# Evaluating Uncertainties in Marine Biogeochemical Models: Benchmarking Aerosol Precursors
## 5 Conclusions  
Marine biogeochemistry remains an important driving force for climate carbon-cycle feedback, as well as the production of aerosol particles in the MBL [5; 6; 53]. There are numerous processes that link surface ocean biology with the composition of the lower atmosphere, such as the sea-air transfer of organic matter, ultimately serving as cloud or ice condensation nuclei and the release of organic macromolecules to become surfactants in the microlayer. The later influence salt spray production and gas exchange rates [5; 80; 90]. Representation of these pathways in underlying biogeochemical routines within ESMs dictates the degree of uncertainty in the chemical composition, concentration, and oceanic emission rates of BVOCs, and the aerosol in general. To identify and reduce the discrepancies, we have developed an open source package that allows for objective data-model evaluation. We conclude that regional sensitivity in polar and tropical marine biogeochemical processes may constitute a major component of the uncertainty in MBL cloud representations. The quantification of errors in MBL aerosol chemistry represents an extremely challenging task for the systems modeling community. This is true in large part because the required biogeochemical processes are currently less than well-represented in most contemporary ESMs. Some of the relevant physico-chemical mechanisms play out on a microscopic scale, so that subgrid parameterizations tend to be problematic on the global mesh. Regional models configured at finer resolution have done a better job of capturing the native dynamics that influence the production and transport of marine aerosols. For the immediate future, we envision rapid progress in the development of subgrid scale parameterizations for distributing and emitting aerosol precursors from the sea. The improvements will be data-driven, as high-quality observation sets are encoded appropriately in order to validate simulation outputs. The International Ocean Model Benchmarking or IOMB activity offers a novel, fully adaptable platform designed specifically for the necessary validation exercises. A wealth of marine physical and chemical processes can be examined independently, or in relation to atmospheric aerosol microphysical coupling. Observational datasets available for benchmarking marine biogeochemistry are limited for logistical reasons that should be obvious: ship cruises are expensive and time-consuming. Similar arguments apply to aircraft campaigns. Remotely sensed data can be extremely convenient to use, but the suite of available variables is severely limited by optical and radiation transfer considerations. Although measurements and related compilations of ocean data have become more numerous and sophisticated in recent years, there is still much work to be done in the area of data collection and organization. Validation will constitute a centerpiece of the community effort as complex processes accumulate in the system codes. In the high-latitude case, a lack of data is even more conspicuous. Adverse weather conditions complicate sampling efforts, leading to restrictions on field campaigns. Profiling floats constitute a marvelous new tool kit, but they are expensive to initiate and operate, and even robotics bring with them certain geographical and temporal limitations. We anticipate that the community will push for improvements to remote sensing algorithms in order to further enhance their reliability--such as for example under cloud cover--and they may be extended to subtle variations on the standard theme of chlorophyll (pigment deconvolutions offering real biological resolution). Novel inversion methods may open up key chemical constituents to global mapping [33]. At the same time, more ESMs involved in the ongoing CMIP exercise should be encouraged to output marine aerosol precursors such as DMS and related organics. Even as the various databases expand, benchmarking and analyses can only occur if the proper variables are simulated.