Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability

By P. Cox, D. Pearson, B. Booth, Pierre Friedlingstein, C. Huntingford, Chris D. Jones, C. M. Luke. Nature, 2013

724 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0225ced4a5ae0b58a09823e0b742fcf3a33904d0

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In Global and Planetary Change

Citations in the corpus

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations (2017, background): “…surface temperature in the present climate correlates in climate models with the amplitude of the terrestrial ecosystem response to global warming (e.g., the balance between CO2 fertilization of plants and enhanced soil and plant respiration under warming) [Cox et al., 2013; Wenzel et al., 2014].”
Climate change impacts in Latin America and the Caribbean and their implications for development (2017, background): “…21 to 0.24 % for a 4 C regional warming when coupled carbon-cycle climate Climate change impacts in Latin America and the Caribbean and their implications for… models are adjusted to better represent the inter-annual variability of tropical temperatures and related CO2 emissions (Cox et al. 2013).”
Machine learning and artificial intelligence to aid climate change research and preparedness (2019, background): “Examples (Hall et al 2019) include physical parts of the climate system, e.g. reducing uncertainty on equilibrium climate sensitivity (Cox et al 2018), and geochemical or ecological features, e.g. refining Amazon ‘die-back’ risk (Cox et al 2013).”
Effect of increasing CO2 on the terrestrial carbon cycle (2014, background): “In models of the future, the biosphere operates as a net sink, reducing the climate impact of fossil fuel and deforestation emissions, until positive feedbacks from climate change [reduced productivity, increased respiration, or dieback (7)] and land use emissions exceed the CO2 effect.”
Causes and implications of persistent atmospheric carbon dioxide biases in Earth System Models (2014, methodology): “Cox et al. [2013] used the observed relationship between the growth rate of atmospheric CO2 and tropical temperature as a constraint to reduce predicted uncertainty in the land carbon storage sensitivity to climate change (γL) in the tropics in C(4)MIP models. Similarly, Gillett et al. [2013] used t”
Evaluating Emergent Constraints on Equilibrium Climate Sensitivity (2018, background): “Our scope is also limited by our focus on ECS, which precludes studies focused on other aspects of the climate system (e.g., Hall and Qu 2006; Cox et al. 2013).”
Compensatory water effects link yearly global land CO2 sink changes to temperature (2017, background): “K.I. acknowledges support from the Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan.”
Exceeding 1.5°C global warming could trigger multiple climate tipping points (2022, neutral): “More recent ESMs tend not to simulate climate-induced Amazon dieback and emergent constraints indicate lower rainforest sensitivity to warming ( 80 ).”
A climate model projection weighting scheme accounting for performance and interdependence (2017, methodology): “And fifth, model dependence gets increasingly relevant with increasing replication of code across institutions, models being run at different resolutions, used as climate versus Earth system models, etc. [Knutti et al., 2013].”
Tipping elements and climate–economic shocks: Pathways toward integrated assessment (2016, methodology): “…interannual variations in CO2 growth rate over 1960–2010 suggested that the tropical forests in the HadCM3 models are overly sensitive to warming [Cox et al., 2013], but to our knowledge, no other Earth system models have been used to investigate the distinction between committed and realized…”
Natural climate solutions (2017, positive): “Increases in temperature, drought, fire, and pest outbreaks could negatively impact photosynthesis and carbon storage, while CO2 fertilization has positive effects (53).”
Functional traits as predictors of vital rates across the life cycle of tropical trees (2016, background): “Such low predictive power strongly limits the potential of traits to serve as proxies for life history variation or inform global vegetation models (Cox et al. 2013; Friedlingstein et al. 2014).”
The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty (2019, background): “5 to CLM5 require further investigation, since climate‐driven variations at interannual timescales may provide useful information about future climate‐ driven changes in terrestrial carbon stocks (Cox et al., 2013; Keppel‐ Aleks et al., 2018).”
Statistical significance of climate sensitivity predictors obtained by data mining (2014, background): “Several constraints of this type have already been proposed [Hall and Qu, 2006; Qu et al., 2013; Cox et al., 2013].”