Using more than 158,000 observations of oceanic nitrous oxide (N2O), researchers trained a supervised learning algorithm to reconstruct global N2O emissions from the ocean, substantially reducing uncertainty compared with previous estimates; the study also uncovers a vigorous seasonal cycle dominated by tropical and coastal upwelling regions that suggests sensitivity of the N2O cycle to natural climate variability and anthropogenic climate change.
Article #19-21914: "Global reconstruction reduces the uncertainty of oceanic nitrous oxide emissions and reveals a vigorous seasonal cycle," by Simon Yang, et al.
MEDIA CONTACT: Daniele Bianchi, University of California Los Angeles, CA; email: dbianchi@atmos.ucla.edu
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Proceedings of the National Academy of Sciences