that are more difficult to capture or predict in a simple way. Such as solar irradiance data from services built on remote sensing of sky conditions, or wind speed estimations from numerical weather prediction (NWP)-models in forecast or reanalysis-mode. Updated information about the past weather and historical climate is available via Copernicus Climate Change Service (C3S) Climate Data
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
