Dimethyl sulfide (DMS) is a biogenic organosulfur compound which contributes strongly to marine aerosol mass and the determination of cloud condensation nuclei over the remote oceans. Since uncertainties in DMS flux to the atmosphere lead to large variations in climate forcing, the global DMS distribution has been the subject of increasingly complex dynamic simulations. DMS concentrations are directly controlled by marine ecosystems. Phaeocystis is a major DMS producer but is often omitted from global reduced sulfur mechanisms. Here we incorporate this phytoplankton group into the marine ecosystem-biogeochemical module of the Community Earth System Model. To examine its role in the ocean sulfur cycle, an earlier DMS model has been enhanced to include new knowledge gained over the last few years. Results from the baseline run show that simulated Phaeocystis biomass generally agrees with observations, with high concentrations near the Antarctic continent and between 50°and 60°north. Given the new explicit Phaeocystis representation, the DMS distribution shows significant improvements, especially regarding the amplitude and location of high-latitude peaks. The simulated global mean surface DMS value is 2.26 nM, comparable to an estimate of 2.34 nM from the latest climatology extrapolated based on observations. The total oceanic DMS source to the atmosphere is 20.4 Tg S/yr, on the low side of previous estimates. Comparisons with and without Phaeocystis show that the group dominates DMS distributions in temperate and cold waters, contributing 13% of the global flux. The proportion may increase as sea ice declines and should be considered in climate projections.

Organic macromolecules constitute a high percentage of remote sea spray. They enter the atmosphere through adsorption onto bubbles followed by bursting at the ocean surface, and go on to influence the chemistry of the fine mode aerosol. We present a global estimate of mixed-layer macromolecular distributions, driven by offline marine systems model output. The approach permits estimation of oceanic concentrations and bubble film surface coverages for several classes of organic compound. Mixed layer levels are computed from the output of a global ocean ecodynamics model by relating the macromolecules to standard biogeochemical tracers. Steady state is assumed for labile forms, and for longer-lived components we rely on ratios to existing transported variables. Adsorption is then represented through conventional Langmuir isotherms, with equilibria deduced from laboratory analogs. Open water concentrations locally exceed one micromolar carbon for the total of proteins, polysaccharides and refractory heteropolycondensates. The shorter-lived lipids remain confined to regions of strong biological activity. Results are evaluated against available measurements for all compound types, and agreement is generally well within an order of magnitude. Global distributions are further estimated for both fractional coverage of bubble films at the air-water interface and the two-dimensional concentration excess. Overall, we show that macromolecular mapping provides a novel tool for the comprehension of oceanic surfactant patterns. These results may prove useful in planning

Abstract. Iron is a key nutrient for phytoplankton growth in the surface ocean. At high latitudes, the iron cycle is closely related to the dynamics of sea ice. In recent decades, Arctic sea ice cover has been declining rapidly and Antarctic sea ice has exhibited large regional trends. A significant reduction of sea ice in both hemispheres is projected in future climate scenarios. In order to adequately study the effect of sea ice on the polar iron cycle, sea ice bearing iron was incorporated in the Community Earth System Model (CESM). Sea ice acts as a reservoir for iron during winter and releases the trace metal to the surface ocean in spring and summer. Simulated iron concentrations in sea ice generally agree with observations in regions where iron concentrations are relatively low. The maximum iron concentrations simulated in Arctic and Antarctic sea ice are much lower than observed, which is likely due to underestimation of iron inputs to sea ice or missing mechanisms. The largest iron source to sea ice is suspended sediments, contributing fluxes of iron of 2.2 × 10 8 mol Fe month −1 in the Arctic and 4

This paper documents the biogeochemistry configuration of the Energy Exascale Earth System Model (E3SM), E3SMv1.1‐BGC. The model simulates historical carbon cycle dynamics, including carbon losses predicted in response to land use and land cover change, and the responses of the carbon cycle to changes in climate. In addition, we introduce several innovations in the treatment of soil nutrient limitation mechanisms, including explicit dependence on phosphorus availability. The suite of simulations described here includes E3SM contributions to the Coupled Climate‐Carbon Cycle Model Intercomparison Project and other projects, as well as simulations to explore the impacts of structural uncertainty in representations of nitrogen and phosphorus limitation. We describe the model spin‐up and evaluation procedures, provide an overview of results from the simulation campaign, and highlight key features of the simulations. Cumulative warming over the twentieth century is similar to observations, with a midcentury cold bias offset by stronger warming in recent decades. Ocean biomass production and carbon uptake are underpredicted, likely due to biases in ocean transport leading to widespread anoxia and undersupply of nutrients to surface waters. The inclusion of nutrient limitations in the land biogeochemistry results in weaker carbon fertilization and carbon‐climate feedbacks than exhibited by other Earth System Models that exclude those limitations. Finally, we compare with an alternative representation of terrestrial biogeochemistry, which differs in structure and in initialization of soil phosphorus. While both configurations agree well with observational benchmarks, they differ significantly in their distribution of carbon among different pools and in the strength of nutrient limitations.

[1] Phaeocystis antarctica is an important phytoplankton species in the Southern Ocean. We incorporated P. antarctica into the biogeochemical elemental cycling ocean model to study Southern Ocean ecosystem dynamics and biogeochemistry. The optimum values of ecological parameters for Phaeocystis were sought through synthesizing laboratory and field observations, and the model output was evaluated with observed chlorophyll a, carbon biomass, and nutrient distributions. Several factors have been proposed to control Southern Ocean ecosystem structure, including light adaptation, iron uptake capability, and loss processes. Optimum simulation results were obtained when P. antarctica had a relatively high a (P-I curve initial slope) value and a higher half-saturation constant for iron uptake than other phytoplankton. Simulation results suggested that P. antarctica had a competitive advantage under low irradiance levels, especially in the Ross Sea and Weddell Sea. However, the distributions of P. antarctica and diatoms were also strongly influenced by iron availability. Although grazing rates had an influence on total biomass, our simulations did not show a strong influence of grazing pressure in the competition between P. antarctica and diatoms. However, limited observations and the relative simplicity of zooplankton in our model suggest further research is needed. Overall, P. antarctica contributed ∼13% of annual primary production and ∼19% of sinking carbon export in the Southern Ocean (>40°S) in our best case simulation. At higher latitudes (>60°S) P. antarctica accounts for ∼23% of annual primary production and ∼30% of sinking carbon export.