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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).

The Green Edge initiative was developed to investigate the processes controlling the primary productivity and fate of organic matter produced during the Arctic phytoplankton spring bloom (PSB) and to determine its role in the ecosystem. Two field campaigns were conducted in 2015 and 2016 at an ice camp located on landfast sea ice southeast of Qikiqtarjuaq Island in Baffin Bay (67.4797∘ N, 63.7895∘ W). During both expeditions, a large suite of physical, chemical and biological variables was measured beneath a consolidated sea-ice cover from the surface to the bottom (at 360 m depth) to better understand the factors driving the PSB. Key variables, such as conservative temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured at the ice camp. Meteorological and snow-relevant variables were also monitored. Here, we present the results of a joint effort to tidy and standardize the collected datasets, which will facilitate their reuse in other Arctic studies.

Phytoplankton blooms in the Arctic marginal ice zone (MIZ) can be prolific dimethylsulfide (DMS) producers, thereby influencing regional aerosol formation and cloud radiative forcing. Here we describe the distribution of DMS and its precursor dimethylsulfoniopropionate (DMSP) across the Baffin Bay receding ice edge in early summer 2016. Overall, DMS and total DMSP (DMSPt) increased towards warmer waters of Atlantic origin concurrently with more advanced ice-melt and bloom stages. Relatively high DMS and DMSPt (medians of 6.3 and 70 nM, respectively) were observed in the surface layer (0–9 m depth), and very high values (reaching 74 and 524 nM, respectively) at the subsurface biomass maximum (15–30 m depth). Microscopic and pigment analyses indicated that subsurface DMS and DMSPt peaks were associated with Phaeocystis pouchetii, which bloomed in Atlantic-influenced waters and reached unprecedented biomass levels in Baffin Bay. In surface waters, DMS concentrations and DMS:DMSPt ratios were higher in the MIZ (medians of 12 nM and 0.15, respectively) than in fully ice-covered or ice-free conditions, potentially associated with enhanced phytoplanktonic DMSP release and bacterial DMSP cleavage (high dddP:dmdA gene ratios). Mean sea–air DMS fluxes (µmol m–2 d–1) increased from 0.3 in ice-covered waters to 10 in open waters (maximum of 26) owing to concurrent trends in near-surface DMS concentrations and physical drivers of gas exchange. Using remotely sensed sea-ice coverage and a compilation of sea–air DMS flux data, we estimated that the pan-Arctic DMS emission from the MIZ (EDMS, MIZ) was 5–13 Gg S yr–1. North of 80°N, EDMS, MIZ might have increased by around 10 ± 4% yr–1 between 2003 and 2014, likely exceeding open-water emissions in June and July. We conclude that EDMS, MIZ must be taken into account to evaluate plankton-climate feedbacks in the Arctic., We acknowledge funding from AGAUR (Generalitat de Catalunya) Beatriu de Pinós postdoctoral fellowship program (MG), the Canada Excellence Research Chair in Remote Sensing of Canada’s New Arctic Frontier (MB), the Canada Research Chair on Ocean Biogeochemistry and Climate and an NSERC Discovery Grant Program and Northern Research Supplement Program (MLe), NETCARE (NSERC Climate Change and Atmospheric Research program, MLe), the U.S. National Science Foundation (NSF-OCE 1756907, DJK), Marie Curie Actions-International Outgoing Fellowship (PIOF-GA-2013-629378, JD), and ArcticNet (The Network of Centres of Excellence of Canada). This is a contribution to the research program of Québec-Océan and the Takuvik Joint International Laboratory (CNRS-France & Université Laval-Canada)., Peer Reviewed, Postprint (published version)

The Green Edge initiative was developed to investigate the processes controlling the primary productivity and the fate of organic matter produced during the Arctic phytoplankton spring bloom (PSB) and to determine its role in the ecosystem. Two field campaigns were conducted in 2015 and 2016 at an ice camp located on landfast sea ice southeast of Qikiqtarjuaq Island in Baffin Bay (67.4797N, 63.7895W). During both expeditions, a large suite of physical, chemical and biological variables was measured beneath a consolidated sea ice cover from the surface to the bottom at 360 m depth to better understand the factors driving the PSB. Key variables such as temperature, salinity, radiance, irradiance, nutrient concentrations, chlorophyll-a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, carbon stocks and fluxes were routinely measured at the ice camp. Here, we present the results of a joint effort to tidy and standardize the collected data sets that will facilitate their reuse in other Arctic studies. The dataset is available at http://www.seanoe.org/data/00487/59892/ (Massicotte et al., 2019a).

There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability. However, a significant gap exists in the ocean observing system in polar regions, compared to most areas of the global ocean, hindering the reliability of ocean and sea ice forecasts. This gap can also be seen from the spread in ocean and sea ice reanalyses for polar regions which provide an estimate of their uncertainty. The reduced reliability of polar predictions may affect the quality of various applications including search and rescue, coupling with numerical weather and seasonal predictions, historical reconstructions (reanalysis), aquaculture and environmental management including environmental emergency response. Here, we outline the status of existing near-real time ocean observational efforts in polar regions, discuss gaps, and explore perspectives for the future. Specific recommendations include a renewed call for open access to data, especially real-time data, as a critical capability for improved sea ice and weather forecasting and other environmental prediction needs. Dedicated efforts are also needed to make use of additional observations made as part of the Year of Polar Prediction (YOPP; 2017-2019) to inform optimal observing system design. To provide a polar extension to the Argo network, it is recommended that a network of ice-borne sea ice and upper-ocean observing buoys be deployed and supported operationally in ice-covered areas together with autonomous profiling floats and gliders (potentially with ice detection capability) in seasonally ice covered seas. Finally, additional efforts to better measure and parameterize

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Testor, P., de Young, B., Rudnick, D. L., Glenn, S., Hayes, D., Lee, C. M., Pattiaratchi, C., Hill, K., Heslop, E., Turpin, V., Alenius, P., Barrera, C., Barth, J. A., Beaird, N., Becu, G., Bosse, A., Bourrin, F., Brearley, J. A., Chao, Y., Chen, S., Chiggiato, J., Coppola, L., Crout, R., Cummings, J., Curry, B., Curry, R., Davis, R., Desai, K., DiMarco, S., Edwards, C., Fielding, S., Fer, I., Frajka-Williams, E., Gildor, H., Goni, G., Gutierrez, D., Haugan, P., Hebert, D., Heiderich, J., Henson, S., Heywood, K., Hogan, P., Houpert, L., Huh, S., Inall, M. E., Ishii, M., Ito, S., Itoh, S., Jan, S., Kaiser, J., Karstensen, J., Kirkpatrick, B., Klymak, J., Kohut, J., Krahmann, G., Krug, M., McClatchie, S., Marin, F., Mauri, E., Mehra, A., Meredith, M. P., Meunier, T., Miles, T., Morell, J. M., Mortier, L., Nicholson, S., O'Callaghan, J., O'Conchubhair, D., Oke, P., Pallas-Sanz, E., Palmer, M., Park, J., Perivoliotis, L., Poulain, P., Perry, R., Queste, B., Rainville, L., Rehm, E., Roughan, M., Rome, N., Ross, T., Ruiz, S., Saba, G., Schaeffer, A., Schonau, M., Schroeder, K., Shimizu, Y., Sloyan, B. M., Smeed, D., Snowden, D., Song, Y., Swart, S., Tenreiro, M., Thompson, A., Tintore, J., Todd, R. E., Toro, C., Venables, H., Wagawa, T., Waterman, S., Watlington, R. A., & Wilson, D. OceanGliders: A component of the integrated GOOS. Frontiers in Marine Science, 6, (2019): 422, doi:10.3389/fmars.2019.00422., The OceanGliders program started in 2016 to support active coordination and enhancement of global glider activity. OceanGliders contributes to the international efforts of the Global Ocean Observation System (GOOS) for Climate, Ocean Health, and Operational Services. It brings together marine scientists and engineers operating gliders around the world: (1) to observe the long-term physical, biogeochemical, and biological ocean processes and phenomena that are relevant for societal applications; and, (2) to contribute to the GOOS through real-time and delayed mode data dissemination. The OceanGliders program is distributed across national and regional observing systems and significantly contributes to integrated, multi-scale and multi-platform sampling strategies. OceanGliders shares best practices, requirements, and scientific knowledge needed for glider operations, data collection and analysis. It also monitors global glider activity and supports the dissemination of glider data through regional and global databases, in real-time and delayed modes, facilitating data access to the wider community. OceanGliders currently supports national, regional and global initiatives to maintain and expand the capabilities and application of gliders to meet key global challenges such as improved measurement of ocean boundary currents, water transformation and storm forecast., The editorial team would like to recognize the support of the global glider community to this paper. Our requests for data and information were met with enthusiasm and welcome contributions from around the globe, clearly demonstrating to us a point made in this paper that there are many active and dedicated teams of glider operators and users. We should also acknowledge the support that OceanGliders has received from the WMO/IOC JCOMM-OCG and JCOMMOPS that have allowed this program to develop, encouraging us to articulate a vision for the role of gliders in the GOOS. We acknowledge support from the EU Horizon 2020 AtlantOS project funded under grant agreement No. 633211 and gratefully acknowledge the many agencies and programs that have supported underwater gliders: AlterEco, ANR, CFI, CIGOM, CLASS Ellet Array, CNES, CNRS/INSU, CONACyT, CSIRO, DEFRA, DFG/SFB-754, DFO, DGA, DSTL, ERC, FCO, FP7, and H2020 Europen Commission, HIMIOFoTS, Ifremer, IMOS, IMS, IOOS, IPEV, IRD, Israel MOST, JSPS, MEOPAR, NASA, NAVOCEANO (Navy), NERC, NFR, NJDEP, NOAA, NRC, NRL, NSF, NSERC, ONR, OSNAP, Taiwan MOST, SANAP-NRF, SENER, SIMS, Shell Exploration and Production Company, Sorbonne Université, SSB, UKRI, UNSW, Vettleson, Wallenberg Academy Fellowship, and WWF.

The use of Lagrangian platforms and of Autonomous Underwater Vehicles (AUVs) in oceanography has increased rapidly over the last decade along with the development of improved biological and chemical sensors. These vehicles provide new spatial and temporal scales for observational studies of the ocean. They offer a broad range of deployment and recovery capabilities that reduce the need of large research vessels. This is especially true for ice-covered Arctic ocean where surface navigation is only possible during the summer period. Moreover, safe underwater navigation in icy waters requires the capability of detecting sea ice on the surface (ice sheets). AUVs navigating in such conditions risk collisions, RF communication shadowing, and being trapped by ice keels. In this paper, an underwater sea-ice detection apparatus is described. The source is a polarized continuous wave (CW) diode-pumped solid-state laser (DPSS) module operating at 532 nm. The detector is composed of a polarizing beam splitter, which separates light of S and P polarization states and two photodetectors, one for each polarized component. Since sea-ice is a strong depolarizer, the ratio P/S is an indicator of the presence or absence of sea-ice. The system is capable of detecting sea-ice at a distance of 12m. This apparatus is designed to be used by free drifting profiling floats (e.g., Argo floats), buoyancy driven vehicles (e.g., sea gliders) and propeller-driven robots (e.g., Hugin class AUV).

Fixation of organic carbon by phytoplankton is the foundation of nearly all open-ocean ecosystems and a critical part of the global carbon cycle. But the quantification and validation of ocean primary productivity at large scale remains a major challenge due to limited coverage of ship-based measurements and the difficulty of validating diverse measurement techniques. Accurate primary productivity measurements from autonomous platforms would be highly desirable due to much greater potential coverage. In pursuit of this goal we estimate gross primary productivity over 2 months in the springtime North Atlantic from an autonomous Lagrangian float using diel cycles of particulate organic carbon derived from optical beam attenuation. We test method precision and accuracy by comparison against entirely independent estimates from a locally parameterized model based on chlorophyll a and light measurements from the same float. During nutrient-replete conditions (80% of the study period), we obtain strong relative agreement between the independent methods across an order of magnitude of productivities (r2 = 0.97), with slight underestimation by the diel cycle method (−19±5%). At the end of the diatom bloom, this relative difference increases to −58% for a 6-day period, likely a response to SiO4 limitation, which is not included in the model. In addition, we estimate gross oxygen productivity from O2 diel cycles and find strong correlation with diel-cycle-based gross primary productivity over the entire deployment, providing further qualitative support for both methods. Finally, simultaneous estimates of net community productivity, carbon export, and particle size suggest that bloom growth is halted by a combination of reduced productivity due to SiO4 limitation and increased export efficiency due to rapid aggregation. After the diatom bloom, high Chl a-normalized productivity indicates that low net growth during this period is due to increased heterotrophic respiration and no