Can we trust empirical marine DMS parameterisations within projections of future climate?

P R Halloran,I J Totterdell,T G Bell

doi:10.5194/bg-7-1645-2010

Abstract

Abstract. Dimethylsulphide (DMS) is a globally important aerosol precurser. In 1987 Charlson and others proposed that an increase in DMS production by certain phytoplankton species in response to a warming climate could stimulate increased aerosol formation, increasing the lower-atmosphere's albedo, and promoting cooling. Despite two decades of research, the global significance of this negative climate feedback remains contentious. It is therefore imperative that schemes are developed and tested, which allow for the realistic incorporation of phytoplankton DMS production into Earth System models. Using these models we can investigate the DMS-climate feedback and reduce uncertainty surrounding projections of future climate. Here we examine two empirical DMS parameterisations within the context of an Earth System model and find them to perform marginally better than the standard DMS climatology at predicting observations from an independent global dataset. We then question whether parameterisations based on our present understanding of DMS production by phytoplankton, and simple enough to incorporate into global climate models, can be shown to enhance the future predictive capacity of those models. This is an important question to ask now, as results from increasingly complex Earth System models lead us into the 5th assessment of climate science by the Intergovernmental Panel on Climate Change. Comparing observed and predicted inter-annual variability, we suggest that future climate projections may underestimate the magnitude of surface ocean DMS change. Unfortunately this conclusion relies on a relatively small dataset, in which observed inter-annual variability may be exaggerated by biases in sample collection. We therefore encourage the observational community to make repeat measurements of sea-surface DMS concentrations an important focus, and highlight areas of apparent high inter-annual variability where sampling might be carried out. Finally, we assess future projections from two similarly valid empirical DMS schemes, and demonstrate contrasting results. We therefore conclude that the use of empirical DMS parameterisations within simulations of future climate should be undertaken only with careful appreciation of the caveats discussed.

Highlights

Phytoplankton DMS production remains a hot topic in climate science despite the results of a number of recent studies suggesting that its impact within a changing climate is likely to be small (e.g., Gunson et al, 2007; Bopp et al, 2003; Woodhouse et al, 2010)
A recent expansion in the size of the global sea surface DMS database, beyond that presented by Kettle et al (1999), allows us to assess the ability of empirical DMS parameterisations, incorporated into Earth System models, to predict observed seawater [DMS] recorded in a dataset independent from that used to create the parameterisations
We examine two empirical DMS parameterisations, one proposed by Anderson et al (2001), and the second by Simo and Dachs (2002), (modified with Aranami and Tsunogai (2004), and both adapted for use with our Earth System model)

Summary

Introduction

Phytoplankton DMS production remains a hot topic in climate science despite the results of a number of recent studies suggesting that its impact within a changing climate is likely to be small (e.g., Gunson et al, 2007; Bopp et al, 2003; Woodhouse et al, 2010). The reason why the hypothesis that phytoplankton DMS production may act as a negative feedback on climate (Charlson et al, 1987) remains in active debate two decades after its proposition, is that we still lack the evidence, observational, or in the form of robust models, necessary to confirm or reject its existence as an important component of the climate system. While this hypothesis remains in limbo, significant questions will surround our ability to interpret Earth System modelling results in the context of climate change. We make a critical assessment of the ability of the two models to match observations and global features emerging from observations, go on to explore whether or not we can apply these models with confidence when making predictions about the climate of the coming century

DMS Parameterisations

Implementation

Predictive capacity in the present ocean

Conclusions