WetCH₄: A Machine Learning-based Upscaling of Methane Fluxes of Northern Wetlands during 2016–2022

Abstract. Wetlands are the largest natural source of methane (CH₄) emissions globally. Northern wetlands (>45° N), accounting for 42 % of global wetland area, are increasingly vulnerable to carbon loss, especially as CH₄ emissions may accelerate under intensified high-latitude warming. However, the magnitude and spatial patterns of high-latitude CH₄ emissions remain relatively uncertain. Here we present estimates of daily CH₄ fluxes obtained using a new machine learning-based wetland CH₄ upscaling framework (WetCH₄) that applies the most complete database of eddy covariance (EC) observations available to date, and satellite remote sensing informed observations of environmental conditions at 10-km resolution. The most important predictor variables included near-surface soil temperatures (top 40 cm), vegetation reflectance, and soil moisture. Our results, modeled from 138 site-years across 26 sites, had relatively strong predictive skill with a mean R² of 0.46 and 0.62 and a mean absolute error (MAE) of 23 nmol m^-2 s^-1 and 21 nmol m^-2 s^-1 for daily and monthly fluxes, respectively. Based on the model results, we estimated an annual average of 20.8 ±2.1 Tg CH₄ yr^-1 for the northern wetland region (2016–2022) and total budgets ranged from 13.7–44.1 Tg CH₄ yr^-1, depending on wetland map extents. Although 86 % of the estimated CH₄ budget occurred during the May–October period, a considerable amount (1.4 ±0.2 Tg CH₄) occurred during winter. Regionally, the West Siberian wetlands accounted for a majority (51 %) of the interannual variation in domain CH₄ emissions. Significant issues with data coverage remain, with only 23 % of the sites observing year-round and most of the data from 11 wetland sites in Alaska and 10 bog/fen sites in Canada and Fennoscandia, and in general, Western Siberian Lowlands are underrepresented by EC CH₄ sites. Our results provide high spatiotemporal information on the wetland emissions in the high-latitude carbon cycle and possible responses to climate change. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH₄ upscaling. The dataset can be found at https://doi.org/10.5281/zenodo.10802154 (Ying et al., 2024).