School of Earth Sciences - Research Publications

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Start date: 2010 × End date: 2019 × Author: Schofield, Robyn × Author: Lane, Todd ×

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    Cloud, precipitation and radiation responses to large perturbations in global dimethyl sulfide
    Fiddes, SL ; Woodhouse, MT ; Nicholls, Z ; Lane, TP ; Schofield, R (Copernicus Publications, 2018)
    Natural aerosol emission represents one of the largest uncertainties in our understanding of the radiation budget. Sulfur emitted by marine organisms, as dimethyl sulfide (DMS), constitutes one-fifth of the global sulfur budget and yet the distribution, fluxes and fate of DMS remain poorly constrained. This study evaluates the Australian Community Climate and Earth System Simulator (ACCESS) United Kingdom Chemistry and Aerosol (UKCA) model in terms of cloud fraction, radiation and precipitation, and then quantifies the role of DMS in the chemistry–climate system. We find that ACCESS-UKCA has similar cloud and radiation biases to other global climate models. By removing all DMS, or alternatively significantly enhancing marine DMS, we find a top of the atmosphere radiative effect of 1.7 and −1.4W m−2 respectively. The largest responses to these DMS perturbations (removal/enhancement) are in stratiform cloud decks in the Southern Hemisphere's eastern ocean basins. These regions show significant differences in low cloud (−9∕ + 6%), surface incoming shortwave radiation (+7∕ − 5W m−2) and large-scale rainfall (+15∕ − 10%). We demonstrate a precipitation suppression effect of DMS-derived aerosol in stratiform cloud deck regions due to DMS, coupled with an increase in low cloud fraction. The difference in low cloud fraction is an example of the aerosol lifetime effect. Globally, we find a sensitivity of temperature to annual DMS flux of 0.027 and 0.019K per Tg yr−1 of sulfur, respectively. Other areas of low cloud formation, such as the Southern Ocean and stratiform cloud decks in the Northern Hemisphere, have a relatively weak response to DMS perturbations. We highlight the need for greater understanding of the DMS–climate cycle within the context of uncertainties and biases of climate models as well as those of DMS–climate observations.