Articles | Volume 12, issue 4
https://doi.org/10.5194/tc-12-1331-2018
© Author(s) 2018. 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-12-1331-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Apr 2018
Research article |
| 13 Apr 2018
| 13 Apr 2018
The color of melt ponds on Arctic sea ice
Peng Lu
CORRESPONDING AUTHOR
State Key Laboratory of Coastal and Offshore Engineering, Dalian
University of Technology, Dalian, 116024, China
Matti Leppäranta
Institute of Atmospheric and Earth Sciences, University of Helsinki,
Helsinki, 00014, Finland
Bin Cheng
Finnish Meteorological Institute, Helsinki, 00101, Finland
Zhijun Li
State Key Laboratory of Coastal and Offshore Engineering, Dalian
University of Technology, Dalian, 116024, China
Larysa Istomina
Institute of Environmental Physics, University of Bremen, Bremen,
28359, Germany
Georg Heygster
Institute of Environmental Physics, University of Bremen, Bremen,
28359, Germany
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Cited
21 citations as recorded by crossref.
- Snow Depth Retrieval on Arctic Sea Ice Using Under-Ice Hyperspectral Radiation Measurements P. Anhaus et al. 10.3389/feart.2021.711306
- Comparison of Passive Microwave Data with Shipborne Photographic Observations of Summer Sea Ice Concentration along an Arctic Cruise Path Q. Wang et al. 10.3390/rs11172009
- Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations S. Rosenburg et al. 10.5194/amt-16-3915-2023
- Joint mapping of melt pond bathymetry and water volume on sea ice using optical remote sensing images and physical reflectance models C. Xiong & X. Li 10.1016/j.rse.2024.114571
- A New Algorithm for Sea Ice Melt Pond Fraction Estimation From High‐Resolution Optical Satellite Imagery M. Wang et al. 10.1029/2019JC015716
- A lightweight machine learning-based melt pond extraction scheme for oblique shipborne imagery J. Zhou et al. 10.1080/17538947.2025.2543573
- Optimized Recognition Algorithm for Remotely Sensed Sea Ice in Polar Ship Path Planning L. Zhou et al. 10.3390/rs17193359
- Arctic summer sea ice phenology including ponding from 1982 to 2017 X. Chen et al. 10.1007/s13131-022-1993-5
- A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data M. König & N. Oppelt 10.5194/tc-14-2567-2020
- Multi-Scale Polar Object Detection Based on Computer Vision S. Ding et al. 10.3390/w15193431
- Mapping the Bathymetry of Melt Ponds on Arctic Sea Ice Using Hyperspectral Imagery M. König et al. 10.3390/rs12162623
- Comparison of Pond Depth and Ice Thickness Retrieval Algorithms for Summer Arctic Sea Ice H. Zhang et al. 10.3390/rs14122831
- Overview of the studies on the interactions between atmosphere, sea ice, and ocean in the Arctic Ocean and its climatic effects: contributions from Chinese scientists R. Lei et al. 10.1007/s13131-025-2466-4
- Impact of a Surface Ice Lid on the Optical Properties of Melt Ponds P. Lu et al. 10.1029/2018JC014161
- Design and Implementation of an Ice-Tethered Observation System for Melt Pond Evolution with Vision and Temperature Profile Measurements G. Zuo et al. 10.3390/jmse12071049
- Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective H. Lappalainen et al. 10.5194/acp-22-4413-2022
- The internal melting of landfast sea ice in Prydz Bay, East Antarctica J. Zhao et al. 10.1088/1748-9326/ac76d9
- Evaporation over a glacial lake in Antarctica E. Shevnina et al. 10.5194/tc-16-3101-2022
- Monitoring evolution of melt ponds on first-year and multiyear sea ice in the Canadian Arctic Archipelago with optical satellite data Q. Li et al. 10.1017/aog.2020.24
- Cross-hole acoustic tomography of Arctic sea ice: insights into temperature-driven velocity and attenuation variations H. Xu et al. 10.1007/s44295-025-00078-z
- Ice floe segmentation and floe size distribution in airborne and high-resolution optical satellite images: towards an automated labelling deep learning approach Q. Zhang & N. Hughes 10.5194/tc-17-5519-2023
21 citations as recorded by crossref.
- Snow Depth Retrieval on Arctic Sea Ice Using Under-Ice Hyperspectral Radiation Measurements P. Anhaus et al. 10.3389/feart.2021.711306
- Comparison of Passive Microwave Data with Shipborne Photographic Observations of Summer Sea Ice Concentration along an Arctic Cruise Path Q. Wang et al. 10.3390/rs11172009
- Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations S. Rosenburg et al. 10.5194/amt-16-3915-2023
- Joint mapping of melt pond bathymetry and water volume on sea ice using optical remote sensing images and physical reflectance models C. Xiong & X. Li 10.1016/j.rse.2024.114571
- A New Algorithm for Sea Ice Melt Pond Fraction Estimation From High‐Resolution Optical Satellite Imagery M. Wang et al. 10.1029/2019JC015716
- A lightweight machine learning-based melt pond extraction scheme for oblique shipborne imagery J. Zhou et al. 10.1080/17538947.2025.2543573
- Optimized Recognition Algorithm for Remotely Sensed Sea Ice in Polar Ship Path Planning L. Zhou et al. 10.3390/rs17193359
- Arctic summer sea ice phenology including ponding from 1982 to 2017 X. Chen et al. 10.1007/s13131-022-1993-5
- A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data M. König & N. Oppelt 10.5194/tc-14-2567-2020
- Multi-Scale Polar Object Detection Based on Computer Vision S. Ding et al. 10.3390/w15193431
- Mapping the Bathymetry of Melt Ponds on Arctic Sea Ice Using Hyperspectral Imagery M. König et al. 10.3390/rs12162623
- Comparison of Pond Depth and Ice Thickness Retrieval Algorithms for Summer Arctic Sea Ice H. Zhang et al. 10.3390/rs14122831
- Overview of the studies on the interactions between atmosphere, sea ice, and ocean in the Arctic Ocean and its climatic effects: contributions from Chinese scientists R. Lei et al. 10.1007/s13131-025-2466-4
- Impact of a Surface Ice Lid on the Optical Properties of Melt Ponds P. Lu et al. 10.1029/2018JC014161
- Design and Implementation of an Ice-Tethered Observation System for Melt Pond Evolution with Vision and Temperature Profile Measurements G. Zuo et al. 10.3390/jmse12071049
- Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective H. Lappalainen et al. 10.5194/acp-22-4413-2022
- The internal melting of landfast sea ice in Prydz Bay, East Antarctica J. Zhao et al. 10.1088/1748-9326/ac76d9
- Evaporation over a glacial lake in Antarctica E. Shevnina et al. 10.5194/tc-16-3101-2022
- Monitoring evolution of melt ponds on first-year and multiyear sea ice in the Canadian Arctic Archipelago with optical satellite data Q. Li et al. 10.1017/aog.2020.24
- Cross-hole acoustic tomography of Arctic sea ice: insights into temperature-driven velocity and attenuation variations H. Xu et al. 10.1007/s44295-025-00078-z
- Ice floe segmentation and floe size distribution in airborne and high-resolution optical satellite images: towards an automated labelling deep learning approach Q. Zhang & N. Hughes 10.5194/tc-17-5519-2023
Discussed (final revised paper)
Latest update: 16 Oct 2025
Short summary
It is the first time that the color of melt ponds on Arctic sea ice was quantitatively and thoroughly investigated. We answer the question of why the color of melt ponds can change and what the physical and optical reasons are that lead to such changes. More importantly, melt-pond color was provided as potential data in determining ice thickness, especially under the summer conditions when other methods such as remote sensing are unavailable.
It is the first time that the color of melt ponds on Arctic sea ice was quantitatively and...
