Algorithm to retrieve the Melt pond fraction and the spectral albedo of Arctic summer ice from satellite optical data

被引:61
作者
Zege, E. [1 ]
Malinka, A. [1 ]
Katsev, I. [1 ]
Prikhach, A. [1 ]
Heygster, G. [2 ]
Istomina, L. [2 ]
Birnbaum, G. [3 ]
Schwarz, P. [4 ]
机构
[1] Natl Acad Sci Belarus, Inst Phys, Minsk 220072, BELARUS
[2] Univ Bremen, Inst Environm Phys, D-28359 Bremen, Germany
[3] Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, D-27570 Bremerhaven, Germany
[4] Univ Trier, Dept Environm Meteorol, D-54286 Trier, Germany
基金
欧盟第七框架计划;
关键词
Melt ponds; Sea-ice; Albedo; Arctic; Remote sensing; SNOW GRAIN-SIZE; SEA-ICE; LIGHT-SCATTERING; SURFACE ALBEDO;
D O I
10.1016/j.rse.2015.03.012
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A new algorithm to retrieve characteristics (albedo and melt pond fraction) of summer ice in the Arctic from optical satellite data is described. In contrast to other algorithms this algorithm does not use a priori values of the spectral albedo of the sea-ice constituents (such as melt ponds, white ice etc.). Instead, it is based on an analytical solution for the reflection from sea ice surface. The algorithm includes the correction of the sought-for ice and ponds characteristics with the iterative procedure based on the Newton-Raphson method. Also, it accounts for the bi-directional reflection from the ice/snow surface, which is particularly important for Arctic regions where the sun is low. The algorithm includes an original procedure for the atmospheric correction, as well. This algorithm is implemented as computer code called Melt Pond Detector (MPD). The input to the current version of the MPD algorithm is the MERIS Level 1B data, including the radiance coefficients at ten wavelengths and the solar and observation angles (zenith and azimuth). Also, specific parameters describing surface and atmospheric state can be set in a configuration input file. The software output is the map of the melt ponds area fraction and the spectral albedo of sea-ice in HDF5 format. The numerical verification shows that the MPD algorithm provides more accurate results for the light ponds than for the dark ones. The spectral albedo is retrieved with high accuracy for any type of ice and ponds. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:153 / 164
页数:12
相关论文
共 50 条
[31]   Comparative Analysis of Arctic Sea Ice Area Derived from Satellite Microwave Radiometry Data (VASIA2 Algorithm) with Ice Charts of the Arctic and Antarctic Research Institute [J].
Alekseeva, T. A. ;
Raev, M. D. ;
Tikhonov, V. V. ;
Sokolova, J., V ;
Sharkov, E. A. ;
Frolov, S., V ;
Serovetnikov, S. S. .
IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS, 2021, 57 (09) :1076-1080
[32]   Comparative Analysis of Arctic Sea Ice Area Derived from Satellite Microwave Radiometry Data (VASIA2 Algorithm) with Ice Charts of the Arctic and Antarctic Research Institute [J].
T. A. Alekseeva ;
M. D. Raev ;
V. V. Tikhonov ;
J. V. Sokolova ;
E. A. Sharkov ;
S. V. Frolov ;
S. S. Serovetnikov .
Izvestiya, Atmospheric and Oceanic Physics, 2021, 57 :1076-1080
[33]   Impacts of sea ice retreat, thinning, and melt-pond proliferation on the summer phytoplankton bloom in the Chukchi Sea, Arctic Ocean [J].
Palmer, Molly A. ;
Saenz, Benjamin T. ;
Arrigo, Kevin R. .
DEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY, 2014, 105 :85-104
[34]   Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice [J].
Nasonova, Sasha ;
Scharien, Randall K. ;
Haas, Christian ;
Howell, Stephen E. L. .
REMOTE SENSING, 2018, 10 (01)
[35]   Delay in Arctic Sea Ice Freeze-Up Linked to Early Summer Sea Ice Loss: Evidence from Satellite Observations [J].
Zheng, Lei ;
Cheng, Xiao ;
Chen, Zhuoqi ;
Liang, Qi .
REMOTE SENSING, 2021, 13 (11)
[36]   Estimating Early Summer Snow Depth on Sea Ice Using a Radiative Transfer Model and Optical Satellite Data [J].
Wang, Mingfeng ;
Oppelt, Natascha .
REMOTE SENSING, 2023, 15 (20)
[37]   Spring melt pond fraction in the Canadian Arctic Archipelago predicted from RADARSAT-2 [J].
Howell, Stephen E. L. ;
Scharien, Randall K. ;
Landy, Jack ;
Brady, Mike .
CRYOSPHERE, 2020, 14 (12) :4675-4686
[38]   Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network [J].
Roesel, A. ;
Kaleschke, L. ;
Birnbaum, G. .
CRYOSPHERE, 2012, 6 (02) :431-446
[39]   Comparison of different retrieval techniques for melt ponds on Arctic sea ice from Landsat and MODIS satellite data [J].
Roesel, Anja ;
Kaleschke, Lars .
ANNALS OF GLACIOLOGY, 2011, 52 (57) :185-191
[40]   Atmospheric and spectral corrections for estimating surface albedo from satellite data [J].
Zoran, M ;
Stefan, S .
JOURNAL OF OPTOELECTRONICS AND ADVANCED MATERIALS, 2006, 8 (01) :247-251