Abstract. Motivated by the need to predict how the Arctic atmosphere will change in a warming world, this article summarizes recent advances made by the research consortium NETCARE (Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments) that contribute to our fundamental understanding of Arctic aerosol particles as they relate to climate forcing. The overall goal of NETCARE research has been to use an interdisciplinary approach encompassing extensive field observations and a range of chemical transport, earth system, and biogeochemical models. Several major findings and advances have emerged from NETCARE since its formation in 2013. (1) Unexpectedly high summertime dimethyl sulfide (DMS) levels were identified in ocean water (up to 75 nM) and the overlying atmosphere (up to 1 ppbv) in the Canadian Arctic Archipelago (CAA). Furthermore, melt ponds, which are widely prevalent, were identified as an important DMS source (with DMS concentrations of up to 6 nM and a potential contribution to atmospheric DMS of 20 % in the study area). (2) Evidence of widespread particle nucleation and growth in the marine boundary layer was found in the CAA in the summertime, with these events observed on 41 % of days in a 2016 cruise. As well, at Alert, Nunavut, particles that are newly formed and grown under conditions of minimal anthropogenic influence during the months of July and August are estimated to contribute 20 % to 80 % of the 30–50 nm particle number density. DMS-oxidation-driven nucleation is facilitated by the presence of atmospheric ammonia arising from seabird-colony emissions, and potentially also from coastal regions, tundra, and biomass burning. Via accumulation of secondary organic aerosol (SOA), a significant fraction of the new particles grow to sizes that are active in cloud droplet formation. Although the gaseous precursors to Arctic marine SOA remain poorly defined, the measured levels of common continental SOA precursors (isoprene and monoterpenes) were low, whereas elevated mixing ratios of oxygenated volatile organic compounds (OVOCs) were inferred to arise via processes involving the sea surface microlayer. (3) The variability in the vertical distribution of black carbon (BC) under both springtime Arctic haze and more pristine summertime aerosol conditions was observed. Measured particle size distributions and mixing states were used to constrain, for the first time, calculations of aerosol–climate interactions under Arctic conditions. Aircraft- and ground-based measurements were used to better establish the BC source regions that supply the Arctic via long-range transport mechanisms, with evidence for a dominant springtime contribution from eastern and southern Asia to the middle troposphere, and a major contribution from northern Asia to the surface. (4) Measurements of ice nucleating particles (INPs) in the Arctic indicate that a major source of these particles is mineral dust, likely derived from local sources in the summer and long-range transport in the spring. In addition, INPs are abundant in the sea surface microlayer in the Arctic, and possibly play a role in ice nucleation in the atmosphere when mineral dust concentrations are low. (5) Amongst multiple aerosol components, BC was observed to have the smallest effective deposition velocities to high Arctic snow (0.03 cm s−1).

A coupled 1-D sea ice-ocean physical-biogeochemical model was developed to investigate the processes governing ice algal and phytoplankton blooms in the seasonally ice-covered Arctic Ocean. The 1-D column is representative of one grid cell in 3-D model applications and provides a tool for parameterization development. The model was applied to Resolute Passage in the Canadian Arctic Archipelago and assessed with observations from a field campaign during spring of 2010. The factors considered to limit the growth of simulated ice algae and phytoplankton were light, nutrients, and in the case of ice algae, ice melt. In addition to the standard simulation, several model experiments were conducted to determine the sensitivity of the simulated ice algal bloom to parameterizations of light, mortality, and pre-bloom biomass. Model results indicated that: (1) ice algae limit subsequent pelagic productivity in the upper 10 m by depleting nutrients to limiting levels; (2) light availability and pre-bloom biomass determine the onset timing of the ice algal bloom; (3) the maximum biomass is relatively insensitive to the pre-bloom biomass, but is limited by nutrient availability; (4) a combination of linear and quadratic parameterizations of mortality rate is required to adequately simulate the evolution of the ice algal bloom; and (5) a sinking rate for large detritus greater than a threshold of ∼10 m d -1 effectively strips the surface waters of the limiting nutrient (silicate) after the ice algal bloom, supporting the development of a deep chlorophyll maximum.

Abstract. Process-based numerical models are a useful tool for studying marine ecosystems and associated biogeochemical processes in ice-covered regions where observations are scarce. To this end, CSIB v1 (Canadian Sea-ice Biogeochemistry version 1), a new sea-ice biogeochemical model, has been developed and embedded into the Nucleus for European Modelling of the Ocean (NEMO) modelling system. This model consists of a three-compartment (ice algae, nitrate, and ammonium) sea-ice ecosystem and a two-compartment (dimethylsulfoniopropionate and dimethylsulfide) sea-ice sulfur cycle which are coupled to pelagic ecosystem and sulfur-cycle models at the sea-ice–ocean interface. In addition to biological and chemical sources and sinks, the model simulates the horizontal transport of biogeochemical state variables within sea ice through a one-way coupling to a dynamic-thermodynamic sea-ice model (LIM2; the Louvain-la-Neuve Sea Ice Model version 2). The model results for 1979 (after a decadal spin-up) are presented and compared to observations and previous model studies for a brief discussion on the model performance. Furthermore, this paper provides discussion on technical aspects of implementing the sea-ice biogeochemistry and assesses the model sensitivity to (1) the temporal resolution of the snowfall forcing data, (2) the representation of light penetration through snow, (3) the horizontal transport of sea-ice biogeochemical state variables, and (4) light attenuation by ice algae. The sea-ice biogeochemical model has been developed within the generic framework of NEMO to facilitate its use within different configurations and domains, and can be adapted for use with other NEMO-based sub-models such as LIM3 (the Louvain-la-Neuve Sea Ice Model version 3) and PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies).

Field observations suggest that oceanic emissions of dimethylsulfide (DMS) may play a dominant role in the production of Arctic aerosols and clouds and therefore modulate the surface irradiance, during spring and summer. DMS is produced not only in the water column but also in various sea ice habitats. The ongoing recession of Arctic sea ice is expected to enhance DMS emissions, but the magnitude of this increase is highly uncertain. Here we investigate the spatiotemporal variability in bottom ice and sea surface DMS concentrations and fluxes using a regional sea ice-ocean physical-biogeochemical model. Model results indicate that the observed accelerated decline of Arctic sea ice extent since the beginning of the 21st century is associated with upward trends in May-August pan-Arctic-averaged sea surface DMS concentration and sea-to-air DMS flux. On the other hand, strong interannual variability and statistically insignificant trends are found for bottom ice DMS concentration and ice-to-sea DMS flux, owing to the counteracting effects of the shrinking horizontal extent and the vertical thinning of sea ice on ice algal production. The pan-Arctic DMS climatology products based on model simulation and satellite algorithms provide dynamically based spatial details that are absent in the in situ measurement-based climatology due to limited spatiotemporal data coverage and inevitable extrapolation bias. Lastly, model results indicate that the bottom ice DMS and its precursor dimethylsulfoniopropionate production can be the only local source of oceanic DMS emissions into the atmosphere during May prior to pelagic blooms, suggesting that it may be a key component of the biological control on Arctic climate at that time.