Affiliation:
1. Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters Key Laboratory for Aerosol‐Cloud‐Precipitation of China Meteorological Administration Nanjing University of Information Science and Technology Nanjing China
2. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China
3. Department of Earth and Atmospheric Sciences Saint Louis University St. Louis MO USA
4. Meteorological Observation Centre China Meteorological Administration Beijing China
Abstract
AbstractHistorical changes and possible future projections of temperature extremes in China, in terms of return values of annual extreme temperatures, are examined based on daily maximum and minimum temperatures from station observations and multiple models of the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP). The observations suggest that increases in temperature extremes are largely attributable to the changing mean climate, while the varying natural variability also has an important impact, which depends on the index of the variability. The models simulate warm extremes reasonably well but underestimate the spatial heterogeneity and temporal trend of cold extremes in China. In comparison, Coupled Model Intercomparison Project Phase 6 (CMIP6) models have higher skill in simulating temperature extremes in China, showing smaller biases and intermodel variability. MRI‐ESM2‐0 and NorESM2‐LM from CMIP6 and GFDL‐ESM2M and NorESM1‐M from CMIP5 are selected as reference models based on the better performance in reproducing observed temperature extremes in China. In the future, projections from CMIP6 multimodel ensemble (MME, represented as the multimodel median) and reference models all show a continued uptick in temperature extremes, with statistically significant increases in warm extremes mainly in the north and increases in cold extremes prominent in most parts of China. Different individual models, which have similar historical simulations, yield divergent future trends of temperature extremes, which may be associated with different climate sensitivities of models. In addition, MME usage should be treated with caution since its smoothing on spatial heterogeneity and possible information from poor models.
Funder
Natural Science Foundation of Jiangsu Province
Publisher
American Geophysical Union (AGU)
Subject
General Earth and Planetary Sciences,Environmental Science (miscellaneous)
Cited by
2 articles.
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