Oceanic Dimethyl Sulfide Research Articles

A 20-year (1998–2017) global sea surface dimethyl sulfide gridded dataset with daily resolution

Abstract. The oceanic emission of dimethyl sulfide (DMS) plays a vital role in the Earth's climate system and constitutes a substantial source of uncertainty when evaluating aerosol radiative forcing. Currently, the widely used monthly climatology of sea surface DMS concentration falls short of meeting the requirement for accurately simulating DMS-derived aerosols with chemical transport models. Hence, there is an urgent need for a high-resolution, multi-year global sea surface DMS dataset. Here we develop an artificial neural network ensemble model that uses nine environmental factors as input features and captures the variability of the DMS concentration across different oceanic regions well. Subsequently, a global sea surface DMS concentration and flux dataset (1° × 1°) with daily resolution spanning from 1998 to 2017 is established. According to this dataset, the global annual average concentration was ∼ 1.71 nM, and the annual total emissions were ∼ 17.2 Tg S yr−1, with ∼ 60 % originating from the Southern Hemisphere. While overall seasonal variations are consistent with previous DMS climatologies, notable differences exist in regional-scale spatial distributions. The new dataset enables further investigations into daily and decadal variations. Throughout the period 1998–2017, the global annual average concentration exhibited a slight decrease, while total emissions showed no significant trend. The DMS flux from our dataset showed a stronger correlation with the observed atmospheric methanesulfonic acid concentration compared to those from previous monthly climatologies. Therefore, it can serve as an improved emission inventory of oceanic DMS and has the potential to enhance the simulation of DMS-derived aerosols and associated radiative effects. The new DMS gridded products are available at https://doi.org/10.5281/zenodo.11879900 (Zhou et al., 2024).

The sensitivity of Southern Ocean atmospheric dimethyl sulfide (DMS) to modeled oceanic DMS concentrations and emissions

Abstract. The biogeochemical formation of dimethyl sulfide (DMS) from the Southern Ocean is complex, dynamic, and driven by physical, chemical, and biological processes. Such processes, produced by marine biogenic activity, are the dominant source of sulfate aerosol over the Southern Ocean. Using an atmosphere-only configuration of the United Kingdom Earth System Model (UKESM1-AMIP), we performed eight 10-year simulations for the recent past (2009–2018) during austral summer. We tested the sensitivity of atmospheric DMS to four oceanic DMS datasets and three DMS transfer velocity parameterizations. One oceanic DMS dataset was developed here from satellite chlorophyll a. We find that the choice of oceanic DMS dataset has a larger influence on atmospheric DMS than the choice of DMS transfer velocity. Simulations with linear transfer velocity parameterizations show a more accurate representation of atmospheric DMS concentration than those using quadratic relationships. This work highlights that the oceanic DMS and DMS transfer velocity parameterizations currently used in climate models are poorly constrained for the Southern Ocean region. Simulations using oceanic DMS derived from satellite chlorophyll a data, and when combined with a recently developed linear transfer velocity parameterization for DMS, show better spatial variability than the UKESM1 configuration. We also demonstrate that capturing large-scale spatial variability can be more important than large-scale interannual variability. We recommend that models use a DMS transfer velocity parameterization that was developed specifically for DMS and improvements to oceanic DMS spatial variability. Such improvements may provide a more accurate process-based representation of oceanic and atmospheric DMS, and therefore sulfate aerosol, in the Southern Ocean region.

Marine Dimethyl Sulfide Fluxes in the Yellow and East China Seas: Scenario Variation During the 1980s–2090s and Its Drivers

AbstractShedding light on the response of oceanic dimethyl sulfide flux (FDMS) on the sea shelf to multi‐pressures (intensified terrigenous nutrient inputs and climate change) is of great importance for regional aerosol budget. Here, we designed 4‐group experiments in scenario (the 1980s, 2010s, 2050s, and 2090s) for the Yellow and East China seas (YECS) based on climate change signals gained from CMIP6 and a 3‐dimension biophysical and geochemical model. Results show that the climatological annual mean of YECS's FDMS will rise from ∼6 μmol m−2 day−1 in the 1980s to >9 μmol m−2 day−1 in the 2090s under Shared Socioeconomic Pathway (SSP) 2−4.5/5−8.5 scenario, and with multi‐pressures, the FDMS peak in the 2050s is one season earlier when compared to that in the 1980s. The elevated terrigenous inputs affect the phytoplankton biomass and/or community on the inner shelf, leading to the rise and phenology change in the YECS's FDMS between the1980s and 2010s, while climate change has little impact. The influence of climate change on the FDMS is projected to increase in the 2050s; climate change will change seasonal pattern of the FDMS on the central part (middle and outer shelves) of East China Sea (CECS) under every SSP scenario. Thereinto, wind change exerts a crucial role, it will enhance summertime offshore transport and, accordingly, stimulate phytoplankton growth in summer changing the phenology of FDMS on the CECS.

Global Ocean dimethylsulfide photolysis rates quantified with a spectrally and vertically resolved model

AbstractPhotochemical reactions initiated by ultraviolet radiation remove the climate‐active gas dimethylsulfide (DMS) from the ocean's surface layer. Here, we quantified DMS photolysis using a satellite‐based model that accounts for spectral irradiance attenuation in the water column, its absorption by chromophoric dissolved organic matter, and the apparent quantum yields (AQYs) with which absorbed photons degrade DMS. Models with two alternative parameterizations for AQY estimate global DMS photolysis at between 17 and 20 Tg S yr−1, equivalent to 13–15 Tg C yr−1, of which ~ 73% occurs in the Southern hemisphere. This asymmetry results mostly from the high AQYs found south of 40° S, which more than counteract the prevailing low irradiance and deep mixing in that region. Simplified schemes currently used in biogeochemical models, whereby photolysis follows the vertical attenuation of visible radiation, overestimate DMS photolysis by around 150% globally. We propose relevant corrections and simple adjustments to those models.

The Response of Oceanic Dimethylsulfide Fluxes Off the Chinese Coastal Waters to Altered Changjiang (Yangtze) Nutrient Inputs

The Response of Oceanic Dimethylsulfide Fluxes Off the Chinese Coastal Waters to Altered Changjiang (Yangtze) Nutrient Inputs

Oceanographic controls on Southern Ocean dimethyl sulfide distributions revealed by machine learning algorithms

AbstractWe developed two machine learning models to map the Southern Ocean distribution of the climate‐active gas dimethyl sulfide (DMS) at 20 km resolution. Results obtained from ensembles of random forest regressions and artificial neural networks reproduce observed DMS distributions with significantly higher accuracy than traditional statistical techniques, and are less prone to biases and spatial distortions than existing interpolation‐based climatologies. Both models predict persistently low offshore DMS concentrations associated with the Antarctic circumpolar current, suggesting that wind‐driven overturning mixing is the dominant regional control on DMS distributions. In addition, 60% of the variance in DMS seasonality is explained by changes in mixed layer depth and sea surface temperature, with a significant correlation between DMS concentrations and sea‐ice cover in coastal waters. We further identify the tracer Si* (defined as ) as a potentially important predictor for regional DMS distributions in Southern Ocean waters. At finer scales, our models capture various oceanographic features, including eddies, hydrographic fronts and jets that appear to play a role in driving DMS variability. Our results yield an estimated Southern Ocean sea‐air DMS flux of 8.7 ± 2.1 Tg S integrated across the phytoplankton growing season (October to April), representing 30.8% of total global oceanic S emissions, and highlighting the region's importance to the marine sulfur cycle. Our work provides new insights into the drivers of spatial variability in Southern Ocean DMS concentrations and sea‐air fluxes, and their potential responses to future climate‐dependent changes.

Biogeochemical controls on climatically active gases and atmospheric sulfate aerosols in the western Pacific

The Pacific Ocean plays an important role in regulating the budget of climatically active gases and the burden of sulfate aerosols. Here, a field investigation was conducted to clarify the key processes and factors controlling climatically active gases, including dimethyl sulfide (DMS), carbonyl sulfide (OCS), carbon disulfide (CS2), and carbon dioxide (CO2), in both surface seawater and the lower atmosphere of the western Pacific. In addition, the relative contributions of different sources to atmospheric sulfate aerosols were quantitatively estimated, and their causes were explored. The maximum concentrations of DMS, OCS and CS2 and the minimum partial pressure of CO2 (pCO2) were observed in the Kuroshio-Oyashio Extension. Kuroshio-induced mesoscale eddies brought abundant nutrients and organic matter from the subsurface layer of Oyashio into the euphotic layer, thus enhancing primary productivity and accelerating the photoreaction of organic matter. These processes led to higher concentrations of DMS, OCS and CS2 and lower pCO2. However, the oligotrophic subsurface layer in the subtropical gyre and the strong barrier layer in the equatorial waters suppressed the upward fluxes of nutrients and organic matter, resulting in lower surface concentrations of DMS, OCS, and CS2 in these areas. Being far from the continents, atmospheric concentrations of DMS, OCS and CS2 and pCO2 in the western Pacific generally were observed to depend on the local sea-to-air exchange and may be regulated by atmospheric oxidation and mixing of air masses. In general, oceanic DMS emissions played an important role in the formation of sulfate aerosols in the western Pacific (accounting for ∼19.5% of total sulfate aerosols), especially in the Kuroshio-Oyashio Extension (∼32.3%). These processes in seawater may also determine the variations and emissions of other climatically active gases from biogenic and photochemical sources.

Increased oceanic dimethyl sulfide emissions in areas of sea ice retreat inferred from a Greenland ice core

Ocean phytoplankton are an important source of dimethyl sulfide, which influences marine cloud formation. Model studies suggest that declines in Arctic sea ice may lead to increased dimethyl sulfide emissions, however observational support is lacking. Here, we present a 55-year high-resolution ice core record of methane sulfonic acid flux, an oxidation product of dimethyl sulfide, from the southeast Greenland Ice Sheet. We infer temporal variations in ocean dimethyl sulfide emissions and find that springtime (April–June) fluxes of methane sulfonic acid correlate well with satellite-derived chlorophyll-a concentration in the Irminger Sea. Summertime (July–September) methane sulfonic acid fluxes were 3 to 6 times higher between 2002–2014 than 1972–2001. We attribute this to sea ice retreat day becoming earlier and a coincident increase in chlorophyll-a concentration in the adjacent open coastal waters.

Influences of Antarctic Ozone Depletion on Southern Ocean Aerosols

AbstractThe Southern Ocean is often identified as a pristine aerosol environment, being distant from anthropogenic sources. We investigate anomalies in aerosol loading over the Southern Ocean due to stratospheric ozone depletion in historical simulations performed for the sixth Coupled Model Intercomparison Project. We explore direct influences of ozone depletion on aerosols via enhanced ultraviolet‐induced production of oceanic dimethyl sulfide (DMS), and indirect influences via changes in the Southern Hemisphere westerly jet, which impacts wind‐driven aerosol fluxes. We identify wind as the key driver of change for austral summertime aerosol, leading to increases in aerosol optical depth of up to 24% compared with the pre–ozone hole era. In contrast to previous studies, direct impacts on aerosol from ozone depletion and enhanced ultraviolet fluxes are less obvious. Our results show that the Southern Ocean summertime aerosol environment cannot be considered to be representative of pre–ozone hole conditions because stratospheric ozone depletion has indirectly increased marine aerosol fluxes.

Simulating the radiative forcing of oceanic dimethylsulfide (DMS) in Asia based on machine learning estimates

Abstract. Dimethylsulfide (DMS) emitted from seawater is a key precursor to new particle formation and acts as a regulator in Earth's warming climate system. However, DMS's effects are not well understood in various ocean regions. In this study, we estimated DMS emissions based on a machine learning method and used the GEOS-Chem global 3D chemical transport model coupled with the TwO Moment Aerosol Sectional (TOMAS) microphysics scheme to simulate the atmospheric chemistry and radiative effects of DMS. The contributions of DMS to atmospheric SO42- aerosol and cloud condensation nuclei (CCN) concentrations along with the radiative effects over the Asian region were evaluated for the first time. First, we constructed novel monthly resolved DMS emissions (0.5∘×0.5∘) for the year 2017 using a machine learning model; 4351 seawater DMS measurements (including the recent measurements made over the Chinese seas) and 12 relevant environment parameters were selected for model training. We found that the model could predict the observed DMS concentrations with a correlation coefficient of 0.75 and fill the values in regions lacking observations. Across the Asian seas, the highest seasonal mean DMS concentration occurred in March–April–May (MAM), and we estimate the annual DMS emission flux of 1.25 Tg (S), which is equivalent to 15.4 % of anthropogenic sulfur emissions over the entire simulation domain (which covered most of Asia) in 2017. The model estimates of DMS and methane sulfonic acid (MSA), using updated DMS emissions, were evaluated by comparing them with cruise survey experiments and long-term online measurement site data. The improvement in model performance can be observed compared with simulation results derived from the global-database DMS emissions. The relative contributions of DMS to SO42- and CCN were higher in remote oceanic areas, contributing 88 % and 42 % of all sources, respectively. Correspondingly, the sulfate direct radiative forcing (DRF) and indirect radiative forcing (IRF) contributed by DMS ranged from −200 to −20 mW m−2 and from −900 to −100 mW m−2, respectively, with levels varying by season. The strong negative IRF is mainly over remote ocean regions (−900 to −600 mW m−2). Generally, the magnitude of IRF derived by DMS was twice as large as its DRF. This work provides insights into the source strength of DMS and the impact of DMS on climate and addresses knowledge gaps related to factors controlling aerosols in the marine boundary layer and their climate impacts.

Improved prediction of dimethyl sulfide (DMS) distributions in the northeast subarctic Pacific using machine-learning algorithms

Abstract. Dimethyl sulfide (DMS) is a volatile biogenic gas with the potential to influence regional climate as a source of atmospheric aerosols and cloud condensation nuclei (CCN). The complexity of the oceanic DMS cycle presents a challenge in accurately predicting sea surface concentrations and sea–air fluxes of this gas. In this study, we applied machine-learning methods to model the distribution of DMS in the northeast subarctic Pacific (NESAP), a global DMS hot spot. Using nearly two decades of ship-based DMS observations, combined with satellite-derived oceanographic data, we constructed ensembles of 1000 machine-learning models using two techniques: random forest regression (RFR) and artificial neural networks (ANN). Our models dramatically improve upon existing statistical DMS models, capturing up to 62 % of observed DMS variability in the NESAP and demonstrating notable regional patterns that are associated with mesoscale oceanographic variability. In particular, our results indicate a strong coherence between DMS concentrations, sea surface nitrate (SSN) concentrations, photosynthetically active radiation (PAR), and sea surface height anomalies (SSHA), suggesting that NESAP DMS cycling is primarily influenced by heterogenous nutrient availability, light-dependent processes and physical mixing. Based on our model output, we derive summertime, sea–air flux estimates of 1.16 ± 1.22 Tg S in the NESAP. Our work demonstrates a new approach to capturing spatial and temporal patterns in DMS variability, which is likely applicable to other oceanic regions.

Abundant microzooplankton possibly cause ultrahigh seawater dimethylsulfide during Southern Ocean algal blooms

Oceanic dimethylsulfide (DMS) is hypothesized to impact cloud formation and consequently the solar radiation budget of Earth’s surface. Ultrahigh seawater DMS concentrations, up to hundreds of nM, have been observed in the Southern Ocean, attributing to concurrent high phytoplankton biomass. However, phytoplankton biomass cannot fully explain the mechanism leading to those extreme values. Herein, measurements, including seawater DMS concentrations and other biological and environmental parameters, were collected in the water column during the austral summer of 2015–2016 at the tip of the Antarctic Peninsula. Notably, large-scale ultrahigh seawater DMS concentrations (up to 85.2 nM and generally above 40 nM in the upper layer) was observed only in areas with co-existing phytoplankton blooms and abundant microzooplankton (indicated by ciliates, whose abundance and biomass were above 1000 ind L-1 and 2 μg L-1, respectively), implying that the grazing of abundant microzooplankton possibly causes the ultrahigh seawater DMS concentrations during the bloom seasons in the Southern Ocean.

Evaluation of ocean dimethylsulfide concentration and emission in CMIP6 models

Evaluation of ocean dimethylsulfide concentration and emission in CMIP6 models

Evaluation of ocean dimethylsulfide concentration and emission in CMIP6 models

Abstract. Characteristics and trends of surface ocean dimethylsulfide (DMS) concentrations and fluxes into the atmosphere of four Earth system models (ESMs: CNRM-ESM2-1, MIROC-ES2L, NorESM2-LM, and UKESM1-0-LL) are analysed over the recent past (1980–2009) and into the future, using Coupled Model Intercomparison Project 6 (CMIP6) simulations. The DMS concentrations in historical simulations systematically underestimate the most widely used observed climatology but compare more favourably against two recent observation-based datasets. The models better reproduce observations in mid to high latitudes, as well as in polar and westerlies marine biomes. The resulting multi-model estimate of contemporary global ocean DMS emissions is 16–24 Tg S yr−1, which is narrower than the observational-derived range of 16 to 28 Tg S yr−1. The four models disagree on the sign of the trend of the global DMS flux from 1980 onwards, with two models showing an increase and two models a decrease. At the global scale, these trends are dominated by changes in surface DMS concentrations in all models, irrespective of the air–sea flux parameterisation used. In turn, three models consistently show that changes in DMS concentrations are correlated with changes in marine productivity; however, marine productivity is poorly constrained in the current generation of ESMs, thus limiting the predictive ability of this relationship. In contrast, a consensus is found among all models over polar latitudes where an increasing trend is predominantly driven by the retreating sea-ice extent. However, the magnitude of this trend between models differs by a factor of 3, from 2.9 to 9.2 Gg S decade−1 over the period 1980–2014, which is at the low end of a recent satellite-derived analysis. Similar increasing trends are found in climate projections over the 21st century.

Unravelling Surface Seawater DMS Concentration and Sea‐To‐Air Flux Changes After Sea Ice Retreat in the Western Arctic Ocean

AbstractThe receding of the seasonal ice cover in the Arctic due to climate change has been predicted by models to increase climate‐active biogenic trace gas emissions, specifically those of dimethylsulfide (DMS). However, insufficient DMS measurements are currently available to either support or refute this hypothesis and to fully understand the various responses of oceanic DMS in a rapidly changing Arctic Ocean environment. Here, we present high‐resolution surface water DMS data collected in the summer of 2014 in combination with a suite of ancillary variables including sea ice cover, salinity, and nutrients. We show that surface seawater DMS concentrations, generally below 0.5 nmol L−1, remained unchanged in the Canada Basin after sea ice retreat probably due to insufficient nutrients supply to the upper mixed layer and resulting low primary production. Moreover, in the Chukchi shelf region, DMS concentrations decreased following a phytoplankton bloom due to the rapid depletion and slow resupply of nutrients. Although the DMS sea‐to‐air fluxes were not high from a global perspective, they increased by a factor of 4‐fold after sea ice retreat in the Arctic Ocean high latitudes. This increase in DMS flux was mainly driven by increased wind speed. This work provides unique observations and insights on how surface seawater DMS and flux to the atmosphere may change in the future Arctic Ocean.

Controlling factors of annual cycle of dimethylsulfide in the Yellow and East China seas

We developed a dimethylsulfide (DMS) module coupled to an ecological dynamics model studying the annual DMS cycle of the Yellow and East China seas (YECS). The model results showed that surface DMS concentrations ([DMS]) peaked in August along the coast, and there exhibited several DMS peaks offshore annually. In addition, surface [DMS] were higher in the Yellow Sea than that in the East China Sea. The annual mean surface [DMS] of the YECS reached to 4.55 nmol/L, and oceanic DMS emissions from this sea area was 6.78 μmol/(m2 day). Several sensitivity experiments demonstrated that phytoplankton community and sea water temperature exerted crucial effects on seasonal variations of surface [DMS]; and phytoplankton community or temperature changed the timing of surface DMS peak while photolysis affected the magnitude of [DMS]. Moreover, the effect size of phytoplankton community or water temperature varied spatially.

Predictability of Seawater DMS During the North Atlantic Aerosol and Marine Ecosystem Study (NAAMES)

This work presents an overview of a unique set of surface ocean dimethylsulfide (DMS) measurements from four shipboard field campaigns conducted during the North Atlantic Aerosol and Marine Ecosystem Study (NAAMES) project. Variations in surface seawater DMS are discussed in relation to biological and physical observations. Results are considered at a range of timescales (seasons to days) and spatial scales (regional to sub-mesoscale). Elevated DMS concentrations are generally associated with greater biological productivity, although chlorophyll a (Chl) only explains a small fraction of the DMS variability (15%). Physical factors that determine the location of oceanic temperature fronts and depth of vertical mixing have an important influence on seawater DMS concentrations during all seasons. The interplay of biomass and physics influences DMS concentrations at regional/seasonal scales and at smaller spatial and shorter temporal scales. Seawater DMS measurements are compared with the global seawater DMS climatology and predictions made using a recently published algorithm and by a neural network model. The climatology is successful at capturing the seasonal progression in average seawater DMS, but does not reproduce the shorter spatial/temporal scale variability. The input terms common to the algorithm and neural network approaches are biological (Chl) and physical (mixed layer depth, photosynthetically active radiation, seawater temperature). Both models predict the seasonal North Atlantic average seawater DMS trends better than the climatology. However, DMS concentrations tend to be under-predicted and the episodic occurrence of higher DMS concentrations is poorly predicted. The choice of climatological seawater DMS product makes a substantial impact on the estimated DMS flux into the North Atlantic atmosphere. These results suggest that additional input terms are needed to improve the predictive capability of current state-of-the-art approaches to estimating seawater DMS.

DMS sea-to-air fluxes and their influence on sulfate aerosols over the Southern Ocean, south-east Indian Ocean and north-west Pacific Ocean

Environmental context The ocean-produced dimethyl sulfide (DMS) molecule is thought to affect cloud formation and the solar radiation budget at the Earth’s surface, hence playing an important role in regulating climate. In this study, we calculated the DMS sea-to-air flux across the Southern Ocean, south-east Indian Ocean and north-west Pacific Ocean, and analysed the influence of DMS fluxes on sulfate aerosols. These results improved our understanding of the effects of DMS emissions on sulfate compounds in the atmosphere over the global ocean. Abstract Oceanic dimethyl sulfide (DMS) is the most abundant biogenic sulfur compound emitted into the atmosphere and could indirectly regulate the global climate by impacting end product sulfate aerosols. DMS emissions and their influence on sulfate aerosols, i.e. methanesulfonic acid (MSA) and non-sea-salt sulfate (nss-SO42–), were investigated over the Atlantic Ocean and Indian Ocean sectors of the Southern Ocean (SO), the south-east Indian Ocean, and the north-west Pacific Ocean from February to April 2014 during the 30th Chinese National Antarctic Research Expedition. We found a strong large-scale DMS source in the marginal sea ice zone from 34 °W to 14 °E of the SO (south of 60 °S), in which the mean flux was 49.0 ± 65.6 μmol m−2 d−1 (0.6–308.3 μmol m−2 d−1, n = 424). We also found a second large-scale DMS source in the South Subtropical Front (~40 °S, up to 50.8 μmol m−2 d−1). An inconsistency between concentrations of atmospheric sulfate compounds and DMS emissions along the cruise track was observed. The horizontal advection of air masses was likely the main reason for this discrepancy. Finally, the biological exposure calculation results also indicated that it is very difficult to observe a straightforward relationship between oceanic biomass and atmospheric MSA.

Long Island enhanced aerosol event during 2018 LISTOS: Association with heatwave and marine influences.

The co-occurrence of enhancement in aerosol concentration, temperatures, and ozone mixing ratio was observed between June 29 and July 4, 2018 (enhanced period, EP) on Long Island (LI) and the greater NYC metropolitan area during part of the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS). Two aerosol formation pathways were identified during the EP, the first being the condensation of semi- and intermediate volatility oxidation products of anthropogenic volatile organic compounds (AVOCs) under stagnant synoptic flow conditions, high temperatures and afternoon sea-breeze circulation. While this first pathway was prevalent, the most abundant organic aerosol factor was less oxidized oxygenated organic aerosol or LO-OOA. The second formation pathway occurred during a period of more persistent (synoptic) on-shore flow transporting more aged aerosol which consisted of an internal mixture of more oxidized oxygenated organic aerosol (MO-OOA), methanesulfonic acid (MSA) and sulfate. It was estimated that 35% of the sulfate observed during the mature period (an average of about 1.2μgm-3) originated from oceanic dimethyl sulfide (DMS) emissions. These two formation pathways helped elucidate the sources of fine particle pollution, highlighted the interaction between human emissions and natural DMS emission, and will help our understanding of pollution affecting other urban areas adjacent to large bodies of water during hot and stagnant periods.

Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

Abstract. Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. Knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to improve understanding of atmospheric sulfur, aerosol/cloud dynamics, and albedo. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 82 996 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of latitude–longitude coordinates, time of day, time of year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, and silicate. Linear regressions of DMS against the environmental parameters show that on a global-scale mixed layer depth and solar radiation are the strongest predictors of DMS. These parameters capture ∼9 % and ∼7 % of the raw DMS data variance, respectively. Multilinear regression can capture more of the raw data variance (∼39 %) but strongly underestimates DMS in high-concentration regions. In contrast, the artificial neural network captures ∼66 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in surface ocean DMS with the highest concentrations and sea-to-air fluxes in the high-latitude summertime oceans. We estimate a lower global sea-to-air DMS flux (20.12±0.43 Tg S yr−1) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used. Our sensitivity test results show that DMS concentration does not change unidirectionally with each of the environmental parameters, which emphasizes the interactions among these parameters. The ANN model suggests that the flux of DMS from the ocean to the atmosphere will increase with global warming. Given that larger DMS fluxes induce greater cloud albedo, this corresponds to a negative climate feedback.