期刊
JOURNAL OF CLIMATE
卷 26, 期 5, 页码 1561-1574出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-11-00678.1
关键词
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资金
- Centre for Earth System Dynamics (CESD)
- Edinburgh Compute and Data Facility (ECDF)
- NFS [ATM-0296007]
- U.S. Department of Energy's Office of Science and Office of Biological and Environmental Research
- National Oceanic and Atmospheric Administration's Climate Program Office (IDAG group)
- NERC [NEH0035331]
- DECC/Defra Met Office Hadley Centre Climate Programme [GA01101]
- NERC [NE/J005363/1] Funding Source: UKRI
- Natural Environment Research Council [NE/J005363/1] Funding Source: researchfish
This study determines whether observed recent changes in the frequency of hot and cold extremes over land can be explained by climate variability or whether they show a detectable response to external influences. The authors analyze changes in the frequency of moderate-to-extreme daily temperatures-namely, the number of days exceeding the 90th percentile and the number of days not reaching the 10th percentile of daily minimum (tn90 and tn10, respectively) and maximum (tx90 and tx10, respectively) temperature-for both cold and warm seasons. The analysis is performed on a range of spatial scales and separately for boreal cold- and warm-season data. The fingerprint for external forcing is derived from an ensemble of simulations produced with the Hadley Centre Global Environmental Model, version 1 (HadGEM1), with both anthropogenic and natural forcings. The observations show an increase in warm extremes and a decrease in cold extremes in both seasons and in almost all regions that are generally well captured by the model. Some regional differences between model and observations may be due to local forcings or changes in climate dynamics. A detection analysis, using both optimized and nonoptimized fingerprints, shows that the influence of external forcing is detectable in observations for both cold and warm extremes, and cold and warm seasons, over the period 1951-2003 at the 5% level. It is also detectable separately for the Northern and Southern Hemispheres, and over most regions analyzed. The model shows a tendency to significantly overestimate changes in warm daytime extremes, particularly in summer.
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