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

摘要

Dimethyl sulphide (DMS) is an important precur-sor of cloud condensation nuclei (CCN), particularly in theremote marine atmosphere. The SE Pacific is consistentlycovered with a persistent stratocumulus layer that increasesthe albedo over this large area. It is not certain whether thesource of CCN to these clouds is natural and oceanic or an-thropogenic and terrestrial. This unknown currently limitsour ability to reliably model either the cloud behaviour orthe oceanic heat budget of the region. In order to better con-strain the marine source of CCN, it is necessary to have animproved understanding of the sea-air flux of DMS. Of thefactors that govern the magnitude of this flux, the greatestunknown is the surface seawater DMS concentration. In thestudy area, there is a paucity of such data, although previ-ous measurements suggest that the concentration can be sub-stantially variable. In order to overcome such data scarcity, anumber of climatologies and algorithms have been devised inthe last decade to predict seawater DMS. Here we test someof these in the SE Pacific by comparing predictions withmeasurements of surface seawater made during the VamosOcean-Cloud-Atmosphere-Land Study Regional Experiment(VOCALS-REx) in October and November of 2008. We con-clude that none of the existing algorithms reproduce localvariability in seawater DMS in this region very well. Fromthese findings, we recommend the best algorithm choice forthe SE Pacific and suggest lines of investigation for futurework.