The El Niño-Southern Oscillation and wetland methane interannual variability

Abstract

[1] Global measurements of atmospheric methane (CH 4 ) concentrations continue to show large interannual variability whose origin is only partly understood. Here we quantify the influence of the El Niño-Southern Oscillation (ENSO) on wetland CH 4 emissions, which are thought to be the dominant contributor to interannual variability of the CH 4 sources. We use a simple wetland CH 4 model that captures variability in wetland extent and soil carbon to model the spatial and temporal dynamics of wetland CH 4 emissions from 1950-2005 and compare these results to an ENSO index. We are able to explain a large fraction of the global and tropical variability in wetland CH 4 emissions through correlation with the ENSO index. We find that repeated El Niño events throughout the 1980s and 1990s were a contributing factor towards reducing CH 4 emissions and stabilizing atmospheric CH 4 concentrations. An increase in emissions from the boreal region would likely strengthen the feedback between ENSO and interannual variability in global wetland CH 4 emissions. Our analysis emphasizes that climate variability has a significant impact on wetland CH 4 emissions, which should be taken into account when considering future trends in CH 4 sources.

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

“…The LPJ-WSL CH 4 model used in this analysis is the same as presented in Hodson et al (2011), but has been recalibrated to a new set of regional CH 4 fluxes as noted below. The wetland CH 4 flux (E) at each 0.5 • × 0.5 • grid cell (x) and monthly time step (t) is calculated as a linear function of two scaling factors (r CH 4 :C and f ecosys ), wetland extent (A) and heterotrophic respiration (R hetr ) according to the following equation:…”

“…(1) has been modified from Hodson et al (2011) to follow Table 5 (to convert between the notation in Eq. (1) and Hodson et al (2011): r CH4:C = β ; f ecosys = F ; A = S).…”

“…Equations 2 and 3 correct unintentional omissions in both equations as written in Hodson et al (2011).…”

“…Model simulations have also moved on from equilibrium-only simulations to transient simulations (Walter et al, 2001a,b;Shindell et al, 2004;Gedney et al, 2004;Zhuang et al, 2006). Regional-to global-scale models have now been applied for the recent past (Ringeval et al, 2010;Hodson et al, 2011;Spahni et al, 2011;Riley et al, 2011), more distant past climates (Kaplan, 2002;Valdes et al, 2005;Hopcroft et al, 2011;Singarayer et al, 2011;Beerling et al, 2011), and to project responses to future climate change (Shindell et al, 2004;Gedney et al, 2004;Bohn et al, 2007;Bohn and Lettenmaier, 2010;Ringeval, 2011). Wetland and wetland CH 4 models are now becoming included in intermediate complexity (Shindell et al, 2004;Gedney et al, 2004;Avis et al, 2011) and comprehensive (Riley et al, 2011) global climate and earth system models.…”

“…The simple scheme of Kaplan (2002) used threshold values of slope and soil moisture content to define wetland areas, with the soil moisture calculated by an equilibrium vegetation model (BIOME4); an approach adopted by other models (Shindell et al, 2004;Weber et al, 2010;Avis et al, 2011). Later schemes used land cover datasets to outline peatland regions (Wania et al, 2009a(Wania et al, , 2010Spahni et al, 2011), and/or satellite-derived inundation datasets to prescribe wetlands either directly (Hodson et al, 2011;Ringeval et al, 2010), or indirectly Riley et al, 2011). Other wetland distribution schemes use internally calculated water table positions or soil moisture thresholds to locate wetlands .…”