Articles | Volume 14, issue 7
https://doi.org/10.5194/essd-14-2963-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-2963-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Third revision of the global surface seawater dimethyl sulfide climatology (DMS-Rev3)
Shrivardhan Hulswar
Indian Institute of Tropical Meteorology (IITM), Ministry of Earth Sciences, Pune, India
Rafel Simó
Institut de Ciències del Mar (CSIC), Barcelona, Catalonia,
Spain
Martí Galí
Institut de Ciències del Mar (CSIC), Barcelona, Catalonia,
Spain
Barcelona Supercomputing Center (BSC), Barcelona, Catalonia, Spain
Thomas G. Bell
Plymouth Marine Laboratory (PML), Plymouth, UK
Arancha Lana
Institut Mediterrani d'Estudis Avançats (IMEDEA, UIB-CSIC),
Esporles, Balearic Islands, Spain
Swaleha Inamdar
Indian Institute of Tropical Meteorology (IITM), Ministry of Earth Sciences, Pune, India
Institute of Environment and Sustainable Development, Banaras Hindu
University, Varanasi, India
Paul R. Halloran
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
George Manville
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
Anoop Sharad Mahajan
CORRESPONDING AUTHOR
Indian Institute of Tropical Meteorology (IITM), Ministry of Earth Sciences, Pune, India
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Dimethyl sulfide (DMS) is the largest natural source of sulfur in the atmosphere and leads to the formation of cloud condensation nuclei. DMS emission and quantification of its impacts have large uncertainties, but a detailed study on the emissions and drivers of their uncertainty is missing to date. The emissions are usually calculated from the seawater DMS concentrations and a flux parameterization. Here we quantify the differences in DMS seawater products, which can affect DMS fluxes.
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Richard P. Sims, Michael Bedington, Ute Schuster, Andrew J. Watson, Vassilis Kitidis, Ricardo Torres, Helen S. Findlay, James R. Fishwick, Ian Brown, and Thomas G. Bell
Biogeosciences, 19, 1657–1674, https://doi.org/10.5194/bg-19-1657-2022, https://doi.org/10.5194/bg-19-1657-2022, 2022
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Kevin J. Sanchez, Bo Zhang, Hongyu Liu, Matthew D. Brown, Ewan C. Crosbie, Francesca Gallo, Johnathan W. Hair, Chris A. Hostetler, Carolyn E. Jordan, Claire E. Robinson, Amy Jo Scarino, Taylor J. Shingler, Michael A. Shook, Kenneth L. Thornhill, Elizabeth B. Wiggins, Edward L. Winstead, Luke D. Ziemba, Georges Saliba, Savannah L. Lewis, Lynn M. Russell, Patricia K. Quinn, Timothy S. Bates, Jack Porter, Thomas G. Bell, Peter Gaube, Eric S. Saltzman, Michael J. Behrenfeld, and Richard H. Moore
Atmos. Chem. Phys., 22, 2795–2815, https://doi.org/10.5194/acp-22-2795-2022, https://doi.org/10.5194/acp-22-2795-2022, 2022
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Atmospheric particle concentrations impact clouds, which strongly impact the amount of sunlight reflected back into space and the overall climate. Measurements of particles over the ocean are rare and expensive to collect, so models are necessary to fill in the gaps by simulating both particle and clouds. However, some measurements are needed to test the accuracy of the models. Here, we measure changes in particles in different weather conditions, which are ideal for comparison with models.
Martí Galí, Marcus Falls, Hervé Claustre, Olivier Aumont, and Raffaele Bernardello
Biogeosciences, 19, 1245–1275, https://doi.org/10.5194/bg-19-1245-2022, https://doi.org/10.5194/bg-19-1245-2022, 2022
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Part of the organic matter produced by plankton in the upper ocean is exported to the deep ocean. This process, known as the biological carbon pump, is key for the regulation of atmospheric carbon dioxide and global climate. However, the dynamics of organic particles below the upper ocean layer are not well understood. Here we compared the measurements acquired by autonomous robots in the top 1000 m of the ocean to a numerical model, which can help improve future climate projections.
Sebastian Landwehr, Michele Volpi, F. Alexander Haumann, Charlotte M. Robinson, Iris Thurnherr, Valerio Ferracci, Andrea Baccarini, Jenny Thomas, Irina Gorodetskaya, Christian Tatzelt, Silvia Henning, Rob L. Modini, Heather J. Forrer, Yajuan Lin, Nicolas Cassar, Rafel Simó, Christel Hassler, Alireza Moallemi, Sarah E. Fawcett, Neil Harris, Ruth Airs, Marzieh H. Derkani, Alberto Alberello, Alessandro Toffoli, Gang Chen, Pablo Rodríguez-Ros, Marina Zamanillo, Pau Cortés-Greus, Lei Xue, Conor G. Bolas, Katherine C. Leonard, Fernando Perez-Cruz, David Walton, and Julia Schmale
Earth Syst. Dynam., 12, 1295–1369, https://doi.org/10.5194/esd-12-1295-2021, https://doi.org/10.5194/esd-12-1295-2021, 2021
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The Antarctic Circumnavigation Expedition surveyed a large number of variables describing the dynamic state of ocean and atmosphere, freshwater cycle, atmospheric chemistry, ocean biogeochemistry, and microbiology in the Southern Ocean. To reduce the dimensionality of the dataset, we apply a sparse principal component analysis and identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and
hotspotsof interaction. Code and data are open access.
Paul R. Halloran, Jennifer K. McWhorter, Beatriz Arellano Nava, Robert Marsh, and William Skirving
Geosci. Model Dev., 14, 6177–6195, https://doi.org/10.5194/gmd-14-6177-2021, https://doi.org/10.5194/gmd-14-6177-2021, 2021
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This paper describes the latest version of a simple model for simulating coastal oceanography in response to changes in weather and climate. The latest revision of this model makes scientific improvements but focuses on improvements that allow the model to be run simply at large scales and for long periods of time to explore the implications of (for example) future climate change along large areas of coastline.
Anoop S. Mahajan, Mriganka S. Biswas, Steffen Beirle, Thomas Wagner, Anja Schönhardt, Nuria Benavent, and Alfonso Saiz-Lopez
Atmos. Chem. Phys., 21, 11829–11842, https://doi.org/10.5194/acp-21-11829-2021, https://doi.org/10.5194/acp-21-11829-2021, 2021
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Iodine plays a vital role in oxidation chemistry over Antarctica, with past observations showing highly elevated levels of iodine oxide (IO) leading to severe depletion of boundary layer ozone. We present IO observations over three summers (2015–2017) at the Indian Antarctic bases of Bharati and Maitri. IO was observed during all campaigns with mixing ratios below 2 pptv, which is lower than the peak levels observed in West Antarctica, showing the differences in regional chemistry and emissions.
Daniel P. Phillips, Frances E. Hopkins, Thomas G. Bell, Peter S. Liss, Philip D. Nightingale, Claire E. Reeves, Charel Wohl, and Mingxi Yang
Atmos. Chem. Phys., 21, 10111–10132, https://doi.org/10.5194/acp-21-10111-2021, https://doi.org/10.5194/acp-21-10111-2021, 2021
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We present the first measurements of the rate of transfer (flux) of three gases between the atmosphere and the ocean, using a direct flux measurement technique, at a coastal site. We show greater atmospheric loss of acetone and acetaldehyde into the ocean than estimated by global models for the open water; importantly, the acetaldehyde transfer direction is opposite to the model estimates. Measured dimethylsulfide fluxes agreed with a recent model. Isoprene fluxes were too weak to be measured.
Anoop S. Mahajan, Qinyi Li, Swaleha Inamdar, Kirpa Ram, Alba Badia, and Alfonso Saiz-Lopez
Atmos. Chem. Phys., 21, 8437–8454, https://doi.org/10.5194/acp-21-8437-2021, https://doi.org/10.5194/acp-21-8437-2021, 2021
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Using a regional model, we show that iodine-catalysed reactions cause large regional changes in the chemical composition in the northern Indian Ocean, with peak changes of up to 25 % in O3, 50 % in nitrogen oxides (NO and NO2), 15 % in hydroxyl radicals (OH), 25 % in hydroperoxyl radicals (HO2), and up to a 50 % change in the nitrate radical (NO3). These results show the importance of including iodine chemistry in modelling the atmosphere in this region.
Yuanxu Dong, Mingxi Yang, Dorothee C. E. Bakker, Vassilis Kitidis, and Thomas G. Bell
Atmos. Chem. Phys., 21, 8089–8110, https://doi.org/10.5194/acp-21-8089-2021, https://doi.org/10.5194/acp-21-8089-2021, 2021
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Eddy covariance (EC) is the most direct method for measuring air–sea CO2 flux from ships. However, uncertainty in EC air–sea CO2 fluxes has not been well quantified. Here we show that with the state-of-the-art gas analysers, instrumental noise no longer contributes significantly to the CO2 flux uncertainty. Applying an appropriate averaging timescale (1–3 h) and suitable air–sea CO2 fugacity threshold (at least 20 µatm) to EC flux data enables an optimal analysis of the gas transfer velocity.
Betty Croft, Randall V. Martin, Richard H. Moore, Luke D. Ziemba, Ewan C. Crosbie, Hongyu Liu, Lynn M. Russell, Georges Saliba, Armin Wisthaler, Markus Müller, Arne Schiller, Martí Galí, Rachel Y.-W. Chang, Erin E. McDuffie, Kelsey R. Bilsback, and Jeffrey R. Pierce
Atmos. Chem. Phys., 21, 1889–1916, https://doi.org/10.5194/acp-21-1889-2021, https://doi.org/10.5194/acp-21-1889-2021, 2021
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North Atlantic Aerosols and Marine Ecosystems Study measurements combined with GEOS-Chem-TOMAS modeling suggest that several not-well-understood key factors control northwest Atlantic aerosol number and size. These synergetic and climate-relevant factors include particle formation near and above the marine boundary layer top, particle growth by marine secondary organic aerosol on descent, particle formation/growth related to dimethyl sulfide, sea spray aerosol, and ship emissions.
Kevin J. Sanchez, Bo Zhang, Hongyu Liu, Georges Saliba, Chia-Li Chen, Savannah L. Lewis, Lynn M. Russell, Michael A. Shook, Ewan C. Crosbie, Luke D. Ziemba, Matthew D. Brown, Taylor J. Shingler, Claire E. Robinson, Elizabeth B. Wiggins, Kenneth L. Thornhill, Edward L. Winstead, Carolyn Jordan, Patricia K. Quinn, Timothy S. Bates, Jack Porter, Thomas G. Bell, Eric S. Saltzman, Michael J. Behrenfeld, and Richard H. Moore
Atmos. Chem. Phys., 21, 831–851, https://doi.org/10.5194/acp-21-831-2021, https://doi.org/10.5194/acp-21-831-2021, 2021
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Models describing atmospheric airflow were combined with satellite measurements representative of marine phytoplankton and other meteorological variables. These combined variables were compared to measured aerosol to identify upwind influences on aerosol concentrations. Results indicate that phytoplankton production rates upwind impact the aerosol mass. Also, results suggest that the condensation of mass onto short-lived large sea spray particles may be a significant sink of aerosol mass.
David C. Loades, Mingxi Yang, Thomas G. Bell, Adam R. Vaughan, Ryan J. Pound, Stefan Metzger, James D. Lee, and Lucy J. Carpenter
Atmos. Meas. Tech., 13, 6915–6931, https://doi.org/10.5194/amt-13-6915-2020, https://doi.org/10.5194/amt-13-6915-2020, 2020
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The loss of ozone to the sea surface was measured from the south coast of the UK and was found to be more rapid than previous observations over the open ocean. This is likely a consequence of different chemistry and biology in coastal environments. Strong winds appeared to speed up the loss of ozone. A better understanding of what influences ozone loss over the sea will lead to better model estimates of total ozone in the troposphere.
Wei-Lei Wang, Guisheng Song, François Primeau, Eric S. Saltzman, Thomas G. Bell, and J. Keith Moore
Biogeosciences, 17, 5335–5354, https://doi.org/10.5194/bg-17-5335-2020, https://doi.org/10.5194/bg-17-5335-2020, 2020
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Dimethyl sulfide, a volatile compound produced as a byproduct of marine phytoplankton activity, can be emitted to the atmosphere via gas exchange. In the atmosphere, DMS is oxidized to cloud condensation nuclei, thus contributing to cloud formation. Therefore, oceanic DMS plays an important role in regulating the planet's climate by influencing the radiation budget. In this study, we use an artificial neural network model to update the global DMS climatology and estimate the sea-to-air flux.
Swaleha Inamdar, Liselotte Tinel, Rosie Chance, Lucy J. Carpenter, Prabhakaran Sabu, Racheal Chacko, Sarat C. Tripathy, Anvita U. Kerkar, Alok K. Sinha, Parli Venkateswaran Bhaskar, Amit Sarkar, Rajdeep Roy, Tomás Sherwen, Carlos Cuevas, Alfonso Saiz-Lopez, Kirpa Ram, and Anoop S. Mahajan
Atmos. Chem. Phys., 20, 12093–12114, https://doi.org/10.5194/acp-20-12093-2020, https://doi.org/10.5194/acp-20-12093-2020, 2020
Short summary
Short summary
Iodine chemistry is generating a lot of interest because of its impacts on the oxidising capacity of the marine boundary and depletion of ozone. However, one of the challenges has been predicting the right levels of iodine in the models, which depend on parameterisations for emissions from the sea surface. This paper discusses the different parameterisations available and compares them with observations, showing that our current knowledge is still insufficient, especially on a regional scale.
Cited articles
Andreae, M. O. and Raemdonck, H.: Dimethyl Sulfide in the Surface Ocean and the Marine Atmosphere: A Global View, Science, 221, 744–747, http://www.jstor.org/stable/1691026 (last access: September 2020), 1983.
Andreae, M. O. and Barnard, W. R.: The marine chemistry of dimethylsulfide, Mar. Chem., 14, 267–279, https://doi.org/10.1016/0304-4203(84)90047-1, 1984.
Andreae, M. O. and Crutzen, P. J.: Atmospheric aerosols: Biogeochemical
sources and role in atmospheric chemistry, Science, 276,
1052–1058, 1997.
Ardyna, M., Babin, M., Gosselin, M., Devred, E., Rainville, L., and Tremblay,
E. J.: Recent Arctic Ocean sea ice loss triggers novel fall phytoplankton
blooms, Geophys. Res. Lett., 41, 6207–6212,
https://doi.org/10.1002/2014GL061047, 2014.
Asher, E. C., Merzouk, A., and Tortell, P. D.: Fine-scale spatial and temporal variability of surface water dimethylsufide (DMS) concentrations and sea-air fluxes in the NE Subarctic Pacific, Mar. Chem.,
126, 63–75, https://doi.org/10.1016/j.marchem.2011.03.009, 2011.
Barnes, S. L.: A Technique for Maximizing Details in Numerical Weather Map
Analysis, J. Appl. Meteorol., 3, 396–409,
https://doi.org/10.1175/1520-0450(1964)003<0396:atfmdi>2.0.co;2,
1964.
Behrenfeld, M. J., Moore, R. H., Hostetler, C. A., Graff, J., Gaube, P., Russell, L. M., Chen, G., Doney, S. C., Giovannoni, S., Liu, H., Proctor, C., Bolaños, L. M., Baetge, N., Davie-Martin, C., Westberry, T. K., Bates, T. S., Bell, T. G., Bidle, K. D., Boss, E. S., Brooks, S. D., Cairns, B., Carlson, C., Halsey, K., Harvey, E. L., Hu, C., Karp-Boss, L., Kleb, M., Menden-Deuer, S., Morison, F., Quinn, P. K., Scarino, A. J., Anderson, B., Chowdhary, J., Crosbie, E., Ferrare, R., Hair, J. W., Hu, Y., Janz, S., Redemann, J., Saltzman, E., Shook, M., Siegel, D. A., Wisthaler, A., Martin, M. Y., and Ziemba, L.: The North Atlantic Aerosol and Marine Ecosystem Study (NAAMES): Science Motive and Mission Overview, Front. Mar. Sci., 6, 1–25, https://doi.org/10.3389/fmars.2019.00122, 2019.
Bell, T. G., Malin, G., Lee, G. A., Stefels, J., Archer, S., Steinke, M., and
Matrai, P.: Global oceanic DMS data inter-comparability, Biogeochemistry,
110, 147–161, https://doi.org/10.1007/s10533-011-9662-3, 2012.
Bell, T. G., De Bruyn, W., Miller, S. D., Ward, B., Christensen, K. H., and Saltzman, E. S.: Air–sea dimethylsulfide (DMS) gas transfer in the North Atlantic: evidence for limited interfacial gas exchange at high wind speed, Atmos. Chem. Phys., 13, 11073–11087, https://doi.org/10.5194/acp-13-11073-2013, 2013.
Bell, T. G., Porter, J. G., Wang, W.-L., Lawler, M. J., Boss, E.,
Behrenfeld, M. J., and Saltzman, E. S.: Predictability of Seawater DMS During
the North Atlantic Aerosol and Marine Ecosystem Study (NAAMES), Front. Mar.
Sci., 7, 596763, https://doi.org/10.3389/fmars.2020.596763, 2021.
Belviso, S., Moulin, C., Bopp, L., and Stefels, J.: Assessment of a global
climatology of oceanic dimethylsulfide (DMS) concentrations based on
SeaWiFS imagery (1998–2001), Can. J. Fish. Aquat. Sci., 61, 804–816,
https://doi.org/10.1139/F04-001, 2004.
Bopp, L., Boucher, O., Aumont, O., Belviso, S., Monfray, P., and Pham, M.:
Will marine dimethylsulfide emissions amplify or alleviate global warming?
– A model study, Can. J. Fish Aquat. Sci., 61, 826–835, 2004.
Carpenter, L. J., Archer, S. D., and Beale, R.: Ocean-atmosphere trace gas
exchange, Chem. Soc. Rev., 41, 6473–6506, https://doi.org/10.1039/c2cs35121h, 2012.
Carslaw, K. S., Lee, L. A., Reddington, C. L., Pringle, K. J., Rap, A.,
Forster, P. M., Mann, G. W., Spracklen, D. V., Woodhouse, M. T., Regayre, L.
A., and Pierce, J. R.: Large contribution of natural aerosols to uncertainty
in indirect forcing, Nature, 503, 67–71, https://doi.org/10.1038/nature12674,
2013.
Charlson, R. J., Lovelock, J. E., Andreae, M. O., and Warren, S. G.: Oceanic phytoplankton, atmospheric sulphur, cloud albedo and climate, Nature, 326, 655–661, https://doi.org/10.1038/326655a0, 1987.
Chiswell, S. M., Bradford-Grieve, J., Hadfield, M. G., and Kennan, S. C.:
Climatology of surface chlorophyll a, autumn-winter and spring blooms in the
southwest Pacific Ocean, J. Geophys. Res.-Oceans, 118, 1003–1018,
https://doi.org/10.1002/jgrc.20088, 2013.
Devred, E., Sathyendranath, S., and Platt, T.: Delineation of ecological
provinces using ocean colour radiometry, Mar. Ecol. Prog. Ser., 346, 1–13,
https://doi.org/10.3354/meps07149, 2007.
Dilmahamod, A. F., Penven, P., Aguiar-González, B., Reason, C. J. C., and
Hermes, J. C.: A New Definition of the South-East Madagascar Bloom and
Analysis of Its Variability, J. Geophys. Res.-Oceans, 124, 1717–1735,
https://doi.org/10.1029/2018JC014582, 2019.
Fiddes, S. L., Woodhouse, M. T., Nicholls, Z., Lane, T. P., and Schofield, R.: Cloud, precipitation and radiation responses to large perturbations in global dimethyl sulfide, Atmos. Chem. Phys., 18, 10177–10198, https://doi.org/10.5194/acp-18-10177-2018, 2018.
Forget, M. H., Platt, T., Sathyendranath, S., and Fanning, P.: Phytoplankton
size structure, distribution, and primary production as the basis for
trophic analysis of Caribbean ecosystems, ICES J. Mar. Sci., 68,
751–765, https://doi.org/10.1093/icesjms/fsq182, 2011.
Friedland, K. D., Record, N. R., Asch, R. G., Kristiansen, T., Saba, V. S.,
Drinkwater, K. F., Henson, S., Leaf, R. T., Morse, R. E., Johns, D. G.,
Large, S. I., Hjøllo, S. S., Nye, J. A., Alexander, M. A., and Ji, R.:
Seasonal phytoplankton blooms in the North Atlantic linked to the
overwintering strategies of copepods, Elementa, 4,
https://doi.org/10.12952/journal.elementa.000099, 2016.
Galí, M. and Simó, R.: A meta-analysis of oceanic DMS and DMSP
cycling processes: Disentangling the summer paradox, Global Biogeochem.
Cy., 29, 496–515, https://doi.org/10.1002/2014GB004940, 2015.
Galí, M., Devred, E., Levasseur, M., Royer, S. J., and Babin, M.: A
remote sensing algorithm for planktonic dimethylsulfoniopropionate (DMSP)
and an analysis of global patterns, Remote Sens. Environ., 171, 171–184,
https://doi.org/10.1016/j.rse.2015.10.012, 2015.
Galí, M., Levasseur, M., Devred, E., Simó, R., and Babin, M.: Sea-surface dimethylsulfide (DMS) concentration from satellite data at global and regional scales, Biogeosciences, 15, 3497–3519, https://doi.org/10.5194/bg-15-3497-2018, 2018.
Hales, B. and Takahashi, T.: High-resolution biogeochemical investigation
of the Ross Sea, Antarctica, during the AESOPS (U. S. JGOFS) Program, Global
Biogeochem. Cy., 18, GB3006, https://doi.org/10.1029/2003GB002165, 2004.
Hayashida, H., Steiner, N., Monahan, A., Galindo, V., Lizotte, M., and Levasseur, M.: Implications of sea-ice biogeochemistry for oceanic production and emissions of dimethyl sulfide in the Arctic, Biogeosciences, 14, 3129–3155, https://doi.org/10.5194/bg-14-3129-2017, 2017.
Hjerne, O., Hajdu, S., Larsson, U., Downing, A., and Winder, M.: Climate
driven changes in timing, composition and size of the Baltic Sea
phytoplankton spring bloom, Front. Mar. Sci., 6, 1–15,
https://doi.org/10.3389/fmars.2019.00482, 2019.
Iida, T., Saitoh, S. I., Miyamura, T., Toratani, M., Fukushima, H., and
Shiga, N.: Temporal and spatial variability of coccolithophore blooms in the
eastern Bering Sea, 1998–2001, Prog. Oceanogr., 55, 165–175,
https://doi.org/10.1016/S0079-6611(02)00076-9, 2002.
Jarníková, T., Tortell, P. D., Jarnikova, T., and Tortell, P. D.:
Towards a revised climatology of summertime dimethylsulfide concentrations
and sea – air fluxes in the Southern Ocean, Environ. Chem., 13,
364–378, https://doi.org/10.1071/EN14272, 2016.
Jin, M., Deal, C., Wang, J., Alexander, V., Gradinger, R., Saitoh, S. I.,
Iida, T., Wan, Z., and Stabeno, P.: Ice-associated phytoplankton blooms in
the southeastern Bering Sea, Geophys. Res. Lett., 34, L06612,
https://doi.org/10.1029/2006GL028849, 2007.
Jury, M. R. and Brundrit, G. B.: Temporal organization of upwelling in the
southern Benguela ecosystem by resonant coastal trapped waves in the ocean
and atmosphere, South African J. Mar. Sci., 12, 219–224,
https://doi.org/10.2989/02577619209504704, 1992.
Kettle, A. J., Andreae, M. O., Amouroux, D., Bates, T. S., Berresheim, H.,
B, H., Boniforti, R., Curran, M. A. J., Ditullio, G. R., Helas, G., Jones,
G. B., Keller, M. D., Leck, C., Levasseur, M., Malin, G., Maspero, M.,
Matrai, P., Mctaggart, A. R., Mihalopoulos, N., Nguyen, B. C., Novo, A.,
Putaud, J. P., Rapsomanikis, S., Roberts, G., Schebeske, G., Sharma, S.,
Sim, R., Staubes, R., Turner, S., Uher, G., Boothbay, W., and Planck, M.: A
global database of sea surface dimethylsulfide (DMS) measurements and a
procedure to predict sea surface DMS as a function of latitude, longitude,
and month TM grazing, Global Biogeochem. Cy., 13, 399–444, 1999.
Kiene, R. P., Linn, L. J., and Bruton, J. A.: New and important roles for
DMSP in marine microbial communities, J. Sea Res., 43, 209–224,
https://doi.org/10.1016/S1385-1101(00)00023-X, 2000.
Lana, A., Bell, T. G., Simó, R., Vallina, S. M., Ballabrera-Poy, J.,
Kettle, A. J., Dachs, J., Bopp, L., Saltzman, E. S., Stefels, J., Johnson,
J. E., and Liss, P. S.: An updated climatology of surface dimethlysulfide
concentrations and emission fluxes in the global ocean, Global Biogeochem.
Cy., 25, 1–17, https://doi.org/10.1029/2010GB003850, 2011.
Longhurst, A. R.: Ecological Geography of the Sea, 2nd edn., Academic Press, ISBN-10 0-12-455521-7, https://doi.org/10.1016/B978-0-12-455521-1.X5000-1, 2007.
Mahajan, A. S.: Third Revision of the Global Surface Seawater Dimethyl
Sulfide Climatology (DMS-Rev3), V1, Mendeley Data [code and data set],
https://doi.org/10.17632/hyn62spny2.1, 2021.
Mahajan, A. S., Fadnavis, S., Thomas, M. A., Pozzoli, L., Gupta, S., Royer,
S. J., Saiz-Lopez, A., and Simó, R.: Quantifying the impacts of an
updated global dimethyl sulfide climatology on cloud microphysics and
aerosol radiative forcing, J. Geophys. Res., 120, 2524–2536,
https://doi.org/10.1002/2014JD022687, 2015.
Matrai, P., Vernet, M., and Wassmann, P.: Relating temporal and spatial
patterns of DMSP in the Barents Sea to phytoplankton biomass and
productivity, J. Mar. Syst., 67, 83–101,
https://doi.org/10.1016/j.jmarsys.2006.10.001, 2007.
Matrai, P. A. and Keller, M. D.: Dimethylsulfide in a large-scale
coccolithophore bloom in the Gulf of Maine, Cont. Shelf Res., 13,
831–843, https://doi.org/10.1016/0278-4343(93)90012-M, 1993.
McCreary, J. P., Kohler, K. E., Hood, R. R., and Olson, D. B.: A
four-component ecosystem model of biological activity in the Arabian Sea,
Prog. Oceanogr., 37, 193–240, https://doi.org/10.1016/S0079-6611(96)00005-5,
1996.
Nightingale, D., Malin, G., Law, C. S., Watson, J., Liss, S., and Liddicoat,
I.: In situ evaluation of air-sea gas exchange parameterizations using novel
conservative and volatile tracers, Global Biogeochem. Cy., 14,
373–387, https://doi.org/10.1029/1999GB900091, 2000.
NOAA-PMEL: Global Surface Seawater Dimethylsulfide (DMS) Database, NOAA [data set], https://saga.pmel.noaa.gov/dms/, last access: 18 February 2020.
Oliver, M. J. and Irwin, A. J.: Objective global ocean biogeographic
provinces, Geophys. Res. Lett., 35, 1–6, https://doi.org/10.1029/2008GL034238,
2008.
Pazmiño, A. F., Godin-Beekmann, S., Ginzburg, M., Bekki, S.,
Hauchecorne, A., Piacentini, R. D., and Quel, E. J.: Impact of Antarctic
polar vortex occurrences on total ozone and UVB radiation at southern
Argentinean and Antarctic stations during 1997–2003 period, J. Geophys. Res.-Atmos., 110, D03103, https://doi.org/10.1029/2004JD005304, 2005.
Penven, P., Echevin, V., Pasapera, J., Colas, F., and Tam, J.: Average
circulation, seasonal cycle, and mesoscale dynamics of the Peru Current
System: A modeling approach, J. Geophys. Res.-Oceans, 110, C10021,
https://doi.org/10.1029/2005JC002945, 2005.
Pérez, V., Fernández, E., Marañón, E., Serret, P., and
García-Soto, C.: Seasonal and interannual variability of chlorophyll a
and primary production in the Equatorial Atlantic: In situ and remote
sensing observations, J. Plankton Res., 27, 189–197,
https://doi.org/10.1093/plankt/fbh159, 2005.
Quinn, P. K. and Bates, T. S.: The case against climate regulation via
oceanic phytoplankton sulphur emissions, Nature, 480, 51–56,
https://doi.org/10.1038/nature10580, 2011.
Quinn, P. K., Coffman, D. J., Johnson, J. E., Upchurch, L. M., and Bates, T.
S.: Small fraction of marine cloud condensation nuclei made up of sea spray
aerosol, Nat. Geosci., 10, 674–679, https://doi.org/10.1038/ngeo3003, 2017.
Reygondeau, G., Longhurst, A., Martinez, E., Beaugrand, G., Antoine, D., and
Maury, O.: Dynamic biogeochemical provinces in the global ocean, Global
Biogeochem. Cy., 27, 1046–1058, https://doi.org/10.1002/gbc.20089, 2013.
Royer, S.-J., Mahajan, A. S., Galí, M., Saltzman, E., and Simó, R.:
Small-scale variability patterns of DMS and phytoplankton in surface waters
of the tropical and subtropical Atlantic, Indian, and Pacific Oceans,
Geophys. Res. Lett., 42, 475–483, https://doi.org/10.1002/2014GL062543, 2015.
Shuman, F. G.: Numerical Methods in Weather Prediction: II. Smoothing and
Filtering, Mon. Weather Rev., 85, 357–361,
https://doi.org/10.1175/1520-0493(1957)085<0357:nmiwpi>2.0.co;2,
1957.
Sigler, M. F., Stabeno, P. J., Eisner, L. B., Napp, J. M., and Mueter, F. J.:
Spring and fall phytoplankton blooms in a productive subarctic ecosystem,
the eastern Bering Sea, during 1995–2011, Deep.-Sea Res. Part II, 109, 71–83, https://doi.org/10.1016/j.dsr2.2013.12.007, 2014.
Simo, R.: Production of atmospheric sulfur by oceanic plankton:
biogeochemical, ecological and evolutionary links, Trends Ecol. Evol.,
16, 287–294, 2001.
Simó, R. and Dachs, J.: Global ocean emission of dimethylsulfide
predicted from biogeophysical data, Global Biogeochem. Cy., 16,
26-1–26-10, https://doi.org/10.1029/2001gb001829, 2002.
Stefels, J., Steinke, M., Turner, S., Malin, G., and Belviso, S.: Review:
Environmental constraints on the production and removal of the climatically
active gas dimethylsulphide (DMS) and implications for ecosystem modelling,
Biogeochemistry, 83, 245–275, https://doi.org/10.1007/s10533-007-9091-5, 2007.
Swan, H. B., Armishaw, P., Iavetz, R., Alamgir, M., Davies, S. R., Bell, T.
G., and Jones, G. B.: An interlaboratory comparison for the quantification of
aqueous dimethylsulfide, Limnol. Oceanogr. Methods, 12, 784–794,
https://doi.org/10.4319/lom.2014.12.784, 2014.
Tesdal, J.-E., Christian, J. R., Monahan, A. H., and von Salzen, K.: Sensitivity of modelled sulfate aerosol and its radiative effect on climate to ocean DMS concentration and air–sea flux, Atmos. Chem. Phys., 16, 10847–10864, https://doi.org/10.5194/acp-16-10847-2016, 2016.
Thornhill, G., Collins, W., Olivié, D., Skeie, R. B., Archibald, A., Bauer, S., Checa-Garcia, R., Fiedler, S., Folberth, G., Gjermundsen, A., Horowitz, L., Lamarque, J.-F., Michou, M., Mulcahy, J., Nabat, P., Naik, V., O'Connor, F. M., Paulot, F., Schulz, M., Scott, C. E., Séférian, R., Smith, C., Takemura, T., Tilmes, S., Tsigaridis, K., and Weber, J.: Climate-driven chemistry and aerosol feedbacks in CMIP6 Earth system models, Atmos. Chem. Phys., 21, 1105–1126, https://doi.org/10.5194/acp-21-1105-2021, 2021.
Toole, D. A., Kieber, D. J., Kiene, R. P., Siegel, D. A., and Nelson, N. B.:
Photolysis and the dimethylsulfide (DMS) summer paradox in the Sargasso
Sea, Limnol. Oceanogr., 48, 1088–1100, https://doi.org/10.4319/lo.2003.48.3.1088, 2003.
Vallina, S. M. and Simó, R.: Strong Relationship Between DMS and the
Solar Radiation Dose over the Global Surface Ocean, Science,
506–508, https://doi.org/10.1126/science.1133680, 2007.
Wang, C., Soden, B., Yang, W., and Vecchi, G. A.: Compensation between cloud
feedback and aerosol-cloud interaction in CMIP6 models, Geophys. Res. Lett., 48, e2020GL091024, https://doi.org/10.1029/2020gl091024, 2021.
Wang, W.-L., Song, G., Primeau, F., Saltzman, E. S., Bell, T. G., and Moore, J. K.: Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network, Biogeosciences, 17, 5335–5354, https://doi.org/10.5194/bg-17-5335-2020, 2020.
Wohl, C., Brown, I., Kitidis, V., Jones, A. E., Sturges, W. T., Nightingale, P. D., and Yang, M.: Underway seawater and atmospheric measurements of volatile organic compounds in the Southern Ocean, Biogeosciences, 17, 2593–2619, https://doi.org/10.5194/bg-17-2593-2020, 2020.
Wohl, C., Jones, A. E., Sturges, W. T., Nightingale, P. D., Else, B., Butterworth, B. J., and Yang, M.: Sea ice concentration impacts dissolved organic gases in the Canadian Arctic, Biogeosciences, 19, 1021–1045, https://doi.org/10.5194/bg-19-1021-2022, 2022.
Woodhouse, M. T., Carslaw, K. S., Mann, G. W., Vallina, S. M., Vogt, M., Halloran, P. R., and Boucher, O.: Low sensitivity of cloud condensation nuclei to changes in the sea-air flux of dimethyl-sulphide, Atmos. Chem. Phys., 10, 7545–7559, https://doi.org/10.5194/acp-10-7545-2010, 2010.
Woodhouse, M. T., Mann, G. W., Carslaw, K. S., and Boucher, O.: Sensitivity of cloud condensation nuclei to regional changes in dimethyl-sulphide emissions, Atmos. Chem. Phys., 13, 2723–2733, https://doi.org/10.5194/acp-13-2723-2013, 2013.
Zavarsky, A., Goddijn-Murphy, L., Steinhoff, T., and Marandino, C. A.:
Bubble-Mediated Gas Transfer and Gas Transfer Suppression of DMS and CO2, J.
Geophys. Res.-Atmos., 123, 6624–6647, https://doi.org/10.1029/2017JD028071, 2018a.
Zavarsky, A., Booge, D., Fiehn, A., Krüger, K., Atlas, E., and Marandino,
C.: The Influence of Air-Sea Fluxes on Atmospheric Aerosols During the
Summer Monsoon Over the Tropical Indian Ocean, Geophys. Res. Lett., 45,
418–426, https://doi.org/10.1002/2017GL076410, 2018b.
Short summary
The third climatological estimation of sea surface dimethyl sulfide (DMS) concentrations based on in situ measurements was created (DMS-Rev3). The update includes a much larger input dataset and includes improvements in the data unification, filtering, and smoothing algorithm. The DMS-Rev3 climatology provides more realistic monthly estimates of DMS, and shows significant regional differences compared to past climatologies.
The third climatological estimation of sea surface dimethyl sulfide (DMS) concentrations based...
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