# Evaluating Uncertainties in Marine Biogeochemical Models: Benchmarking Aerosol Precursors
## 1 Introduction
### Background
The collective marine organics SOA and POA are additionally important in influencing particle composition, hygroscopicity, and size distribution, and with them come the usual microphysical implications [2; 11]. Over roughly the last decade, there have been major advances in the quantification of marine aerosol sources, and this has been in part because logistical barriers are being overcome [15]. As aerosol uncertainties are steadily reduced in coming years, there will be parallel needs for both increased long-term field measurements and the assessment of simulations attempting to reproduce them. The natural marine aerosol dominated by chloride and sulfate has noticeable direct and indirect effects on the climate. Aerosol components such as sea salt, soil dust, organic macromolecules, and natural sulfate are often hygroscopic and act as cloud condensation nuclei, thus modulating cloud reflectivity [27; 28; 29]. However, emissions of dimethylsulfide and volcanic sulfate lead to the greatest impact on global radiative forcing, both as a consequence of albedo effects [30]. The global cloud albedo effect that is attributable to sea salt is reported to be about \(-0.04\) Wm\({}^{-2}\), while DMS-derived sulfate and volcanic sulfate contribute \(-0.76\) Wm\({}^{-2}\)and \(-0.61\) Wm\({}^{-2}\), respectively [30]. Despite this potential for net cooling, the situation is confounded by numerous nonlinearities. Cloud albedo does not respond in a simple manner to the source strength of natural precursors [31], and this is partly because of the superposition of anthropogenic emissions. There has been general difficulty representing baseline emissions in the absence of industrial fingerprints [18; 20]. To reduce uncertainties implied by the inclusion of natural particles in climate models, we need to access and exploit a variety of the available observational datasets. These will include surface ocean concentration measurements [13; 14], the direct quantification of fluxes [3; 32], the analysis of detailed organic chemistry [2; 5; 6], and studies conducted from the atmosphere and space [33; 34]. The community must determine the level of realism that can be attached to the current suite of climate models. It must eventually be possible to faithfully simulate not only the recent past, but also to extend into the future in the predictive sense. The aerosol knowledge base must improve in order to constrain the next generation of model development. There is currently a strong interest in the design and implementation of new metrics to evaluate and quantify biogeochemical uncertainties, and aerosol cycles are foremost among them. As a general rule, the specific biological processes underlying biogeochemical transfer to and from the global ocean are insufficiently represented in most Earth System Models (ESMs) [6; 35; 36]. The best known examples involve the trace greenhouse gas carbon dioxide, which currently demands almost an entire generation of validation effort, which has led to the community beginning to display confidence in its computed and globally distributed fluxes [17]. Similarly however, surface ocean fluxes of marine aerosol precursors such as DMS are crucial to the planetary climate state. Uncertainty with regard to the effects of aerosol chemical composition on cloud albedo is also applicable to the SOA and POA, through their influence on sea spray and hygroscopicity [2; 29]. Moreover, the organic chemistry also affects nutrient cycling [8]. In the present work, we adopt DMS as the springboard to demonstrate means of automating the global aerosol validation effort, with discussions of the other issues included as well.