Climatic Change

, 108:581 | Cite as

Near-term increase in frequency of seasonal temperature extremes prior to the 2°C global warming target

  • Bruce T. AndersonEmail author


Given current international efforts to reduce greenhouse gas emissions and limit human-induced global-mean near-surface temperature increases to 2°C, relative to the pre-industrial era, we seek to determine the impact such a temperature increase might have upon the frequency of seasonal-mean temperature extremes; further we seek to determine what global-mean temperature increase would prevent extreme temperature values from becoming the norm. Results indicate that given a 2°C global mean temperature increase it is expected that for 70–80% of the land surface maximum seasonal-mean temperatures will exceed historical extremes (as determined from the 95th percentile threshold value over the second half of the 20th Century) in at least half of all years, i.e. the current historical extreme values will effectively become the norm. Many regions of the globe—including much of Africa, the southeastern and central portions of Asia, Indonesia, and the Amazon—will reach this point given the “committed” future global-mean temperature increase of 0.6°C (1.4°C relative to the pre-industrial era) and 50% of the land surface will reach it given a future global-mean temperature increase of between 0.8 and 0.95°C (1.6–1.75°C relative to the pre-industrial era). These results suggest substantial fractions of the globe could experience seasonal-mean temperature extremes with high regularity, even if the global-mean temperature increase remains below the 2°C target.


Exceedence Threshold 95th Percentile Threshold Global Warming Target Full Temperature Field Stochastic Modeling Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We first thank the anonymous reviewers their insightful comments on the manuscript. We also acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modeling (WGCM) for their roles in making available the WCRP CMIP3 multi-model dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy. University of East Anglia Climate Research Unit (CRU) temperature data made available by the British Atmospheric Data Centre, 2008. Available from

Supplementary material

10584_2011_196_MOESM1_ESM.doc (36 kb)
ESM 1 (DOC 36 kb)


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Department of Geography and EnvironmentBoston UniversityBostonUSA

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