Global ocean emission of dimethylsulfide predicted from biogeophysical data

TLDR

DMS emissions from the ocean are a key driver of cloud albedo, yet large‑scale oceanic DMS has been difficult to capture with remote sensing, synoptic variables, or mechanistic models. The study aims to enhance synoptic and predictive capabilities for the coupled ocean‑atmosphere DMS system. A simple empirical relationship linking chlorophyll‑a and mixed‑layer depth to global monthly DMS concentrations was derived, enabling synoptic estimates of the ocean‑to‑atmosphere sulfur flux (23–35 Tg S yr⁻¹) and indicating a biogenic DMS/solar‑radiation negative feedback that can be quantified under warming.

Abstract

Among the biosphere‐atmosphere interactions that influence climate, the emission of dimethylsulfide (DMS) from the ocean plays a prominent role for its high potential in cloud albedo regulation. In order to advance in our understanding and quantification of this coupled ocean‐atmosphere system, both synoptic and predictive capabilities must be largely improved. Hitherto, large‐scale oceanic DMS has eluded being captured from remote sensing, correlated with synoptic variables, or simulated by mechanistic modeling. We have found a simple empirical relationship that permits global‐ocean monthly distributions of DMS concentration to be computed from a combination of remotely sensed biospheric data (chlorophyll a ) and climatological geophysical data (mixed layer depth). This relationship allows for the desired synopticity and predictability in the ocean‐to‐atmosphere sulfur flux, which we have globally quantified as 23–35 Tg S yr −1 . Also, our algorithm stands in support of a biogenic‐DMS/solar‐radiation negative feedback and opens the door toward quantifying its strength and its response to global warming.