Articles | Volume 14, issue 1
https://doi.org/10.5194/tc-14-165-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-165-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jan 2020
Research article |
| 22 Jan 2020
| 22 Jan 2020
Broadband albedo of Arctic sea ice from MERIS optical data
Christine Pohl
CORRESPONDING AUTHOR
Institute of Environmental Physics, University of Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany
Larysa Istomina
Institute of Environmental Physics, University of Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany
Steffen Tietsche
European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
Evelyn Jäkel
Leipzig Institute for Meteorology, University of Leipzig, Stephanstr. 3, 04103 Leipzig, Germany
Johannes Stapf
Leipzig Institute for Meteorology, University of Leipzig, Stephanstr. 3, 04103 Leipzig, Germany
Gunnar Spreen
Institute of Environmental Physics, University of Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany
Georg Heygster
Institute of Environmental Physics, University of Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany
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Cited
17 citations as recorded by crossref.
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- Relationships between summertime surface albedo and melt pond fraction in the central Arctic Ocean: The aggregate scale of albedo obtained on the MOSAiC floe R. Calmer et al. 10.1525/elementa.2023.00001
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- The retrieval of snow properties from SLSTR Sentinel-3 – Part 1: Method description and sensitivity study L. Mei et al. 10.5194/tc-15-2757-2021
- A New Structure for the Sea Ice Essential Climate Variables of the Global Climate Observing System T. Lavergne et al. 10.1175/BAMS-D-21-0227.1
- Review of Land Surface Albedo: Variance Characteristics, Climate Effect and Management Strategy X. Zhang et al. 10.3390/rs14061382
- Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model H. Niehaus et al. 10.5194/tc-18-933-2024
- Estimating Surface Albedo of Arctic Sea Ice Using an Ensemble Back-Propagation Neural Network: Toward a Better Consideration of Reflectance Anisotropy and Melt Ponds Y. Ding et al. 10.1109/TGRS.2022.3202046
- Development of Land Surface Albedo Algorithm for the GK-2A/AMI Instrument K. Lee et al. 10.3390/rs12152500
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- Daily Arctic Sea-Ice Albedo Retrieval With a Multiband Reflectance Iteration Algorithm Q. Cheng et al. 10.1109/TGRS.2023.3323506
17 citations as recorded by crossref.
- Evaluation of downward and upward solar irradiances simulated by the Integrated Forecasting System of ECMWF using airborne observations above Arctic low-level clouds H. Müller et al. 10.5194/acp-24-4157-2024
- Four decades of global surface albedo estimates in the third edition of the CM SAF cLoud, Albedo and surface Radiation (CLARA) climate data record A. Riihelä et al. 10.5194/essd-16-1007-2024
- Sea Ice Melt Pond Fraction Derived From Sentinel‐2 Data: Along the MOSAiC Drift and Arctic‐Wide H. Niehaus et al. 10.1029/2022GL102102
- Relationships between summertime surface albedo and melt pond fraction in the central Arctic Ocean: The aggregate scale of albedo obtained on the MOSAiC floe R. Calmer et al. 10.1525/elementa.2023.00001
- Radiative closure and cloud effects on the radiation budget based on satellite and shipborne observations during the Arctic summer research cruise, PS106 C. Barrientos-Velasco et al. 10.5194/acp-22-9313-2022
- Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982–2018 K. Kouki et al. 10.5194/tc-17-5007-2023
- Observations and modeling of areal surface albedo and surface types in the Arctic E. Jäkel et al. 10.5194/tc-18-1185-2024
- Year-round impact of winter sea ice thickness observations on seasonal forecasts B. Balan-Sarojini et al. 10.5194/tc-15-325-2021
- The retrieval of snow properties from SLSTR Sentinel-3 – Part 1: Method description and sensitivity study L. Mei et al. 10.5194/tc-15-2757-2021
- A New Structure for the Sea Ice Essential Climate Variables of the Global Climate Observing System T. Lavergne et al. 10.1175/BAMS-D-21-0227.1
- Review of Land Surface Albedo: Variance Characteristics, Climate Effect and Management Strategy X. Zhang et al. 10.3390/rs14061382
- Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model H. Niehaus et al. 10.5194/tc-18-933-2024
- Estimating Surface Albedo of Arctic Sea Ice Using an Ensemble Back-Propagation Neural Network: Toward a Better Consideration of Reflectance Anisotropy and Melt Ponds Y. Ding et al. 10.1109/TGRS.2022.3202046
- Development of Land Surface Albedo Algorithm for the GK-2A/AMI Instrument K. Lee et al. 10.3390/rs12152500
- Sea ice cover in the Copernicus Arctic Regional Reanalysis Y. Batrak et al. 10.5194/tc-18-1157-2024
- Parameterizing anisotropic reflectance of snow surfaces from airborne digital camera observations in Antarctica T. Carlsen et al. 10.5194/tc-14-3959-2020
- Daily Arctic Sea-Ice Albedo Retrieval With a Multiband Reflectance Iteration Algorithm Q. Cheng et al. 10.1109/TGRS.2023.3323506
Latest update: 18 Apr 2024
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.
A spectral to broadband conversion is developed empirically that can be used in combination with...
