A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models

Abstract

Abstract. Wetland emissions remain one of the principal sources of uncertainty in the global atmospheric methane (CH4) budget, largely due to poorly constrained process controls on CH4 production in waterlogged soils. Process-based estimates of global wetland CH4 emissions and their associated uncertainties can provide crucial prior information for model-based top-down CH4 emission estimates. Here we construct a global wetland CH4 emission model ensemble for use in atmospheric chemistry and transport models. Our 0.5° × 0.5° resolution model ensemble is based on satellite-derived surface water extent and precipitation re-analyses, nine heterotrophic respiration simulations (eight carbon cycle models and a data-constrained terrestrial carbon cycle analysis) and three temperature parameterizations for the period 2009–2010; an extended ensemble subset – based solely on precipitation and the data-constrained terrestrial carbon cycle analysis – is derived for the period 2001–2015. We incorporate the mean of the full and extended model ensembles into GEOS-Chem and compare model against surface measurements of atmospheric CH4; model performance (site-level and zonal mean anomaly residuals) compares favourably against published wetland CH4 emissions scenarios. We find that uncertainties in carbon decomposition rates and wetland extent together account for more than 80 % of the primary uncertainty in the timing, magnitude and seasonal variability of wetland CH4 emissions, although uncertainty in the temperature CH4:C dependence is a significant contributor to seasonal variations in mid-latitude wetland CH4 emissions. The combination of satellite, carbon cycle models and temperature dependence parameterizations provides a physically informed structural a priori uncertainty critical for top-down estimates of wetland CH4 fluxes: specifically, our ensemble can provide enhanced information on the prior CH4 emissions uncertainty and the error covariance structure, as well as a means for using posterior flux estimates and their uncertainties to quantitatively constrain global wetland CH4 emission biogeochemical process controls.