Articles | Volume 14, issue 1
https://doi.org/10.5194/tc-14-165-2020
https://doi.org/10.5194/tc-14-165-2020
Research article
 | 
22 Jan 2020
Research article |  | 22 Jan 2020

Broadband albedo of Arctic sea ice from MERIS optical data

Christine Pohl, Larysa Istomina, Steffen Tietsche, Evelyn Jäkel, Johannes Stapf, Gunnar Spreen, and Georg Heygster

Related authors

Multi-wavelength dataset of aerosol extinction profiles retrieved from GOMOS stellar occultation measurements
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Didier Fussen, Christine Bingen, Filip Vanhellemont, Nina Mateshvili, Alexei Rozanov, and Christine Pohl
Atmos. Meas. Tech., 17, 3085–3101, https://doi.org/10.5194/amt-17-3085-2024,https://doi.org/10.5194/amt-17-3085-2024, 2024
Short summary
Retrieval of stratospheric aerosol extinction coefficients from OMPS-LP measurements
Alexei Rozanov, Christine Pohl, Carlo Arosio, Adam Bourassa, Klaus Bramstedt, Elizaveta Malinina, Landon Rieger, and John P. Burrows
EGUsphere, https://doi.org/10.5194/egusphere-2024-358,https://doi.org/10.5194/egusphere-2024-358, 2024
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Stratospheric aerosol characteristics from SCIAMACHY limb observations: 2-parameter retrieval
Christine Pohl, Felix Wrana, Alexei Rozanov, Terry Deshler, Elizaveta Malinina, Christian von Savigny, Landon A. Rieger, Adam E. Bourassa, and John P. Burrows
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-156,https://doi.org/10.5194/amt-2023-156, 2023
Revised manuscript accepted for AMT
Short summary
The retrieval of snow properties from SLSTR Sentinel-3 – Part 1: Method description and sensitivity study
Linlu Mei, Vladimir Rozanov, Christine Pohl, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2757–2780, https://doi.org/10.5194/tc-15-2757-2021,https://doi.org/10.5194/tc-15-2757-2021, 2021
Short summary

Related subject area

Discipline: Sea ice | Subject: Remote Sensing
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Andreas Wernecke, Dirk Notz, Stefan Kern, and Thomas Lavergne
The Cryosphere, 18, 2473–2486, https://doi.org/10.5194/tc-18-2473-2024,https://doi.org/10.5194/tc-18-2473-2024, 2024
Short summary
Sea ice transport and replenishment across and within the Canadian Arctic Archipelago, 2016–2022
Stephen E. L. Howell, David G. Babb, Jack C. Landy, Isolde A. Glissenaar, Kaitlin McNeil, Benoit Montpetit, and Mike Brady
The Cryosphere, 18, 2321–2333, https://doi.org/10.5194/tc-18-2321-2024,https://doi.org/10.5194/tc-18-2321-2024, 2024
Short summary
SAR deep learning sea ice retrieval trained with airborne laser scanner measurements from the MOSAiC expedition
Karl Kortum, Suman Singha, Gunnar Spreen, Nils Hutter, Arttu Jutila, and Christian Haas
The Cryosphere, 18, 2207–2222, https://doi.org/10.5194/tc-18-2207-2024,https://doi.org/10.5194/tc-18-2207-2024, 2024
Short summary
MMSeaIce: a collection of techniques for improving sea ice mapping with a multi-task model
Xinwei Chen, Muhammed Patel, Fernando J. Pena Cantu, Jinman Park, Javier Noa Turnes, Linlin Xu, K. Andrea Scott, and David A. Clausi
The Cryosphere, 18, 1621–1632, https://doi.org/10.5194/tc-18-1621-2024,https://doi.org/10.5194/tc-18-1621-2024, 2024
Short summary
Lead fractions from SAR-derived sea ice divergence during MOSAiC
Luisa von Albedyll, Stefan Hendricks, Nils Hutter, Dmitrii Murashkin, Lars Kaleschke, Sascha Willmes, Linda Thielke, Xiangshan Tian-Kunze, Gunnar Spreen, and Christian Haas
The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024,https://doi.org/10.5194/tc-18-1259-2024, 2024
Short summary

Cited articles

Bannehr, L. and Schwiesow, R.: A Technique to Account for the Misalignment of Pyranometers Installed on Aircraft, J. Atmos. Ocean. Tech., 10, 774–777, https://doi.org/10.1175/1520-0426(1993)010<0774:ATTAFT>2.0.CO;2, 1993. a, b
Bierwirth, E., Wendisch, M., Ehrlich, A., Heese, B., Tesche, M., Althausen, D., Schladitz, A., Müller, D., Otto, S., Trautmann, T., Dinter, T., Hoyningen-Huene, W. V., and Kahn, R.: Spectral surface albedo over Morocco and its impact on radiative forcing of Saharan dust, Tellus B, 61, 252–269, https://doi.org/10.1111/j.1600-0889.2008.00395.x, 2009. a
Birnbaum, G., Dierking, W., Hartmann, J., Lüpkes, C., Ehrlich, A., Garbrecht, T., and Sellmann, L.: The campaign MELTEX with research aircraft ”POLAR 5” in the Arctic in 2008, Berichte zur Polar-und Meeresforschung (Reports on Polar and Marine Research), 593, 93 pp., 2009. a, b, c
Bourgeois, C. S., Calanca, P., and Ohmura, A.: A field study of the hemispherical directional reflectance factor and spectral albedo of dry snow, J. Geophys. Res.-Atmos., 111, D20108, https://doi.org/10.1029/2006JD007296, 2006. a
CERES-EBAF: CERES_EBAF_Ed2.8 Data Quality Summary, available at: https://ceres.larc.nasa.gov/documents/DQ_summaries/CERES_EBAF_Ed2.8_DQS.pdf (last access: 20 December 2018), 2014. a, b
Download
Short summary
A spectral to broadband conversion is developed empirically that can be used in combination with the Melt Pond Detector algorithm to derive broadband albedo (300–3000 nm) of Arctic sea ice from MERIS data. It is validated and shows better performance compared to existing conversion methods. A comparison of MERIS broadband albedo with respective values from ERA5 reanalysis suggests a revision of the albedo values used in ERA5. MERIS albedo might be useful for improving albedo representation.