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

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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. 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 °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 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. 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.

Figures

  • Table 1. List of WETCHIMP participating models. Not all models contributed results to all experiments. The conceptualized, general description of net methane flux, F , by each model is adapted from Table 5 in Wania et al. (2012). This formulation is for illustrative purposes; thus the main variables and parameters used in CH4 production are detailed, but oxidation, O, and atmospheric oxidation, Oatm, are not. For all results presented in this paper, all Oatm values were set to 0, allowing comparison of modelled gross fluxes. All variables listed are described in the table footnotes. Note that identical parameters/variables for different models do not imply identical values used in the models. A full listing of contributed experiments and model set-ups for the experiments, as well as greater detail on the models’ methane flux parameterizations, is provided in Wania et al. (2012).
  • Fig. 1. Simulated mean annual maximal wetland extent for 1993–2004. The SDGVM and UVic-ESCM model results are from Experiment 2-Transient. The GIEMS inundation dataset is plotted as the mean annual maximum value across all years (1993–2004).
  • Table 2. Mean annual maximum wetland extent for participating models over the period 1993–2004 (Experiment 2-Transient). For a description of how each model determines wetland extent, see Table 1 and Wania et al. (2012). GLCC is the USGS Global Land Cover Characteristics database (Loveland et al., 2000). MODIS is the MODerate resolution Imaging Spectroradiometer land cover product (ORNL DAAC, 2000). Some of the observational estimates do not include transient wetlands (GLCC & MODIS), and are not specific to the 1993–2004 period with the exception of the GIEMS dataset.
  • Fig. 2. Monthly global wetland extent for 1993–2004 for all models that do not use an external dataset for calculation of intra- and/or interannual variability. Plot (g) is the normalized monthly global wetland extent for all models in plots (a)–(f), the unaltered GIEMS inundation dataset, as well as the mean extent of the models (excluding LPJ-Bern due to its wet mineral soils parameterization). The grey shading denotes the 25th and 75th percentiles of the model distribution (excluding LPJ-Bern). The grey dashed lines are the 5th and 95th percentiles.
  • Fig. 3. Zonal sum of mean annual maximal wetland area for 1993–2004 for all models that have dynamic wetland extents. LPJ-Bern is plotted here excluding its wet mineral soils (keeping inundated areas and peatlands). Also included are the K07 and GIEMS datasets. The grey shading denotes the 25th and 75th percentiles of the model distribution (excluding LPJ-Bern); the grey dashed lines the 5th and 95th. The wetland extents are summed across 3◦ bins.
  • Fig. 4. Global maps of mean annual CH4 flux intensity per meter squared of wetland with meridional and zonal emission sums for 1993 to 2004. The zonal and meridional sums are per 0.5◦ of latitude/longitude. The CLM4Me and ORCHIDEE models were interpolated to a 0.5◦ grid to allow inter-comparison with the other models.
  • Table 3. Simulated annual mean total methane emitted to atmosphere from natural wetlands for 1993–2004. All units are TgCH4 yr−1 ± 1σ , where the standard deviation represents the inter-annual variation in the model estimates. Note that estimates from some other reference studies are not for the same time period, or are for slightly different geographic regions. These exceptions are noted in the table footnotes.
  • Fig. 5. Zonally summed mean annual CH4 emissions for 1993–2004. The grey shading denotes the limits of the 25th and 75th percentile of the model distribution. Grey dashed lines are the 5th and 95th percentile limits. The CH4 emissions are summed across 3 ◦ bins.

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Melton, J. R., Wania, R., Hodson, E. L., Poulter, B., Ringeval, B., Spahni, R., … Kaplan, J. O. (2013). Present state of global wetland extent and wetland methane modelling: Conclusions from a model inter-comparison project (WETCHIMP). Biogeosciences, 10(2), 753–788. https://doi.org/10.5194/bg-10-753-2013

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