Projected changes of temperature extremes over nine major basins in China based on the CMIP5 multimodel ensembles View Full Text


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Article Info

DATE

2018-06-09

AUTHORS

Kai Xu, Chuanhao Wu, Bill X. Hu

ABSTRACT

Based on the outputs of 27 global climate models (GCMs) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5), projected changes of extreme temperature events have been analyzed over nine river basins in China by the end of the twenty-first century relative to the reference period 1961–1990. The temporal and spatial changes and their projection uncertainty are studied using the extreme temperature indices defined by the Expert Team of Climate Change Detection and Indices (ETCCDI) under two Representative Concentration Pathways (RCPs). The model simulations predict a general increasing (decreasing) trend in warm (cold) extremes over China in the twenty-first century, with more pronounced warming trend under a higher emission scenario. The projected changes in cold and warm extremes exhibit a large difference in spatial patterns. The high-latitude and high-elevation regions of China (e.g., Continental and Southwest basins) are projected to respond more strongly to changes in cold extremes, while eastern and southern China (e.g., Yangtze River and Pearl River basins) tend to be more sensitive to the increases in warm extremes. In general, projected changes in cold indices based on minimum temperature tend to be more pronounced than in warm indices based on maximum temperature. Uncertainty analysis shows a large difference among the 27 GCMs under 2 RCP scenarios, and the uncertainty ranges tend to be larger under a higher emission scenario. Overall, the uncertainties in the emission scenarios are smaller than those from the climate models in the near future period. However, for the long-term climate projections (e.g., by the end of the twenty-first century), the projected difference under various emission scenarios tends to be larger than those by different climate models and hence can be the dominant contributor to the projection uncertainty of temperature indices. More... »

PAGES

321-339

References to SciGraph publications

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