Paddy rice methane emissions across Monsoon Asia

Although rice cultivation is one of the most important agricultural sources of methane and contributes ~8 % of total global anthropogenic emissions, large discrepancies remain among estimates of global methane emissions from rice cultivation due to a lack of observational constraints. The spatial distribution of paddy-rice emissions has been assessed at regional-to-global scales by bottom-up inventories and land surface models over coarse spatial resolution (e.g., > 0.5 degrees) or spatial units (e.g., agro-ecological zones). However, high-resolution CH4 flux estimates capable of capturing the effects of local climate and management practices on emissions, as well as replicating in situ data, remain challenging to produce because of the scarcity of high-resolution maps of paddy-rice and insufficient understanding of CH4 predictors. Here, we combined paddy-rice methane-flux data from 23 global eddy covariance sites and MODIS remote sensing data with machine learning, and produced gridded up-scaling estimates of rice methane emissions at 5000-m resolution at 8-day intervals across Monsoon Asia, where ~87% of global rice area is cultivated and ~90% of global rice production occurs.