Modelling the future climate and outdoor thermal comfort over Eurasia

• Main Author: Top, Sara
• Other Authors: Caluwaerts, Steven, De Maeyer, Philippe, Termonia, Piet
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Ghent University. Faculty of Sciences 2022
• Subjects: Physics and Astronomy; Earth and Environmental Sciences; regional climate modelling; outdoor thermal comfort; CORDEX; Central Asia; urban measurement network; urban climate; Arctic; Remo; Global warming; Human health
• Online Access: https://biblio.ugent.be/publication/8755381; http://hdl.handle.net/1854/LU-8755381; https://biblio.ugent.be/publication/8755381/file/8755387

Unprecedented widespread and rapid changes in the climate system have been observed over every region across the globe. Moreover, the increase in global near surface temperature is projected to continue until at least 2050, which will lead towards more extreme events. This ongoing global warming will cause more frequent exceedance of human health heat thresholds, leading to reduced well-being, labour productivity and an excess in mortality. Regional climate models (RCMs) are used to downscale the information of global models over particular regions of interest to study the effect of global warming at higher spatial and temporal resolutions. The Coordinated Regional Climate Downscaling Experiment (CORDEX) creates a framework for scientists to perform such regional climate downscaling in a systematic way. High-resolution climate information over Asia is still scarce and this region deserves attention since it comprises a large range of climatic zones and affects some highly populated regions. To fill this gap, two RCMs, ALARO and REMO, were run over the Central Asia CORDEX (CAS-CORDEX) domain, covering most of the Eurasian continent. The resulting climate data was evaluated to investigate whether these RCMs produce reliable climate information. In general both RCMs reproduced realistic spatial patterns for temperature, but they underestimated the diurnal temperature range. There were also significant biases found in multiple subregions during several seasons, e.g., a warm bias in the north during winter and a wet bias over the Asian monsoon region. The projections of four global-regional climate model combinations of a small multi-model ensemble showed for the 1.5 °C, 2 °C and 3 °C global warming levels geographically unequal warming and precipitation trends over Eurasia, with a faster warming rate and increasing precipitation in northern Eurasia due to the Arctic amplification. Further, a significant decrease in precipitation was found over southeastern China for global warming beyond 2 °C. Outdoor thermal ...