FN Archimer Export Format
PT J
TI Third Revision of the Global Surface Seawater Dimethyl Sulfide Climatology (DMS-Rev3)
BT 
AF Hulswar, Shrivardhan
   Simo, Rafel
   Galí, Martí
   Bell, Thomas
   Lana, Arancha
   Inamdar, Swaleha
   Halloran, Paul R.
   Manville, George
   Mahajan, Anoop Sharad
AS 1:1;2:2;3:2,3;4:4;5:5;6:1,6;7:7;8:7;9:1;
FF 1:;2:;3:;4:;5:;6:;7:;8:;9:;
C1 Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India
   Institut de Ciències del Mar (CSIC), Barcelona, Catalonia, Spain
   Barcelona Supercomputing Center (BSC), Spain
   Plymouth Marine Laboratory (PML), Plymouth, UK
   Institut Mediterrani d’Estudis Avançats (IMEDEA, UIB-CSIC), Esporles, Balearic Islands, Spain
   Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India
   College of Life and Environmental Sciences, University of Exeter, Exeter, UK
C2 INDIAN INSTTROP METEO, INDIA
   ICM CSIC, SPAIN
   BSC, SPAIN
   PML, UK
   IMEDEA, SPAIN
   UNIV BANARAS HINDU, INDIA
   UNIV EXETER, UK
IN DOAJ
IF 11.4
TC 28
UR https://archimer.ifremer.fr/doc/00755/86741/92211.pdf
   https://archimer.ifremer.fr/doc/00755/86741/95273.pdf
   https://archimer.ifremer.fr/doc/00755/86741/95274.pdf
   https://archimer.ifremer.fr/doc/00755/86741/95275.pdf
LA English
DT Article
CR OISO - OCÉAN INDIEN SERVICE D'OBSERVATION
AB 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 872,427 observations leading to a ~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 results 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. And finally, 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 ~1.87 nM (2.35 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 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.   
PY 2022
PD JUN
SO Earth System Science Data
SN 1866-3508
PU Copernicus GmbH
VL 14
IS 7
UT 000820743700001
BP 2963
EP 2987
DI 10.5194/essd-2021-236
ID 86741
ER

EF