4.0 Article

Future changes in thermal comfort conditions over China based on multi-RegCM4 simulations

Journal

ATMOSPHERIC AND OCEANIC SCIENCE LETTERS
Volume 11, Issue 4, Pages 291-299

Publisher

KEAI PUBLISHING LTD
DOI: 10.1080/16742834.2018.1471578

Keywords

Thermal comfort conditions; RegCM; climate change; population

Funding

  1. National Key Research and Development Program of China [2016YFA0600704]
  2. National Natural Science Foundation of China [41375104]

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A set of high resolution (25 km) 21st century climate change projections using the regional climate model RegCM4 driven by four global model simulations were conducted over East Asia under the mid-range RCP4.5 scenario. In the present paper, the authors investigate the change in thermal comfort conditions over china based on an ensemble of the projections, using the index of effective temperature (ET), which considers the aggregate effects of temperature, relative humidity, and wind on human thermal perception. The analysis also accounts for exposure as measured by distributed population amount scenarios. The authors find that the general increase in ET leads to a large increase in population exposure to very hot days (a China-aggregated sixfold increase in 'person-days' by the end of the 21st century. There is a decrease in cool, cold, and very cold person-days. Meanwhile, a decrease in comfortable day conditions by 22% person-days is found despite an increase in climate-based comfortable days. Analysis of the different contributions to the changes (climate, population, and interactions between the two) show that climate effects play a more important role in the hot end of the thermal comfort categories, while the population effects tend to be dominant in the cold categories. Thus, overall, even a mid-level warming scenario is found to increase the thermal stress over China, although there is a strong geographical dependence. The inclusion of population exposure strongly modulates the climate-only signal, which highlights the need for including socioeconomic factors in the assessment of risks associated with climate change.

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