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

摘要

Dimethyl sulphide (DMS) is an important precursor of cloud condensationnuclei (CCN), particularly in the remote marine atmosphere. The SE Pacificis consistently covered with a persistent stratocumulus layer that increasesthe albedo over this large area. It is not certain whether the source of CCNto these clouds is natural and oceanic or anthropogenic and terrestrial.This unknown currently limits our ability to reliably model either the cloudbehaviour or the oceanic heat budget of the region. In order to betterconstrain the marine source of CCN, it is necessary to have an improvedunderstanding of the sea-air flux of DMS. Of the factors that govern themagnitude of this flux, the greatest unknown is the surface seawater DMSconcentration. In the study area, there is a paucity of such data, althoughprevious measurements suggest that the concentration can be substantiallyvariable. In order to overcome such data scarcity, a number of climatologiesand 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 withmeasurements of surface seawater made during the VamosOcean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) inOctober and November of 2008. We conclude that none of the existingalgorithms reproduce local variability in seawater DMS in this region verywell. From these findings, we recommend the best algorithm choice for the SEPacific and suggest lines of investigation for future work.