ALBERT

Description: Pan-Arctic sea ice thickness has been monitored over recent decades by satellite radar altimeters such as CryoSat-2, which emits Ku-band radar waves that are assumed in publicly available sea ice thickness products to penetrate overlying snow and scatter from the ice–snow interface. Here we examine two expressions for the time delay caused by slower radar wave propagation through the snow layer and related assumptions concerning the time evolution of overlying snow density. Two conventional treatments introduce systematic underestimates of up to 15 cm into ice thickness estimates and up to 10 cm into thermodynamic growth rate estimates over multi-year ice in winter. Correcting these biases would impact a wide variety of model projections, calibrations, validations and reanalyses.

Description: Pan-Arctic sea ice thickness has been monitored over recent decades by satellite radar altimeters such as CryoSat-2, which emit Ku-band radar waves that are conventionally assumed to penetrate overlying snow and scatter from the ice-snow interface. Here we examine two expressions for the time delay caused by slower radar wave propagation through the snow layer and related assumptions concerning the time-evolution of overlying snow density. Two conventional treatments lead to systematic underestimates of winter ice thickness and thermodynamic growth rate of up to 15 cm over multiyear ice. Correcting these biases would improve the accuracy of sea ice thickness products, which feed a wide variety of model projections, calibrations, validations and reanalyses.

Description: To improve our understanding of how snow properties influence sea ice thickness retrievals from presently operational and upcoming satellite radar altimeter missions, as well as to investigate the potential for combining dual frequencies to simultaneously map snow depth and sea ice thickness, a new, surface-based, fully polarimetric Ku- and Ka-band radar (KuKa radar) was built and deployed during the 2019–2020 year-long MOSAiC international Arctic drift expedition. This instrument, built to operate both as an altimeter (stare mode) and as a scatterometer (scan mode), provided the first in situ Ku- and Ka-band dual-frequency radar observations from autumn freeze-up through midwinter and covering newly formed ice in leads and first-year and second-year ice floes. Data gathered in the altimeter mode will be used to investigate the potential for estimating snow depth as the difference between dominant radar scattering horizons in the Ka- and Ku-band data. In the scatterometer mode, the Ku- and Ka-band radars operated under a wide range of azimuth and incidence angles, continuously assessing changes in the polarimetric radar backscatter and derived polarimetric parameters, as snow properties varied under varying atmospheric conditions. These observations allow for characterizing radar backscatter responses to changes in atmospheric and surface geophysical conditions. In this paper, we describe the KuKa radar, illustrate examples of its data and demonstrate their potential for these investigations.

Description: To improve our understanding of how snow properties influence sea ice thickness retrievals from presently operational and upcoming satellite radar altimeter missions, as well as to investigate the potential for combining dual frequencies to simultaneously map snow depth and sea ice thickness, a new, surface-based, fully polarimetric Ku- and Ka-band radar (KuKa radar) was built and deployed during the 2019–2020 year-long MOSAiC international Arctic drift expedition. This instrument, built to operate both as an altimeter (stare mode) and as a scatterometer (scan mode), provided the first in situ Ku- and Ka-band dual-frequency radar observations from autumn freeze-up through midwinter and covering newly formed ice in leads and first-year and second-year ice floes. Data gathered in the altimeter mode will be used to investigate the potential for estimating snow depth as the difference between dominant radar scattering horizons in the Ka- and Ku-band data. In the scatterometer mode, the Ku- and Ka-band radars operated under a wide range of azimuth and incidence angles, continuously assessing changes in the polarimetric radar backscatter and derived polarimetric parameters, as snow properties varied under varying atmospheric conditions. These observations allow for characterizing radar backscatter responses to changes in atmospheric and surface geophysical conditions. In this paper, we describe the KuKa radar, illustrate examples of its data and demonstrate their potential for these investigations.

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Spooner, P. T., Thornalley, D. J. R., Oppo, D. W., Fox, A. D., Radionovskaya, S., Rose, N. L., Mallett, R., Cooper, E., & Roberts, J. M. Exceptional 20th century ocean circulation in the Northeast Atlantic. Geophysical Research Letters, 47(10), (2020): e2020GL087577, doi:10.1029/2020GL087577.

Description: The North Atlantic subpolar gyre (SPG) connects tropical and high‐latitude waters, playing a leading role in deep‐water formation, propagation of Atlantic water into the Arctic, and as habitat for many ecosystems. Instrumental records spanning recent decades document significant decadal variability in SPG circulation, with associated hydrographic and ecological changes. Emerging longer‐term records provide circumstantial evidence that the North Atlantic also experienced centennial trends during the 20th century. Here, we use marine sediment records to show that there has been a long‐term change in SPG circulation during the industrial era, largely during the 20th century. Moreover, we show that the shift and late 20th century SPG configuration were unprecedented in the last 10,000 years. Recent SPG dynamics resulted in an expansion of subtropical ecosystems into new habitats and likely also altered the transport of heat to high latitudes.

Description: We thank Janet Hope and UCL laboratory staff, colleagues who sailed on EN539, Kathryn Pietro‐Rose, Sean O'Keefe and Henry Abrams, Sara Chipperton, Tanya Monica, Laura Thrower and Kitty Green for sediment processing, Miles Irving for artwork assistance, James Rolfe for nitrogen isotope measurement, Maryline Vautravers and Michael Kucera for guidance, Arne Biastoch and Christian Mohn for discussion of VIKING20, and Chris Brierley, Meric Srokosz, and Jon Robson for comments. Funding was provided by National Science Foundation (NSF) grant OCE‐1304291 to D.W.O. and D.J.R.T., the Leverhulme Trust, National Environment Research Council (NERC) grant NE/S009736/1, and the ATLAS project to D.J.R.T. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement 678760 (ATLAS). This paper reflects only the authors views and the European Union cannot be held responsible for any use that may be made of the information contained herein.

Description: The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rabe, B., Heuze, C., Regnery, J., Aksenov, Y., Allerholt, J., Athanase, M., Bai, Y., Basque, C., Bauch, D., Baumann, T. M., Chen, D., Cole, S. T., Craw, L., Davies, A., Damm, E., Dethloff, K., Divine, D., Doglioni, F., Ebert, F., Fang, Y-C., Fer, I., Fong, A. A., Gradinger, R., Granskog, M. A., Graupner, R., Haas, C., He, H., He, Y., Hoppmann, M., Janout, M., Kadko, D., Kanzow, T., Karam, S., Kawaguchi, Y., Koenig, Z., Kong, B., Krishfield, R. A., Krumpen, T., Kuhlmey, D., Kuznetsov, I., Lan, M., Laukert, G., Lei, R., Li, T., Torres-Valdés, S., Lin, L,. Lin, L., Liu, H., Liu, N., Loose, B., Ma, X., MacKay, R., Mallet, M., Mallett, R. D. C., Maslowski, W., Mertens, C., Mohrholz, V., Muilwijk, M., Nicolaus, M., O’Brien, J. K., Perovich, D., Ren, J., Rex, M., Ribeiro, N., Rinke, A., Schaffer, J., Schuffenhauer, I., Schulz, K., Shupe, M. D., Shaw, W., Sokolov, V., Sommerfeld, A., Spreen, G., Stanton, T., Stephens, M., Su, J., Sukhikh, N., Sundfjord, A., Thomisch, K., Tippenhauer, S., Toole, J. M., Vredenborg, M., Walter, M., Wang, H., Wang, L., Wang, Y., Wendisch, M., Zhao, J., Zhou, M., & Zhu, J. Overview of the MOSAiC expedition: physical oceanography. Elementa: Science of the Anthropocene, 10(1), (2022): 1, https://doi.org/10.1525/elementa.2021.00062.

Description: Arctic Ocean properties and processes are highly relevant to the regional and global coupled climate system, yet still scarcely observed, especially in winter. Team OCEAN conducted a full year of physical oceanography observations as part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), a drift with the Arctic sea ice from October 2019 to September 2020. An international team designed and implemented the program to characterize the Arctic Ocean system in unprecedented detail, from the seafloor to the air-sea ice-ocean interface, from sub-mesoscales to pan-Arctic. The oceanographic measurements were coordinated with the other teams to explore the ocean physics and linkages to the climate and ecosystem. This paper introduces the major components of the physical oceanography program and complements the other team overviews of the MOSAiC observational program. Team OCEAN’s sampling strategy was designed around hydrographic ship-, ice- and autonomous platform-based measurements to improve the understanding of regional circulation and mixing processes. Measurements were carried out both routinely, with a regular schedule, and in response to storms or opening leads. Here we present along-drift time series of hydrographic properties, allowing insights into the seasonal and regional evolution of the water column from winter in the Laptev Sea to early summer in Fram Strait: freshening of the surface, deepening of the mixed layer, increase in temperature and salinity of the Atlantic Water. We also highlight the presence of Canada Basin deep water intrusions and a surface meltwater layer in leads. MOSAiC most likely was the most comprehensive program ever conducted over the ice-covered Arctic Ocean. While data analysis and interpretation are ongoing, the acquired datasets will support a wide range of physical oceanography and multi-disciplinary research. They will provide a significant foundation for assessing and advancing modeling capabilities in the Arctic Ocean.

Description: The following projects and funding agencies contributed to this work: Why is the deep Arctic Ocean Warming is funded by the Swedish Research Council, project number 2018-03859, and berth fees for this project were covered by the Swedish Polar Research Secretariat; The Changing Arctic Ocean (CAO) program, jointly funded by the United Kingdom Research and Innovation (UKRI) Natural Environment Research Council (NERC) and the Bundesministerium für Bildung und Forschung (BMBF), in particular, the CAO projects Advective Pathways of nutrients and key Ecological substances in the ARctic (APEAR) grants NE/R012865/1, NE/R012865/2, and #03V01461, and the project Primary productivity driven by Escalating Arctic NUTrient fluxeS grant #03F0804A; The Research Council of Norway (AROMA, grant no 294396; HAVOC, grant no 280292; and CAATEX, grant no 280531); Collaborative Research: Thermodynamics and Dynamic Drivers of the Arctic Sea Ice Mass Budget at Multidisciplinary drifting Observatory for the Study of the Arctic Climate; National Science Foundation (NSF) projects 1723400, Stanton; OPP-1724551, Shupe; The Helmholtz society strategic investment Frontiers in Arctic Marine monitoring (FRAM); Deutsche Forschungsgemeinschaft (German Research Foundation) through the Transregional Collaborative Research Centre TRR 172 “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3” (grant 268020496); The Japan Society for the Promotion of Science (grant numbers JP18H03745, JP18KK0292, and JP17KK0083) and the COLE grant of U. Tokyo; National Key Research and Development Plan Sub-Project of Ministry of Science and Technology of China (2016YFA0601804), “Simulation, Prediction and Regional Climate Response of Global Warming Hiatus”, 2016/07-2021/06; National Science Foundation grant number OPP-1756100 which funded two of the Ice-Tethered Profilers and all the Ice-Tethered Profiler deployments; Chinese Polar Environmental Comprehensive Investigation and Assessment Programs, funded by the Chinese Arctic and Antarctic Administration; Marine Science and Technology Fund of Shandong Province for Qingdao National Laboratory for Marine Science and Technology (Grant: 2018SDKJ0104-1) and Chinese Natural Science Foundation (Grant: 41941012); UK NERC Long-term Science Multiple Centre National Capability Programme “North Atlantic Climate System Integrated Study (ACSIS)”, grant NE/N018044/1; The London NERC Doctoral Training Partnership grant (NE/L002485/1) which funded RDCM; NSF grant number OPP-1753423, which funded the 7Be tracer –measurements; and The Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) through its projects: AWI_OCEAN, AWI_ROV, AWI_ICE, AWI_SNOW, AWI_ECO, AWI_ATMO, and AWI_BGC.