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2. Lead fractions from SAR-derived sea ice divergence during MOSAiC

Author

Howell, Stephen, von Albedyll, Luisa, Hendricks, Stefan, Hutter, Nils, Murashkin, Dmitrii, Kaleschke, Lars, Willmes, Sascha, Thielke, Linda, Tian-Kunze, Xiangshan, Spreen, Gunnar, Haas, Christian, Howell, Stephen, von Albedyll, Luisa, Hendricks, Stefan, Hutter, Nils, Murashkin, Dmitrii, Kaleschke, Lars, Willmes, Sascha, Thielke, Linda, Tian-Kunze, Xiangshan, Spreen, Gunnar, and Haas, Christian

Abstract

Leads and fractures in sea ice play a crucial role in the heat and gas exchange between the ocean and atmosphere, impacting atmospheric, ecological, and oceanic processes. We estimated lead fractions from high-resolution divergence obtained from satellite synthetic aperture radar (SAR) data and evaluated them against existing lead products. We derived two new lead fraction products from divergence with a spatial resolution of 700mcalculated from daily Sentinel-1 images. For the first lead product, we advected and accumulated the lead fractions of individual time nstances. With those accumulated divergence-derived lead fractions, we comprehensively described the presence of up to 10 d old leads and analyzed their deformation history. For the second lead product, we used only divergence pixels that were identified as part of linear kinematic features (LKFs). Both new lead products accurately captured the formation of new leads with widths of up to a few hundred meters. We resented a Lagrangian time series of the divergence-based lead fractions along the drift of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic Ocean during winter 2019–2020. Lead activity was high in fall and spring, consistent with wind forcing and ice pack consolidation. At larger scales of 50–150 km around the MOSAiC expedition, lead activity on all scales was similar, but differences emerged at smaller scales (10 km). We compared our lead products with six others from satellite and airborne sources, including classified SAR, thermal infrared, microwave radiometer, and altimeter data. We found that the mean lead fractions varied by 1 order of magnitude across different lead products due to different physical lead and sea ice properties observed by the sensors and methodological factors such as spatial resolution. Thus, the choice of lead product should align with the specific application.

Published
2024

4. Lead fractions from SAR-derived sea ice divergence during MOSAiC.

Author

von Albedyll, Luisa, Hendricks, Stefan, Hutter, Nils, Murashkin, Dmitrii, Kaleschke, Lars, Willmes, Sascha, Thielke, Linda, Tian-Kunze, Xiangshan, Spreen, Gunnar, and Haas, Christian

Subjects
SYNTHETIC aperture radar, ARCTIC exploration, ARCTIC climate, SEA ice, CONSUMER preferences, MICROWAVE radiometers
Abstract

Leads and fractures in sea ice play a crucial role in the heat and gas exchange between the ocean and atmosphere, impacting atmospheric, ecological, and oceanic processes. We estimated lead fractions from high-resolution divergence obtained from satellite synthetic aperture radar (SAR) data and evaluated them against existing lead products. We derived two new lead fraction products from divergence with a spatial resolution of 700 m calculated from daily Sentinel-1 images. For the first lead product, we advected and accumulated the lead fractions of individual time instances. With those accumulated divergence-derived lead fractions, we comprehensively described the presence of up to 10 d old leads and analyzed their deformation history. For the second lead product, we used only divergence pixels that were identified as part of linear kinematic features (LKFs). Both new lead products accurately captured the formation of new leads with widths of up to a few hundred meters. We presented a Lagrangian time series of the divergence-based lead fractions along the drift of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic Ocean during winter 2019–2020. Lead activity was high in fall and spring, consistent with wind forcing and ice pack consolidation. At larger scales of 50–150 km around the MOSAiC expedition, lead activity on all scales was similar, but differences emerged at smaller scales (10 km). We compared our lead products with six others from satellite and airborne sources, including classified SAR, thermal infrared, microwave radiometer, and altimeter data. We found that the mean lead fractions varied by 1 order of magnitude across different lead products due to different physical lead and sea ice properties observed by the sensors and methodological factors such as spatial resolution. Thus, the choice of lead product should align with the specific application. [ABSTRACT FROM AUTHOR]

Published
2024
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5. Lead fractions from SAR-derived sea ice divergence during MOSAiC

Author

von Albedyll, Luisa, primary, Hendricks, Stefan, additional, Hutter, Nils, additional, Murashkin, Dmitrii, additional, Kaleschke, Lars, additional, Willmes, Sascha, additional, Thielke, Linda, additional, Tian-Kunze, Xiangshan, additional, Spreen, Gunnar, additional, and Haas, Christian, additional

Published
2023
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6. Winter sea ice characteristics in the central Arctic from thermal infrared imaging

Author

Thielke, Linda

Subjects
leads, Arctic, satellite, heat flux, airborne, thermal infrared, melt ponds, winter, sea ice
Abstract

This dissertation is based on helicopter-borne thermal infrared (TIR) imaging performed during the MOSAiC expedition in the central Arctic in winter. The aim is to increase the understanding of processes influencing the Arctic heat budget. TIR imaging benefits from the large temperature differences between the colder thick sea ice and the warmer leads of open water or covered with thin ice. Between October 2019 and April 2020, 35 helicopter flights were used for investigation on the local (5-10 km) and regional scale (20-40 km). From several thousands of images, surface temperature maps at 1 m resolution were created for each flight. This thesis focuses on (i) melt pond pre-conditioning based on warm temperature anomalies, (ii) lead classification resulting in area fraction, width distribution, and orientations down to the spatial scale of meters, and (iii) the relevance of the satellite sub-footprint scale variability of surface temperatures for the heat exchange. Melt ponds are a crucial part of the summer heat budget as they lower the surface albedo and contribute to the positive ice-albedo feedback. The comparison of winter temperature and summer images from the same ice revealed the presence of warm anomalies of 0.3-2.5 K at the melt pond locations of the subsequent summer. This pre-conditioning enabled a correct seasonal prediction of 41% of the melt ponds. Leads are relevant for the winter heat budget as they allow for an increased heat transfer from the warmer ocean to the colder atmosphere. The determined lead area fraction is 1.2% on average and up to 4% on 24 December 2019, with stronger variability on the local than on the regional scale. The power law distribution of lead width has a negative exponent of 2.63 that is valid to a width of 3 m. Consequently, there is an exponentially larger number of narrow than wider leads. The numerous small-scale leads are not resolved in operationally used satellite products. Due to the lack of sub-footprint scale variability the sensible heat flux derived from these products is underestimated. The decrease of the average sensible heat flux of up to 0.69 W m⁻² between the 1 m and re-gridded 1 km resolution helicopter data has a linear relation with the lead area fraction. A comparison between the overlapping helicopter and satellite surface temperatures of MODIS showed no alignment in spatial variability. The thesis’ findings provide results to improve satellite retrievals and model parameterizations.

Published
2023
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8. Thin and transient meltwater layers and false bottoms in the Arctic sea ice pack—Recent insights on these historically overlooked features

Author

Smith, Madison M, Angot, Hélène, Chamberlain, Emelia J, Droste, Elise S, Karam, Salar, Muilwijk, Morven, Webb, Alison L, Archer, Stephen D, Beck, Ivo, Blomquist, Byron W, Bowman, Jeff, Boyer, Matthew, Bozzato, Deborah, Chierici, Melissa, Creamean, Jessie, D’Angelo, Alessandra, Delille, Bruno, Fer, Ilker, Fong, Allison A, Fransson, Agneta, Fuchs, Niels, Gardner, Jessie, Granskog, Mats A, Hoppe, Clara JM, Hoppema, Mario, Hoppmann, Mario, Mock, Thomas, Muller, Sofia, Müller, Oliver, Nicolaus, Marcel, Nomura, Daiki, Petäjä, Tuukka, Salganik, Evgenii, Schmale, Julia, Schmidt, Katrin, Schulz, Kirstin M, Shupe, Matthew D, Stefels, Jacqueline, Thielke, Linda, Tippenhauer, Sandra, Ulfsbo, Adam, van Leeuwe, Maria, Webster, Melinda, Yoshimura, Masaki, Zhan, Liyang, Smith, Madison M, Angot, Hélène, Chamberlain, Emelia J, Droste, Elise S, Karam, Salar, Muilwijk, Morven, Webb, Alison L, Archer, Stephen D, Beck, Ivo, Blomquist, Byron W, Bowman, Jeff, Boyer, Matthew, Bozzato, Deborah, Chierici, Melissa, Creamean, Jessie, D’Angelo, Alessandra, Delille, Bruno, Fer, Ilker, Fong, Allison A, Fransson, Agneta, Fuchs, Niels, Gardner, Jessie, Granskog, Mats A, Hoppe, Clara JM, Hoppema, Mario, Hoppmann, Mario, Mock, Thomas, Muller, Sofia, Müller, Oliver, Nicolaus, Marcel, Nomura, Daiki, Petäjä, Tuukka, Salganik, Evgenii, Schmale, Julia, Schmidt, Katrin, Schulz, Kirstin M, Shupe, Matthew D, Stefels, Jacqueline, Thielke, Linda, Tippenhauer, Sandra, Ulfsbo, Adam, van Leeuwe, Maria, Webster, Melinda, Yoshimura, Masaki, and Zhan, Liyang

Abstract

The rapid melt of snow and sea ice during the Arctic summer provides a significant source of low-salinity meltwater to the surface ocean on the local scale. The accumulation of this meltwater on, under, and around sea ice floes can result in relatively thin meltwater layers in the upper ocean. Due to the small-scale nature of these upper-ocean features, typically on the order of 1 m thick or less, they are rarely detected by standard methods, but are nevertheless pervasive and critically important in Arctic summer. Observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in summer 2020 focused on the evolution of such layers and made significant advancements in understanding their role in the coupled Arctic system. Here we provide a review of thin meltwater layers in the Arctic, with emphasis on the new findings from MOSAiC. Both prior and recent observational datasets indicate an intermittent yet longlasting (weeks to months) meltwater layer in the upper ocean on the order of 0.1 m to 1.0 m in thickness, with a large spatial range. The presence of meltwater layers impacts the physical system by reducing bottom ice melt and allowing new ice formation via false bottom growth. Collectively, the meltwater layer and false bottoms reduce atmosphere-ocean exchanges of momentum, energy, and material.The impacts on the coupled Arctic system are far-reaching, including acting as a barrier for nutrient and gas exchange and impacting ecosystem diversity and productivity.

Published
2023

9. Preconditioning of Summer Melt Ponds From Winter Sea Ice Surface Temperature

Author

Thielke, Linda, Fuchs, Niels, Spreen, Gunnar, Tremblay, Bruno, Birnbaum, Gerit, Huntemann, Marcus, Hutter, Nils, Itkin, Polona, Jutila, Arttu, Webster, Melinda A, Thielke, Linda, Fuchs, Niels, Spreen, Gunnar, Tremblay, Bruno, Birnbaum, Gerit, Huntemann, Marcus, Hutter, Nils, Itkin, Polona, Jutila, Arttu, and Webster, Melinda A

Abstract

Comparing helicopter-borne surface temperature maps in winter and optical orthomosaics in summer from the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition, we find a strong geometric correlation between warm anomalies in winter and melt pond location the following summer. Warm anomalies are associated with thinner snow and ice, that is, surface depression and refrozen leads, that allow for water accumulation during melt. Warm surface temperature anomalies in January were 0.3–2.5 K warmer on sea ice that later formed melt ponds. A one-dimensional steady-state thermodynamic model shows that the observed surface temperature differences are in line with the observed ice thickness and snow depth. We demonstrate the potential of seasonal prediction of summer melt pond location and coverage from winter surface temperature observations. A threshold-based classification achieves a correct classification for 41% of the melt ponds.

Published
2023

11. Thin and transient meltwater layers and false bottoms in the Arctic sea ice pack—Recent insights on these historically overlooked features

Author

Smith, Madison M., primary, Angot, Hélène, additional, Chamberlain, Emelia J., additional, Droste, Elise S., additional, Karam, Salar, additional, Muilwijk, Morven, additional, Webb, Alison L., additional, Archer, Stephen D., additional, Beck, Ivo, additional, Blomquist, Byron W., additional, Bowman, Jeff, additional, Boyer, Matthew, additional, Bozzato, Deborah, additional, Chierici, Melissa, additional, Creamean, Jessie, additional, D’Angelo, Alessandra, additional, Delille, Bruno, additional, Fer, Ilker, additional, Fong, Allison A., additional, Fransson, Agneta, additional, Fuchs, Niels, additional, Gardner, Jessie, additional, Granskog, Mats A., additional, Hoppe, Clara J. M., additional, Hoppema, Mario, additional, Hoppmann, Mario, additional, Mock, Thomas, additional, Muller, Sofia, additional, Müller, Oliver, additional, Nicolaus, Marcel, additional, Nomura, Daiki, additional, Petäjä, Tuukka, additional, Salganik, Evgenii, additional, Schmale, Julia, additional, Schmidt, Katrin, additional, Schulz, Kirstin M., additional, Shupe, Matthew D., additional, Stefels, Jacqueline, additional, Thielke, Linda, additional, Tippenhauer, Sandra, additional, Ulfsbo, Adam, additional, van Leeuwe, Maria, additional, Webster, Melinda, additional, Yoshimura, Masaki, additional, and Zhan, Liyang, additional

Published
2023
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12. Critically important, yet forgotten: thin and transient meltwater layers and false bottoms in the Arctic sea ice pack

Author

Smith, Madison M., Angot, Helene, Chamberlain, Emelia J., Droste, Elise, Karam, Salar, Muilwijk, Morven, Webb, Alison, Archer, Stephen, Beck, Ivo, Blomquist, Byron, Bowman, Jeff, Boyer, Matthew, Bozzato, Deborah, Chierici, Melissa, Creamean, Jessie, D'Angelo, Alessandra, Delille, Bruno, Fer, Ilker, Fong, Allison A., Fransson, Agneta, Fuchs, Niels, Gardner, Jessie, Granskog, Mats A., Hoppe, Clara J. M., Hoppema, Mario, Hoppmann, Mario, Mock, Thomas, Muller, Sofia, Müller, Oliver, Nicolaus, Marcel, Nomura, Daiki, Petäjä, Tuukka, Salganik, Evgenii, Schmale, Julia, Schmidt, Katrin, Schulz, Kirstin, Shupe, Matthew D., Stefels, Jacqueline, Thielke, Linda, Tippenhauer, Sandra, Ulfsbo, Adam, van Leeuwe, Maria, Webster, Melinda, Yoshimura, Masaki, and Zhan, Liyang

Subjects
Arctic, meltwater, interdisciplinary science, sea ice
Abstract

The rapid melt of snow and sea ice during the Arctic summer provides a significant source of low-salinity meltwater to the surface ocean on the local scale. The accumulation of this meltwater on, under, and around sea ice floes can result in relatively thin meltwater layers in the upper ocean. Due to the small-scale nature of these upper-ocean features, typically on the order of 1 m thick or less, they are rarely detected by standard methods, but are nevertheless pervasive and critically important in Arctic summer. Observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in summer 2020 focused on the evolution of such layers and made significant advancements in understanding their role in the coupled Arctic system. Here we provide a review of thin meltwater layers in the Arctic, with emphasis on the new findings from MOSAiC. Both prior and recent observational datasets indicate an intermittent yet long-lasting (weeks to months) meltwater layer in the upper ocean on the order of 0.1 to 1.0 m in thickness, with a large spatial range. The presence of meltwater layers impacts the physical system by reducing bottom ice melt and allowing new ice formation via false bottom growth. Collectively, the meltwater layer and false bottoms reduce atmosphere-ocean exchanges of momentum, energy, and material. The impacts on the coupled Arctic system are far-reaching, including acting as a barrier for nutrient and gas exchange and impacting ecosystem diversity and productivity.

Published
2023
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14. Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate)

Author

Stroeve, Julienne, primary, Nandan, Vishnu, additional, Willatt, Rosemary, additional, Dadic, Ruzica, additional, Rostosky, Philip, additional, Gallagher, Michael, additional, Mallett, Robbie, additional, Barrett, Andrew, additional, Hendricks, Stefan, additional, Tonboe, Rasmus, additional, McCrystall, Michelle, additional, Serreze, Mark, additional, Thielke, Linda, additional, Spreen, Gunnar, additional, Newman, Thomas, additional, Yackel, John, additional, Ricker, Robert, additional, Tsamados, Michel, additional, Macfarlane, Amy, additional, Hannula, Henna-Reetta, additional, and Schneebeli, Martin, additional

Published
2022
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15. Lead fractions from SAR-derived sea ice divergence during MOSAiC.

Author

von Albedyll, Luisa, Hendricks, Stefan, Hutter, Nils, Murashkin, Dmitrii, Kaleschke, Lars, Willmes, Sascha, Thielke, Linda, Tian-Kunze, Xiangshan, Spreen, Gunnar, and Haas, Christian

Abstract

Leads and fractures in sea ice play a crucial role in the heat and gas exchange between the ocean and atmosphere, impacting atmospheric, ecological, and oceanic processes. Our aim was to estimate lead fractions from high-resolution divergence obtained from satellite synthetic-aperture radar (SAR) data and to evaluate it against existing lead products. We derived two new leadfraction products from divergence with a spatial resolution of 700m calculated from daily Sentinel-1 images. For the first lead product, we advected and accumulated the lead fractions of individual time steps. With those accumulated divergence-derived lead fractions, we described comprehensively the presence of up to 10-day-old leads and analyzed their deformation history. For the second lead product, we used only divergence pixels that were identified as part of linear kinematic features (LKFs). Both new lead products accurately captured the formation of new leads with widths of a few hundred meters. We presented a Lagrangian time series of the divergence-based lead fractions along the drift of the MOSAiC expedition in the central Arctic Ocean during winter 2019/2020. Lead activity was high in fall and spring, consistent with wind forcing and ice pack consolidation. At larger scales of 50-150 km around the MOSAiC expedition, lead activity on all scales was similar, but differences emerged at smaller scales (10 km). We compared our lead products with 6 others from satellite and airborne sources, including classified SAR, thermal infrared, microwave radiometer, and altimeter data. We found that the mean lead fractions varied by 1 magnitude across different lead products due to different physical lead and sea ice properties observed by the sensors and methodological factors such as spatial resolution. Thus, the choice of lead product should align with the specific application. [ABSTRACT FROM AUTHOR]

Published
2023
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18. 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

19. Same same, but different: Lead Fractions from divergence

Author

von Albedyll, Luisa, Murashkin, Dmitrii, Willmes, Sascha, Hutter, Nils, Thielke, Linda, Hendricks, Stefan, Kaleschke, Lars, Tian-Kunze, Xiangshan, Spreen, Gunnar, Haas, Christian, von Albedyll, Luisa, Murashkin, Dmitrii, Willmes, Sascha, Hutter, Nils, Thielke, Linda, Hendricks, Stefan, Kaleschke, Lars, Tian-Kunze, Xiangshan, Spreen, Gunnar, and Haas, Christian

Abstract

In the polar oceans in winter, fractures and leads are the hotspots of exchange between the ocean and atmosphere which are otherwise well separated by sea ice. By altering the heat, gas, and momentum fluxes they play a crucial role in atmospheric, ecological, and oceanic processes. At the same time, leads represent a part of the present state of strain of the ice cover, opening up the possibility to study ice rheology. The transient nature of leads and their narrow appearance has set limits to the detection of leads from satellites. Different approaches using active and passive sensors from the microwave and infrared spectrum are employed so far to observe leads by means of satellite data. They make use of the strong contrast between leads and the surrounding ice pack in (i) surface temperature, (ii) microwave backscatter, (iii) emission or (iv) a change in ice drift speed. With the increasing availability of high-resolution SAR data for the Arctic, we explored the potential to use SAR derived sea ice deformation to estimate lead fractions. We calculated sea ice drift and divergence with a spatial resolution of 1.4 km from daily Sentinel-1 scenes. We obtained the divergence-based lead fraction of a region by summing up all positive divergence pixels multiplied by the respective time step length. We derived a second lead fraction product from the deformation fields that calculates the position of linear kinematic features (LKFs) first. The advantage is a skilled noise reduction, and a tracking algorithm of the deformation zones. We compared divergence- and LKF-based lead fractions to several other established lead fraction products in the Transpolar Drift along the drift track of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) between October 2019 to April 2020. We used lead fractions from helicopter-borne infrared surveys at a grid resolution of 5 m, classified Sentinel-1 (SAR) scenes at 80 m, MODIS (thermal infrared) at 1 km, AMS

Published
2022

20. Remote Sensing of Sea Ice on the MOSAiC Ice Floe - An Overview

Author

Spreen, Gunnar, Cardellach, Estel, Casal, Tânia, Demir, Oguz, Duguay, Claude R., Gabarró, Carolina, Hendricks, Stefan, Huntemann, Marcus, Johnson, Joel T., Kaleschke, Lars, Kristensen, Steen Savstrup, Lemmetyinen, Juha, Mahmud, Mallik S., Naderpour, Reza, Nandan, Vishnu, Ricker, Robert, Rostosky, Philip, Scharien, Randy, Schwank, Mike, Semmling, Maximilian, Stroeve, Julienne, Tavrii, Aikaterini, Thielke, Linda, Tonboe, Rasmus, von Albedyll, Luisa, Yackel, John, Spreen, Gunnar, Cardellach, Estel, Casal, Tânia, Demir, Oguz, Duguay, Claude R., Gabarró, Carolina, Hendricks, Stefan, Huntemann, Marcus, Johnson, Joel T., Kaleschke, Lars, Kristensen, Steen Savstrup, Lemmetyinen, Juha, Mahmud, Mallik S., Naderpour, Reza, Nandan, Vishnu, Ricker, Robert, Rostosky, Philip, Scharien, Randy, Schwank, Mike, Semmling, Maximilian, Stroeve, Julienne, Tavrii, Aikaterini, Thielke, Linda, Tonboe, Rasmus, von Albedyll, Luisa, and Yackel, John

Abstract

During MOSAiC several remote sensing instruments designed for observing the sea ice and its snow cover were installed on the ice floe next to Polarstern and on the vessel itself. Satellite measurements constitute a few of the most important climate data records for polar regions. The MOSAiC experiments will help to improve their quality and better assess their uncertainties. In particular the following measurements were performed during MOSAiC: (i) 0.5-89 GHz microwave radiometers, (ii) L to Ka-band microwave radar scatterometers, (iii) reflected GNSS measurements, and (iv) infrared, visual, and hyperspectral cameras. The remote sensing measurements were accompanied by extensive measurements of snow and ice properties. By having these coincident multi-frequency remote sensing and in-situ observations, factors influencing the emission, reflection, and scattering of microwaves in sea ice and snow can be better understood. New remote sensing methods can be developed and contribute to new and upcoming satellite missions. Here we will present an overview of the measurement program and first results from simultaneously measuring instruments during two events in November 2019 (winter) and September 2020 (summer)

Published
2022

21. Comparing MOSAiC and ICESat-2 data: Thermal signatures and topography over sea ice features driven by convergence and divergence

Author

Hansen, Renée Mie Fredensborg, Thielke, Linda, Duncan, Kyle, Mchedlishvili, Alexander, Farrell, Sinead, Spreen, Gunnar, Jutila, Arttu, Hutter, Nils, Hendricks, Stefan, Skourup, Henriette, Hansen, Renée Mie Fredensborg, Thielke, Linda, Duncan, Kyle, Mchedlishvili, Alexander, Farrell, Sinead, Spreen, Gunnar, Jutila, Arttu, Hutter, Nils, Hendricks, Stefan, and Skourup, Henriette

Published
2022

22. First results of the ARIEL L-band radiometer on the MOSAiC Arctic Expedition during the late summer and autumn period

Author

Ministerio de Ciencia, Innovación y Universidades (España), German Research Foundation, European Commission, Agencia Estatal de Investigación (España), Gabarró, Carolina, Fabregat, Pau, Hernández-Macià, Ferran, Jove-Casulleras, Roger, Salvador, Joaquín, Spreen, Gunnar, Thielke, Linda, Dadic, Ruzica, Huntemann, Marcus, Kolabutin, Nikolai, Nomura, Daiki, Hannula, Henna-Reetta, Schneebeli, Martin, Ministerio de Ciencia, Innovación y Universidades (España), German Research Foundation, European Commission, Agencia Estatal de Investigación (España), Gabarró, Carolina, Fabregat, Pau, Hernández-Macià, Ferran, Jove-Casulleras, Roger, Salvador, Joaquín, Spreen, Gunnar, Thielke, Linda, Dadic, Ruzica, Huntemann, Marcus, Kolabutin, Nikolai, Nomura, Daiki, Hannula, Henna-Reetta, and Schneebeli, Martin

Abstract

Arctic sea ice is changing rapidly. Its retreat significantly impacts Arctic heat fluxes, ocean currents, and ecology, warranting the continuous monitoring and tracking of changes to sea ice extent and thickness. L-band (1.4 GHz) microwave radiometry can measure sea ice thickness for thin ice ≤1 m, depending on salinity and temperature. The sensitivity to thin ice makes L-band measurements complementary to radar altimetry which can measure the thickness of thick ice with reasonable accuracy. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we deployed the mobile ARIEL L-band radiometer on the sea ice floe next to research vessel Polarstern to study the sensitivity of the L-band to different sea ice parameters (e.g., snow and ice thickness, ice salinity, ice and snow temperature), with the aim to help improve/validate current microwave emission models. Our results show that ARIEL is sensitive to different types of surfaces (ice, leads, and melt ponds) and to ice thickness up to 70 cm when the salinity of the sea ice is low. The measurements can be reproduced with the Burke emission model when in situ snow and ice measurements for the autumn transects were used as model input. The correlation coefficient for modeled Burke brightness temperature (BT) versus ARIEL measurements was approximately 0.8. The discrepancy between the measurements and the model is about 5%, depending on the transects analyzed. No explicit dependence on snow depth was detected. We present a qualitative analysis for thin ice observations on leads. We have demonstrated that the ARIEL radiometer is an excellent field instrument for quantifying the sensitivity of L-band radiometry to ice and snow parameters, leading to insights that can enhance sea ice thickness retrievals from L-band radiometer satellites (such as Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP)) and improve estimates of Arctic sea-ice thickness change

Published
2022

23. 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

24. 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

25. Rain-on-Snow (ROS) Understudied in Sea Ice Remote Sensing: A Multi-Sensor Analysis of ROS during MOSAiC

Author

Stroeve, Julienne, primary, Nandan, Vishnu, additional, Willatt, Rosemary, additional, Dadic, Ruzica, additional, Rotosky, Philip, additional, Gallagher, Michael, additional, Mallett, Robbie, additional, Barrett, Andrew, additional, Hendricks, Stefan, additional, Tonboe, Rasmus, additional, Serreze, Mark, additional, Thielke, Linda, additional, Spreen, Gunnar, additional, Newman, Thomas, additional, Yackel, John, additional, Ricker, Robert, additional, Tsamados, Michel, additional, Macfarlane, Amy, additional, Hannula, Henna-Reetta, additional, and Schneebeli, Martin, additional

Published
2022
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26. Supplementary material to "Rain-on-Snow (ROS) Understudied in Sea Ice Remote Sensing: A Multi-Sensor Analysis of ROS during MOSAiC"

Author

Stroeve, Julienne, primary, Nandan, Vishnu, additional, Willatt, Rosemary, additional, Dadic, Ruzica, additional, Rotosky, Philip, additional, Gallagher, Michael, additional, Mallett, Robbie, additional, Barrett, Andrew, additional, Hendricks, Stefan, additional, Tonboe, Rasmus, additional, Serreze, Mark, additional, Thielke, Linda, additional, Spreen, Gunnar, additional, Newman, Thomas, additional, Yackel, John, additional, Ricker, Robert, additional, Tsamados, Michel, additional, Macfarlane, Amy, additional, Hannula, Henna-Reetta, additional, and Schneebeli, Martin, additional

Published
2022
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27. First results of the ARIEL L-band radiometer on the MOSAiC Arctic Expedition during the late summer and autumn period

Author

Gabarró, Carolina, primary, Fabregat, Pau, additional, Hernández-Macià, Ferran, additional, Jove, Roger, additional, Salvador, Joaquin, additional, Spreen, Gunnar, additional, Thielke, Linda, additional, Dadic, Ruzica, additional, Huntemann, Marcus, additional, Kolabutin, Nikolai, additional, Nomura, Daiki, additional, Hannula, Henna-Reetta, additional, and Schneebeli, Martin, additional

Published
2022
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28. 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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30. Remote Sensing of Sea Ice on the MOSAiC Ice Floe

Author

Spreen, Gunnar, Cardellach, Estel, Casal, Tânia, Demir, Oguz, Duguay, Claude R., Gabarró, Carolina, Huntemann, Marcus, Johnson, Joel T., Jove-Casulleras, Roger, Kaleschke, Lars, Linhardt, Robert J., Mahmud, Mallik S., Naderpour, Reza, Nandan, Vishnu, Ricker, Robert, Kristensen, Steen Savstrup, Scharien, Randy, Schwank, Mike, Semmling, Maximilian, Stroeve, Julienne, Tavrii, Aikaterini, Thielke, Linda, Tonboe, Rasmus, von Albedyll, Luisa, Wan, Wei, and Yackel, John

Abstract

Talk delivered in American Geophysical Union Fall Meeting online, 1-17 December 2020, The one-year long MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) drift expedition presents an excellent opportunity to evaluate current satellite remote sensing observations and develop new remote sensing methods. While the research icebreaker Polarstern is drifting with the sea ice from October 2019 to September 2020 several remote sensing instruments designed for observing the sea ice and snow on top were installed on the ice floe next to Polarstern and on the vessel itself. This, for the first time, will allow to monitoring the freeze-up to melt onset cycle and different ice types. Most of the instruments have counterparts in space, and their measurements are designed to obtain a better process understanding of the interaction of electromagnetic waves with snow and sea ice. Satellite measurements constitute a few of the most important climate data records for polar regions. The MOSAiC experiments will help to improve them and better assess their uncertainties. In particular the following measurements were performed during MOSAiC: (i) microwave radiometer observations at 0.5¿2, 1.4, 7, 11, 19, 37, and 89 GHz frequencies in dual polarization, (ii) fully-polarimetric, microwave radar scatterometer observations at L-, C-, X-, Ku-, and Ka-band frequencies, (iii) reflected GNSS measurements from snow and ice, and (iv) infrared, visual, and hyperspectral cameras. The instruments on the ice floe were oriented to observe similar snow and ice conditions. The remote sensing measurements were accompanied by extensive measurements of snow and ice properties in the vicinity of the measurement field. By having these coincident multi-frequency remote sensing and in-situ observations as well as the environmental conditions measured by other MOSAiC teams, factors influencing the emission, reflection, and scattering of microwaves in sea ice and snow can be better understood so that new remote sensing methods can be developed and contribute to new satellite missions. Here we will present an overview of the measurement program and first results from simultaneously measuring instruments.

Published
2020

32. 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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