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Climate warming increases global oceanic dimethyl sulfide emissions.

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Area of Science:

  • * Atmospheric Chemistry and Climate Science
  • * Biogeochemical Cycles
  • * Ocean-Atmosphere Interactions

Background:

  • * Oceanic dimethyl sulfide (DMS) is the primary natural source of atmospheric sulfur.
  • * DMS oxidation products influence aerosol formation, cloud properties, and Earth's radiative budget.
  • * Current climate model projections for DMS emissions under global warming are uncertain and contradictory.

Purpose of the Study:

  • * To reduce uncertainty in climate model projections of DMS emissions.
  • * To simulate future seawater DMS concentrations using machine learning and CMIP6 data.
  • * To assess the changing relative importance of DMS in climate regulation.

Main Methods:

  • * Utilized machine-learning models trained on biome-resolved global DMS observations.
  • * Incorporated physico-chemical and biological predictors from eight Coupled Model Intercomparison Project Phase 6 (CMIP6) models.
  • * Simulated seawater DMS concentrations from 1850 to 2100.

Main Results:

  • * Machine learning models significantly reduced scatter in current DMS projection uncertainties.
  • * Globally averaged seawater DMS concentrations are predicted to decrease in the near future.
  • * Global DMS emissions are projected to increase due to rising sea surface temperatures and wind speeds, contradicting previous assessments.

Conclusions:

  • * Future increases in DMS emissions are expected due to climate change impacts on oceans.
  • * The relative contribution of DMS to sulfate aerosol formation and its cooling effect may increase.
  • * This highlights the critical need to accurately model DMS in climate change scenarios.