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Carbon cycle extremes during the 21st century in CMIP5 models: Future evolution and attribution to climatic drivers
Author(s) -
Zscheischler Jakob,
Reichstein Markus,
von Buttlar Jannis,
Mu Mingquan,
Randerson James T.,
Mahecha Miguel D.
Publication year - 2014
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2014gl062409
Subject(s) - coupled model intercomparison project , environmental science , carbon cycle , primary production , ecosystem , biogeochemical cycle , climate change , climatology , atmospheric sciences , climate extremes , climate model , earth system science , water cycle , representative concentration pathways , ecology , geology , biology
Climate extremes such as droughts and heat waves affect terrestrial ecosystems and may alter local carbon budgets. However, it still remains uncertain to what degree extreme impacts in the carbon cycle influence the carbon cycle‐climate feedback both today and the near future. Here we analyze spatiotemporally contiguous negative extreme anomalies in gross primary production (GPP) and net ecosystem production (NEP) in model output of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble and investigate their future development and attribution to climatic drivers. We find that relative to the overall increase in global carbon uptake, negative extremes in GPP and NEP lose importance toward the end of the 21st century. This effect can be related to elevated CO 2 concentrations and higher amounts of available water at the global scale, partially mitigating the impacts of droughts and heat waves, respectively. Overall, based on CMIP5 models, we hypothesize that terrestrial ecosystems might be more resilient against future climate extremes than previously thought. Future work will have to further scrutinize these results considering that various biological and biogeochemical feedbacks are not yet integrated within Earth system models.