Third revision of the global surface seawater dimethyl sulfide climatology (DMS-Rev3)

Abstract

Abstract. This paper presents an updated estimation of the bottom-up global surface seawater dimethyl sulfide (DMS) climatology. This update, called DMS-Rev3, is the third of its kind and includes five significant changes from the last climatology, L11 (Lana et al., 2011), that was released about a decade ago. The first change is the inclusion of new observations that have become available over the last decade, creating a database of 873 539 observations leading to an ∼ 18-fold increase in raw data as compared to the last estimation. The second is significant improvements in data handling, processing, and filtering, to avoid biases due to different observation frequencies which result from different measurement techniques. Thirdly, we incorporate the dynamic seasonal changes observed in the geographic boundaries of the ocean biogeochemical provinces. The fourth change involves the refinement of the interpolation algorithm used to fill in the missing data. Lastly, an upgraded smoothing algorithm based on observed DMS variability length scales (VLS) helps to reproduce a more realistic distribution of the DMS concentration data. The results show that DMS-Rev3 estimates the global annual mean DMS concentration to be ∼ 2.26 nM (2.39 nM without a sea-ice mask), i.e., about 4 % lower than the previous bottom-up L11 climatology. However, significant regional differences of more than 100 % as compared to L11 are observed. The global sea-to-air flux of DMS is estimated at ∼ 27.1 TgS yr−1, which is about 4 % lower than L11, although, like the DMS distribution, large regional differences were observed. The largest changes are observed in high concentration regions such as the polar oceans, although oceanic regions that were under-sampled in the past also show large differences between revisions of the climatology. Finally, DMS-Rev3 reduces the previously observed patchiness in high productivity regions. The new climatology, along with the algorithm, can be found in the online repository: https://doi.org/10.17632/hyn62spny2.1 (Mahajan, 2021).

Global analysis of the controls on seawater dimethylsulfide spatial variability

“…4). DMS concentration variability in mid-high latitude regions is seasonal (Hulswar et al, 2022) and VLSDMS could be influenced by the season / time of year. 1; Fig.…”

“…Oceanic DMS production and consumption pathways are complex and the controls of DMS spatial distribution in the global ocean are not fully resolved (Galí & Simó, 2015). The global surface seawater DMS database contains measurements that show large scale temporal and spatial variability in DMS concentrations (Hulswar et al, 2022;Lana et al, 2011). In-situ DMS measurements are relatively sparse and limited with respect to global distribution, coverage, and spatiotemporal sampling frequency, which renders the majority of DMS observations insufficient to resolve local and sub-mesoscale variability Lana et al, 2011;Tortell et al, 2011).…”

“…Relatively simple extrapolation methods have been used to fill the gaps between sparse observations to provide globally representative estimates of DMS (Hulswar et al, 2022;Kettle et al, 1999;Lana et al, 2011). More complex algorithms have been generated at the basin or global scale using parameters such as chlorophyll, light, nutrients, surface temperature, and mixed layer depth (Anderson et al, 2001;Aranami & Tsunogai, 2004;Aumont et al, 2002;Chu et al, 2003;Galí et al, , 2018Halloran et al, 2010;Miles et al, 2009;Simó & Dachs, 2002;Vallina & Simó, 2007).…”

“…For example, to observe variations within 10 km when the research ship is travelling at 8 m s -1 requires measurements every 20 mins. Instruments that can observe variability at these high resolutions have been deployed in recent years and have contributed substantially to the global DMS database (Hulswar et al, 2022). A wealth of high frequency DMS data offers a new opportunity for a global analysis of the drivers of DMS variability at small scales.…”

Winter season Southern Ocean distributions of climate-relevant trace gases

“…The broader Southern Ocean (latitude range: 35 to 75 • S) is represented by 21 580 points for all seasons, but only 158 points (0.7 %) are from the austral winter. All three DMS climatologies draw heavily on this database (Hulswar et al, 2022;Kettle et al, 1999;Lana et al, 2011). This DMS data product and resulting climatologies, along with those for other trace gases (MEMENTO, MarinE MethanE and NiTrous Oxide; SOCAT, Surface Ocean CO 2 Atlas; HalOcAt, Halocarbons in the Ocean and Atmosphere; among others), are extremely important for model input and validation.…”