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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. 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 TgCH4 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% 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 comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely-sensed inundation datasets. And fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for. [ABSTRACT FROM AUTHOR]

Terrestrial and oceanic carbon cycle processes remove ~55% of global carbon emissions, with the remaining 45 %, known as the "airborne fraction", accumulating in the atmosphere. The long-term dynamics of the component fluxes contributing to the airborne fraction are challenging to interpret, but important for informing fossil-fuel emission targets and for monitoring the trends of biospheric carbon fluxes. Climate and land-cover forcing data for terrestrial ecosystem models are a largely unexplored source of uncertainty in terms of their contribution to understanding airborne fraction dynamics. Here we present results using a single dynamic global vegetation model forced by an ensemble experiment of climate (CRU, ERA-Interim, NCEP-DOE II), and diagnostic land-cover datasets (GLC2000, GlobCover, MODIS). For the averaging period 1996-2005, forcing uncertainties resulted in a large range of simulated global carbon fluxes, up to 13% for net primary production (52.4 to 60.2 Pg C a-1) and 19% for soil respiration (44.2 to 54.8 Pg C a-1). The sensitivity of contemporary global terrestrial carbon fluxes to climate strongly depends on forcing data (1.2-5.9 Pg C K-1 or 0.5 to 2.7 ppmv CO2 K-1), but weakening carbon sinks in sub-tropical regions and strengthening carbon sinks in northern latitudes are found to be robust. The climate and land-cover combination that best correlate to the inferred carbon sink, and with the lowest residuals, is from observational data (CRU) rather than reanalysis climate data and with land-cover categories that have more stringent criteria for forest cover (MODIS). Since 1998, an increasing positive trend in residual error from bottom-up accounting of global sinks and sources (from 0.03 (1989-2005) to 0.23 Pg C a-1 (1998-2005)) suggests that either modeled drought sensitivity of carbon fluxes is too high, or that carbon emissions from net land-cover change is too large. [ABSTRACT FROM AUTHOR]

Terrestrial and oceanic carbon cycle processes remove ~55% of global carbon emissions, with the remaining 45%, known as the "airborne fraction", accumulating in the atmosphere. The long-term dynamics of the component fluxes contributing to the airborne fraction are challenging to interpret, but important for informing fossil-fuel emission targets and for monitoring the trends of biospheric carbon fluxes. Climate and land-cover forcing data for terrestrial ecosystem models are a largely unexplored source of uncertainty in terms of their contribution to understanding airborne fraction dynamics. Here we present results using a single dynamic global vegetation model forced by an ensemble experiment of climate (CRU, ERA-Interim, NCEP-DOE II), and diagnostic land-cover datasets (GLC2000, GlobCover, MODIS). Forcing uncertainties resulted in a large range of simulated global carbon fluxes, up to 13% for net primary production (52.4 to 60.2 Pg C a-1) and 19% for soil respiration (44.2 to 54.8Pg C a-1). The sensitivity of contemporary global terrestrial carbon fluxes to climate strongly depends on forcing data (1.2-5.9 Pg C K-1 or 0.5 to 2.7 ppmv CO2 K-1), but weakening carbon sinks in sub-tropical regions and strengthening carbon sinks in northern latitudes are found to be robust. The climate and land-cover combination that best correlate to the inferred carbon sink, and with the lowest residuals, is from observational data (CRU) rather than reanalysis climate data and with land-cover categories that have more stringent criteria for forest cover (MODIS). Since 1998, an increasing positive trend in residual error from bottom-up accounting of global sinks and sources (from 0.03 (1989-2005) to 0.23Pg C a-1 (1998-2005)) suggests that either modeled drought sensitivity of carbon fluxes is too high, or that the trend toward decreased net land-use fluxes (~0.5 Pg C) is overestimated. [ABSTRACT FROM AUTHOR]