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

Abstract. 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 used.

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Publication Details

Journal
Biogeosciences
Published
2024-10-14
DOI
https://doi.org/10.5194/bg-21-4439-2024
Citations
7
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
2.63

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article

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

Shrivardhan Hulswar, Sankirna D. Joge, Rafel Simó, Christa Marandino et al.
7 citations
Biogeosciences
Atmospheric chemistry and aerosols
2.63
article

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

Shrivardhan Hulswar, Sankirna D. Joge, Rafel Simó, Christa Marandino, Anoop S. Mahajan, Martí Galí, Thomas G. Bell
article en
7 citations

Abstract

Abstract. 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 used.

BiogeosciencesVol. 21(19)
Indian Institute of Tropical Meteorology (IN), Plymouth Marine Laboratory (GB), GEOMAR Helmholtz Centre for Ocean Research Kiel (DE), Institut Català de Ciències del Clima (ES), Institut de Ciències del Mar (ES), Savitribai Phule Pune University (IN)
European Commission, Ministry of Earth Sciences
Life below water
Openalex Percentile: Top 10%
Atmospheric chemistry and aerosols
2.63
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