Browsing by Author "Hodson, Elke L."

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Emerging role of wetland methane emissions in driving 21st century climate change
(2017-09) Zhang, Zhen; Zimmermann, Niklaus E.; Stenke, Andrea; Li, Xin; Hodson, Elke L.; Zhu, Gaofeng; Huang, Chunlin; Poulter, Benjamin
Wetland methane (CH4) emissions are the largest natural source in the global CH4 budget, contributing to roughly one third of total natural and anthropogenic emissions. As the second most important anthropogenic greenhouse gas in the atmosphere after CO2, CH4 is strongly associated with climate feedbacks. However, due to the paucity of data, wetland CH4 feedbacks were not fully assessed in the Intergovernmental Panel on Climate Change Fifth Assessment Report. The degree to which future expansion of wetlands and CH4 emissions will evolve and consequently drive climate feedbacks is thus a question of major concern. Here we present an ensemble estimate of wetland CH4 emissions driven by 38 general circulation models for the 21st century. We find that climate change-induced increases in boreal wetland extent and temperature-driven increases in tropical CH4 emissions will dominate anthropogenic CH4 emissions by 38 to 56% toward the end of the 21st century under the Representative Concentration Pathway (RCP2.6). Depending on scenarios, wetland CH4 feedbacks translate to an increase in additional global mean radiative forcing of 0.04W.m(-2) to 0.19W.m(-2) by the end of the 21st century. Under the \worst-case\" RCP8.5 scenario, with no climate mitigation, boreal CH4 emissions are enhanced by 18.05 Tg to 41.69 Tg, due to thawing of inundated areas during the cold season (December to May) and rising temperature, while tropical CH4 emissions accelerate with a total increment of 48.36 Tg to 87.37 Tg by 2099. Our results suggest that climate mitigation policies must consider mitigation of wetland CH4 feedbacks to maintain average global warming below 2 degrees C.
Sensitivity of global terrestrial carbon cycle dynamics to variability in satellite-observed burned area
(2015-02) Poulter, Benjamin; Cadule, Patricia; Chelney, Audrey; Ciais, Philippe; Hodson, Elke L.; Peylin, Phili; Plummer, Stephen; Spessa, Allan; Saatchi, Sassan S.; Yue, Chao; Zimmermann, Niklaus E.
Fire plays an important role in terrestrial ecosystems by regulating biogeochemistry, biogeography, and energy budgets, yet despite the importance of fire as an integral ecosystem process, significant advances remain to improve its prognostic representation in carbon cycle models. To recommend and to help prioritize model improvements, this study investigates the sensitivity of a coupled global biogeography and biogeochemistry model, LPJ, to observed burned area measured by three independent satellite-derived products, GFED v3.1, L3JRC, and GlobCarbon. Model variables are compared with benchmarks that include pantropical aboveground biomass, global tree cover, and CO2 and CO trace gas concentrations. Depending on prescribed burned area product, global aboveground carbon stocks varied by 300 Pg C, and woody cover ranged from 50 to 73 Mkm2. Tree cover and biomass were both reduced linearly with increasing burned area, i.e., at regional scales, a 10% reduction in tree cover per 1000 km2, and 0.04-to-0.40 Mg C reduction per 1000 km2. In boreal regions, satellite burned area improved simulated tree cover and biomass distributions, but in savanna regions, model-data correlations decreased. Global net biome production was relatively insensitive to burned area, and the long-term land carbon sink was robust, ~2.5 Pg C yr−1, suggesting that feedbacks from ecosystem respiration compensated for reductions in fuel consumption via fire. CO2 transport provided further evidence that heterotrophic respiration compensated any emission reductions in the absence of fire, with minor differences in modeled CO2 fluxes among burned area products. CO was a more sensitive indicator for evaluating fire emissions, with MODIS-GFED burned area producing CO concentrations largely in agreement with independent observations in high latitudes. This study illustrates how ensembles of burned area data sets can be used to diagnose model structures and parameters for further improvement and also highlights the importance in considering uncertainties and variability in observed burned area data products for model applications.