38 results on '"Krampe, Daniela"'
Search Results
2. A Database of Snow on Sea Ice in the Central Arctic Collected during the MOSAiC expedition
- Author
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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
- Full Text
- View/download PDF
3. Ocean-sourced snow: An unaccounted process on Arctic sea ice
- Author
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Macfarlane, Amy, primary, Mellat, Moein, additional, Dadic, Ruzica, additional, Meyer, Hanno, additional, Werner, Martin, additional, Brunello, Camilla, additional, Arndt, Stefanie, additional, Krampe, Daniela, additional, and Schneebeli, Martin, additional
- Published
- 2023
- Full Text
- View/download PDF
4. Retrieval of Snow Depth on Arctic Sea Ice From Surface‐Based, Polarimetric, Dual‐Frequency Radar Altimetry
- Author
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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
- Full Text
- View/download PDF
5. Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice
- Author
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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
- Full Text
- View/download PDF
6. Snow and meteorological conditions at Villum Research Station, Northeast Greenland: on the adequacy of using atmospheric reanalysis for detailed snow simulations
- Author
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Krampe, Daniela, primary, Kauker, Frank, additional, Dumont, Marie, additional, and Herber, Andreas, additional
- Published
- 2023
- Full Text
- View/download PDF
7. Interdisciplinary observations of the under-ice environment using a remotely operated vehicle
- Author
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Anhaus, Philipp, Katlein, Christian, Matero, Ilkka, Arndt, Stefanie, Krampe, Daniela, Lange, Benjamin A, Regnery, Julia, Rohde, Jan, Schiller, Martin, Nicolaus, Marcel, Anhaus, Philipp, Katlein, Christian, Matero, Ilkka, Arndt, Stefanie, Krampe, Daniela, Lange, Benjamin A, Regnery, Julia, Rohde, Jan, Schiller, Martin, and Nicolaus, Marcel
- Abstract
Improving our understanding of the climate and ecosystem of the sea-ice covered Arctic Ocean was a key objective during MOSAiC. We aimed for a better understanding of the linkages of physical and biological processes at the interface between sea ice and ocean. To enhance the quantification of these linkages, year-round observations of physical, biological, and chemical parameters are needed. We operated a remotely operated vehicle (ROV) equipped with an interdisciplinary sensor platform to simultaneously measure these parameters underneath the drifting sea ice. These observations were made synchronous in time and place enabling a description of their spatial and temporal variability. Overall, we completed more than 80 surveys covering all seasons and various sea ice and surface conditions. We focused on optical parameters, sea-ice bottom topography, and upper ocean physical and biological oceanography. In addition, visual documentation of the under-ice environment was performed, nets for zooplankton were towed, and the ROV was used for instrument deployment and maintenance. Here, we present all ROV sensor data, allowing for a comprehensive picture of the under-ice environment. We are inviting discussions on further collaboration in data analyses and usage, in particular co-location and merging with other datasets from MOSAiC and other (also future) projects.
- Published
- 2023
8. Retrieval of Snow Depth on Arctic Sea Ice From Surface‐Based, Polarimetric, Dual‐Frequency Radar Altimetry
- Author
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Sub Dynamics Meteorology, Marine and Atmospheric Research, Willatt, Rosemary, Stroeve, Julienne, Nandan, Vishnu, Newman, Thomas, Mallett, Robbie, Hendricks, Stefan, Ricker, Robert, Mead, James, Itkin, Polona, Tonboe, Rasmus, Wagner, David Nicholas, 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, Sub Dynamics Meteorology, Marine and Atmospheric Research, Willatt, Rosemary, Stroeve, Julienne, Nandan, Vishnu, Newman, Thomas, Mallett, Robbie, Hendricks, Stefan, Ricker, Robert, Mead, James, Itkin, Polona, Tonboe, Rasmus, Wagner, David Nicholas, 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
- Published
- 2023
9. Retrieval of Snow Depth on Arctic Sea Ice From Surface-Based, Polarimetric, Dual-Frequency Radar Altimetry
- Author
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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. Energy and glacier mass balance of Fürkeleferner, Italy: past, present, and future
- Author
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Krampe, Daniela, primary, Arndt, Anselm, additional, and Schneider, Christoph, additional
- Published
- 2022
- Full Text
- View/download PDF
11. Wind Transport of Snow Impacts Ka- and Ku-band Radar Signatures on Arctic Sea Ice
- Author
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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
- Full Text
- View/download PDF
12. Snowfall and snow accumulation during the MOSAiC winter and spring seasons
- Author
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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
- Full Text
- View/download PDF
13. Overview of the MOSAiC expedition: Snow and sea ice
- Author
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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
14. Snowfall and snow accumulation during the MOSAiC winter and spring seasons
- Author
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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
15. Energy and glacier mass balance of Fürkeleferner, Italy: past, present, and future
- Author
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Huss, Matthias, Krampe, Daniela, Arndt, Anselm, Schneider, Christoph, Huss, Matthias, Krampe, Daniela, Arndt, Anselm, and Schneider, Christoph
- Abstract
The energy and mass balance of mountain glaciers translate into volume changes that play out as area changes over time. From this, together with former moraines during maximum advances, information on past climate conditions and the climatic drivers behind during glacier advances can be obtained. Here, we use the distributed COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY) to simulate the present state of an Italian glacier, named Fürkeleferner, for the mass balance years 2013–2017. Next, we investigate the local climate during the time of the last “Little Ice Age” (LIA) maximum glacier advance using COSIPY together with the LIA glacier outline retrieved from moraine mapping and a digital elevation model (DEM) adapted for the glacier’s geometry at the time of the LIA as a benchmark. Furthermore, the glacier’s sensitivity to future air temperature increase of +1 K and +2 K is investigated using the same model. For all simulations, meteorological data of closely located climate stations are used to force the model. We show the individual monthly contribution of individual energy and mass balance components. Refreezing during the summer months is an important component of the energy and mass balance, on average about 9 % relative to total annual ablation. The results from simulating past climate show a 2.8 times larger glacier area for Fürkeleferner during the LIA than today. This further implies a 2.5 K colder climate, assuming that the amount of precipitation was 10 %–20 % in excess of today’s value. Concerning further temperature increase of 2 K, the glacier would only consist of the ablation area implying sustained mass loss and eventual total mass loss. Even under current climatic conditions, the glacier area would have to decrease to 17 % of its current area to be in a steady state. We discuss the reliability of the results by comparing simulated present mass balance to measured mass balances of neighboring glaciers in the Europea
- Published
- 2022
16. Overview of the MOSAiC expedition: Snow and sea ice
- Author
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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
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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.
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- 2022
18. Overview of the MOSAiC expedition: Snow and sea ice
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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
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- 2022
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19. Wind Transport of Snow Impacts Ka- and Ku-band Radar Signatures on Arctic Sea Ice.
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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]
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- 2022
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20. Snowfall and snow accumulation processes during the MOSAiC winter and spring season
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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
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- 2021
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21. On the performance of the snow model Crocus driven by in situ and reanalysis data at Villum Research Station in northeast Greenland
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Krampe, Daniela, primary, Kauker, Frank, additional, Dumont, Marie, additional, and Herber, Andreas, additional
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- 2021
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22. Snowfall and snow accumulation processes during MOSAiC
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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
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- 2021
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23. KuKa altimeter mode data gathered during MOSAiC: scattering from snow covered sea ice and snow depth determination using dual-frequency and polarimetric approaches
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Willatt, Rosemary, primary, Stroeve, Julienne, additional, Nandan, Vishnu, additional, Tonboe, Rasmus, additional, Hendricks, Stefan, additional, Ricker, Robert, additional, Mead, James, additional, Newman, Thomas, additional, Itkin, Polona, additional, Liston, Glen, additional, Mallett, Robbie, additional, Zhou, Lu, additional, Schneebeli, Martin, additional, Krampe, Daniela, additional, Tsamados, Michel, additional, Demir, Oguz, additional, Oggier, Marc, additional, Buehner Gattis, Ella, additional, and Wilkinson, Jeremy, additional
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- 2021
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24. The MOSAiC ROV Program: One Year of Comprehensive Under-Ice Observations
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Katlein, Christian, Anhaus, Philipp, Matero, Ilkka, Krampe, Daniela, Arndt, Stefanie, Regnery, Julia, and Nicolaus, Marcel
- Abstract
The overarching goal of the remotely operated vehicle (ROV) operations during MOSAiC was to provide access to the underside of sea ice for a variety of interdisciplinary science objectives throughout an entire year. The M500 ROV was equipped with a large variety of sensors and operated at several sites within the MOSAiC central observatory. Despite logistical and technological challenges, over the full year we accomplished a total of ~60 days of operations with over 300 hours of scientific dive time. 3D ice bottom geometry was mapped in high resolution using an acoustic multibeam sonar covering a 300 m circle around the access hole complementing other ice mass balance measurements on transects, by autonomous systems, airborne laser scanning and from classical ablation stakes. Various camera systems enabled us to document features of sea ice growth and decay. From early March onwards, with the sun rising again, a main focus was the investigation of the spatial variability in ice optical properties. Light transmittance was measured with several hyperspectral radiometers under marked survey areas, including various ice types such as first-year ice, second-year ice, pressure ridges, and leads. Optical surveys were coordinated with surface albedo measurements, vertical snow profiles and aerial photography. The ROV also supported ecosystem research by deploying sediment traps underneath pressure ridges, sampling algal communities at the ice bottom and in ridge cavities with a suction sampler as well as the regular towed under-ice zooplankton and phytoplankton nets. Ice algal coverage was further investigated using an underwater hyperspectral imaging system, while the ROV video cameras enabled the observation of fish and seals living in ridge cavities. The ROV also carried further oceanographic sensors providing vertical and horizontal transect measurements of small-scale bio-physical water column properties such as chlorophyll content, nutrients, optical properties, temperature, salinity and dissolved oxygen. Here we present first highlights from the year-long operations: the discovery of platelet ice under Arctic winter sea ice during polar night and the extensive time series of multibeam derived ice draft maps, which allow together with airborne laser scanner data a full 3D documentation of ice geometry.
- Published
- 2020
25. Surface-based Ku- and Ka-band polarimetric radar for sea ice studies
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Stroeve, Julienne, Nandan, Vishnu, Willatt, Rosemary, Tonboe, Rasmus, Hendricks, Stefan, Ricker, Robert, Mead, James, Mallett, Robbie, Huntemann, Marcus, Itkin, Polona, Schneebeli, Martin, Krampe, Daniela, Spreen, Gunnar, Wilkinson, Jeremy, Matero, Ilkka, Hoppmann, Mario, Tsamados, Michel, Stroeve, Julienne, Nandan, Vishnu, Willatt, Rosemary, Tonboe, Rasmus, Hendricks, Stefan, Ricker, Robert, Mead, James, Mallett, Robbie, Huntemann, Marcus, Itkin, Polona, Schneebeli, Martin, Krampe, Daniela, Spreen, Gunnar, Wilkinson, Jeremy, Matero, Ilkka, Hoppmann, Mario, and Tsamados, Michel
- Abstract
To improve our understanding of how snow properties influence sea ice thickness retrievals from presently operational and upcoming satellite radar altimeter missions, as well as to investigate the potential for combining dual frequencies to simultaneously map snow depth and sea ice thickness, a new, surface-based, fully polarimetric Ku- and Ka-band radar (KuKa radar) was built and deployed during the 2019–2020 year-long MOSAiC international Arctic drift expedition. This instrument, built to operate both as an altimeter (stare mode) and as a scatterometer (scan mode), provided the first in situ Ku- and Ka-band dual-frequency radar observations from autumn freeze-up through midwinter and covering newly formed ice in leads and first-year and second-year ice floes. Data gathered in the altimeter mode will be used to investigate the potential for estimating snow depth as the difference between dominant radar scattering horizons in the Ka- and Ku-band data. In the scatterometer mode, the Ku- and Ka-band radars operated under a wide range of azimuth and incidence angles, continuously assessing changes in the polarimetric radar backscatter and derived polarimetric parameters, as snow properties varied under varying atmospheric conditions. These observations allow for characterizing radar backscatter responses to changes in atmospheric and surface geophysical conditions. In this paper, we describe the KuKa radar, illustrate examples of its data and demonstrate their potential for these investigations.
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- 2020
26. Platelet Ice under Arctic Pack Ice in Winter
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Katlein, Christian, Mohrholz, Volker, Sheikin, Igor, Itkin, Polona, Divine, Dmitry V., Stroeve, Julienne, Jutila, Arttu, Krampe, Daniela, Shimanchuk, Egor, Raphael, Ian, Rabe, Benjamin, Kuznetsov, Ivan, Mallet, Maria, Liu, Hailong, Hoppmann, Mario, Fang, Ying‐Chih, Dumitrascu, Adela, Arndt, Stefanie, Anhaus, Philipp, Nicolaus, Marcel, Matero, Ilkka, Oggier, Marc, Eicken, Hajo, Haas, Christian, Katlein, Christian, Mohrholz, Volker, Sheikin, Igor, Itkin, Polona, Divine, Dmitry V., Stroeve, Julienne, Jutila, Arttu, Krampe, Daniela, Shimanchuk, Egor, Raphael, Ian, Rabe, Benjamin, Kuznetsov, Ivan, Mallet, Maria, Liu, Hailong, Hoppmann, Mario, Fang, Ying‐Chih, Dumitrascu, Adela, Arndt, Stefanie, Anhaus, Philipp, Nicolaus, Marcel, Matero, Ilkka, Oggier, Marc, Eicken, Hajo, and Haas, Christian
- Abstract
Platelet ice is a unique type of sea ice; its occurrence has numerous implications for physical and ecological systems. Mostly, platelet ice has been reported from the Antarctic where ice crystals grow in supercooled ice shelf water and accumulate below sea ice to form sub-ice platelet layers. In the Arctic however, platelet ice formation has only been sparsely documented so far. The associated formation processes and morphology differ significantly from the Antarctic, but currently remain poorly understood. Here, we present the first comprehensive, repeat in-situ observations of a decimeter thick sub-ice platelet layer under drifting pack ice of the Central Arctic in winter. Observations carried out with a remotely operated underwater vehicle (ROV) during the midwinter leg of the MOSAiC drift expedition provided clear evidence of the growth of platelet layers from supercooled water present in the ocean mixed layer. This process was observed under all ice types present during the surveys. Oceanographic data from autonomous observing platforms leads us to the conclusion that platelet ice formation is a widespread yet overlooked feature of Arctic winter sea ice growth.
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- 2020
27. Surface-based Ku- and Ka-band polarimetric radar for sea ice studies
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Stroeve, Julienne, primary, Nandan, Vishnu, additional, Willatt, Rosemary, additional, Tonboe, Rasmus, additional, Hendricks, Stefan, additional, Ricker, Robert, additional, Mead, James, additional, Mallett, Robbie, additional, Huntemann, Marcus, additional, Itkin, Polona, additional, Schneebeli, Martin, additional, Krampe, Daniela, additional, Spreen, Gunnar, additional, Wilkinson, Jeremy, additional, Matero, Ilkka, additional, Hoppmann, Mario, additional, and Tsamados, Michel, additional
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- 2020
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28. Platelet Ice Under Arctic Pack Ice in Winter
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Katlein, Christian, primary, Mohrholz, Volker, additional, Sheikin, Igor, additional, Itkin, Polona, additional, Divine, Dmitry V., additional, Stroeve, Julienne, additional, Jutila, Arttu, additional, Krampe, Daniela, additional, Shimanchuk, Egor, additional, Raphael, Ian, additional, Rabe, Benjamin, additional, Kuznetsov, Ivan, additional, Mallet, Maria, additional, Liu, Hailong, additional, Hoppmann, Mario, additional, Fang, Ying‐Chih, additional, Dumitrascu, Adela, additional, Arndt, Stefanie, additional, Anhaus, Philipp, additional, Nicolaus, Marcel, additional, Matero, Ilkka, additional, Oggier, Marc, additional, Eicken, Hajo, additional, and Haas, Christian, additional
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- 2020
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29. Supplementary material to "Surface-Based Ku- and Ka-band Polarimetric Radar for Sea Ice Studies"
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Stroeve, Julienne, primary, Nandan, Vishnu, additional, Willatt, Rosemary, additional, Tonboe, Rasmus, additional, Hendricks, Stefan, additional, Ricker, Robert, additional, Mead, James, additional, Huntemann, Marcus, additional, Itkin, Polona, additional, Schneebeli, Martin, additional, Krampe, Daniela, additional, Spreen, Gunnar, additional, Wilkinson, Jeremy, additional, Matero, Ilkka, additional, Hoppmann, Mario, additional, Mallett, Robbie, additional, and Tsamados, Michel, additional
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- 2020
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30. Towards dedicated snow over sea ice modeling: Comparison between ERA5 data and in-situ observations in Northest Greenland
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Krampe, Daniela, Kauker, Frank, Herber, Andreas, and Zanatta, Marco
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- 2019
31. Modelling of mass balance response of Glacier Fürkeleferner, Italy, withthe COupled Snowpack and Ice surface energy and MAss balance modelin PYthon (COSIPY)
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Krampe, Daniela, Arndt, Anselm, Schneider, Christoph, Krampe, Daniela, Arndt, Anselm, and Schneider, Christoph
- Abstract
Glacier melt water is crucial for irrigation used for agriculture in the Martell valley, Italy. Therefore, indicationsof glacier development in the Ortler-Cevedale massive are of significant economic and social interest especiallyin the context of climate variability and climate change. In this study the “COupled Snowpack and Ice surfaceenergy and MAss balance model in PYthon” (COSIPY) is used to investigate the state of recent mass balance ofthe glacier Fürkeleferner which is located at the top of Martell valley. Meteorological data of the climate stationHintermartelltal is used after adjusting to altitude by linear lapse rates. The model output is in good agreementwith in situ observations during August 2016 and 2017 as well as with measured mass balances from neighboringglaciers in the European Alps. Results show a significant negative cumulative mass balance between October 2012and September 2017. Negative mass balances throughout the total area indicate that glacier Fürkeleferner on aver-age did not have any accumulation area left during the study period. Therefore, under present climate conditions,the glacier would completely melt away on the long run. Model runs with temperature increased by +1 K and +2K as assumed for the European Alps between 2021 and 2050 show enhanced glacier melting. Related mass fluxesindicate a strong increase in surface melt while the decrease in solid precipitation caused by warmer temperaturesis negligible. We further force COSIPY with decreased temperature and increased precipitation to reproduce azero mass balance for the glacier surface according to glacier Fürkelen’s maximum Little Ice Age (LIA) extent in1855. Glacier area and volume for its 1855 extent were determined by mapping of terminal and lateral moraines.The model results indicate that air temperatures must have been substantially lower in the mid 19th century evenif higher precipitation sums are assumed. Overall, the results are consistent with previous knowledge on pal
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- 2019
32. Soil CO2 concentrations and efflux dynamics of a tree island in the Pantanal wetland
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Lathuillière, Michael J., primary, Pinto, Osvaldo B., additional, Johnson, Mark S., additional, Jassal, Rachhpal S., additional, Dalmagro, Higo J., additional, Leite, Nei K., additional, Speratti, Alicia B., additional, Krampe, Daniela, additional, and Couto, Eduardo G., additional
- Published
- 2017
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33. Soil CO2 concentrations and efflux dynamics of a tree island in the Pantanal wetland.
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Lathuillière, Michael J., Pinto, Osvaldo B., Johnson, Mark S., Jassal, Rachhpal S., Dalmagro, Higo J., Leite, Nei K., Speratti, Alicia B., Krampe, Daniela, and Couto, Eduardo G.
- Abstract
The Pantanal is the largest tropical wetland on the planet, and yet little information is available on the biome's carbon cycle. We used an automatic station to measure soil CO
2 concentrations and oxidation-reduction potential over the 2014 and 2015 flood cycles of a tree island in the Pantanal that is immune to inundation during the wetland's annual flooding. The soil CO2 concentration profile was then used to estimate soil CO2 efflux over the two periods. In 2014, subsurface soil saturation at 0.30 m depth created conditions in that layer that led to CO2 buildup close to 200,000 ppm and soil oxidation-reduction potential below −300 mV, conditions that were not repeated in 2015 due to annual variability in soil saturation at the site. Mean CO2 efflux over the 2015 flood cycle was 0.023 ± 0.103 mg CO2 -C m−2 s−1 representing a total annual efflux of 593 ± 2690 mg CO2 -C m−2 y−1 . Unlike a nearby tree island site that experiences full inundation during the wet season, here the soil dried quickly following repeated rain events throughout the year, which led to the release of CO2 pulses from the soil. This study highlights not only the complexity and heterogeneity in the Pantanal's carbon balance based on differences in topography, flood cycles, and vegetation but also the challenges of applying the gradient method in the Pantanal due to deviations from steady state conditions. [ABSTRACT FROM AUTHOR]- Published
- 2017
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34. Soil CO2concentrations and efflux dynamics of a tree island in the Pantanal wetland
- Author
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Lathuillière, Michael J., Pinto, Osvaldo B., Johnson, Mark S., Jassal, Rachhpal S., Dalmagro, Higo J., Leite, Nei K., Speratti, Alicia B., Krampe, Daniela, and Couto, Eduardo G.
- Abstract
The Pantanal is the largest tropical wetland on the planet, and yet little information is available on the biome's carbon cycle. We used an automatic station to measure soil CO2concentrations and oxidation‐reduction potential over the 2014 and 2015 flood cycles of a tree island in the Pantanal that is immune to inundation during the wetland's annual flooding. The soil CO2concentration profile was then used to estimate soil CO2efflux over the two periods. In 2014, subsurface soil saturation at 0.30 m depth created conditions in that layer that led to CO2buildup close to 200,000 ppm and soil oxidation‐reduction potential below −300 mV, conditions that were not repeated in 2015 due to annual variability in soil saturation at the site. Mean CO2efflux over the 2015 flood cycle was 0.023 ± 0.103 mg CO2‐C m−2s−1representing a total annual efflux of 593 ± 2690 mg CO2‐C m−2y−1. Unlike a nearby tree island site that experiences full inundation during the wet season, here the soil dried quickly following repeated rain events throughout the year, which led to the release of CO2pulses from the soil. This study highlights not only the complexity and heterogeneity in the Pantanal's carbon balance based on differences in topography, flood cycles, and vegetation but also the challenges of applying the gradient method in the Pantanal due to deviations from steady state conditions. The Pantanal is the largest wetland in the world whose carbon balance is expected to change with seasonal flooding, especially in tree islands that can be immune to flooding. We provide a half‐hourly time series of soil CO2concentrations, efflux, and oxidation‐reduction potential at a tree island site in the Pantanal. Soil CO2concentration at 0.30 m depth was as high as 200,000 ppm, while our 2015 average soil efflux estimate using the gradient method was 0.023 mg CO2‐C m−2s−1. Our results allow for a spatial assessment of soil CO2effluxes in the Pantanal, revealing complex biogeochemical processes in the tropical wetland with controls more heavily influenced by topography and vegetation. This research also highlights instrumental challenges in applying the gradient method in the tropical wetland. Tree island soil CO2concentrations were as high as 200,000 ppm (0.30 m depth)Mean 2015 soil CO2efflux at the site was 0.023 ± 0.103 mg CO2‐C m−2s−1The gradient method presents challenges for application in the Pantanal
- Published
- 2017
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35. Modelling of mass balance response of Glacier Fürkeleferner, Italy, with the COupled Snowpack and Ice surface energy and MAss balance model in PYthon (COSIPY).
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Krampe, Daniela, Arndt, Anselm, and Schneider, Christoph
- Subjects
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GLACIERS , *SURFACE energy , *MASS budget (Geophysics) , *LITTLE Ice Age , *MELTWATER , *IRRIGATION farming , *ICE - Abstract
Glacier melt water is crucial for irrigation used for agriculture in the Martell valley, Italy. Therefore, indications of glacier development in the Ortler-Cevedale massive are of significant economic and social interest especially in the context of climate variability and climate change. In this study the "COupled Snowpack and Ice surface energy and MAss balance model in PYthon" (COSIPY) is used to investigate the state of recent mass balance of the glacier Fürkeleferner which is located at the top of Martell valley. Meteorological data of the climate station Hintermartelltal is used after adjusting to altitude by linear lapse rates. The model output is in good agreement with in situ observations during August 2016 and 2017 as well as with measured mass balances from neighboring glaciers in the European Alps. Results show a significant negative cumulative mass balance between October 2012 and September 2017. Negative mass balances throughout the total area indicate that glacier Fürkeleferner on average did not have any accumulation area left during the study period. Therefore, under present climate conditions, the glacier would completely melt away on the long run. Model runs with temperature increased by +1 K and +2 K as assumed for the European Alps between 2021 and 2050 show enhanced glacier melting. Related mass fluxes indicate a strong increase in surface melt while the decrease in solid precipitation caused by warmer temperatures is negligible. We further force COSIPY with decreased temperature and increased precipitation to reproduce a zero mass balance for the glacier surface according to glacier Fürkelen's maximum Little Ice Age (LIA) extent in 1855. Glacier area and volume for its 1855 extent were determined by mapping of terminal and lateral moraines. The model results indicate that air temperatures must have been substantially lower in the mid 19th century even if higher precipitation sums are assumed. Overall, the results are consistent with previous knowledge on paleo-climate in the Alps as reported in other studies. The study exemplifies the strong response of glacier Fürkelen's mass balance to atmospheric forcing in past, present and future. It further highlights the need of adaption of regional water management strategies in order to cope with diminishing glacier melt water in the Martell valley hydrological system in coming decades. [ABSTRACT FROM AUTHOR]
- Published
- 2019
36. Snowfall and snow accumulation during the MOSAiC winter and spring seasons
- Author
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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.
37. Overview of the MOSAiC expedition: Snow and sea ice
- Author
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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.
38. Evolution and spatial variability of small-scale surface roughness of snow and sea ice during MOSAiC
- Author
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Dadic, Ruzica, Schneebeli, Martin, Hannula, Henna-Reetta, Pirazzini, Roberta, Macfarlane, Amy, Wigmore, Oliver, Vargo, Lauren, Wagner, David, Brus, David, Arndt, Stefanie, Jaggi, Matthias, Krampe, Daniela, Lehning, Michael, Spreen, Gunnar, and Stroeve, Julienne
- Subjects
Astrophysics::Earth and Planetary Astrophysics ,Physics::Geophysics - Abstract
Small-scale surface roughness (on an area of about 0.5 m x 0.5 m) affects remote sensing retrieval algorithms and radiative transfer models, yet data of snow and ice surface roughness over sea ice is scarce. Microwave emissivity, important for satellite retrievals of sea ice concentration, type, thickness, etc., is a function of ice/snow and snow/air interface roughness (amongst other factors). During MOSAiC, we collected data to determine the small-scale surface roughness of the surface (snow and surface scattering layer) and the snow/sea-ice interface using a rapid photogrammetric method. Surface roughness data was collected with most snow pits as well as on some transects to account for temporal and spatial variability. Here, we present the surface roughness evolution for the year-long snow pit observations and discuss the applicability and relevance of this dataset for remote sensing and radiative transfer studies. We will consider the spatial variability and anisotropy of surface roughness for different snow and surface types. Furthermore, we will compare this small-scale surface roughness to ∼100m-scale surface roughness obtained from UAVs to determine relevant roughness scales for different applications. We will also discuss other potential applications for this dataset, such as correlations between the small-scale surface roughness and specific surface area (from near-infrared photography, SnowMicroPen, and microCT), shear strength (from SnowMicroPen), or aerodynamic roughness for turbulent fluxes.
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