Abstract Polar oceans are critical components of the oceanic uptake of atmospheric carbon dioxide. Estimates of this uptake across the air‐sea interface require parameterizations of gas transfer velocity that account for variable sea ice concentrations. Previous studies, using eddy covariance measurements of gas exchange, have concluded that linear scaling of carbon dioxide gas transfer with sea ice concentration is appropriate. The influence of sea ice concentration data resolution and associated uncertainties in these analyses has not been fully examined. Here we re‐assess published in situ air‐sea gas exchange data from the Arctic and Southern Oceans using a selection of sea ice concentration data sets. In the Southern Ocean, the linear scaling assumption holds irrespective of spatial resolution. In the Arctic Ocean, deviation from the linear case occurs at ice concentrations as low as 50%. Greater deviations become apparent in both polar oceans when sea ice concentration data uncertainties are considered. In the Southern Ocean, results using satellite data sets remain consistent with linear scaling, while ship‐based observations indicate greater suppression of uptake within the marginal ice zone. The Arctic response, after including uncertainties, indicates that gas exchange could be suppressed in regions with ice concentrations of 50% or higher. The contrast between the Arctic and Southern Ocean data sets potentially reflects differences in sea ice variability and environmental conditions during the observation periods, with the Arctic data capturing a transitional regime. Linear scaling may therefore serve as a first‐order approximation, but intermediate to high ice concentrations, particularly in the Arctic, require further investigation.

We present spatial and temporal measurements of surface water nitrous oxide (N2O) and methane (CH4) concentrations around Vancouver Island, BC. Using an automated, high-frequency measurement system, we conducted a spatial survey along the island's east and west coasts, and obtained a one-week time series from Barkley Sound on the west coast. These measurements allowed us to assess the influence of wind-driven circulation and tidal forcing on surface water hydrography and N2O and CH4 distributions. Across the spatial survey, surface water N2O ranged from 69% to 133% saturation, while CH4 ranged from 83% to 936% saturation. Elevated concentrations of both gases were associated with regions of intense tidal mixing in the Strait of Juan de Fuca and Johnstone Strait. In contrast, waters along the west coast of Vancouver Island exhibited greater mixed layer stratification, limiting vertical inputs of N2O and CH4 to the mixed layer. Elevated surface water concentrations in this region are more likely attributable to horizontal transport via the Vancouver Island Coastal Current. High-frequency measurements in Barkley Sound demonstrated significant temporal variability over a one-week period, with N2O saturation ranging from 76% to 177%, and CH4 saturation ranging from 163% to 556%. This variability was associated with tidal forcing and diel changes in surface winds, which drove lateral transport of different source water masses with distinct gas signatures. Our work highlights the utility of high frequency measurements to capture variability in N2O and CH4 concentrations in a dynamic coastal region, and provides insights into the interacting physical processes driving this variability.

Turbulence-driven nutrient supply has the potential to shape bottom sea ice microbial communities, affecting the balance of O2 uptake and release which defines the net community production (NCP) of the ice. This study contrasts sea ice NCP at two sites with comparatively high and low under-ice turbulent conditions. These locations were sampled over a 4-week spring bloom period in the Dease Strait region of the Kitikmeot Sea near the community of Cambridge Bay and the Canadian High Arctic Research Station (CHARS). We found that strong under-ice tidal currents promoted nutrient replenishment into the bottom ice, often supporting increased sea ice algal growth and a net autotrophic (i.e., net release of O2) signal of NCP throughout the study period. However, the stronger currents also accelerated bottom-ice melt and led to periodic reductions in ice algal chlorophyll a and times of net heterotrophy (net uptake of O2). In contrast, the location of lower turbulence and more stable currents presented more limited chlorophyll a accumulation and a persistent heterotrophic signal of NCP, potentially driven by a greater proportion of heterotrophic bacterial activity within the ice. These observations of contrasting NCP demonstrate the spatio-temporal complexity of bottom-ice algal blooms in the Arctic and challenge the use of a singular autotrophic bloom phenology to describe their seasonal growth. Rather, we show that the phenology of bottom-ice algal bloom development and the balance between autotrophic and heterotrophic activity vary with the sub-ice turbulent regime.

Accurately quantifying carbon sinks and sources in coastal regions is essential for global carbon budgeting, but it can be a challenging task. This is especially true for rapidly changing sub-Arctic and Arctic seas where baseline observations of seawater CO2 partial pressure (pCO2) are limited. Hudson Bay, Canada, is a prime example of an area with sparse data geographically and temporally. To bridge this gap, we utilized a novel approach by integrating predictor variables from satellite imagery and reanalysis data with advanced machine learning algorithms to provide more precise regional estimates of pCO2. In addition, we examined the ocean's carbon uptake and spatiotemporal fluctuations over different periods by incorporating wind speed and atmospheric CO2 data. Our study not only reveals insights into the dynamics of Hudson Bay CO2 sources and sinks but also demonstrates the potential of machine learning in extrapolating ship observations over space and time.

The Canadian Arctic is warming four times faster than the global average, yet the impact of this perturbation on the marine carbon cycle remains unknown. Dissolved inorganic carbon (DIC) stable isotope (δ 13 C) and radiocarbon (Δ 14 C) values are powerful tools for tracing water mass transport, residence times and carbon cycling. While the hydrography of the Canadian Arctic Archipelago (CAA) is well documented, few DIC δ 13 C and Δ 14 C values exist for the region. Here, we present new DIC δ 13 C and Δ 14 C depth profiles from 19 stations across the CAA sampled in 2021 and place them into the context of five recently published Baffin Bay values. CAA DIC δ 13 C and Δ 14 C values ranged from −0.68‰ to +1.86‰, and −90.7 to +49.5‰, respectively. Several negative DIC Δ 14 C values (−44.7‰ and −51.9‰) were observed near the Mackenzie River, indicating riverine permafrost carbon is actively incorporated into the nearshore DIC pool. “Bomb” DIC Δ 14 C values in the Kitikmeot Sea were attributed to enhanced tidal mixing and heterotrophy together with high regional water mass residence times. A comparison of historical DIC Δ 14 C depth profiles from 2009 to 2021 reveals significant dilution of “bomb” 14 C and minor contributions (2.1%–4.4%) of fossil anthropogenic CO 2 within Pacific Summer Water (PSW), Pacific Winter Water (PWW) and Atlantic Fram Strait Water (ATL FS ) in the Beaufort Sea. Finally, the contrast between deep Beaufort Sea and Baffin Bay DIC δ 13 C and Δ 14 C values reveal differences in residence time and carbon sources in the two regions.

Vessel operators in the Canadian Arctic rely on accurate weather, water, ice, and climate (WWIC) information to make safe navigational decisions, particularly where sea ice is present. Despite the necessity of accurate WWIC information, it is currently unknown what services are being accessed by users on vessels in the Canadian Arctic, and to what extent user needs are being met by available WWIC services. User perspectives are crucial for developing meaningful WWIC services, yet there remains a gap between what service providers believe to be useful information and what users need and use for their decision-making. To address this gap, a mixed-methods online survey targeted individuals who use WWIC information while navigating in the Canadian Arctic onboard marine vessels of various sizes and types (e.g., general cargo vessels, pleasure craft, cruise ships). The results show that the needs of most respondents (61%) were met "frequently" by current WWIC services, but 63% said that their voyages would benefit from additional information and better services. Sea ice concentration was the most important WWIC factor identified to support safe navigation, followed by sea ice age/thickness, wind speed, wind direction, and then sea ice drift. The southern route of the Northwest Passage and the Arctic Ocean north of Ellesmere Island were consistently identified as areas where information was regularly inaccurate and where improvements are needed. Some of the recommended improvements for WWIC service delivery included the need for more frequent information updates, improving internet connectivity speed and satellite coverage, and more information offered in low-bandwidth formats.

In cold region such as sea ice areas, it is difficult to evaluate the carbon dioxide exchange between the surface and atmosphere (CO2 flux) by eddy covariance due to their small flux magnitudes. Drying air samples using a closed-path infrared gas analyzer is effective for measuring small CO2 fluxes. However, using drying equipment leads to the attenuation of turbulent fluctuations, which tends to result in underestimation of CO2 flux. Therefore, it is necessary to survey which dryer is best to minimize this underestimation while effectively drying air samples. In this study, we evaluated the drying ability and persistence using desiccants and a membrane dryer, and the impact of air-drying on CO2 fluxes by simultaneous observations of the drying and non-drying systems. The drying systems with desiccants showed high drying abilities, but their persistence was only a few hours. The drying system with a membrane dryer had a lower drying ability. However, it successfully eliminated the water vapor fluctuation, which was important for accurate CO2 flux measurements. The use of the membrane dryer in the drying system resulted in only 5% underestimation of CO2 fluxes due to the attenuation of CO2 mixing ratio fluctuations, further suggesting its usefulness.

Climate change is expected to alter the input of nitrogen (N) sources in the Eastern Canadian Arctic Archipelago (ECAA) and Baffin Bay due to increased discharge from glacial meltwater and permafrost thaw. Since dissolved inorganic N is generally depleted in surface waters, dissolved organic N (DON) could represent a significant N source fueling phytoplankton activity in Arctic ecosystems. Yet, few DON data for this region exist. We measured concentrations and stable isotope ratios (δ15N and δ18O) of DON and nitrate (NO3−) to investigate the sources and cycling of dissolved nitrogen in regional rivers and at the sea surface from samples collected in the ECAA and Baffin Bay during the summer of 2019. The isotopic signatures of NO3- in rivers could be reproduced in a steady state isotopic model by invoking mixing between atmospheric NO3- and nitrified ammonium as well as NO3- assimilation by phytoplankton. DON concentrations were low in most rivers (≤4.9 µmol L−1), whereas the concentrations (0.54–12 µmol L−1) and δ15N of DON (−0.71–9.6 ‰) at the sea surface were variable among stations, suggesting dynamic cycling and/or distinctive sources. In two regions with high chl-a, DON concentrations were inversely correlated with chlorophyll‐an and the d15N of DON, suggesting net DON consumption in localized phytoplankton blooms. We derived an isotope effect of −6.9‰ for DON consumption. Our data helps establish a baseline to assess future change in nutrient regime for this climate sensitive region.

Hierarchical modeling is frequently used to model ecological processes because of its ability to handle complex ecological phenomena by decomposing them into naturally explainable sub-models. Hierarchical Bayesian approaches have gained widespread use in health, social, and environmental sciences, including in the estimation of demographic parameters such as survival. In this study, we combine Bayesian hierarchical models with acoustic telemetry data to estimate survival probabilities for high-latitude populations of an anadromous salmonid, the Arctic char, while incorporating environmental and biological covariates to assess their impact on survival. The model we present here can also account for temporally varying detection probabilities due to changes to the acoustic receiver array design and seasonal variation in the detection probabilities related to environmental conditions (e.g., ice vs. no ice). As previously documented in this species, survival was high (>0.87) and we found that the covariates pertaining to sea ice coverage and Fulton's condition factor impacted the survival probabilities. Contrary to our expectations, high-condition fish had lower survival rates. Survival was also considerably lower during the summer (open-water) compared to winter (ice-covered) seasons. While the biological explanations and implications of these findings require further exploration, they nonetheless demonstrate the utility of this approach. Specifically, we present a hierarchical Bayesian model that can consider environmental and biological covariates while accounting for varying detection probabilities, a major concern of acoustic telemetry studies. The model can be easily adapted for other taxa with similar life histories where mark recapture data are available and can be extended to include additional environmental (e.g., salinity) and biological parameters (e.g., sex). ### Competing Interest Statement The authors have declared no competing interest.

The Arctic Ocean is an oligotrophic ecosystem facing escalating threats of oil spills as ship traffic increases owing to climate change-induced sea ice retreat. Biostimulation is an oil spill mitigation strategy that involves introducing bioavailable nutrients to enhance crude oil biodegradation by endemic oil-degrading microbes. For bioremediation to offer a viable response for future oil spill mitigation in extreme Arctic conditions, a better understanding of the effects of nutrient addition on Arctic marine microorganisms is needed. Controlled experiments tracking microbial populations revealed a significant decline in community diversity along with changes in microbial community composition. Notably, differential abundance analysis highlighted the significant enrichment of the unexpected genera Lacinutrix, Halarcobacter and Candidatus Pseudothioglobus. These groups are not normally associated with hydrocarbon biodegradation, despite closer inspection of genomes from closely related isolates confirming the potential for hydrocarbon metabolism. Co-occurrence analysis further revealed significant associations between these genera and well-known hydrocarbon-degrading bacteria, suggesting potential synergistic interactions during oil biodegradation. While these findings broaden our understanding of how biostimulation promotes enrichment of endemic hydrocarbon-degrading genera, further research is needed to fully assess the suitability of nutrient addition as a stand-alone oil spill mitigation strategy in this sensitive and remote polar marine ecosystem.

Thinning sea ice cover and earlier melt in the Arctic impact primary producer (PP) phenology, causing earlier ice algal bloom termination and phytoplankton bloom commencement. However, logistic constraints limit capturing the complete seasonal evolution of PPs and their physical drivers. Here, we combine spectral irradiance data from subsurface oceanographic moorings with synthetic aperture radar backscatter and meteorological variables to study light in Dease Strait, investigating its relation to timing and magnitude of surface PPs for 2017 and 2019. Ice algal blooms in 2017 and 2019 lasted 66 and 84 days, respectively, peaking within 2 days of snow melt onset. In 2019, lower temperatures and a deeper snowpack before snow melt extended the ice algal bloom. Melt pond formation increased light transmission, enabling a short, 6-7-day under-ice phytoplankton bloom in both years that was likely nutrient-limited. The 2019 phytoplankton bloom was less productive, possibly due to the longer ice algal bloom depleting surface nutrients. After ice break-up in 2019, a 31-day late-summer bloom occurred via wind-driven mixing. Our findings suggest that the combined remote sensing technique has novel applicability in other settings, providing insights into the changing state of PP phenology, and the need for long-term Arctic observations to discern regional climate change effects.

Utilizing a $1/12<^>\circ$1/12 circle numerical model, we examine the diapycnal mixing patterns in the Kitikmeot Sea, a semi-enclosed water body within the southern Canadian Arctic Archipelago. The analysis reveals that mixing intensity near the sea surface varies seasonally, with effective diffusivity values ranging from $10<^>{-5}$10-5 to $10<^>{-3}\, {\rm m}<^>2\, {\rm s}<^>{-1}$10-3m2s-1, while away from the surface, the effective diffusivity remains relatively stable between $10<^>{-5}$10-5 and $10<^>{-4}\, {\rm m}<^>2\, {\rm s}<^>{-1}$10-4m2s-1. The seasonal fluctuations in surface mixing intensity are strongly influenced by ice coverage, which impacts both the stratification and the energy input to the surface driving the mixing process. Mixing energetics analysis indicates that the majority of energy contributing to the mixing processes are applied to the sea surface. During ice-free periods, wind-driven stirring dominates near-surface mixing with effective diffusivities of $10<^>{-5}$10-5 to $10<^>{-4}\, {\rm m}<^>2\, {\rm s}<^>{-1}$10-4m2s-1. Minimum near-surface effective diffusivity values occur in July and August, when the surface water is fresher and near-surface stratification is stronger due to spring freshet. Conversely, during ice-covered seasons, surface cooling and brine rejection primarily drive near-surface mixing, leading to effective diffusivities of $10<^>{-3}\, {\rm m}<^>2\, {\rm s}<^>{-1}$10-3m2s-1 or higher. In most cases, the observed mixing efficiency is within the range of what has been found in other regions of the Arctic Ocean. [Traduit par la rcedaction] En utilisant un modele numerique $1/12<^>\circ$1/12 circle, nous examinons les schemas de melange diapycniques dans la mer de Kitikmeot, une masse d'eau semi-fermee situee dans le sud de l'archipel Arctique canadien. L'analyse revele que l'intensite du melange pres de la surface de la mer varie selon les saisons, avec des valeurs de diffusivite effective allant de $10<^>{-5}$10-5 a $10<^>{-3}\, {\rm m}<^>2\, {\rm s}<^>{-1}$10-3m2s-1, tandis que loin de la surface, la diffusivite effective reste relativement stable entre $10<^>{-5}$10-5 et $10<^>{-4}\, {\rm m}<^>2\, {\rm s}<^>{-1}$10-4m2s-1. Les fluctuations saisonnieres de l'intensite du melange de surface sont fortement influencees par la couverture de glace, qui a une incidence a la fois sur la stratification et sur l'apport d'energie a la surface qui alimente le processus de melange. L'analyse energetique du melange indique que la majorite de l'energie contribuant aux processus de melange est appliquee a la surface de la mer. Pendant les periodes sans glace, l'agitation causee par le vent domine le melange pres de la surface avec des diffusivites effectives de $10<^>{-5}$10-5 a $10<^>{-4}\, {\rm m}<^>2\, {\rm s}<^>{-1}$10-4m2s-1. Les valeurs minimales de diffusivite effective pres de la surface se produisent en juillet et en aout, lorsque les eaux de surface sont plus fraiches et que la stratification pres de la surface est plus forte en raison de la crue printaniere. Inversement, pendant les saisons ou la glace est presente, le refroidissement de la surface et le rejet de saumure sont les principaux moteurs du melange pres de la surface, ce qui conduit a des diffusivites effectives de $10<^>{-3}\, {\rm m}<^>2\, {\rm s}<^>{-1}$10-3m2s-1 ou plus. Dans la plupart des cas, l'efficacite de melange observee se situe dans la fourchette de ce qui a ete trouve dans d'autres regions de l'ocean Arctique.

Utilizing an 11-year (2011-2021) data set, we report surface-ocean pCO(2) in Baffin Bay during the open-water season (June-October) to establish a baseline understanding of surface seawater carbon dynamics in this region. We found pCO(2) was strongly undersaturated (70-130 mu atm below saturation, depending on year), albeit with substantial regional variability. Though temperature was found to be a generally strong control of pCO(2), sea-ice dynamics and other non-thermal drivers controlled pCO(2) at certain times and in certain regions. The Baffin Island Current region (western Baffin Bay) experienced relatively high pCO(2) during instances of high sea-ice cover, usually in early spring. Average pCO(2) was comparatively lower in the West Greenland Current region (eastern Baffin Bay) which is ice-free substantially longer (by 3-4 months) and where temperature acted as the dominant control to pCO(2). With respect to temporal variations, June had the lowest pCO(2) of the open-water season, coinciding with active sea-ice melt. Surface-ocean pCO(2) then increased month-to-month through July and August due to warming and decreased meltwater dilution, increasing again into September before stabilizing into October. Generally, non-thermal controls acted to decrease pCO(2) during mid-summer (possibly primary production, sea-ice melt, and circulation), but acted to increase pCO(2) during early fall (vertical mixing). Despite spatial and temporal variation over the open-water season, persistent undersaturation suggests that Baffin Bay is a potentially strong CO2 sink, even in comparison to other uptake regions across the western Arctic.

Polar oceans and sea ice cover 15% of the Earth’s ocean surface, and the environment is changing rapidly at both poles. Improving knowledge on the interactions between the atmospheric and oceanic realms in the polar regions, a Surface Ocean–Lower Atmosphere Study (SOLAS) project key focus, is essential to understanding the Earth system in the context of climate change. However, our ability to monitor the pace and magnitude of changes in the polar regions and evaluate their impacts for the rest of the globe is limited by both remoteness and sea-ice coverage. Sea ice not only supports biological activity and mediates gas and aerosol exchange but can also hinder some in-situ and remote sensing observations. While satellite remote sensing provides the baseline climate record for sea-ice properties and extent, these techniques cannot provide key variables within and below sea ice. Recent robotics, modeling, and in-situ measurement advances have opened new possibilities for understanding the ocean–sea ice–atmosphere system, but critical knowledge gaps remain. Seasonal and long-term observations are clearly lacking across all variables and phases. Observational and modeling efforts across the sea-ice, ocean, and atmospheric domains must be better linked to achieve a system-level understanding of polar ocean and sea-ice environments. As polar oceans are warming and sea ice is becoming thinner and more ephemeral than before, dramatic changes over a suite of physicochemical and biogeochemical processes are expected, if not already underway. These changes in sea-ice and ocean conditions will affect atmospheric processes by modifying the production of aerosols, aerosol precursors, reactive halogens and oxidants, and the exchange of greenhouse gases. Quantifying which processes will be enhanced or reduced by climate change calls for tailored monitoring programs for high-latitude ocean environments. Open questions in this coupled system will be best resolved by leveraging ongoing international and multidisciplinary programs, such as efforts led by SOLAS, to link research across the ocean–sea ice–atmosphere interface.

The water mass assembly of Nares Strait is variable, owing to fluctuating wind forcings over the central Arctic Basin, and irregular northward flows from the West Greenland Current (WGC) in Baffin Bay. Here we characterize the physico-chemical properties of the water masses entering Nares Strait in August 2014. We employ an extended optimum multi-parameter (OMP) analysis to estimate the mixing fractions of predefined source water masses, and to distinguish the role of physical and biological processes in governing the distribution of dissolved inorganic carbon (DIC) in Nares Strait. We show the first documented evidence of Siberian shelf waters arriving in Nares Strait, along with a diluted upper halocline layer of partial Pacific-origin. These mixed-origin water masses appear to play an important role in driving a modest phytoplankton bloom in Kane Basin, leading to decreased surface pCO(2) concentrations in Nares Strait. Although inorganic nitrogen was already limited near the surface in northern Nares Strait, the rather shallow upper halocline layer and the shoaling bathymetry in Kane Basin facilitated upwelling of nutrients to the surface. Our observations suggest that the positioning of the Transpolar Drift, and hence the balance of Atlantic and Pacific water delivered to Nares Strait, may play an important role in regional biological productivity and carbon uptake from the atmosphere. We also observed water masses from the WGC transported as far north as Kane Basin, contributing to relatively high pCO(2) and low pH in the intermediate and deep water column of southern Nares Strait and northern Baffin Bay.

Warming of the Arctic due to climate change means the Arctic Ocean is now free from ice for longer, as sea ice melts earlier and refreezes later. Yet, it remains unclear how this extended ice-free period will impact carbon dioxide (CO2) fluxes due to scarcity of surface ocean CO2 measurements. Baseline measurements are urgently needed to understand spatial and temporal air–sea CO2 flux variability in the changing Arctic Ocean. There is also uncertainty as to whether the previous basin-wide surveys are representative of the many smaller bays and inlets that make up the Canadian Arctic Archipelago (CAA). By using a research vessel that is based in the remote Inuit community of Ikaluqtuutiak (Cambridge Bay, Nunavut), we have been able to reliably survey pCO2 shortly after ice melt and access previously unsampled bays and inlets in the nearby region. Here we present 4 years of consecutive summertime pCO2 measurements collected in the Kitikmeot Sea in the southern CAA. Overall, we found that this region is a sink for atmospheric CO2 in August (average of all calculated fluxes over the four cruises was −4.64 mmol m−2 d−1), but the magnitude of this sink varies substantially between years and locations (average calculated fluxes of +3.58, −2.96, −16.79 and −0.57 mmol m−2 d−1 during the 2016, 2017, 2018 and 2019 cruises, respectively). Surface ocean pCO2 varied by up to 156 µatm between years, highlighting the importance of repeat observations in this region, as this high interannual variability would not have been captured by sparse and infrequent measurements. We find that the surface ocean pCO2 value at the time of ice melt is extremely important in constraining the magnitude of the air–sea CO2 flux throughout the ice-free season. However, further constraining the air–sea CO2 flux in the Kitikmeot Sea will require a better understanding of how pCO2 changes outside of the summer season. Surface ocean pCO2 measurements made in small bays and inlets of the Kitikmeot Sea were ∼ 20–40 µatm lower than in the main channels. Surface ocean pCO2 measurements made close in time to ice breakup (i.e. within 2 weeks) were ∼ 50 µatm lower than measurements made > 4 weeks after breakup. As previous basin-wide surveys of the CAA have focused on the deep shipping channels and rarely measure close to the ice breakup date, we hypothesize that there may be an observational bias in previous studies, leading to an underestimate of the CO2 sink in the CAA. These high-resolution measurements constitute an important new baseline for gaining a better understanding of the role this region plays in the uptake of atmospheric CO2.

The Canadian Arctic is warming at three times the rate of the rest of the planet and the effects of climate change on the Arctic marine carbon cycle remains unconstrained. Baffin Bay is a semi-enclosed, Arctic basin that connects the Arctic Ocean to the north to the Labrador Sea to the south. While the physical oceanography of surface Baffin Bay is well characterized, less is known about deep water formation mechanisms within the Basin. Only a few residence-time estimates for Baffin Bay Deep Water (BBDW) exist and range from 20 to 1450 years. Better residence time estimates are needed to understand the oceanographic significance of Baffin Bay. Here we report stable carbon (δ 13 C) and radiocarbon (Δ 14 C) values of dissolved inorganic carbon (DIC) collected aboard the CCGS Amundsen in 2019. DIC δ 13 C and Δ 14 C values between ranged between -0.7‰ to +1.9‰ and -90.0‰ to +29.8‰, respectively. Surface DIC δ 13 C values were between +0.7‰ to +1.9‰, while deep (>100m) values were 0.0 to -0.7‰. Surface DIC Δ 14 C values ranged between -5.4‰ to +22.9‰, while deep DIC (>1400m) DIC Δ 14 C averaged -82.2 ± 8.5‰ ( n = 9). To constrain natural DIC Δ 14 C values, we quantified the amount of atmospheric “bomb” 14 C in DIC (Δ 14 C bomb ; using the potential alkalinity method; P alk ) and anthropogenic DIC (DIC anth ; using the ΔC * method). Both proxies indicate an absence of Δ 14 C bomb and DIC anth below 1000m. Using two previously proposed deep water formation mechanisms and our corrected DIC Δ 14 C natural values, we estimated a 14 C-based residence time of 360-690 years for BBDW. Based on these residence times, we infer carbon is likely stored for centuries in deep Baffin Bay.

Sparse in situ measurements and poor understanding of the impact of sea ice on air-sea gas exchange introduce large uncertainties to models of polar oceanic carbon uptake. The eddy covariance technique can be used to produce insightful air-sea gas exchange datasets in the presence of sea ice, but results differ between studies. We present a critical review of historical polar eddy covariance studies and can identify only five that present comparable flux datasets. Assessment of ancillary datasets, including sea-ice coverage and type and air-sea concentration gradient of carbon dioxide, used to interpret flux datasets (with a specific focus on their role in estimating and interpreting sea ice zone gas transfer velocities) identifies that standardised methodologies to characterise the flux footprint would be beneficial. In heterogeneous ice environments both ancillary data uncertainties and controls on gas exchange are notably complex. To address the poor understanding, we highlight how future efforts should focus on the collection of robust gas flux datasets within heterogeneous sea ice regions during key seasonal processes alongside consistent ancillary data with a full characterisation of their associated uncertainties.

The Green Edge project was designed to investigate the onset, life, and fate of a phytoplankton spring bloom (PSB) in the Arctic Ocean. The lengthening of the ice-free period and the warming of seawater, amongst other factors, have induced major changes in Arctic Ocean biology over the last decades. Because the PSB is at the base of the Arctic Ocean food chain, it is crucial to understand how changes in the Arctic environment will affect it. Green Edge was a large multidisciplinary, collaborative project bringing researchers and technicians from 28 different institutions in seven countries together, aiming at understanding these changes and their impacts on the future. The fieldwork for the Green Edge project took place over two years (2015 and 2016) and was carried out from both an ice camp and a research vessel in Baffin Bay, in the Canadian Arctic. This paper describes the sampling strategy and the dataset obtained from the research cruise, which took place aboard the Canadian Coast Guard ship (CCGS) Amundsen in late spring and early summer 2016. The sampling strategy was designed around the repetitive, perpendicular crossing of the marginal ice zone (MIZ), using not only ship-based station discrete sampling but also high-resolution measurements from autonomous platforms (Gliders, BGC-Argo floats …) and under-way monitoring systems. The dataset is available at https://doi.org/10.17882/86417 (Bruyant et al., 2022).

Abstract. The Green Edge project was designed to investigate the onset, life and fate of a phytoplankton spring bloom (PSB) in the Arctic Ocean. The lengthening of the ice-free period and the warming of seawater, amongst other factors, have induced major changes in arctic ocean biology over the last decades. Because the PSB is at the base of the Arctic Ocean food chain, it is crucial to understand how changes in the arctic environment will affect it. Green Edge was a large multidisciplinary collaborative project bringing researchers and technicians from 28 different institutions in seven countries, together aiming at understanding these changes and their impacts into the future. The fieldwork for the Green Edge project took place over two years (2015 and 2016) and was carried out from both an ice-camp and a research vessel in the Baffin Bay, canadian arctic. This paper describes the sampling strategy and the data set obtained from the research cruise, which took place aboard the Canadian Coast Guard Ship (CCGS) Amundsen in spring 2016. The dataset is available at https://doi.org/10.17882/59892 (Massicotte et al., 2019a).