[1] The potentially significant role of the biogenic trace gas dimethylsulfide (DMS) in determining the Earth’s radiation budget makes it necessary to accurately reproduce seawater DMS distribution and quantify its global flux across the sea/air interface. Following a threefold increase of data (from 15,000 to over 47,000) in the global surface ocean DMS database over the last decade, new global monthly climatologies of surface ocean DMS concentration and sea‐to‐air emission flux are presented as updates of those constructed 10 years ago. Interpolation/extrapolation techniques were applied to project the discrete concentration data onto a first guess field based on Longhurst’s biogeographic provinces. Further objective analysis allowed us to obtain the final monthly maps. The new climatology projects DMS concentrations typically in the range of 1–7 nM, with higher levels occurring in the high latitudes, and with a general trend toward increasing concentration in summer. The increased size and distribution of the observations in the DMS database have produced in the new climatology substantially lower DMS concentrations in the polar latitudes and generally higher DMS concentrations in regions that were severely undersampled 10 years ago, such as the southern Indian Ocean. Using the new DMS concentration climatology in conjunction with state‐of‐the‐art parameterizations for the sea/air gas transfer velocity and climatological wind fields, we estimate that 28.1 (17.6–34.4) Tg of sulfur are transferred from the oceans into the atmosphere annually in the form of DMS. This represents a global emission increase of 17% with respect to the equivalent calculation using the previous climatology. This new DMS climatology represents a valuable tool for atmospheric chemistry, climate, and Earth System models.

/pdf/an-updated-climatology-of-surface-dimethlysulfide-nlbezyvaed.pdf

An updated climatology of surface dimethlysulfide concentrations and emission fluxes in the global ocean

Air/sea fluxes of dimethylsulfide (DMS) were measured by eddy correlation over the Eastern South Pa- cific Ocean during January 2006. The cruise track extended from Manzanillo, Mexico, along 110 W, to Punta Arenas, Chile. Bulk air and surface ocean DMS levels were also measured and gas transfer coefficients ( kDMS) were com- puted. Air and seawater DMS measurements were made us- ing chemical ionization mass spectrometry (API-CIMS) and a gas/liquid membrane equilibrator. Mean surface seawa- ter DMS concentrations were 3.8±2.2 nM and atmospheric mixing ratios were 340±370 ppt. The air/sea flux of DMS was uniformly out of the ocean, with an average value of 12±15µmol m 2 d 1 . Sea surface concentration and flux were highest around 15 S, in a region influenced by shelf waters and lowest around 25 S, in low chlorophyll gyre waters. The DMS gas transfer coefficient exhibited a lin- ear wind speed-dependence over the wind speed range of 1 to 9 m s 1 . This relationship is compared with previ- ously measured estimates of k from DMS, CO2, and dual tracer data from the Atlantic and Pacific Ocean, and with the NOAA/COARE gas transfer model. The model generated slope of k vs. wind speed is at the low end of those observed in previous DMS field studies.

/pdf/open-ocean-dms-air-sea-fluxes-over-the-eastern-south-pacific-541dh77lex.pdf

Open Ocean DMS Air/Sea Fluxes Over the Eastern South Pacific Ocean

This paper reports on the influence of the Fe fertilization conducted during the subarctic ecosystem response to iron enrichment study (SERIES) on the distribution of the biogenic sulfur compounds dimethylsulfoniopropionate (DMSP) and dimethylsulfide (DMS) in the context of changes in plankton composition. The Fe enrichment resulted in a rapid increase in the abundance of a nanoplankton assemblage dominated by Prymnesiophyceae, Prasinophyceae, small diatoms (<5 μm), heterotrophic dinoflagellates, and zooflagellates. This first assemblage persisted for 8 days before collapsing abruptly due to an increase in microzooplankton herbivory. The abundance of large diatoms started to increase shortly after the initial Fe fertilization but peaked 1–2 days after the crash of the nanoplankton bloom. Inside the Fe patch, particulate DMSP (DMSPp) increased from 100 to 285 nmol L−1 during the nanoplankton bloom, decreased rapidly back to initial level as this bloom collapsed, and remained low during the bloom of large diatoms. Outside the patch, phytoplankton and protists abundance and DMSPp concentrations remained low and relatively stable throughout the experiment. DMS concentrations were elevated at the onset of the experiment outside the patch (maximum of 15.7 nmol L−1 on day 1), increased up to 26.5 nmol L−1 10 days after the enrichment, and decreased to ca. 6 nmol L−1 by the end of the experiment. This large natural pulse in DMS coincided with conditions of high irradiance and decreasing wind speed. Inside the Fe patch, DMS concentrations exhibited the same general pattern, but with distinctive features related to the Fe fertilization. First, DMS concentrations tended to increase more rapidly inside the patch during the initial nanoplankton bloom, leading to DMS concentrations ca. 2 times higher inside the patch than outside on day 6. Second, DMS concentrations became consistently lower inside the patch (often below our limit of quantification of 0.03 nmol L−1) than outside (ca. 6 nmol L−1) during the peak of the diatom bloom. Our results thus confirm the rapid increase in nanoplankton and DMSPp reported during all previous Fe-fertilization experiments. On the other hand, the decrease in DMS concentrations measured inside the Fe patch during SERIES is unique and shows that adding Fe to HNLC waters may not always lead to conditions that could mitigate climate warming.

DMSP and DMS dynamics during a mesoscale iron fertilization experiment in the Northeast Pacific-Part I: Temporal and vertical distributions

Ocean dimethylsulfide (DMS) produced by marine biota is the largest natural source of atmospheric sulfur, playing a major role in the formation and evolution of aerosols, and consequently affecting climate. Several dynamic process-based DMS models have been developed over the last decade, and work is progressing integrating them into climate models. Here we report on the first international comparison exercise of both 1D and 3D prognostic ocean DMS models. Four global 3D models were compared to global sea surface chlorophyll and DMS concentrations. Three local 1D models were compared to three different oceanic stations (BATS, DYFAMED, OSP) where available time series data offer seasonal coverage of chlorophyll and DMS variability. Two other 1D models were run at one site only. The major point of divergence among models, both within 3D and 1D models, relates to their ability to reproduce the summer peak in surface DMS concentrations usually observed at low to mid- latitudes. This significantly affects estimates of global DMS emissions predicted by the models. The inability of most models to capture this summer DMS maximum appears to be constrained by the basic structure of prognostic DMS models: dynamics of DMS and dimethylsulfoniopropionate (DMSP), the precursor of DMS, are slaved to the parent ecosystem models. Only the models which include environmental effects on DMS fluxes independently of ecological dynamics can reproduce this summer mismatch between chlorophyll and DMS. A major conclusion of this exercise is that prognostic DMS models need to give more weight to the direct impact of environmental forcing (e.g., irradiance) on DMS dynamics to decouple them from ecological processes.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2009GB003721

A first appraisal of prognostic ocean DMS models and prospects for their use in climate models

Dimethylsulfoniopropionate (DMSP) and dimethylsulfide (DMS) biological cycling rates were determined during SERIES, a mesoscale iron-fertilization experiment conducted in the high-nutrient low-chlorophyll (HNLC) waters of the northeast subarctic Pacific. The iron fertilization resulted in the rapid development of a nanoplankton assemblage that persisted for 11 days before abruptly crashing. The nanoplankton bloom was followed by a diatom bloom, accompanied by an important increase in bacterial abundance and production. These iron-induced alterations of the plankton assemblage coincided with changes in the size and biological cycling of the DMSP and DMS pools. The initial nanoplankton bloom resulted in increases in particulate DMSP (DMSPp; 77–180 nmol L−1), dissolved DMSP (DMSPd; 1–24 nmol L−1), and biological gross (0.11–0.78 nmol L−1 h−1) and net (0.04–0.74 nmol L−1 h−1) DMS production rates. During the nanoplankton bloom, DMSPd consumption by bacteria exceeded their sulfur demand and the excess sulfur was probably released as DMS, consistent with the high gross DMS production rates observed during that period. The crash of the nanoplankton bloom was marked by the rapid decline of DMSPp, DMSPd, and gross DMS production to their initial values. Following the crash of the nanoplankton bloom, bacterial production and estimated sulfur demand reached transient maxima of 9.3 μg C L−1 d−1 and 14.2 nmol S L−1 d−1, respectively. During this period of high bacterial production, bacterial DMSPd consumption was also very high (6 nmol L−1 h−1), but none of the consumed DMSPd was converted into DMS and a net biological DMS consumption was measured. This transient period initiated a rapid decrease in DMS concentrations inside the iron-enriched patch, which persisted during the following diatom bloom due to low biological gross and net DMS production that prevented the replenishment of DMS. Our results show that the impact of Fe fertilization on DMS production in HNLC waters result from a complex interplay between the dynamics of the algal blooms and their influence on bacterial DMSP and DMS metabolism.

DMSP and DMS dynamics during a mesoscale iron fertilization experiment in the Northeast Pacific–Part II: Biological cycling

Dimethylsulfide (DMS) was measured in the upper 400 m of the northeast Pacific from February 1996 to June 2001. The sampling took place along Line P (48°34.5′N, 125°30′W to 50°N, 145°W). DMS concentrations increased diurnally from a pre-dawn low to a mid-day maximum and from coastal waters to open ocean, in a high-nutrient–low-chlorophyll- a (HNLC) water mass. The mean surface DMS in winter was 2 nM, in spring 6 nM and in summer 10 nM. Our June surface DMS amounts were comparable with those obtained by the Pacific Marine Environmental Laboratory. A sea to air flux of DMS at Station P (50°N, 145°W) was high in the summer of 1997 and the early autumn of 1998 and 2000 and was significantly higher than at other Line P stations. The average flux along Line P was 27 μmol m −2 d −1 by Wanninkhof's formula while that by Liss and Merlivat was 16 μmol m −2 d −1 . DMS profiles showed a decreasing trend with depth, as did temperature and chlorophyll- a (Chl- a ), but an increasing trend with salinity and nitrate. Average DMS concentrations at mixed-layer depth (DMS MLD ) were low in winter at an average of 2.4 nM, moderate in spring at 8 nM and high in summer at 16 nM. For open ocean stations P20 and P26 DMS MLD was high, while Chl- a MLD was low for late spring and early summer during 1996–1998. That is the “summer paradox” phenomenon. The ratio of DMS MLD to Chl- a MLD was out of phase with the mixed-layer depth. Our data confirm the high DMS concentrations previously reported for this region and suggest that this is characteristic of the subarctic HNLC region. DOI: 10.1111/j.1600-0889.2005.00156.x

https://www.tandfonline.com/doi/pdf/10.3402/tellusb.v57i4.16556

Temporal and spatial distribution of dimethylsulfide in the subarctic northeast Pacific Ocean: a high-nutrient—low-chlorophyll region

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

G. E. Smith

Author Tools

Chat about Author

Papers

Temporal and spatial distribution of dimethylsulfide in the subarctic northeast Pacific Ocean: a high-nutrient—low-chlorophyll region