Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations

14 pages, 4 figures, 1 table, supplement https://doi.org/10.5194/bg-21-4439-2024-supplement.-- Data availability: The climatological data of H22 is publicly available at https://doi.org/10.17632/hyn62spny2.2 (Mahajan, 2023; Hulswar et al., 2022). Similarly, for W20 and G18 it is available at https:/...

ver descrição completa

Detalhes bibliográficos
Autores: Joge, Sankirna D., Mahajan, Anoop S., Hulswar, Shrivardhan, Marandino, Christa A., Galí, Martí, Bell, Thomas G., Simó, Rafel
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/373371
Acesso em linha:http://hdl.handle.net/10261/373371
Access Level:acceso abierto
id ES_83d739361dea1e5b440147687bb257e1
oai_identifier_str oai:digital.csic.es:10261/373371
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations
title Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations
spellingShingle Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations
Joge, Sankirna D.
title_short Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations
title_full Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations
title_fullStr Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations
title_full_unstemmed Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations
title_sort Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimations
dc.creator.none.fl_str_mv Joge, Sankirna D.
Mahajan, Anoop S.
Hulswar, Shrivardhan
Marandino, Christa A.
Galí, Martí
Bell, Thomas G.
Simó, Rafel
author Joge, Sankirna D.
author_facet Joge, Sankirna D.
Mahajan, Anoop S.
Hulswar, Shrivardhan
Marandino, Christa A.
Galí, Martí
Bell, Thomas G.
Simó, Rafel
author_role author
author2 Mahajan, Anoop S.
Hulswar, Shrivardhan
Marandino, Christa A.
Galí, Martí
Bell, Thomas G.
Simó, Rafel
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv European Commission
Ministerio de Ciencia e Innovación (España)
Agencia Estatal de Investigación (España)
Ministry of Earth Sciences (India)
Natural Environment Research Council (UK)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
description 14 pages, 4 figures, 1 table, supplement https://doi.org/10.5194/bg-21-4439-2024-supplement.-- Data availability: The climatological data of H22 is publicly available at https://doi.org/10.17632/hyn62spny2.2 (Mahajan, 2023; Hulswar et al., 2022). Similarly, for W20 and G18 it is available at https://doi.org/10.5281/zenodo.3833233 (Wang et al., 2020a, b) and https://doi.org/10.5281/zenodo.2558511 (Tapias, 2019; Galí et al., 2018), respectively. The sea surface temperature (SST), salinity, and nutrients data is available at https://www.ncei.noaa.gov/access/world-ocean-atlas-2018/ (last access: 9 January 2024, Garcia et al., 2019). The MLD from MIMOC at https://www.pmel.noaa.gov/mimoc/ (last access: 9 January 2024, Schmidtko et al., 2013) and satellite-based variables from NASA SeaWiFS at https://oceancolor.gsfc.nasa.gov/l3/ (last access: 9 January 2024, NASA Ocean Biology Processing Group, 2022)
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/373371
url http://hdl.handle.net/10261/373371
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/H2020/834162
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-140872NB-I00
https://doi.org/10.5194/bg-21-4439-2024
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv European Geosciences Union
publisher.none.fl_str_mv European Geosciences Union
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869412165417435136
spelling Dimethyl sulfide (DMS) climatologies, fluxes, and trends - Part 1: Differences between seawater DMS estimationsJoge, Sankirna D.Mahajan, Anoop S.Hulswar, ShrivardhanMarandino, Christa A.Galí, MartíBell, Thomas G.Simó, Rafel14 pages, 4 figures, 1 table, supplement https://doi.org/10.5194/bg-21-4439-2024-supplement.-- Data availability: The climatological data of H22 is publicly available at https://doi.org/10.17632/hyn62spny2.2 (Mahajan, 2023; Hulswar et al., 2022). Similarly, for W20 and G18 it is available at https://doi.org/10.5281/zenodo.3833233 (Wang et al., 2020a, b) and https://doi.org/10.5281/zenodo.2558511 (Tapias, 2019; Galí et al., 2018), respectively. The sea surface temperature (SST), salinity, and nutrients data is available at https://www.ncei.noaa.gov/access/world-ocean-atlas-2018/ (last access: 9 January 2024, Garcia et al., 2019). The MLD from MIMOC at https://www.pmel.noaa.gov/mimoc/ (last access: 9 January 2024, Schmidtko et al., 2013) and satellite-based variables from NASA SeaWiFS at https://oceancolor.gsfc.nasa.gov/l3/ (last access: 9 January 2024, NASA Ocean Biology Processing Group, 2022)Dimethyl sulfide (DMS) is a naturally emitted trace gas that can affect the Earth's radiative budget by changing cloud albedo. Most atmospheric models that represent aerosol processes depend on regional or global distributions of seawater DMS concentrations and sea–air flux parameterizations to estimate its emissions. In this study, we analyse the differences between three estimations of seawater DMS, one of which is an observation-based interpolation method following Hulswar et al. (2022) (hereafter referred to as H22) and two of which are proxy-based parameterization methods following Galí et al. (2018) (hereafter referred to as G18) and Wang et al. (2020a) (hereafter referred to as W20). The interpolation-based method depends on the distribution of observations and the methods used to fill data between observations, while the parameterization-based methods rely on establishing a relationship between DMS and environmental parameters such as chlorophyll a, mixed-layer depth, nutrients, sea surface temperature, etc., which can then be used to predict DMS concentrations. On average, the interpolation-based methods show higher DMS values compared to the parameterization-based methods. Even though the interpolation method shows higher values than the parameterization-based methods, it fails to capture mesoscale variability. The regression-based parameterization method (G18) shows the lowest values compared to other estimations, especially in the Southern Ocean, which is the high-DMS region in austral summer. The parameterization-based methods suggest positive long-term trends in seawater DMS (3.82±0.79 % per decade for G18 and 2.13±0.32 % per decade for W20). Since large differences, often more than 100 %, are observed between the different estimations of seawater DMS, the derived sea–air fluxes and, hence, the impact of DMS on the radiative budget are sensitive to the estimate usedThe Indian Institute of Tropical Meteorology is funded by the Ministry of Earth Sciences, Government of India. Martí Galí and Rafel Simó acknowledge support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 834162 – SUMMIT Advanced Grant to RS) and the Spanish Government through the grant GOOSE (no. PID2022_140872NB_I00), as well as the “Severo Ochoa Centre of Excellence” accreditation grant (no. CEX2019-000928-S). The contribution of TGB to this work was via funding from the UK Natural Environmental Research Council CARES project (ConstrAining the Role of sulfur in the Earth System, NE/W009277/1)Peer reviewedEuropean Geosciences UnionEuropean CommissionMinisterio de Ciencia e Innovación (España)Agencia Estatal de Investigación (España)Ministry of Earth Sciences (India)Natural Environment Research Council (UK)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202420242024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/373371reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/834162info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-140872NB-I00https://doi.org/10.5194/bg-21-4439-2024Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3733712026-05-22T06:33:51Z
score 15,198674

Registos relacionados