Improving Global Methane Emission Predictions
A multiscale comparison of modeled and observed seasonal methane emissions in northern wetlands.
Wetlands are the largest global natural methane (CH4) source, yet predictive capability of land models is low. In a recent study, researchers improved the methane module in the Community Land Model (CLM) and Accelerated Climate Modeling for Energy (ACME) Land Model (ALM) and compared predictions with tower and aircraft observations and atmospheric inversions. The findings highlight new observations and model requirements to improve global CH4 predictions.
Model changes substantially improved CH4 emission predictions compared to observations. Cold season CH4 emissions estimates remain biased low, motivating more observations during this period. Large CH4 emissions uncertainties also are generated by uncertainties in wetland hydrology.
The study compared wetland CH4 emission model predictions with site- to regional-scale observations. A comparison of the CH4 fluxes with eddy flux data highlighted needed changes to the model’s estimate of aerenchyma area, which were implemented and tested. The model modifications substantially reduced biases in CH4 emissions when compared with CarbonTracker CH4 predictions. CLM4.5 CH4 emission predictions agree well with Alaskan growing season (May–September) CarbonTracker CH4 predictions and site-level observations. However, the model underestimated CH4 emissions in the cold season (October–April). The monthly atmospheric CH4 mole fraction enhancements due to wetland emissions also were assessed using the Weather Research and Forecasting-Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model and compared with measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold season CH4 emissions. The greatest uncertainties in predicting the seasonal CH4 cycle are from the wetland extent, cold season CH4 production, and CH4 transport processes. Predicted CH4 emissions remain uncertain, but the study’s findings show that benchmarking against observations across spatial scales can inform model structural and parameter improvements.
William J. Riley William J. Riley
Lawrence Berkeley National Laboratory
Funding for this study was provided by the Regional and Global Climate Model (RGCM) program and Next-Generation Ecosystem Experiments (NGEE)–Arctic project of the Office of Biological and Environmental Research, within the U.S. Department of Energy (DOE) Office of Science, under the under contract # DE-AC02-05CH11231.
Xu, X., W.J. Riley, C.D. Koven, et al. “A multi-scale comparison of modeled and observed seasonal methane emissions in northern wetlands.” Biogeosciences 13, 5043–5056 (2016). [DOI:10.5194/bg-13-5043-2016]