The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms

Author:

Rabe Benjamin1ORCID,Cox Christopher J.2,Fang Ying-Chih13,Goessling Helge1,Granskog Mats A.4,Hoppmann Mario1,Hutchings Jennifer K.5,Krumpen Thomas1,Kuznetsov Ivan1,Lei Ruibo6,Li Tao78,Maslowski Wieslaw9,Nicolaus Marcel1,Perovich Don10,Persson Ola1112,Regnery Julia1,Rigor Ignatius13,Shupe Matthew D.1112,Sokolov Vladimir14,Spreen Gunnar15,Stanton Tim9,Watkins Daniel M.516,Blockley Ed17,Buenger H. Jakob1,Cole Sylvia18,Fong Allison1,Haapala Jari19,Heuzé Céline20,Hoppe Clara J. M.1,Janout Markus1,Jutila Arttu119,Katlein Christian1,Krishfield Richard18,Lin Long6,Ludwig Valentin1,Morgenstern Anne1,O’Brien Jeff18,Zurita Alejandra Quintanilla1,Rackow Thomas21,Riemann-Campe Kathrin1,Rohde Jan1,Shaw William9,Smolyanitsky Vasily14,Solomon Amy1112,Sperling Anneke1,Tao Ran1,Toole John18,Tsamados Michel22,Zhu Jialiang7,Zuo Guangyu23

Affiliation:

1. 1Alfred-Wegener-Institut Helmholtz Zentrum für Polar-und Meeresforschung, Bremerhaven, Germany

2. 2NOAA Physical Sciences Laboratory (PSL), Boulder, CO, USA

3. 3Department of Oceanography, College of Marine Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan

4. 4Norwegian Polar Institute, Fram Centre, Tromsø, Norway

5. 5Oregon State University, Corvallis, OR, USA

6. 6Polar Research Institute of China, Shanghai, China

7. 7College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China

8. 8Pilot National Laboratory for Marine Science and Technology, Qingdao, China

9. 9Naval Postgraduate School and Moss Landing Marine Laboratories, Monterey, CA, USA

10. 10Thayer School of Engineering, Dartmouth College, Hanover, MA, USA

11. 11Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA

12. 12Physical Sciences Laboratory, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA

13. 13University of Washington, Seattle, WA, USA

14. 14Arctic and Antarctic Research Institute, St. Petersburg, Russia

15. 15Institute of Environmental Physics, University of Bremen, Bremen, Germany

16. 16Center for Fluid Mechanics, Brown University, Providence, RI, USA

17. 17Met Office Hadley Centre, FitzRoy Road, Exeter, UK

18. 18Woods Hole Oceanographic Institution, Woods Hole, MA, USA

19. 19Finnish Meteorological Institute, Helsinki, Finland

20. 20Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden

21. 21European Centre for Medium-Range Weather Forecasts (ECMWF), Bonn, Germany

22. 22Centre for Polar Observation and Modelling, Earth Sciences, UCL, London, UK

23. 23College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan City, China

Abstract

Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.

Publisher

University of California Press

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