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1. Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project

Author

Wendisch, M., Brückner, M., Crewell, Susanne, Ehrlich, A., Notholt, J., Lüpkes, C., Macke, A., Burrows, J. P., Rinke, A., Quaas, J., Maturilli, M., Schemann, V., Shupe, M. D., Akansu, E. F., Barrientos-Velasco, C., Bärfuss, K., Blechschmidt, A.-M., Block, K., Bougoudis, I., Bozem, H., Böckmann, C., Bracher, A., Bresson, H., Bretschneider, L., Buschmann, M., Chechin, D. G., Chylik, J., Dahlke, S., Deneke, H., Dethloff, K., Donth, T., Dorn, W., Dupuy, R., Ebell, K., Egerer, U., Engelmann, R., Eppers, O., Gerdes, R., Gierens, R., Gorodetskaya, I. V., Gottschalk, M., Griesche, H., Gryanik, V. M., Handorf, D., Harm-Altstädter, B., Hartmann, J., Hartmann, M., Heinold, B., Herber, A., Herrmann, H., Heygster, G., Höschel, I., Hofmann, Z., Hölemann, J., Hünerbein, A., Jafariserajehlou, S., Jäkel, E., Jacobi, C., Janout, M., Jansen, F., Jourdan, O., Jurányi, Z., Kalesse-Los, H., Kanzow, T., Käthner, R., Kliesch, L. L., Klingebiel, M., Knudsen, E. M., Kovács, T., Körtke, W., Krampe, D., Kretzschmar, J., Kreyling, D., Kulla, B., Kunkel, D., Lampert, A., Lauer, M., Lelli, L., von Lerber, A., Linke, O., Löhnert, U., Lonardi, M., Losa, S. N., Losch, M., Maahn, M., Mech, M., Mei, L., Mertes, S., Metzner, E., Mewes, D., Michaelis, J., Mioche, G., Moser, Manuel, Nakoudi, K., Neggers, R., Neuber, R., Nomokonova, T., Oelker, J., Papakonstantinou-Presvelou, I., Pätzold, F., Pefanis, V., Pohl, C., van Pinxteren, M., Radovan, A., Rhein, M., Rex, Markus, Richter, A., Risse, N., Ritter, C., Rostosky, P., Rozanov, V. V., Ruiz Donoso, E., Saavedra-Garfias, P., Salzmann, M., Schacht, J., Schäfer, M., Schneider, J., Schnierstein, N., Seifert, P., Seo, S., Siebert, H., Soppa, M. A., Spreen, G., Stachlewska, I. S., Stapf, J., Stratmann, F., Tegen, I., Viceto, C., Voigt, Christiane, Vountas, M., Walbröl, A., Walter, M., Wehner, B., Wex, H., Willmes, S., Zanatta, M., Zeppenfeld, S., Laboratoire de Météorologie Physique (LaMP), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)

Subjects
Atmospheric Science, [SDU]Sciences of the Universe [physics], clouds, Arctic amplification
Abstract

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.

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

Author

Nandan, V., Willatt, R., Mallett, R., Stroeve, J., Geldsetzer, T., Scharien, R., Tonboe, R., Yackel, J., Landy, J., Clemens-Sewall, D., Jutila, A., Wagner, D. N., Krampe, D., Huntemann, M., Mahmud, M., Jensen, D., Newman, T., Hendricks, S., Spreen, G., Macfarlane, A., Schneebeli, M., Mead, J., Ricker, R., Gallagher, M., Duguay, C., Raphael, I., Polashenski, C., Tsamados, M., Matero, I., and Hoppmann, M.

Subjects
SDG 13 - Climate Action
Abstract

Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0∘ (nadir) and 50∘. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected 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 altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice.

Published
2023
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3. Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project

Author

Wendisch, M, Brückner, M, Crewell, S, Ehrlich, A, Notholt, J, Lüpkes, C, Macke, A, Burrows, JP, Rinke, A, Quaas, J, Maturilli, M, Schemann, V, Shupe, MD, Akansu, EF, Barrientos-Velasco, C, Bärfuss, K, Blechschmidt, A-M, Block, K, Bougoudis, I, Bozem, H, Böckmann, C, Bracher, A, Bresson, H, Bretschneider, L, Buschmann, M, Chechin, DG, Chylik, J, Dahlke, S, Deneke, H, Dethloff, K, Donth, T, Dorn, W, Dupuy, R, Ebell, K, Egerer, U, Engelmann, R, Eppers, O, Gerdes, R, Gierens, R, Gorodetskaya, IV, Gottschalk, M, Griesche, H, Gryanik, VM, Handorf, D, Harm-Altstädter, B, Hartmann, J, Hartmann, M, Heinold, B, Herber, A, Herrmann, H, Heygster, G, Höschel, I, Hofmann, Z, Hölemann, J, Hünerbein, A, Jafariserajehlou, S, Jäkel, E, Jacobi, C, Janout, M, Jansen, F, Jourdan, O, Jurányi, Z, Kalesse-Los, H, Kanzow, T, Käthner, R, Kliesch, LL, Klingebiel, M, Knudsen, EM, Kovács, T, Körtke, W, Krampe, D, Kretzschmar, J, Kreyling, D, Kulla, B, Kunkel, D, Lampert, A, Lauer, M, Lelli, L, von Lerber, A, Linke, O, Löhnert, U, Lonardi, M, Losa, SN, Losch, M, Maahn, M, Mech, M, Mei, L, Mertes, S, Metzner, E, Mewes, D, Michaelis, J, Mioche, G, Moser, M, Nakoudi, K, Neggers, R, Neuber, R, Nomokonova, T, Oelker, J, Papakonstantinou-Presvelou, I, Pätzold, F, Pefanis, V, Pohl, C, van Pinxteren, M, Radovan, A, Rhein, M, Rex, M, Richter, A, Risse, N, Ritter, C, Rostosky, P, Rozanov, VV, Donoso, E Ruiz, Saavedra Garfias, P, Salzmann, M, Schacht, J, Schäfer, M, Schneider, J, Schnierstein, N, Seifert, P, Seo, S, Siebert, H, Soppa, MA, Spreen, G, Stachlewska, IS, Stapf, J, Stratmann, F, Tegen, I, Viceto, C, Voigt, C, Vountas, M, Walbröl, A, Walter, M, Wehner, B, Wex, H, Willmes, S, Zanatta, M, Zeppenfeld, S, Wendisch, M, Brückner, M, Crewell, S, Ehrlich, A, Notholt, J, Lüpkes, C, Macke, A, Burrows, JP, Rinke, A, Quaas, J, Maturilli, M, Schemann, V, Shupe, MD, Akansu, EF, Barrientos-Velasco, C, Bärfuss, K, Blechschmidt, A-M, Block, K, Bougoudis, I, Bozem, H, Böckmann, C, Bracher, A, Bresson, H, Bretschneider, L, Buschmann, M, Chechin, DG, Chylik, J, Dahlke, S, Deneke, H, Dethloff, K, Donth, T, Dorn, W, Dupuy, R, Ebell, K, Egerer, U, Engelmann, R, Eppers, O, Gerdes, R, Gierens, R, Gorodetskaya, IV, Gottschalk, M, Griesche, H, Gryanik, VM, Handorf, D, Harm-Altstädter, B, Hartmann, J, Hartmann, M, Heinold, B, Herber, A, Herrmann, H, Heygster, G, Höschel, I, Hofmann, Z, Hölemann, J, Hünerbein, A, Jafariserajehlou, S, Jäkel, E, Jacobi, C, Janout, M, Jansen, F, Jourdan, O, Jurányi, Z, Kalesse-Los, H, Kanzow, T, Käthner, R, Kliesch, LL, Klingebiel, M, Knudsen, EM, Kovács, T, Körtke, W, Krampe, D, Kretzschmar, J, Kreyling, D, Kulla, B, Kunkel, D, Lampert, A, Lauer, M, Lelli, L, von Lerber, A, Linke, O, Löhnert, U, Lonardi, M, Losa, SN, Losch, M, Maahn, M, Mech, M, Mei, L, Mertes, S, Metzner, E, Mewes, D, Michaelis, J, Mioche, G, Moser, M, Nakoudi, K, Neggers, R, Neuber, R, Nomokonova, T, Oelker, J, Papakonstantinou-Presvelou, I, Pätzold, F, Pefanis, V, Pohl, C, van Pinxteren, M, Radovan, A, Rhein, M, Rex, M, Richter, A, Risse, N, Ritter, C, Rostosky, P, Rozanov, VV, Donoso, E Ruiz, Saavedra Garfias, P, Salzmann, M, Schacht, J, Schäfer, M, Schneider, J, Schnierstein, N, Seifert, P, Seo, S, Siebert, H, Soppa, MA, Spreen, G, Stachlewska, IS, Stapf, J, Stratmann, F, Tegen, I, Viceto, C, Voigt, C, Vountas, M, Walbröl, A, Walter, M, Wehner, B, Wex, H, Willmes, S, Zanatta, M, and Zeppenfeld, S

Abstract

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.

Published
2023

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

Author

Willatt, R., Stroeve, J.C., Nandan, V., Newman, T., Mallett, R., Hendricks, S., Ricker, R., Mead, J., Itkin, P., Tonboe, R., Wagner, D.N., Spreen, G., Liston, G., Schneebeli, M., Krampe, D., Tsamados, M., Demir, O., Wilkinson, J., Jaggi, M., Zhou, L., Huntermann, M., Raphael, I.A., Jutila, A., Oggier, M., Willatt, R., Stroeve, J.C., Nandan, V., Newman, T., Mallett, R., Hendricks, S., Ricker, R., Mead, J., Itkin, P., Tonboe, R., Wagner, D.N., Spreen, G., Liston, G., Schneebeli, M., Krampe, D., Tsamados, M., Demir, O., Wilkinson, J., Jaggi, M., Zhou, L., Huntermann, M., Raphael, I.A., Jutila, A., and Oggier, M.

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

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

Author

Macfarlane AR, Schneebeli M, Dadic R, Tavri A, Immerz A, Polashenski C, Krampe D, Clemens-Sewall D, Wagner DN, Perovich DK, Henna-Reetta H, Raphael I, Matero I, Regnery J, Smith MM, Nicolaus M, Jaggi M, Oggier M, Webster MA, Lehning M, Kolabutin N, Itkin P, Naderpour R, Pirazzini R, Hämmerle S, Arndt S, and Fons S

Abstract

Snow plays an essential role in the Arctic as the interface between the sea ice and the atmosphere. Optical properties, thermal conductivity and mass distribution are critical to understanding the complex Arctic sea ice system's energy balance and mass distribution. By conducting measurements from October 2019 to September 2020 on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have produced a dataset capturing the year-long evolution of the physical properties of the snow and surface scattering layer, a highly porous surface layer on Arctic sea ice that evolves due to preferential melt at the ice grain boundaries. The dataset includes measurements of snow during MOSAiC. Measurements included profiles of depth, density, temperature, snow water equivalent, penetration resistance, stable water isotope, salinity and microcomputer tomography samples. Most snowpit sites were visited and measured weekly to capture the temporal evolution of the physical properties of snow. The compiled dataset includes 576 snowpits and describes snow conditions during the MOSAiC expedition., (© 2023. The Author(s).)

Published
2023
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7. Retrospective analysis of 10,000 implants from insertion up to 20 years-analysis of implantations using augmentative procedures.

Author

Knöfler W, Barth T, Graul R, and Krampe D

Abstract

Background: A sufficient amount of bone is essential to ensure long-term stability of dental implants. To support the bone regeneration process, different techniques and materials are available. It has been questioned whether these techniques and materials may compromise implant survival compared to pristine bone. To properly answer this question, long-term stability up to 20.2 years after insertion of implants placed in augmented or non-augmented sites was retrospectively analysed., Methods: Retrospective analysis included 10,158 implants from 3095 patients in three private practices who underwent implant therapy with or without bone augmentation procedures. Different graft materials and membranes were used for augmentation. If necessary, the graft was stabilised using a titanium mesh. Implant survival was evaluated analysing explantation rates and Kaplan-Meier survival curves in augmented or non-augmented sites. In additional subgroup analyses, augmentation procedures, graft materials and membranes were compared applying descriptive statistics., Results: The observation period varied from the day of implantation up to 20.2 years after implant insertion. The overall implant survival was 95.5% (augmented sites 96.33%; native sites 94.27%). Comparison of Kaplan-Meier survival curves revealed significantly better survival of implants in augmented sites (p = 0.0025). When comparing different augmentation procedures, the best results were found for bone condensing followed by lateral augmentation. Graft materials were used in 58.2%, membranes in 36.6% of all implant sites. The most often used graft materials were a deproteinized bovine bone mineral (53.0%) and autogenous bone particles (32.5%). Both provided the best results and showed a significantly better implant survival compared to no graft material using the Kaplan-Meier method (p = 0.0104 and p < 0.0001). A native collagen membrane was used most often (74.0% of the membrane sites) and provided the best results regarding implant survival in the log-rank test., Conclusions: The retrospective analysis shows that implants inserted in augmented or native bone demonstrate similar implant survival under the conditions of private practice compared to prospective studies. To establish a broad base of support, further well-designed clinical trials are necessary.

Published
2016
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