4.4 Article

Climate change in the Tianshan and northern Kunlun Mountains based on GCM simulation ensemble with Bayesian model averaging

Journal

JOURNAL OF ARID LAND
Volume 9, Issue 4, Pages 622-634

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s40333-017-0100-9

Keywords

climate change; GCM ensemble; Bayesian model averaging; Tianshan and northern Kunlun Mountains

Funding

  1. Thousand Youth Talents Plan (Xinjiang Project)
  2. National Natural Science Foundation of China [41630859]
  3. West Light Foundation of Chinese Academy of Sciences [2016QNXZB12]

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Climate change in mountainous regions has significant impacts on hydrological and ecological systems. This research studied the future temperature, precipitation and snowfall in the 21st century for the Tianshan and northern Kunlun Mountains (TKM) based on the general circulation model (GCM) simulation ensemble from the coupled model intercomparison project phase 5 (CMIP5) under the representative concentration pathway (RCP) lower emission scenario RCP4.5 and higher emission scenario RCP8.5 using the Bayesian model averaging (BMA) technique. Results show that (1) BMA significantly outperformed the simple ensemble analysis and BMA mean matches all the three observed climate variables; (2) at the end of the 21st century (2070-2099) under RCP8.5, compared to the control period (1976-2005), annual mean temperature and mean annual precipitation will rise considerably by 4.8A degrees C and 5.2%, respectively, while mean annual snowfall will dramatically decrease by 26.5%; (3) precipitation will increase in the northern Tianshan region while decrease in the Amu Darya Basin. Snowfall will significantly decrease in the western TKM. Mean annual snowfall fraction will also decrease from 0.56 of 1976-2005 to 0.42 of 2070-2099 under RCP8.5; and (4) snowfall shows a high sensitivity to temperature in autumn and spring while a low sensitivity in winter, with the highest sensitivity values occurring at the edge areas of TKM. The projections mean that flood risk will increase and solid water storage will decrease.

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