No abstract

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH₄). Increased wetland CH₄ emissions could act as a positive feedback to future warming. The Wetland and Wetland CH₄ Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH₄ emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO₂) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO₂ concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. <br><br> Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH₄ emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH₄ emissions, but large variation between the models remains. For annual global CH₄ emissions, the models vary by ±40% of the all-model mean (190 Tg CH₄ yr⁻¹). Second, all models show a strong positive response to increased atmospheric CO₂ concentrations (857 ppm) in both CH₄ emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH₄ fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH₄ fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale c...

This is a repository copy of Acceleration of global N2O emissions seen from two decades of atmospheric inversion.

We undertook this study to increase our understanding of how forest clearing for pasture in the Brazilian Amazon is affecting N20 fluxes from tropical soils. More specifically, we wanted to do four things: (1) develop an understanding of the dynamics of N20 fluxes during pasture establishment in the Amazon; (2) evaluate the finding that intact forests have 34,179

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH₄). Increased wetland CH₄ emissions could act as a positive feedback to future warming. The Wetland and Wetland CH₄ Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large scale wetland characteristics and corresponding CH₄ emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO₂) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO₂ concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location with some models simulating wetland area prognostically, while other models relied on remotely-sensed inundation datasets, or an approach intermediate between the two. <br><br> Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH₄ emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH₄ emissions, but large variation between the models remains. For annual global CH₄ emissions, the models vary by ±40 % of the all model mean (190 Tg CH₄ yr^&minus;1). Second, all models show a strong positive response to increased atmospheric CO₂ concentrations (857 ppm) in both CH₄ emissions and wetland area. In response to increasing global temperatures (+3.4 % globally spatially uniform), on average, the models decreased wetland area and CH₄ fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH₄ fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatia...