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Wetland emissions remain one of the principal sources of\uduncertainty in the global atmospheric methane (CH4) budget, largely due\udto poorly constrained process controls on CH4 production in waterlogged\udsoils. Process-based estimates of global wetland CH4 emissions and their\udassociated uncertainties can provide crucial prior information for\udmodel-based top-down CH4 emission estimates. Here we construct a global\udwetland CH4 emission model ensemble for use in atmospheric chemical\udtransport models (WetCHARTs version 1.0). Our\ud0.5°  ×  0.5° resolution model ensemble is based on\udsatellite-derived surface water extent and precipitation reanalyses, nine\udheterotrophic respiration simulations (eight carbon cycle models and a\uddata-constrained terrestrial carbon cycle analysis) and three temperature\uddependence parameterizations for the period 2009–2010; an extended ensemble\udsubset based solely on precipitation and the data-constrained terrestrial\udcarbon cycle analysis is derived for the period 2001–2015. We incorporate\udthe mean of the full and extended model ensembles into GEOS-Chem and compare\udthe model against surface measurements of atmospheric CH4; the model\udperformance (site-level and zonal mean anomaly residuals) compares favourably\udagainst published wetland CH4 emissions scenarios. We find that\uduncertainties in carbon decomposition rates and the wetland extent together\udaccount for more than 80 % of the dominant uncertainty in the timing,\udmagnitude and seasonal variability in wetland CH4 emissions, although\uduncertainty in the temperature CH4 : C dependence is a significant\udcontributor to seasonal variations in mid-latitude wetland CH4\udemissions. The combination of satellite, carbon cycle models and temperature\uddependence parameterizations provides a physically informed structural a\udpriori uncertainty that is critical for top-down estimates of wetland\udCH4 fluxes. Specifically, our ensemble can provide enhanced information\udon the prior CH4 emission uncertainty and the error covariance\udstructure, as well as a means for using posterior flux estimates and their\uduncertainties to quantitatively constrain the biogeochemical process controls\udof global wetland CH4 emissions

A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0)