The Vatic Weather File Generator (VWFG v1.0.0)

Abstract

To combat climate change caused by cities, it is necessary to perform urban physics modeling to assess mitigation solutions suitable for future climates. A challenge is availability of reliable future weather files for investigation of future climate scenarios. This research aims to develop the Vatic Weather File Generator (VWFG) using the statistical downscaling approach to fill this gap. VWFG is novel by using a history of weather files over multiple years to downscale future climate model data utilizing (1) quantile–quantile bias corrections, (2) record matching by the Finkelstein–Schafer method, and (3) shifting–stretching corrections. This implementation of VWFG uses the CanRCM4 climate model (1980–2100) and the ERA5 reanalysis data product as weather files (1980–2020) for two Representative Concentration Pathway (RCP) scenarios. VWFG outputs are consistent with findings in other studies. Further, to investigate the performance of VWFG for a case in Toronto, Canada, the Vertical City Weather Generator (VCWG) is forced by VWFG to predict the building sensible heating and cooling energy demands for a two-story single-family residential house. It is found that the building sensible heating demand is reduced over time (∼ 15%–30% for RCP 4.5–8.5 W m−2) and the building sensible cooling demand is increased over time (∼ 20%–50% for RCP 4.5–8.5 W m−2). The amount of change is greater for RCP 8.5 than RCP 4.5 W m−2. VWFG is a simple, practical, and widely applicable tool for urban physics simulations of future climates, particularly in cases where reliable forcing data is lacking otherwise.