# Evaluating Uncertainties in Marine Biogeochemical Models: Benchmarking Aerosol Precursors
## 3 Results
The maximum wintertime value is about 400 m within the Nordic seas, and even greater around the Southern Ocean and Weddell Sea. Estimates of the mixed layer depth (MLD) in biogeochemical models use temperature or density gradient for the upper ocean. It can be concluded that CMIP5 models with underlying biogeochemistry give reasonable performance with respect to a benchmark global temporal mean of MLD; results are within \(\pm\)10 m of observational data. Both mixed and low-resolution MPI-ESM models have a global period mean of about 110 m. This is primarily ascribed to higher wind-driven turbulence in the North Atlantic and Southern Ocean, especially the Weddell Sea and Ross Sea. The results presented in this paper are limited to analyses of the upper ocean biogeochemistry as it relates to the production and flux of dimethylsulfide. Uncertainties in nutrients will transfer through connecting biogeochemical processes to aerosol precursor emission, since the production of marine biogenic volatile organic compounds is strongly  
Figure 1: Benchmarking results showing absolute score (S) and relative score (\(Z\)-score), computed between five Earth Surface Models (ESMs) and various observational datasets (described in Table 1). Chemical oceanographic variables (from chlorophyll to pH) are colored in light green, physical oceanographic variables (salinity to shortwave radiation) are colored in light cornflower blue. DMS fluxes are colored in light orange. coupled to the underlying ecosystem. As expected, model-data benchmarking identifies areas of increased bias at high latitudes as well as in the tropical Pacific. Nutrient concentrations in the high-nutrient, low-chlorophyll (HNLC) region of the eastern tropical Pacific are lower in CMIP5 models when compared with World Ocean Atlas (WOA) datasets. Concentrations of nitrate, an essential macronutrient, are biased low by about 10 \(\upmu\)mol L\({}^{-1}\) in the upwelling region (Figure 2). The reduced concentrations of nutrients observed in these models suggest either weak vertical advection (mixing of nutrient-rich water) or a faster rate of consumption in the region. The availability of iron in this region will also play a part in regulating phytoplankton growth. Appropriate metrics to evaluate all of these issues will be strongly considered in the upcoming version of IOMB. Even with nitrate concentrations under-predicted in the tropical Pacific, net primary production is over-predicted by at least 0.2 \(\upmu\)mol m\({}^{-2}\)s\({}^{-1}\) in HadGEM2-ES, and greater than 0.6 \(\upmu\)mol m\({}^{-2}\)s\({}^{-1}\) in MPI models. Our results suggest that higher rates of carbon fixation in a given model could be responsible for the depletion of nitrate. The positive excess in the rate of carbon fixation across upwelling regions of the tropical Pacific is also evident in the surface ocean DMS concentrations (Figure 2). The tropical Pacific is of special interest because the environmental condition supports the constant production and flux of DMS. In the available observational dataset, the mean concentration of about 4 nM of DMS is maintained in the tropical Pacific throughout the year. This continual source of sulfur to the marine boundary layer provides natural equatorial sulfate that can be transported horizontally and vertically with the converging trade winds. The resulting aerosol moves poleward, and even into the stratosphere ([PERSON], 2016). Results for DMS surface ocean concentrations show a positive bias of almost a factor of 2 in the CMIP5 models. There is thus a possibility in the tropical Pacific of over-predicting the contribution of sulfate aerosol to cloud formation. This would lead to over-predicting of the equatorial albedo and cooling beyond observations. Figure 2: Nitrate (Nit), net primary production (NPP), and dimethylsulfide (DMS) surface mean bias. Three ESMs with DMS concentrations were considered: HadGEM2-ES, MPI-ESM-MR, and MPI-ESM-LR.