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2. Author Correction: A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition

Author

Macfarlane, Amy R., Schneebeli, Martin, Dadic, Ruzica, Tavri, Aikaterini, Immerz, Antonia, Polashenski, Chris, Krampe, Daniela, Clemens-Sewall, David, Wagner, David N., Perovich, Donald K., Henna-Reetta, Hannula, Raphael, Ian, Matero, Ilkka, Regnery, Julia, Smith, Madison M., Nicolaus, Marcel, Jaggi, Matthias, Oggier, Marc, Webster, Melinda A., Lehning, Michael, Kolabutin, Nikolai, Itkin, Polona, Naderpour, Reza, Pirazzini, Roberta, Hämmerle, Stefan, Arndt, Stefanie, and Fons, Steven

Published
2023
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3. A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition

Author

Macfarlane, Amy R., Schneebeli, Martin, Dadic, Ruzica, Tavri, Aikaterini, Immerz, Antonia, Polashenski, Chris, Krampe, Daniela, Clemens-Sewall, David, Wagner, David N., Perovich, Donald K., Henna-Reetta, Hannula, Raphael, Ian, Matero, Ilkka, Regnery, Julia, Smith, Madison M., Nicolaus, Marcel, Jaggi, Matthias, Oggier, Marc, Webster, Melinda A., Lehning, Michael, Kolabutin, Nikolai, Itkin, Polona, Naderpour, Reza, Pirazzini, Roberta, Hämmerle, Stefan, Arndt, Stefanie, and Fons, Steven

Published
2023
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5. Retrieval of Snow Depth on Arctic Sea Ice From Surface‐Based, Polarimetric, Dual‐Frequency Radar Altimetry

Author

Willatt, Rosemary, primary, Stroeve, Julienne C., additional, Nandan, Vishnu, additional, Newman, Thomas, additional, Mallett, Robbie, additional, Hendricks, Stefan, additional, Ricker, Robert, additional, Mead, James, additional, Itkin, Polona, additional, Tonboe, Rasmus, additional, Wagner, David N., additional, Spreen, Gunnar, additional, Liston, Glen, additional, Schneebeli, Martin, additional, Krampe, Daniela, additional, Tsamados, Michel, additional, Demir, Oguz, additional, Wilkinson, Jeremy, additional, Jaggi, Matthias, additional, Zhou, Lu, additional, Huntemann, Marcus, additional, Raphael, Ian A., additional, Jutila, Arttu, additional, and Oggier, Marc, additional

Published
2023
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6. Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice

Author

Nandan, Vishnu, primary, Willatt, Rosemary, additional, Mallett, Robbie, additional, Stroeve, Julienne, additional, Geldsetzer, Torsten, additional, Scharien, Randall, additional, Tonboe, Rasmus, additional, Yackel, John, additional, Landy, Jack, additional, Clemens-Sewall, David, additional, Jutila, Arttu, additional, Wagner, David N., additional, Krampe, Daniela, additional, Huntemann, Marcus, additional, Mahmud, Mallik, additional, Jensen, David, additional, Newman, Thomas, additional, Hendricks, Stefan, additional, Spreen, Gunnar, additional, Macfarlane, Amy, additional, Schneebeli, Martin, additional, Mead, James, additional, Ricker, Robert, additional, Gallagher, Michael, additional, Duguay, Claude, additional, Raphael, Ian, additional, Polashenski, Chris, additional, Tsamados, Michel, additional, Matero, Ilkka, additional, and Hoppmann, Mario, additional

Published
2023
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7. Author Correction: A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition

Author

Macfarlane, Amy R, Schneebeli, Martin, Dadic, Ruzica, Tavri, Aikaterini, Immerz, Antonia, Polashenski, Chris, Krampe, Daniela, Clemens-Sewall, David, Wagner, David N, Perovich, Donald K, Henna-Reetta, Hannula, Raphael, Ian, Matero, Ilkka, Regnery, Julia, Smith, Madison M, Nicolaus, Marcel, Jaggi, Matthias, Oggier, Marc, Webster, Melinda A, Lehning, Michael, Kolabutin, Nikolai, Itkin, Polona, Naderpour, Reza, Pirazzini, Roberta, Hämmerle, Stefan, Arndt, Stefanie, Fons, Steven, Macfarlane, Amy R, Schneebeli, Martin, Dadic, Ruzica, Tavri, Aikaterini, Immerz, Antonia, Polashenski, Chris, Krampe, Daniela, Clemens-Sewall, David, Wagner, David N, Perovich, Donald K, Henna-Reetta, Hannula, Raphael, Ian, Matero, Ilkka, Regnery, Julia, Smith, Madison M, Nicolaus, Marcel, Jaggi, Matthias, Oggier, Marc, Webster, Melinda A, Lehning, Michael, Kolabutin, Nikolai, Itkin, Polona, Naderpour, Reza, Pirazzini, Roberta, Hämmerle, Stefan, Arndt, Stefanie, and Fons, Steven

Abstract

Correction to: Scientific Data, published online 22 June 2023 The original version showed the wrong image for Figure 3, with the image for Figure 4 used for both. This has been corrected in the pdf and HTML versions of the article, with the correct version of Figure 3 replacing the duplicated figure. The dates in the figure captions were also incorrect and have been amended as follows: Figure 3 caption: “from 2019-10-25 - 2020-07-30” modified to “from 2019-10-25 - 2020-05-15” Figure 4 caption: “from 2020-02-25 - 2020-07-30” modified to “from 2020-06-13 - 2020-07-30”.

Published
2023

8. A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition

Author

Macfarlane, Amy R, Schneebeli, Martin, Dadic, Ruzica, Tavri, Aikaterini, Immerz, Antonia, Polashenski, Chris, Krampe, Daniela, Clemens-Sewall, David, Wagner, David N, Perovich, Donald K, Henna-Reetta, Hannula, Raphael, Ian, Matero, Ilkka, Regnery, Julia, Smith, Madison M, Nicolaus, Marcel, Jaggi, Matthias, Oggier, Marc, Webster, Melinda A, Lehning, Michael, Kolabutin, Nikolai, Itkin, Polona, Naderpour, Reza, Pirazzini, Roberta, Hämmerle, Stefan, Arndt, Stefanie, Fons, Steven, Macfarlane, Amy R, Schneebeli, Martin, Dadic, Ruzica, Tavri, Aikaterini, Immerz, Antonia, Polashenski, Chris, Krampe, Daniela, Clemens-Sewall, David, Wagner, David N, Perovich, Donald K, Henna-Reetta, Hannula, Raphael, Ian, Matero, Ilkka, Regnery, Julia, Smith, Madison M, Nicolaus, Marcel, Jaggi, Matthias, Oggier, Marc, Webster, Melinda A, Lehning, Michael, Kolabutin, Nikolai, Itkin, Polona, Naderpour, Reza, Pirazzini, Roberta, Hämmerle, Stefan, Arndt, Stefanie, and Fons, Steven

Abstract

Snow plays an essential role in the Arctic as the interface between the sea ice and the atmosphere. Optical properties, thermal conductivity and mass distribution are critical to understanding the complex Arctic sea ice system’s energy balance and mass distribution. By conducting measurements from October 2019 to September 2020 on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have produced a dataset capturing the year-long evolution of the physical properties of the snow and surface scattering layer, a highly porous surface layer on Arctic sea ice that evolves due to preferential melt at the ice grain boundaries. The dataset includes measurements of snow during MOSAiC. Measurements included profiles of depth, density, temperature, snow water equivalent, penetration resistance, stable water isotope, salinity and microcomputer tomography samples. Most snowpit sites were visited and measured weekly to capture the temporal evolution of the physical properties of snow. The compiled dataset includes 576 snowpits and describes snow conditions during the MOSAiC expedition.

Published
2023

9. Retrieval of Snow Depth on Arctic Sea Ice From Surface-Based, Polarimetric, Dual-Frequency Radar Altimetry

Author

Willatt, Rosemary, Stroeve, Julienne C., Nandan, Vishnu, Newman, Thomas, Mallett, Robbie, Hendricks, Stefan, Ricker, Robert, Mead, James, Itkin, Polona, Tonboe, Rasmus, Wagner, David N., Spreen, Gunnar, Liston, Glen, Schneebeli, Martin, Krampe, Daniela, Tsamados, Michel, Demir, Oguz, Wilkinson, Jeremy, Jaggi, Matthias, Zhou, Lu, Huntemann, Marcus, Raphael, Ian A., Jutila, Arttu, Oggier, Marc, Willatt, Rosemary, Stroeve, Julienne C., Nandan, Vishnu, Newman, Thomas, Mallett, Robbie, Hendricks, Stefan, Ricker, Robert, Mead, James, Itkin, Polona, Tonboe, Rasmus, Wagner, David N., Spreen, Gunnar, Liston, Glen, Schneebeli, Martin, Krampe, Daniela, Tsamados, Michel, Demir, Oguz, Wilkinson, Jeremy, Jaggi, Matthias, Zhou, Lu, Huntemann, Marcus, Raphael, Ian A., Jutila, Arttu, and Oggier, Marc

Abstract

Snow depth on sea ice is an Essential Climate Variable and a major source of uncertainty in satellite altimetry-derived sea ice thickness. During winter of the MOSAiC Expedition, the “KuKa” dual-frequency, fully polarized Ku- and Ka-band radar was deployed in “stare” nadir-looking mode to investigate the possibility of combining these two frequencies to retrieve snow depth. Three approaches were investigated: dual-frequency, dual-polarization and waveform shape, and compared to independent snow depth measurements. Novel dual-polarization approaches yielded r2 values up to 0.77. Mean snow depths agreed within 1 cm, even for data sub-banded to CryoSat-2 SIRAL and SARAL AltiKa bandwidths. Snow depths from co-polarized dual-frequency approaches were at least a factor of four too small and had a r2 0.15 or lower. r2 for waveform shape techniques reached 0.72 but depths were underestimated. Snow depth retrievals using polarimetric information or waveform shape may therefore be possible from airborne/satellite radar altimeters.

Published
2023

10. Thermal Conductivity of Snow on Arctic Sea Ice

Author

Macfarlane, Amy R., primary, Löwe, Henning, additional, Gimenes, Lucille, additional, Wagner, David N., additional, Dadic, Ruzica, additional, Ottersberg, Rafael, additional, Hämmerle, Stefan, additional, and Schneebeli, Martin, additional

Published
2023
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11. Wind Transport of Snow Impacts Ka- and Ku-band Radar Signatures on Arctic Sea Ice

Author

Nandan, Vishnu, primary, Willatt, Rosemary, additional, Mallett, Robbie, additional, Stroeve, Julienne, additional, Geldsetzer, Torsten, additional, Scharien, Randall, additional, Tonboe, Rasmus, additional, Landy, Jack, additional, Clemens-Sewall, David, additional, Jutila, Arttu, additional, Wagner, David N., additional, Krampe, Daniela, additional, Huntemann, Marcus, additional, Yackel, John, additional, Mahmud, Mallik, additional, Jensen, David, additional, Newman, Thomas, additional, Hendricks, Stefan, additional, Spreen, Gunnar, additional, Macfarlane, Amy, additional, Schneebeli, Martin, additional, Mead, James, additional, Ricker, Robert, additional, Gallagher, Michael, additional, Duguay, Claude, additional, Raphael, Ian, additional, Polashenski, Chris, additional, Tsamados, Michel, additional, Matero, Ilkka, additional, and Hoppman, Mario, additional

Published
2022
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12. Leadership Education Reconsidered: Examining Self-Perceived Leadership Styles and Motivation Sources among Undergraduate Leaders

Author

Wagner, David N.

Abstract

This study examined the relationships between undergraduate leaders' self-perceptions of their transformational and transactional leadership behaviors and their sources of work motivation. The sample was comprised of 145 elected and appointed leaders at a mid-west university. The survey included both the Motivation Sources Inventory and the Multifactor Leadership Questionnaire. Other survey items collected demographic and leadership-experience data. Participants overall scored higher for transformational self-perceived behaviors than for transactional, and higher for intrinsic motivation than extrinsic. Intrinsic motivation related positively to transformational self-perceived behaviors, and extrinsic motivation related positively to transactional self-perceived behaviors. By understanding undergraduates' self-perceptions of their leadership behaviors and motivation, models and methods can be developed to foster and strengthen perspectives that embrace situational application of transformational and transactional behaviors. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2010

13. Snowfall and snow accumulation during the MOSAiC winter and spring seasons

Author

Wagner, David N, Shupe, Matthew D, Cox, Christopher, Persson, Ola G, Uttal, Taneil, Frey, Markus M, Kirchgaessner, Amélie, Schneebeli, Martin, Jaggi, Matthias, Macfarlane, Amy R, Itkin, Polona, Arndt, Stefanie, Hendricks, Stefan, Krampe, Daniela, Nicolaus, Marcel, Ricker, Robert, Regnery, Julia, Kolabutin, Nikolai, Shimanshuck, Egor, Oggier, Marc, Raphael, Ian, Stroeve, Julienne, Lehning, Michael, Wagner, David N, Shupe, Matthew D, Cox, Christopher, Persson, Ola G, Uttal, Taneil, Frey, Markus M, Kirchgaessner, Amélie, Schneebeli, Martin, Jaggi, Matthias, Macfarlane, Amy R, Itkin, Polona, Arndt, Stefanie, Hendricks, Stefan, Krampe, Daniela, Nicolaus, Marcel, Ricker, Robert, Regnery, Julia, Kolabutin, Nikolai, Shimanshuck, Egor, Oggier, Marc, Raphael, Ian, Stroeve, Julienne, and Lehning, Michael

Abstract

Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERA5 reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 m SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio2 pluviometer and the OTT Parsivel2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERA5 reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based Ka-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERA5. Based on the results, we suggest the Ka-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 m and a preci

Published
2022

14. Overview of the MOSAiC expedition: Snow and sea ice

Author

Nicolaus, Marcel, Perovich, Donald K., Spreen, Gunnar, Granskog, Mats A., von Albedyll, Luisa, Angelopoulos, Michael, Anhaus, Philipp, Arndt, Stefanie, Belter, H. Jakob, Bessonov, Vladimir, Birnbaum, Gerit, Brauchle, Jörg, Calmer, Radiance, Cardellach, Estel, Cheng, Bin, Clemens-Sewall, David, Dadic, Ruzica, Damm, Ellen, de Boer, Gijs, Demir, Oguz, Dethloff, Klaus, Divine, Dmitry V., Fong, Allison A., Fons, Steven, Frey, Markus M., Fuchs, Niels, Gabarró, Carolina, Gerland, Sebastian, Goessling, Helge F., Gradinger, Rolf, Haapala, Jari, Haas, Christian, Hamilton, Jonathan, Hannula, Henna-Reetta, Hendricks, Stefan, Herber, Andreas, Heuzé, Céline, Hoppmann, Mario, Høyland, Knut Vilhelm, Huntemann, Marcus, Hutchings, Jennifer K., Hwang, Byongjun, Itkin, Polona, Jacobi, Hans-Werner, Jaggi, Matthias, Jutila, Arttu, Kaleschke, Lars, Katlein, Christian, Kolabutin, Nikolai, Krampe, Daniela, Kristensen, Steen Savstrup, Krumpen, Thomas, Kurtz, Nathan, Lampert, Astrid, Lange, Benjamin Allen, Lei, Ruibo, Light, Bonnie, Linhardt, Felix, Liston, Glen E., Loose, Brice, Macfarlane, Amy R., Mahmud, Mallik, Matero, Ilkka O., Maus, Sönke, Morgenstern, Anne, Naderpour, Reza, Nandan, Vishnu, Niubom, Alexey, Oggier, Marc, Oppelt, Natascha, Pätzold, Falk, Perron, Christophe, Petrovsky, Tomasz, Pirazzini, Roberta, Polashenski, Chris, Rabe, Benjamin, Raphael, Ian A., Regnery, Julia, Rex, Markus, Ricker, Robert, Riemann-Campe, Kathrin, Rinke, Annette, Rohde, Jan, Salganik, Evgenii, Scharien, Randall K., Schiller, Martin, Schneebeli, Martin, Semmling, Maximilian, Shimanchuk, Egor, Shupe, Matthew D., Smith, Madison M., Smolyanitsky, Vasily, Sokolov, Vladimir, Stanton, Tim, Stroeve, Julienne, Thielke, Linda, Timofeeva, Anna, Tonboe, Rasmus Tage, Tavri, Aikaterini, Tsamados, Michel, Wagner, David N., Watkins, Daniel, Webster, Melinda, Wendisch, Manfred, Nicolaus, Marcel, Perovich, Donald K., Spreen, Gunnar, Granskog, Mats A., von Albedyll, Luisa, Angelopoulos, Michael, Anhaus, Philipp, Arndt, Stefanie, Belter, H. Jakob, Bessonov, Vladimir, Birnbaum, Gerit, Brauchle, Jörg, Calmer, Radiance, Cardellach, Estel, Cheng, Bin, Clemens-Sewall, David, Dadic, Ruzica, Damm, Ellen, de Boer, Gijs, Demir, Oguz, Dethloff, Klaus, Divine, Dmitry V., Fong, Allison A., Fons, Steven, Frey, Markus M., Fuchs, Niels, Gabarró, Carolina, Gerland, Sebastian, Goessling, Helge F., Gradinger, Rolf, Haapala, Jari, Haas, Christian, Hamilton, Jonathan, Hannula, Henna-Reetta, Hendricks, Stefan, Herber, Andreas, Heuzé, Céline, Hoppmann, Mario, Høyland, Knut Vilhelm, Huntemann, Marcus, Hutchings, Jennifer K., Hwang, Byongjun, Itkin, Polona, Jacobi, Hans-Werner, Jaggi, Matthias, Jutila, Arttu, Kaleschke, Lars, Katlein, Christian, Kolabutin, Nikolai, Krampe, Daniela, Kristensen, Steen Savstrup, Krumpen, Thomas, Kurtz, Nathan, Lampert, Astrid, Lange, Benjamin Allen, Lei, Ruibo, Light, Bonnie, Linhardt, Felix, Liston, Glen E., Loose, Brice, Macfarlane, Amy R., Mahmud, Mallik, Matero, Ilkka O., Maus, Sönke, Morgenstern, Anne, Naderpour, Reza, Nandan, Vishnu, Niubom, Alexey, Oggier, Marc, Oppelt, Natascha, Pätzold, Falk, Perron, Christophe, Petrovsky, Tomasz, Pirazzini, Roberta, Polashenski, Chris, Rabe, Benjamin, Raphael, Ian A., Regnery, Julia, Rex, Markus, Ricker, Robert, Riemann-Campe, Kathrin, Rinke, Annette, Rohde, Jan, Salganik, Evgenii, Scharien, Randall K., Schiller, Martin, Schneebeli, Martin, Semmling, Maximilian, Shimanchuk, Egor, Shupe, Matthew D., Smith, Madison M., Smolyanitsky, Vasily, Sokolov, Vladimir, Stanton, Tim, Stroeve, Julienne, Thielke, Linda, Timofeeva, Anna, Tonboe, Rasmus Tage, Tavri, Aikaterini, Tsamados, Michel, Wagner, David N., Watkins, Daniel, Webster, Melinda, and Wendisch, Manfred

Abstract

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

Published
2022

15. Snowfall and snow accumulation during the MOSAiC winter and spring seasons

Author

Wagner, David N., Shupe, Matthew D., Cox, Christopher, Persson, Ola G., Uttal, Taneil, Frey, Markus M., Kirchgaessner, Amélie, Schneebeli, Martin, Jaggi, Matthias, Macfarlane, Amy R., Itkin, Polona, Arndt, Stefanie, Hendricks, Stefan, Krampe, Daniela, Nicolaus, Marcel, Ricker, Robert, Regnery, Julia, Kolabutin, Nikolai, Shimanshuck, Egor, Oggier, Marc, Raphael, Ian, Stroeve, Julienne, Lehning, Michael, Wagner, David N., Shupe, Matthew D., Cox, Christopher, Persson, Ola G., Uttal, Taneil, Frey, Markus M., Kirchgaessner, Amélie, Schneebeli, Martin, Jaggi, Matthias, Macfarlane, Amy R., Itkin, Polona, Arndt, Stefanie, Hendricks, Stefan, Krampe, Daniela, Nicolaus, Marcel, Ricker, Robert, Regnery, Julia, Kolabutin, Nikolai, Shimanshuck, Egor, Oggier, Marc, Raphael, Ian, Stroeve, Julienne, and Lehning, Michael

Abstract

Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERA5 reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio2 pluviometer and the OTT Parsivel2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERA5 reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based Ka-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERA5. Based on the results, we suggest the Ka-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a pre

Published
2022

16. Overview of the MOSAiC expedition: Snow and sea ice

Author

German Research Foundation, National Science Foundation (US), European Commission, Agencia Estatal de Investigación (España), Department of Energy (US), National Aeronautics and Space Administration (US), European Space Agency, Canadian Space Agency, Research Council of Norway, Natural Environment Research Council (UK), Swedish Research Council, Swedish Polar Research Secretariat, Swiss Polar Institute, Dr. Werner-Petersen Foundation, European Organisation for the Exploitation of Meteorological Satellites, Nicolaus, Marcel, Perovich, Donald K., Spreen, Gunnar, Granskog, Mats A., von Albedyll, Luisa, Angelopoulos, Michael, Anhaus, Philipp, Arndt, Stefanie, Belter, H. Jakob, Bessonov, Vladimir, Birnbaum, Gerit, Wagner, David N., Watkins, Daniel, Webster, Melinda, Wendisch, Manfred, Brauchle, Jörg, Calmer, Radiance, Cardellach, Estel, Cheng, Bin, Clemens-Sewall, David, Dadic, Ruzica, Damm, Ellen, Boer, Gijs de, Demir, Oguz, Dethloff, Klaus, Divine, Dmitry V., Fong, Allison A., Fons, Steven, Frey, Markus M., Fuchs, Niel, Gabarró, Carolina, Gerland, Sebastian, Goessling, Helge F., Gradinger, Rolf, Haapala, Jari, Haas, Christian, Hamilton, Jonathan, Hannula, Henna-Reetta, Hendricks, Stefan, Herber, Adreas, Heuzé, Céline, Hoppmann, Mario, Høyland, Knut Vilhelm, Huntemann, Marcus, Hutchings, Jennifer K., Hwang, Byongjun, Itkin, Polona, Jacobi, Hans-Werner, Jaggi, Matthias, Jutila, Arttu, Kaleschke, Lars, Katlein, Christian, Kolabutin, Nikolai, Krampe, Daniela, Kristensen, Steen Savstrup, Krumpen, Thomas, Kurtz, Nathan, Lampert, Astrid, Lange, Benjamin Allen, Lei, Ruibo, Light, Bonnie, Linhardt, Felix, Liston, Glen E., Loose, Brice, Macfarlane, Amy R., Mahmud, Mallik S., Matero, Ilkka O., Maus, Sönke, Morgenstern, Anne, Naderpour, Reza, Nandan, Vishnu, Niubom, Alexey, Oggier, Marc, Oppelt, Natascha, Pätzold, Falk, Perron, Christophe, Petrovsky, Tomasz, Pirazzini, Roberta, Polashenski, Chris, Rabe, Benjamin, Raphael, Ian A., Regnery, Julia, Rex, Markus, Ricker, Robert, Riemann-Campe, K., Rinke, Annette, Rohde, Jan, Salganik, Evgenii, Scharien, Randy, Schiller, Martin, Schneebeli, Martin, Semmling, Maximilian, Shimanchuk, Egor, Shupe, Matthew D., Smith, Madison, Smolyanitsky, Vasily, Sokolov, Vladimir, Stanton, Tim, Stroeve, Julienne, Thielke, Linda, Timofeeva, Anna, Tonboe, Rasmus, Tavrii, Aikaterini, Tsamados, Michel, German Research Foundation, National Science Foundation (US), European Commission, Agencia Estatal de Investigación (España), Department of Energy (US), National Aeronautics and Space Administration (US), European Space Agency, Canadian Space Agency, Research Council of Norway, Natural Environment Research Council (UK), Swedish Research Council, Swedish Polar Research Secretariat, Swiss Polar Institute, Dr. Werner-Petersen Foundation, European Organisation for the Exploitation of Meteorological Satellites, Nicolaus, Marcel, Perovich, Donald K., Spreen, Gunnar, Granskog, Mats A., von Albedyll, Luisa, Angelopoulos, Michael, Anhaus, Philipp, Arndt, Stefanie, Belter, H. Jakob, Bessonov, Vladimir, Birnbaum, Gerit, Wagner, David N., Watkins, Daniel, Webster, Melinda, Wendisch, Manfred, Brauchle, Jörg, Calmer, Radiance, Cardellach, Estel, Cheng, Bin, Clemens-Sewall, David, Dadic, Ruzica, Damm, Ellen, Boer, Gijs de, Demir, Oguz, Dethloff, Klaus, Divine, Dmitry V., Fong, Allison A., Fons, Steven, Frey, Markus M., Fuchs, Niel, Gabarró, Carolina, Gerland, Sebastian, Goessling, Helge F., Gradinger, Rolf, Haapala, Jari, Haas, Christian, Hamilton, Jonathan, Hannula, Henna-Reetta, Hendricks, Stefan, Herber, Adreas, Heuzé, Céline, Hoppmann, Mario, Høyland, Knut Vilhelm, Huntemann, Marcus, Hutchings, Jennifer K., Hwang, Byongjun, Itkin, Polona, Jacobi, Hans-Werner, Jaggi, Matthias, Jutila, Arttu, Kaleschke, Lars, Katlein, Christian, Kolabutin, Nikolai, Krampe, Daniela, Kristensen, Steen Savstrup, Krumpen, Thomas, Kurtz, Nathan, Lampert, Astrid, Lange, Benjamin Allen, Lei, Ruibo, Light, Bonnie, Linhardt, Felix, Liston, Glen E., Loose, Brice, Macfarlane, Amy R., Mahmud, Mallik S., Matero, Ilkka O., Maus, Sönke, Morgenstern, Anne, Naderpour, Reza, Nandan, Vishnu, Niubom, Alexey, Oggier, Marc, Oppelt, Natascha, Pätzold, Falk, Perron, Christophe, Petrovsky, Tomasz, Pirazzini, Roberta, Polashenski, Chris, Rabe, Benjamin, Raphael, Ian A., Regnery, Julia, Rex, Markus, Ricker, Robert, Riemann-Campe, K., Rinke, Annette, Rohde, Jan, Salganik, Evgenii, Scharien, Randy, Schiller, Martin, Schneebeli, Martin, Semmling, Maximilian, Shimanchuk, Egor, Shupe, Matthew D., Smith, Madison, Smolyanitsky, Vasily, Sokolov, Vladimir, Stanton, Tim, Stroeve, Julienne, Thielke, Linda, Timofeeva, Anna, Tonboe, Rasmus, Tavrii, Aikaterini, and Tsamados, Michel

Abstract

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice

Published
2022

17. Overview of the MOSAiC expedition

Author

Nicolaus, Marcel, Perovich, Donald K., Spreen, Gunnar, Granskog, Mats A., von Albedyll, Luisa, Angelopoulos, Michael, Anhaus, Philipp, Arndt, Stefanie, Belter, H. Jakob, Bessonov, Vladimir, Birnbaum, Gerit, Brauchle, Jörg, Calmer, Radiance, Cardellach, Estel, Cheng, Bin, Clemens-Sewall, David, Dadic, Ruzica, Damm, Ellen, de Boer, Gijs, Demir, Oguz, Dethloff, Klaus, Divine, Dmitry V., Fong, Allison A., Fons, Steven, Frey, Markus M., Fuchs, Niels, Gabarró, Carolina, Gerland, Sebastian, Goessling, Helge F., Gradinger, Rolf, Haapala, Jari, Haas, Christian, Hamilton, Jonathan, Hannula, Henna-Reetta, Hendricks, Stefan, Herber, Andreas, Heuzé, Céline, Hoppmann, Mario, Høyland, Knut Vilhelm, Huntemann, Marcus, Hutchings, Jennifer K., Hwang, Byongjun, Itkin, Polona, Jacobi, Hans-Werner, Jaggi, Matthias, Jutila, Arttu, Kaleschke, Lars, Katlein, Christian, Kolabutin, Nikolai, Krampe, Daniela, Kristensen, Steen Savstrup, Krumpen, Thomas, Kurtz, Nathan, Lampert, Astrid, Lange, Benjamin Allen, Lei, Ruibo, Light, Bonnie, Linhardt, Felix, Liston, Glen E., Loose, Brice, Macfarlane, Amy R., Mahmud, Mallik, Matero, Ilkka O., Maus, Sönke, Morgenstern, Anne, Naderpour, Reza, Nandan, Vishnu, Niubom, Alexey, Oggier, Marc, Oppelt, Natascha, Pätzold, Falk, Perron, Christophe, Petrovsky, Tomasz, Pirazzini, Roberta, Polashenski, Chris, Rabe, Benjamin, Raphael, Ian A., Regnery, Julia, Rex, Markus, Ricker, Robert, Riemann-Campe, Kathrin, Rinke, Annette, Rohde, Jan, Salganik, Evgenii, Scharien, Randall K., Schiller, Martin, Schneebeli, Martin, Semmling, Maximilian, Shimanchuk, Egor, Shupe, Matthew D., Smith, Madison M., Smolyanitsky, Vasily, Sokolov, Vladimir, Stanton, Tim, Stroeve, Julienne, Thielke, Linda, Timofeeva, Anna, Tonboe, Rasmus Tage, Tavri, Aikaterini, Tsamados, Michel, Wagner, David N., Watkins, Daniel, Webster, Melinda, Wendisch, Manfred, Nicolaus, Marcel, Perovich, Donald K., Spreen, Gunnar, Granskog, Mats A., von Albedyll, Luisa, Angelopoulos, Michael, Anhaus, Philipp, Arndt, Stefanie, Belter, H. Jakob, Bessonov, Vladimir, Birnbaum, Gerit, Brauchle, Jörg, Calmer, Radiance, Cardellach, Estel, Cheng, Bin, Clemens-Sewall, David, Dadic, Ruzica, Damm, Ellen, de Boer, Gijs, Demir, Oguz, Dethloff, Klaus, Divine, Dmitry V., Fong, Allison A., Fons, Steven, Frey, Markus M., Fuchs, Niels, Gabarró, Carolina, Gerland, Sebastian, Goessling, Helge F., Gradinger, Rolf, Haapala, Jari, Haas, Christian, Hamilton, Jonathan, Hannula, Henna-Reetta, Hendricks, Stefan, Herber, Andreas, Heuzé, Céline, Hoppmann, Mario, Høyland, Knut Vilhelm, Huntemann, Marcus, Hutchings, Jennifer K., Hwang, Byongjun, Itkin, Polona, Jacobi, Hans-Werner, Jaggi, Matthias, Jutila, Arttu, Kaleschke, Lars, Katlein, Christian, Kolabutin, Nikolai, Krampe, Daniela, Kristensen, Steen Savstrup, Krumpen, Thomas, Kurtz, Nathan, Lampert, Astrid, Lange, Benjamin Allen, Lei, Ruibo, Light, Bonnie, Linhardt, Felix, Liston, Glen E., Loose, Brice, Macfarlane, Amy R., Mahmud, Mallik, Matero, Ilkka O., Maus, Sönke, Morgenstern, Anne, Naderpour, Reza, Nandan, Vishnu, Niubom, Alexey, Oggier, Marc, Oppelt, Natascha, Pätzold, Falk, Perron, Christophe, Petrovsky, Tomasz, Pirazzini, Roberta, Polashenski, Chris, Rabe, Benjamin, Raphael, Ian A., Regnery, Julia, Rex, Markus, Ricker, Robert, Riemann-Campe, Kathrin, Rinke, Annette, Rohde, Jan, Salganik, Evgenii, Scharien, Randall K., Schiller, Martin, Schneebeli, Martin, Semmling, Maximilian, Shimanchuk, Egor, Shupe, Matthew D., Smith, Madison M., Smolyanitsky, Vasily, Sokolov, Vladimir, Stanton, Tim, Stroeve, Julienne, Thielke, Linda, Timofeeva, Anna, Tonboe, Rasmus Tage, Tavri, Aikaterini, Tsamados, Michel, Wagner, David N., Watkins, Daniel, Webster, Melinda, and Wendisch, Manfred

Abstract

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

Published
2022

18. Snowfall and snow accumulation during the MOSAiC winter and spring seasons

Author

Wagner, David N., primary, Shupe, Matthew D., additional, Cox, Christopher, additional, Persson, Ola G., additional, Uttal, Taneil, additional, Frey, Markus M., additional, Kirchgaessner, Amélie, additional, Schneebeli, Martin, additional, Jaggi, Matthias, additional, Macfarlane, Amy R., additional, Itkin, Polona, additional, Arndt, Stefanie, additional, Hendricks, Stefan, additional, Krampe, Daniela, additional, Nicolaus, Marcel, additional, Ricker, Robert, additional, Regnery, Julia, additional, Kolabutin, Nikolai, additional, Shimanshuck, Egor, additional, Oggier, Marc, additional, Raphael, Ian, additional, Stroeve, Julienne, additional, and Lehning, Michael, additional

Published
2022
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19. Overview of the MOSAiC expedition: Snow and sea ice

Author

Nicolaus, Marcel, primary, Perovich, Donald K., additional, Spreen, Gunnar, additional, Granskog, Mats A., additional, von Albedyll, Luisa, additional, Angelopoulos, Michael, additional, Anhaus, Philipp, additional, Arndt, Stefanie, additional, Belter, H. Jakob, additional, Bessonov, Vladimir, additional, Birnbaum, Gerit, additional, Brauchle, Jörg, additional, Calmer, Radiance, additional, Cardellach, Estel, additional, Cheng, Bin, additional, Clemens-Sewall, David, additional, Dadic, Ruzica, additional, Damm, Ellen, additional, de Boer, Gijs, additional, Demir, Oguz, additional, Dethloff, Klaus, additional, Divine, Dmitry V., additional, Fong, Allison A., additional, Fons, Steven, additional, Frey, Markus M., additional, Fuchs, Niels, additional, Gabarró, Carolina, additional, Gerland, Sebastian, additional, Goessling, Helge F., additional, Gradinger, Rolf, additional, Haapala, Jari, additional, Haas, Christian, additional, Hamilton, Jonathan, additional, Hannula, Henna-Reetta, additional, Hendricks, Stefan, additional, Herber, Andreas, additional, Heuzé, Céline, additional, Hoppmann, Mario, additional, Høyland, Knut Vilhelm, additional, Huntemann, Marcus, additional, Hutchings, Jennifer K., additional, Hwang, Byongjun, additional, Itkin, Polona, additional, Jacobi, Hans-Werner, additional, Jaggi, Matthias, additional, Jutila, Arttu, additional, Kaleschke, Lars, additional, Katlein, Christian, additional, Kolabutin, Nikolai, additional, Krampe, Daniela, additional, Kristensen, Steen Savstrup, additional, Krumpen, Thomas, additional, Kurtz, Nathan, additional, Lampert, Astrid, additional, Lange, Benjamin Allen, additional, Lei, Ruibo, additional, Light, Bonnie, additional, Linhardt, Felix, additional, Liston, Glen E., additional, Loose, Brice, additional, Macfarlane, Amy R., additional, Mahmud, Mallik, additional, Matero, Ilkka O., additional, Maus, Sönke, additional, Morgenstern, Anne, additional, Naderpour, Reza, additional, Nandan, Vishnu, additional, Niubom, Alexey, additional, Oggier, Marc, additional, Oppelt, Natascha, additional, Pätzold, Falk, additional, Perron, Christophe, additional, Petrovsky, Tomasz, additional, Pirazzini, Roberta, additional, Polashenski, Chris, additional, Rabe, Benjamin, additional, Raphael, Ian A., additional, Regnery, Julia, additional, Rex, Markus, additional, Ricker, Robert, additional, Riemann-Campe, Kathrin, additional, Rinke, Annette, additional, Rohde, Jan, additional, Salganik, Evgenii, additional, Scharien, Randall K., additional, Schiller, Martin, additional, Schneebeli, Martin, additional, Semmling, Maximilian, additional, Shimanchuk, Egor, additional, Shupe, Matthew D., additional, Smith, Madison M., additional, Smolyanitsky, Vasily, additional, Sokolov, Vladimir, additional, Stanton, Tim, additional, Stroeve, Julienne, additional, Thielke, Linda, additional, Timofeeva, Anna, additional, Tonboe, Rasmus Tage, additional, Tavri, Aikaterini, additional, Tsamados, Michel, additional, Wagner, David N., additional, Watkins, Daniel, additional, Webster, Melinda, additional, and Wendisch, Manfred, additional

Published
2022
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20. Thermal Conductivity of Snow on Arctic Sea Ice.

Author

Macfarlane, Amy R., Löwe, Henning, Gimenes, Lucille, Wagner, David N., Dadic, Ruzica, Ottersberg, Rafael, Hämmerle, Stefan, and Schneebeli, Martin

Subjects
THERMAL conductivity, SEA ice, THERMAL properties, SNOW cover, SNOW accumulation, GLACIAL Epoch, THERMAL resistance
Abstract

Snow significantly impacts the seasonal growth of Arctic sea ice due to its thermally insulating properties. Various measurements and parametrizations of thermal properties exist, but an assessment of the entire seasonal evolution of thermal conductivity and snow resistance is hitherto lacking. Using the comprehensive snow data set from the MOSAiC expedition, we have evaluated for the first time the seasonal evolution of the snow's thermal conductivity and thermal resistance on different ice ages (leads, first and second-year ice) and topographic features (ridges). Combining different measurement parametrizations and assessing the robustness against spatial variability, we infer and quantify a hitherto undocumented feature in the seasonal dynamics of snow on sea ice. We observe an increase in thermal conductivity up to March and a decrease thereafter, both on first-year and second-year ice before the melt period started. Since a similar non-monotonic behaviour is extracted for the snow depth, the thermal resistance of snow on level sea ice remains approximately constant with a value of 515 ± 404 m2 K W−1 on first-year ice and 660 ± 475m2 K W−1 on second-year ice. We found approximately three times higher thermal resistance on ridges (1411 ± 910 m2 K W−1). Our findings are that the micropenetrometer-derived thermal conductivities give accurate values, and confirm that spatial variability of the snow cover is vertically and horizontally large. The implications of our findings for Arctic sea ice are discussed. [ABSTRACT FROM AUTHOR]

Published
2023
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23. Snow microstructure on sea ice: Importance for remote sensing applications

Author

Macfarlane, Amy R., Arndt, Stefanie, Dadic, Ruzica, Gabarró, Carolina, Light, Bonnie, Mahmud, Mallik S., Naderpour, Reza, Scharien, Randy, Smith, Madison, Spreen, Gunnar, Stroeve, Julienne, Tavrii, Aikaterini, Wagner, David N., Schneebeli, Martin, Macfarlane, Amy R., Arndt, Stefanie, Dadic, Ruzica, Gabarró, Carolina, Light, Bonnie, Mahmud, Mallik S., Naderpour, Reza, Scharien, Randy, Smith, Madison, Spreen, Gunnar, Stroeve, Julienne, Tavrii, Aikaterini, Wagner, David N., and Schneebeli, Martin

Abstract

Snow plays a key role in interpreting satellite remote sensing data from both active and passive sensors in the high Arctic and therefore impacts retrieved sea ice variables from these systems ( e.g., sea ice extent, thickness and age). Because there is high spatial and temporal variability in snow properties, this porous layer adds uncertainty to the interpretation of signals from spaceborne optical sensors, microwave radiometers, and radars (scatterometers, SAR, altimeters). We therefore need to improve our understanding of physical snow properties, including the snow specific surface area, snow wetness and the stratigraphy of the snowpack on different ages of sea ice in the high Arctic. The MOSAiC expedition provided a unique opportunity to deploy equivalent remote sensing sensors in-situ on the sea ice similar to those mounted on satellite platforms. To aid in the interpretation of the in situ remote sensing data collected, we used a micro computed tomography (micro-CT) device. This instrument was installed on board the Polarstern and was used to evaluate geometric and physical snow properties of in-situ snow samples. This allowed us to relate the snow samples directly to the data from the remote sensing instruments, with the goal of improving interpretation of satellite retrievals. Our data covers the full annual evolution of the snow cover properties on multiple ice types and ice topographies including level first-year (FYI), level multi-year ice (MYI) and ridges. First analysis of the data reveals possible uncertainties in the retrieved remote sensing data products related to previously unknown seasonal processes in the snowpack. For example, the refrozen porous summer ice surface, known as surface scattering layer, caused the formation of a hard layer at the multiyear ice/snow interface in the winter months, leading to significant differences in the snow stratigraphy and remote sensing signals from first-year ice, which has not experienced summer melt, and m

Published
2021

24. Wind Transport of Snow Impacts Ka- and Ku-band Radar Signatures on Arctic Sea Ice.

Author

Nandan, Vishnu, Willatt, Rosemary, Mallett, Robbie, Stroeve, Julienne, Geldsetzer, Torsten, Scharien, Randall, Tonboe, Rasmus, Landy, Jack, Clemens-Sewall, David, Jutila, Arttu, Wagner, David N., Krampe, Daniela, Huntemann, Marcus, Yackel, John, Mahmud, Mallik, Jensen, David, Newman, Thomas, Hendricks, Stefan, Spreen, Gunnar, and Macfarlane, Amy

Abstract

Wind transport alters the snow topography and microstructure on sea ice through snow redistribution controlled by deposition and erosion. The impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution on Arctic sea ice from Ka- and Ku-band radar signatures. Measurements were obtained during two wind events in November 2019 during the MOSAiC expedition. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coincident with surface height changes measured from a terrestrial laser scanner are observed. At both frequencies, snow redistribution events increased the dominance of the air/snow interface at nadir as the dominant radar scattering surface, due to wind densifying the snow surface and uppermost layers. The radar waveform data also detect the presence of previous air/snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air/snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite radar altimeters. The relative scattering contribution of the air/snow interface decreases, and the snow/sea ice interface increases with increasing incidence angles. Relative to pre-wind conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Binned backscatter within 5° azimuth bins reveals substantial backscatter variability in the radar footprint at all incidence angles and polarizations. The sensitivity of the co-polarized phase difference is linked to changes in snow settling and temperature-gradient induced grain metamorphism, demonstrating the potential of the radar to discriminate between newly deposited and older snow on sea ice. Our results reveal the importance of wind, through its geophysical impact on Ka- and Ku-band radar signatures of snow on sea ice and has implications for reliable interpretation of airborne and satellite radar measurements of snow-covered sea ice. [ABSTRACT FROM AUTHOR]

Published
2022
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25. Snowfall and snow accumulation processes during the MOSAiC winter and spring season

Author

Wagner, David N., primary, Shupe, Matthew D., additional, Persson, Ola G., additional, Uttal, Taneil, additional, Frey, Markus M., additional, Kirchgaessner, Amélie, additional, Schneebeli, Martin, additional, Jaggi, Matthias, additional, Macfarlane, Amy R., additional, Itkin, Polona, additional, Arndt, Stefanie, additional, Hendricks, Stefan, additional, Krampe, Daniela, additional, Ricker, Robert, additional, Regnery, Julia, additional, Kolabutin, Nikolai, additional, Shimanshuck, Egor, additional, Oggier, Marc, additional, Raphael, Ian, additional, and Lehning, Michael, additional

Published
2021
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26. Snowfall and snow accumulation processes during MOSAiC

Author

Wagner, David N., primary, Shupe, Matthew D., additional, Persson, Ola G., additional, Uttal, Taneil, additional, Frey, Markus, additional, Kirchgaessner, Amélie, additional, Schneebeli, Martin, additional, Jaggi, Matthias, additional, Macfarlane, Amy R., additional, Itkin, Polona, additional, Arndt, Stefanie, additional, Hendricks, Stefan, additional, Krampe, Daniela, additional, Regnery, Julia, additional, Ricker, Robert, additional, Kolabutin, Nikolai, additional, Shimanchuck, Egor, additional, Oggier, Marc, additional, Raphael, Ian, additional, and Lehning, Michael, additional

Published
2021
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28. Snow microstructure on sea ice: Importance for remote sensing applications

Author

Macfarlane, Amy R., primary, Arndt, Stefanie, additional, Dadic, Ruzica, additional, Gabarró, Carolina, additional, Light, Bonnie, additional, Mahmud, Mallik, additional, Naderpour, Reza, additional, Scharien, Randall, additional, Smith, Madison, additional, Spreen, Gunnar, additional, Stroeve, Julienne, additional, Tavri, Aikaterini, additional, Wagner, David N., additional, and Schneebeli, Martin, additional

Published
2021
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29. Modelling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

Author

Hames, Océane, JafariCRYOS, School of Architecture, Civil and EnvironmentalEngineering, EPFL, Lausanne, Switzerland;These authors contributed equally to this work;mahdi.jafari@epfl.ch, Mahdi, Wagner, David N., Raphael, Ian, Clemens-Sewall, David, Polashenski, Chris, Shupe, Matthew D., Schneebeli, Martin, and Lehning, Michael

Subjects
SEA ice, SURFACE dynamics, FLUID dynamics, MEASUREMENT errors, SURFACE structure, COMPUTER simulation
Abstract

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these regions, the wind has a substantial effect and redistributes a large part of the snow, which complicates precipitation estimates. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove these uncertainties. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial lidar observations of surface dynamics to simulate snow deposition on a piece of MOSAiC sea ice with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against terrestrial laser scans. However, the approximations imposed by the numerical framework together with potential measurement errors (precipitation) give rise to quantitative inaccuracies. The modelling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic. [ABSTRACT FROM AUTHOR]

Published
2021
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31. The Obligation of Government Toward Humanity: The Role of the State in the Common Good.

Author

WAGNER, DAVID N.

Subjects
COMMON good, HUMANITY, OBLIGATIONS (Law), CHURCH & state, REVELATION
Abstract

In this article the author discusses obligation of the government toward humanity and the role played by state in common good of the people. He reflects on philosopher John Finnis article "Religion and State: Some Main Issues and Sources," which explores the place of religion in political communities. He examines the relationship of church and state by discussing some church teachings of the last century including revelation.

Published
2012

32. Snowfall and snow accumulation during the MOSAiC winter and spring seasons

Author

Wagner, David N., Shupe, Matthew D., Cox, Christopher, Persson, Ola G., Uttal, Taneil, Frey, Markus M., Kirchgaessner, Amélie, Schneebeli, Martin, Jaggi, Matthias, MacFarlane, Amy R., Itkin, Polona, Arndt, Stefanie, Hendricks, Stefan, Krampe, Daniela, Nicolaus, Marcel, Ricker, Robert, Regnery, Julia, Kolabutin, Nikolai, Shimanshuck, Egor, Oggier, Marc, Raphael, Ian, Stroeve, Julienne, and Lehning, Michael

Subjects
sea-ice, thermodynamics, model, variability, surface heat-budget, microstructure, blowing snow, precipitation, cover, redistribution
Abstract

Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERA5 reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio2 pluviometer and the OTT Parsivel2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERA5 reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based Ka-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERA5. Based on the results, we suggest the Ka-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a precipitation mass loss of the snow cover due to erosion and sublimation as between 47 % and 68 %, for the time period between 31 October 2019 and 26 April 2020. Extending this period beyond available snow cover measurements, we suggest a cumulative snowfall of 98–114 mm.

33. Thermal Conductivity of Snow on Arctic Sea Ice

Author

Macfarlane, Amy R., Löwe, Henning, Gimenes, Lucille, Wagner, David N., Dadiz, Ruzica, Hämmerle, Stefan, Schneebeli, Martin, Dadic, Ruzica, and Ottersberg, Rafael

Subjects
Thermal conductivity, Snow, sea ice, MOSAiC
Abstract

Snow significantly impacts the seasonal growth of Arctic sea ice due to its thermally insulating properties. Various measurements and parametrizations of thermal properties exist, but an assessment of the entire seasonal evolution of thermal conductivity and snow resistance is hitherto lacking. Using the comprehensive snow data set from the MOSAiC expedition, we have evaluated for the first time the seasonal evolution of the snow's thermal conductivity and thermal resistance on different ice ages (leads, first and second-year ice) and topographic features (ridges). Combining different measurement parametrizations and assessing the robustness against spatial variability, we infer and quantify a hitherto undocumented feature in the seasonal dynamics of snow on sea ice. We observe an increase in thermal conductivity up to March and a decrease thereafter, both on first-year and second-year ice before the melt period started. Since a similar non-monotonic behaviour is extracted for the snow depth, the thermal resistance of snow on level sea ice remains approximately constant with a value of 515 ± 404 m2 K W−1 on first-year ice and 660 ± 475m2 K W−1 on second-year ice. We found approximately three times higher thermal resistance on ridges (1411 ± 910 m2 K W−1). Our findings are that the micropenetrometer-derived thermal conductivities give accurate values, and confirm that spatial variability of the snow cover is vertically and horizontally large. The implications of our findings for Arctic sea ice are discussed.

34. Overview of the MOSAiC expedition: Snow and sea ice

Author

Nicolaus, Marcel, Perovich, Donald K., Spreen, Gunnar, Granskog, Mats A., von Albedyll, Luisa, Angelopoulos, Michael, Anhaus, Philipp, Arndt, Stefanie, Belter, H. Jakob, Bessonov, Vladimir, Birnbaum, Gerit, Brauchle, Joerg, Calmer, Radiance, Cardellach, Estel, Cheng, Bin, Clemens-Sewall, David, Dadic, Ruzica, Damm, Ellen, de Boer, Gijs, Demir, Oguz, Dethloff, Klaus, Divine, Dmitry, V, Fong, Allison A., Fons, Steven, Frey, Markus M., Fuchs, Niels, Gabarro, Carolina, Gerland, Sebastian, Goessling, Helge F., Gradinger, Rolf, Haapala, Jari, Haas, Christian, Hamilton, Jonathan, Hannula, Henna-Reetta, Hendricks, Stefan, Herber, Andreas, Heuze, Celine, Hoppmann, Mario, Hoyland, Knut Vilhelm, Huntemann, Marcus, Hutchings, Jennifer K., Hwang, Byongjun, Itkin, Polona, Jacobi, Hans-Werner, Jaggi, Matthias, Jutila, Arttu, Kaleschke, Lars, Katlein, Christian, Kolabutin, Nikolai, Krampe, Daniela, Kristensen, Steen Savstrup, Krumpen, Thomas, Kurtz, Nathan, Lampert, Astrid, Lange, Benjamin Allen, Lei, Ruibo, Light, Bonnie, Linhardt, Felix, Liston, Glen E., Loose, Brice, Macfarlane, Amy R., Mahmud, Mallik, Matero, Ilkka O., Morgenstern, Anne, Naderpour, Reza, Nandan, Vishnu, Niubom, Alexey, Oggier, Marc, Oppelt, Natascha, Perron, Christophe, Petrovsky, Tomasz, Pirazzini, Roberta, Polashenski, Chris, Rabe, Benjamin, Raphael, Ian A., Regnery, Julia, Rex, Markus, Ricker, Robert, Riemann-Campe, Kathrin, Rinke, Annette, Rohde, Jan, Salganik, Evgenii, Scharien, Randall K., Schiller, Martin, Schneebeli, Martin, Semmling, Maximilian, Shimanchuk, Egor, Shupe, Matthew D., Smith, Madison M., Smolyanitsky, Vasily, Sokolov, Vladimir, Stanton, Tim, Stroeve, Julienne, Thielke, Linda, Timofeeva, Anna, Tonboe, Rasmus Tage, Tavri, Aikaterini, Tsamados, Michel, Wagner, David N., Watkins, Daniel, Webster, Melinda, and Wendisch, Manfred

Subjects
atmosphere-ice-ocean interaction, depth, deformation, arctic drift study, temperature, snow and sea ice, thickness, thermodynamics, frequency, interdisciplinary research, impact, pack ice, mass-balance, coupled climate system, radar
Abstract

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice-ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

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