Title

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

Document Type

Article

Publication details

Kettle, AJ, Andreae, MO, Amouroux, D, Andreae, TW, Bates, TS, Berresheim, H, Bingemer, H, Boniforti, R, Curran, MAJ, DiTullio, GR, Helas, G, Jones, GB, Keller, MD, Kiene, RP, Leck, C, Levasseur, M, Malin, G, Maspero, M, Matrai, P, McTaggart, AR, Mihalopoulos, N, Nguyen, BC, Novo, A, Putaud, JP, Rapsomanikis, S, Roberts, G, Schebeske, G, Sharma, S, Simó, R, Staubes, R, Turner, S & Uher, G 1999, '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', Global Biogeochemical Cycles, vol. 13, no. 2, pp. 399-444.

Published version available from:

http://dx.doi.org/10.1029/1999GB900004

Peer Reviewed

Peer-Reviewed

Abstract

A database of 15,617 point measurements of dimethylsulfide (DMS) in surface waters along with lesser amounts of data for aqueous and particulate dimethylsulfoniopropionate concentration, chlorophyll concentration, sea surface salinity and temperature, and wind speed has been assembled. The database was processed to create a series of climatological annual and monthly l°×l° latitude-longitude squares of data. The results were compared to published fields of geophysical and biological parameters. No significant correlation was found between DMS and these parameters, and no simple algorithm could be found to create monthly fields of sea surface DMS concentration based on these parameters. Instead, an annual map of sea surface DMS was produced using an algorithm similar to that employed by Conkright et al. [1994]. In this approach, a first-guess field of DMS sea surface concentration measurements is created and then a correction to this field is generated based on actual measurements. Monthly sea surface grids of DMS were obtained using a similar scheme, but the sparsity of DMS measurements made the method difficult to implement. A scheme was used which projected actual data into months of the year where no data were otherwise present.