RESUMEN
The Wet Bulb Globe Temperature (WBGT) is an international standard heat index used by the health, industrial, sports, and climate sectors to assess thermal comfort during heat extremes. Observations of its components, the globe and the wet bulb temperature (WBT), are however sparse. Therefore WBGT is difficult to derive, making it common to rely on approximations, such as the ones developed by Liljegren et al. (2008, https://doi.org/10.1080/15459620802310770, W B G T L i l j e g r e n ) and by the American College of Sports Medicine ( W B G T A C S M 87 ). In this study, a global data set is created by implementing an updated WBGT method using ECMWF ERA5 gridded meteorological variables and is evaluated against existing WBGT methods. The new method, W B G T B r i m i c o m b e , uses globe temperature calculated using mean radiant temperature and is found to be accurate in comparison to W B G T L i l j e g r e n across three heatwave case studies. In addition, it is found that W B G T A C S M 87 is not an adequate approximation of WBGT. Our new method is a candidate for a global forecasting early warning system.
RESUMEN
Computational science is crucial for delivering reliable weather and climate predictions. However, despite decades of high-performance computing experience, there is serious concern about the sustainability of this application in the post-Moore/Dennard era. Here, we discuss the present limitations in the field and propose the design of a novel infrastructure that is scalable and more adaptable to future, yet unknown computing architectures.
