121 citations as recorded by crossref.

1. Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice S. Nasonova et al. 10.3390/rs10010037
2. Delay in Arctic Sea Ice Freeze-Up Linked to Early Summer Sea Ice Loss: Evidence from Satellite Observations L. Zheng et al. 10.3390/rs13112162
3. Reflective properties of white sea ice and snow A. Malinka et al. 10.5194/tc-10-2541-2016
4. Towards reliable Arctic sea ice prediction using multivariate data assimilation J. Liu et al. 10.1016/j.scib.2018.11.018
5. Investigation of Under‐Ice Phytoplankton Growth in the Fully‐Coupled, High‐Resolution Regional Arctic System Model J. Clement Kinney et al. 10.1029/2022JC019000
6. An improved radiative forcing scheme for better representation of Arctic under-ice blooms Y. Gao et al. 10.1016/j.ocemod.2022.102075
7. First-year sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 1: In situ observations R. Scharien et al. 10.5194/tc-8-2147-2014
8. IceMap250—Automatic 250 m Sea Ice Extent Mapping Using MODIS Data C. Gignac et al. 10.3390/rs9010070
9. Regional melt-pond fraction and albedo of thin Arctic first-year drift ice in late summer D. Divine et al. 10.5194/tc-9-255-2015
10. A physical algorithm to measure sea ice concentration from passive microwave remote sensing data V. Tikhonov et al. 10.1016/j.asr.2015.07.009
11. Observing the evolution of summer melt on multiyear sea ice with ICESat-2 and Sentinel-2 E. Buckley et al. 10.5194/tc-17-3695-2023
12. Regions of open water and melting sea ice drive new particle formation in North East Greenland M. Dall´Osto et al. 10.1038/s41598-018-24426-8
13. Summer High‐Wind Events and Phytoplankton Productivity in the Arctic Ocean A. Crawford et al. 10.1029/2020JC016565
14. Changes in summer sea ice, albedo, and portioning of surface solar radiation in the Pacific sector of Arctic Ocean during 1982–2009 R. Lei et al. 10.1002/2016JC011831
15. Spring melt pond fraction in the Canadian Arctic Archipelago predicted from RADARSAT-2 S. Howell et al. 10.5194/tc-14-4675-2020
16. Detecting Melt Pond Onset on Landfast Arctic Sea Ice Using a Dual C-Band Satellite Approach S. Maknun et al. 10.3390/rs16122091
17. A neural network-based method for satellite-based mapping of sediment-laden sea ice in the Arctic H. Waga et al. 10.1016/j.rse.2021.112861
18. Arctic summer sea ice phenology including ponding from 1982 to 2017 X. Chen et al. 10.1007/s13131-022-1993-5
19. MODIS Sea Ice Thickness and Open Water–Sea Ice Charts over the Barents and Kara Seas for Development and Validation of Sea Ice Products from Microwave Sensor Data M. Mäkynen & J. Karvonen 10.3390/rs9121324
20. Melt Pond Retrieval Based on the LinearPolar Algorithm Using Landsat Data Y. Qin et al. 10.3390/rs13224674
21. Reducing Weather Influences on an 89 GHz Sea Ice Concentration Algorithm in the Arctic Using Retrievals From an Optimal Estimation Method J. Lu et al. 10.1029/2019JC015912
22. Interactions between wind-blown snow redistribution and melt ponds in a coupled ocean–sea ice model O. Lecomte et al. 10.1016/j.ocemod.2014.12.003
23. Predicting Melt Pond Fraction on Landfast Snow Covered First Year Sea Ice from Winter C-Band SAR Backscatter Utilizing Linear, Polarimetric and Texture Parameters S. Ramjan et al. 10.3390/rs10101603
24. The Arctic Ocean Observation Operator for 6.9 GHz (ARC3O) – Part 2: Development and evaluation C. Burgard et al. 10.5194/tc-14-2387-2020
25. Comparing elevation and backscatter retrievals from CryoSat-2 and ICESat-2 over Arctic summer sea ice G. Dawson & J. Landy 10.5194/tc-17-4165-2023
26. Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice A. Bateson et al. 10.5194/tc-14-403-2020
27. Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions S. Kern et al. 10.5194/tc-14-2469-2020
28. Enhanced Arctic Ice Concentration Estimation Merging MODIS Ice Surface Temperature and SSM/I Sea-Ice Concentration W. Tan et al. 10.1080/07055900.2014.883491
29. Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle Data H. Han et al. 10.3390/rs8010057
30. Broadband radiometric measurements from GPS satellites reveal summertime Arctic Ocean Albedo decreases more rapidly than sea ice recedes P. Dreike et al. 10.1038/s41598-023-39877-x
31. Overview paper: New insights into aerosol and climate in the Arctic J. Abbatt et al. 10.5194/acp-19-2527-2019
32. Changes in the Ice-Free Period Duration in the Kara Sea Coastal Zone from Satellite Data P. Shabanov 10.1134/S0001437022040105
33. Open Access Data in Polar and Cryospheric Remote Sensing A. Pope et al. 10.3390/rs6076183
34. New insight from CryoSat-2 sea ice thickness for sea ice modelling D. Schröder et al. 10.5194/tc-13-125-2019
35. Melt pond fraction and spectral sea ice albedo retrieval from MERIS data – Part 2: Case studies and trends of sea ice albedo and melt ponds in the Arctic for years 2002–2011 L. Istomina et al. 10.5194/tc-9-1567-2015
36. The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations S. Kern et al. 10.5194/tc-10-2217-2016
37. Separability of sea ice types from wide swath C- and L-band synthetic aperture radar imagery acquired during the melt season J. Casey et al. 10.1016/j.rse.2015.12.021
38. Improvement of sea ice thermodynamics with variable sea ice salinity and melt pond parameterizations in an OGCM T. Toyoda et al. 10.1016/j.ocemod.2023.102288
39. Sea Ice Melt Pond Fraction Derived From Sentinel‐2 Data: Along the MOSAiC Drift and Arctic‐Wide H. Niehaus et al. 10.1029/2022GL102102
40. Retrieval of Melt Pond Fraction over Arctic Sea Ice during 2000–2019 Using an Ensemble-Based Deep Neural Network Y. Ding et al. 10.3390/rs12172746
41. Linking winter and spring thermodynamic sea-ice states at critical scales using an object-based image analysis of Sentinel-1 R. Scharien et al. 10.1017/aog.2017.43
42. Winter Sentinel‐1 Backscatter as a Predictor of Spring Arctic Sea Ice Melt Pond Fraction R. Scharien et al. 10.1002/2017GL075547
43. Level-ice melt ponds in the Los Alamos sea ice model, CICE E. Hunke et al. 10.1016/j.ocemod.2012.11.008
44. Melt Pond Scheme Parameter Estimation Using an Adjoint Model Y. Lu et al. 10.1007/s00376-021-0305-x
45. Co-production of knowledge reveals loss of Indigenous hunting opportunities in the face of accelerating Arctic climate change D. Hauser et al. 10.1088/1748-9326/ac1a36
46. 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
47. Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review T. Vihma et al. 10.5194/acp-14-9403-2014
48. Machine learning approaches to retrieve pan-Arctic melt ponds from visible satellite imagery S. Lee et al. 10.1016/j.rse.2020.111919
49. Automated Detection and Depth Determination of Melt Ponds on Sea Ice in ICESat-2 ATLAS Data—The Density-Dimension Algorithm for Bifurcating Sea-Ice Reflectors (DDA-Bifurcate-Seaice) U. Herzfeld et al. 10.1109/TGRS.2023.3268073
50. Winter arctic sea ice volume decline: uncertainties reduced using passive microwave-based sea ice thickness C. Soriot et al. 10.1038/s41598-024-70136-9
51. 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
52. The Effect of Melt Pond Geometry on the Distribution of Solar Energy Under First‐Year Sea Ice C. Horvat et al. 10.1029/2019GL085956
53. Melt pond detection on landfast sea ice using dual co-polarized Ku-band backscatter T. Geldsetzer et al. 10.1016/j.rse.2023.113725
54. Effect of melt ponds fraction on sea ice anomalies in the Arctic Ocean J. Feng et al. 10.1016/j.jag.2021.102297
55. CHANGES IN THE ICE-FREE PERIOD IN THE KARA SEA FROM COASTAL OBSERVATIONS P. Shabanov & N. Shabanova 10.29006/1564-2291.JOR-2024.52(3).4
56. First-year sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 2: Scaling in situ to Radarsat-2 R. Scharien et al. 10.5194/tc-8-2163-2014
57. Revisiting the potential of melt pond fraction as a predictor for the seasonal Arctic sea ice extent minimum J. Liu et al. 10.1088/1748-9326/10/5/054017
58. Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations N. Ivanova et al. 10.5194/tc-9-1797-2015
59. Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data Y. Tanaka 10.3390/rs12061033
60. ОТРАЖАТЕЛЬНЫЕ СВОЙСТВА АРКТИЧЕСКОГО ЛЕТНЕГО ЛЬДА В ВИДИМОМ И ИНФРАКРАСНОМ ДИАПАЗОНАХ, "Фундаментальная и прикладная гидрофизика" Э. Зеге et al. 10.7868/S2073667318030024
61. The 2018 North Greenland polynya observed by a newly introduced merged optical and passive microwave sea-ice concentration dataset V. Ludwig et al. 10.5194/tc-13-2051-2019
62. Next-generation angular distribution models for top-of-atmosphere radiative flux calculation from CERES instruments: methodology W. Su et al. 10.5194/amt-8-611-2015
63. The color of melt ponds on Arctic sea ice P. Lu et al. 10.5194/tc-12-1331-2018
64. A New Algorithm for Sea Ice Melt Pond Fraction Estimation From High‐Resolution Optical Satellite Imagery M. Wang et al. 10.1029/2019JC015716
65. Application of Sentinel-2 MSI in Arctic Research: Evaluating the Performance of Atmospheric Correction Approaches Over Arctic Sea Ice M. König et al. 10.3389/feart.2019.00022
66. Research on Fast Extraction Method of Sea Ice Boundary in Arctic Channel Based on MODIS Data Y. Yang et al. 10.1088/1755-1315/310/2/022049
67. Algorithm to retrieve the melt pond fraction and the spectral albedo of Arctic summer ice from satellite optical data E. Zege et al. 10.1016/j.rse.2015.03.012
68. Estimation of melt pond fraction over high‐concentration Arctic sea ice using AMSR‐E passive microwave data Y. Tanaka et al. 10.1002/2016JC011876
69. Estimating Early Summer Snow Depth on Sea Ice Using a Radiative Transfer Model and Optical Satellite Data M. Wang & N. Oppelt 10.3390/rs15205016
70. Mosaicking Opportunistically Acquired Very High-Resolution Helicopter-Borne Images over Drifting Sea Ice Using COTS Sensors C. Hyun et al. 10.3390/s19051251
71. MeltPondNet: A Swin Transformer U-Net for Detection of Melt Ponds on Arctic Sea Ice I. Sudakow et al. 10.1109/JSTARS.2022.3213192
72. Arctic sea ice melt pond fraction in 2000–2021 derived by dynamic pixel spectral unmixing of MODIS images C. Xiong & Y. Ren 10.1016/j.isprsjprs.2023.01.023
73. Sediment-laden sea ice in southern Hudson Bay: Entrainment, transport, and biogeochemical implications D. Barber et al. 10.1525/elementa.2020.00108
74. Cold-air outbreaks over the ocean at high latitudes and associated mesoscale atmospheric circulations: Problems of numerical modelling D. Chechin & M. Pichugin 10.1134/S0001433815090078
75. Comparison of Arctic Sea Ice Concentrations from the NASA Team, ASI, and VASIA2 Algorithms with Summer and Winter Ship Data T. Alekseeva et al. 10.3390/rs11212481
76. Spatiotemporal evolution of melt ponds on Arctic sea ice M. Webster et al. 10.1525/elementa.2021.000072
77. Reflective properties of melt ponds on sea ice A. Malinka et al. 10.5194/tc-12-1921-2018
78. Changing state of Arctic sea ice across all seasons J. Stroeve & D. Notz 10.1088/1748-9326/aade56
79. A method to derive satellite PAR albedo time series over first-year sea ice in the Arctic Ocean J. Laliberté et al. 10.1525/elementa.2020.00080
80. A sensor-agnostic albedo retrieval method for realistic sea ice surfaces: model and validation Y. Zhou et al. 10.5194/tc-17-1053-2023
81. Characterization of sea ice and its snow cover in the Arctic Pacific sector during the summer of 2016 Q. Ji et al. 10.1007/s13131-021-1716-3
82. Declassified high-resolution visible imagery for Arctic sea ice investigations: An overview R. Kwok 10.1016/j.rse.2013.11.015
83. Pan-Arctic melt pond fraction trend, variability, and contribution to sea ice changes J. Feng et al. 10.1016/j.gloplacha.2022.103932
84. Detection of Melt Ponds on Arctic Summer Sea Ice From ICESat‐2 R. Tilling et al. 10.1029/2020GL090644
85. Meltwater sources and sinks for multiyear Arctic sea ice in summer D. Perovich et al. 10.5194/tc-15-4517-2021
86. Combining “Deep Learning” and Physically Constrained Neural Networks to Derive Complex Glaciological Change Processes from Modern High-Resolution Satellite Imagery: Application of the GEOCLASS-Image System to Create VarioCNN for Glacier Surges U. Herzfeld et al. 10.3390/rs16111854
87. Multi-scale observations of the co-evolution of sea ice thermophysical properties and microwave brightness temperatures during the summer melt period in Hudson Bay M. Harasyn et al. 10.1525/elementa.412
88. Development of Geo-KOMPSAT-2A Algorithm for Sea-Ice Detection Using Himawari-8/AHI Data D. Jin et al. 10.3390/rs12142262
89. A Regional Seasonal Forecast Model of Arctic Minimum Sea Ice Extent: Reflected Solar Radiation versus Late Winter Coastal Divergence R. Kim et al. 10.1175/JCLI-D-20-0846.1
90. Arctic climate: changes in sea ice extent outweigh changes in snow cover A. Letterly et al. 10.5194/tc-12-3373-2018
91. Semantic segmentation of Arctic Sea ice in summer from remote sensing satellite images based on BAU-NET W. Ji et al. 10.1117/1.JRS.16.046514
92. Modeling sea ice albedo and transmittance measurements with a fully-coupled radiative transfer model Z. Jin et al. 10.1364/OE.491306
93. Applications of soft computing models for predicting sea surface temperature: a comprehensive review and assessment M. Haghbin et al. 10.1186/s40645-020-00400-9
94. From Bright Windows to Dark Spots: Snow Cover Controls Melt Pond Optical Properties During Refreezing P. Anhaus et al. 10.1029/2021GL095369
95. Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review G. Balsamo et al. 10.3390/rs10122038
96. Arctic Sea Ice Thickness Estimation From Passive Microwave Satellite Observations Between 1.4 and 36 GHz C. Soriot et al. 10.1029/2022EA002542
97. Sea ice floe size: its impact on pan-Arctic and local ice mass and required model complexity A. Bateson et al. 10.5194/tc-16-2565-2022
98. Essential gaps and uncertainties in the understanding of the roles and functions of Arctic sea ice S. Gerland et al. 10.1088/1748-9326/ab09b3
99. Evaluation of summer passive microwave sea ice concentrations in the Chukchi Sea based on KOMPSAT-5 SAR and numerical weather prediction data H. Han & H. Kim 10.1016/j.rse.2018.02.058
100. 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
101. Sunlight, clouds, sea ice, albedo, and the radiative budget: the umbrella versus the blanket D. Perovich 10.5194/tc-12-2159-2018
102. Dimethyl sulfide dynamics in first-year sea ice melt ponds in the Canadian Arctic Archipelago M. Gourdal et al. 10.5194/bg-15-3169-2018
103. Sensitivity of Arctic sea ice to melt pond processes and atmospheric forcing: A model study J. Sterlin et al. 10.1016/j.ocemod.2021.101872
104. The internal melting of landfast sea ice in Prydz Bay, East Antarctica J. Zhao et al. 10.1088/1748-9326/ac76d9
105. Seasonal cycle and long-term trend of solar energy fluxes through Arctic sea ice S. Arndt & M. Nicolaus 10.5194/tc-8-2219-2014
106. Radar backscattering changes in Arctic sea ice from late summer to early autumn observed by space-borne X-band HH-polarization SAR J. Park et al. 10.1080/2150704X.2016.1165881
107. Sea and Freshwater Ice Concentration from VIIRS on Suomi NPP and the Future JPSS Satellites Y. Liu et al. 10.3390/rs8060523
108. Insights on past and future sea-ice evolution from combining observations and models J. Stroeve & D. Notz 10.1016/j.gloplacha.2015.10.011
109. Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery N. Wright & C. Polashenski 10.5194/tc-12-1307-2018
110. Generating a Long-Term Spatiotemporally Continuous Melt Pond Fraction Dataset for Arctic Sea Ice Using an Artificial Neural Network and a Statistical-Based Temporal Filter Z. Peng et al. 10.3390/rs14184538
111. Projected future biophysical states of the Bering Sea A. Hermann et al. 10.1016/j.dsr2.2015.11.001
112. Estimation of summer pan-Arctic ice draft from satellite passive microwave observations J. Kim et al. 10.1016/j.rse.2023.113662
113. Dynamic Preconditioning of the Minimum September Sea-Ice Extent J. Williams et al. 10.1175/JCLI-D-15-0515.1
114. Mapping the Bathymetry of Melt Ponds on Arctic Sea Ice Using Hyperspectral Imagery M. König et al. 10.3390/rs12162623
115. Melt pond fraction and spectral sea ice albedo retrieval from MERIS data – Part 1: Validation against in situ, aerial, and ship cruise data L. Istomina et al. 10.5194/tc-9-1551-2015
116. Estimating Sea Ice Concentration From Microwave Radiometric Data for Arctic Summer Conditions Using Machine Learning X. Li & C. Xiong 10.1109/TGRS.2024.3382756
117. 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
118. On the Estimation of Melt Pond Fraction on the Arctic Sea Ice With ENVISAT WSM Images M. Makynen et al. 10.1109/TGRS.2014.2311476
119. Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation Q. Yang et al. 10.5194/tc-10-761-2016
120. Signature of Arctic first-year ice melt pond fraction in X-band SAR imagery A. Fors et al. 10.5194/tc-11-755-2017
121. Melt pond distribution and geometry in high Arctic sea ice derived from aerial investigations W. Huang et al. 10.1017/aog.2016.30