Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

Abstract

Abstract. The Wetland and Wetland CH 4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH 4 ) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO 2 ) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO 2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH 4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH 4 fluxes from wetland systems. Even though modelling of wetland extent and CH 4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH 4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

The global methane budget 2000–2012

“…These emissions represent about 30 % of the total methane source. The large range in the estimates of wetland emissions results from difficulties in defining wetland CH 4 -producing areas as well as in parameterizing terrestrial anaerobic sources and oxidative sinks Wania et al, 2013).…”

“…One simplification for CH 4 compared to CO 2 is that the oceanic contribution to the global methane budget is very small (∼ 1-3 %), making source estimation mostly a continental problem (USEPA, 2010a). Finally, we lack observations to constrain (1) process models that produce estimates of wetland extent (Stocker et al, 2014;Kleinen et al, 2012) and emissions Wania et al, 2013), (2) other inland water sources (Bastviken et al, 2011), (3) inventories of anthropogenic emissions (USEPA, 2012;EDGARv4.2FT2010, 2013, and (4) atmospheric inversions, which aim at representing or estimating the different methane emissions from global to regional scales Kirschke et al, 2013;Bohn et al, 2015;Spahni et al, 2011;Tian et al, 2016). Finally, information contained in the ice core methane records has only been used in a few studies to evaluate process models Singarayer et al, 2011).…”

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

“…To be consistent with WETCHIMP's transient simulation ("Experiment 2-trans", Wania et al, 2013), we focused our analysis on the period 1993-2004, although several non-WETCHIMP models provided data from 1993-2010. All models used the CRUNCEP gridded meteorological forcings (Viovy and Ciais, 2011) as a common input.…”

“…Among the participating models (Table 2) were those of the WETCHIMP study Wania et al, 2013) that contributed CH 4 emissions estimates: CLM4Me (Riley et al, 2011), DLEM (Tian et al, 2010(Tian et al, , 2011a(Tian et al, , b, 2012, IAP-RAS (Mokhov et al, 2007;Eliseev et al, 2008), LPJ-Bern (Spahni et al, 2011, LPJWHyMe (Wania et al, 2009a(Wania et al, , b, 2010, LPJ-WSL (Hodson et al, 2011), ORCHIDEE (Ringeval et al, 2010), SDGVM (Hopcroft et al, 2011), and UW-VIC (denoted by "UW-VIC (GIEMS)"; Bohn et al, 2013). In addition, we analyzed several other models.…”

“…Large-scale biogeochemical models, especially those embedded within earth system models, are particularly important for estimating the magnitudes of feedbacks to climate change (e.g., Gedney et al, 2004;Eliseev et al, 2008;. However, as shown in the global Wetland and Wetland CH 4 Intercomparison of Models Project (WETCHIMP; Melton et al, 2013;Wania et al, 2013), there was wide disagreement among large-scale models as to the magnitude of global and regional wetland CH 4 emissions, in terms of both wetland areas and CH 4 emissions per unit wetland area. These discrepancies were due in part to the large variety of schemes used for representing hydrological and biogeochemical processes, in part to uncertainties in model parameterizations, and in part to the sparseness of in situ observations with which to evaluate model performance .…”