The use of algorithms to predict surface seawater dimethyl sulphide concentrations in the SE Pacific, a region of steep gradients in primary productivity, biomass and mixed layer depth

Hind, A.J., Rauschenberg, C.D., Johnson, J.E., Yang, M. and Matrai, P.A. (2011) The use of algorithms to predict surface seawater dimethyl sulphide concentrations in the SE Pacific, a region of steep gradients in primary productivity, biomass and mixed layer depth. Biogeosciences, 8. pp. 1-16. ISSN 1726-4189

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Abstract

Dimethyl sulphide (DMS) is an important precursor of cloud condensation nuclei (CCN), particularly in the remote marine atmosphere. The SE Pacific is consistently covered with a persistent stratocumulus layer that increases the albedo over this large area. It is not certain whether the source of CCN to these clouds is natural and oceanic or anthropogenic and terrestrial. This unknown currently limits our ability to reliably model either the cloud behaviour or the oceanic heat budget of the region. In order to better constrain the marine source of CCN, it is necessary to have an improved understanding of the sea-air flux of DMS. Of the factors that govern the magnitude of this flux, the greatest unknown is the surface seawater DMS concentration. In the study area, there is a paucity of such data, although previous measurements suggest that the concentration can be substantially variable. In order to overcome such data scarcity, a number of climatologies and algorithms have been devised in the last decade to predict seawater DMS. Here we test some of these in the SE Pacific by comparing predictions with measurements of surface seawater made during the Vamos Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) in October and November of 2008. We conclude that none of the existing algorithms reproduce local variability in seawater DMS in this region very well. From these findings, we recommend the best algorithm choice for the SE Pacific and suggest lines of investigation for future work.

Item Type: Article
Additional Information: © Author(s) 2011. This work is distributed under the Creative Commons Attribution 3.0 License.
Faculty \ School: Faculty of Science
Faculty of Science > School of Environmental Sciences
Depositing User: Pure Connector
Date Deposited: 27 Jun 2016 14:00
Last Modified: 25 Jun 2020 00:02
URI: https://ueaeprints.uea.ac.uk/id/eprint/59605
DOI: 10.5194/bg-8-1-2011

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