Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions

被引:46
|
作者
Kern, Stefan [1 ]
Lavergne, Thomas [2 ]
Notz, Dirk [3 ,4 ]
Pedersen, Leif Toudal [5 ]
Tonboe, Rasmus [6 ]
机构
[1] Univ Hamburg, Integrated Climate Data Ctr ICDC, Ctr Earth Syst Res & Sustainabil CEN, Hamburg, Germany
[2] Norwegian Meteorol Inst, Res & Dev Dept, Oslo, Norway
[3] Univ Hamburg, Inst Marine Res, Hamburg, Germany
[4] Max Planck Inst Meteorol, Hamburg, Germany
[5] Danish Tech Univ, Lyngby, Denmark
[6] Danish Meteorol Inst, Copenhagen, Denmark
来源
CRYOSPHERE | 2020年 / 14卷 / 07期
关键词
MELT-POND FRACTION; LONG-TERM; ALBEDO; EVOLUTION; CLIMATE; SURFACE; COVER; MODEL; VALIDATION; RETRIEVAL;
D O I
10.5194/tc-14-2469-2020
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
We report on results of a systematic inter-comparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite passive microwave (PMW) observations for the Arctic during summer. The products are compared against SIC and net ice surface fraction (ISF) - SIC minus the per-grid-cell melt pond fraction (MPF) on sea ice - as derived from MODerate resolution Imaging Spectroradiometer (MODIS) satellite observations and observed from ice-going vessels. Like in Kern et al. (2019), we group the 10 products based on the concept of the SIC retrieval used. Group I consists of products of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) and European Space Agency (ESA) Climate Change Initiative (CCI) algorithms. Group II consists of products derived with the Comiso bootstrap algorithm and the National Oceanographic and Atmospheric Administration (NOAA) National Snow and Ice Data Center (NSIDC) SIC climate data record (CDR). Group III consists of Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) and National Aeronautics and Space Administration (NASA) Team (NT) algorithm products, and group IV consists of products of the enhanced NASA Team algorithm (NT2). We find widespread positive and negative differences between PMW and MODIS SIC with magnitudes frequently reaching up to 20 %-25 % for groups I and III and up to 30 %-35 % for groups II and IV. On a pan-Arctic scale these differences may cancel out: Arctic average SIC from group I products agrees with MODIS within 2 %-5 % accuracy during the entire melt period from May through September. Group II and IV products overestimate MODIS Arctic average SIC by 5 %-10 %. Out of group III, ASI is similar to group I products while NT SIC underestimates MODIS Arctic average SIC by 5 %-10 %. These differences, when translated into the impact computing Arctic sea-ice area (SIA), match well with the differences in SIA between the four groups reported for the summer months by Kern et al. (2019). MODIS ISF is systematically overestimated by all products; NT provides the smallest overestimations (up to 25 %) and group II and IV products the largest overestimations (up to 45 %). The spatial distribution of the observed overestimation of MODIS ISF agrees reasonably well with the spatial distribution of the MODIS MPF and we find a robust linear relationship between PMW SIC and MODIS ISF for group I and III products during peak melt, i.e. July and August. We discuss different cases taking into account the expected influence of ice surface properties other than melt ponds, i.e. wet snow and coarse-grained snow/refrozen surface, on brightness temperatures and their ratios used as input to the SIC retrieval algorithms. Based on this discussion we identify the mismatch between the actually observed surface properties and those represented by the ice tie points as the most likely reason for (i) the observed differences between PMW SIC and MODIS ISF and for (ii) the often surprisingly small difference between PMW and MODIS SIC in areas of high melt pond fraction. We conclude that all 10 SIC products are highly inaccurate during summer melt. We hypothesize that the unknown number of melt pond signatures likely included in the ice tie points plays an important role - particularly for groups I and II - and recommend conducting further research in this field.
引用
收藏
页码:2469 / 2493
页数:25
相关论文
共 50 条
  • [21] Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval
    Zhou, Lu
    Stroeve, Julienne
    Xu, Shiming
    Petty, Alek
    Tilling, Rachel
    Winstrup, Mai
    Rostosky, Philip
    Lawrence, Isobel R.
    Liston, Glen E.
    Ridout, Andy
    Tsamados, Michel
    Nandan, Vishnu
    [J]. CRYOSPHERE, 2021, 15 (01): : 345 - 367
  • [22] Arctic sea-ice conditions and the distribution of solar radiation during summer
    Perovich, DK
    Tucker, WB
    [J]. ANNALS OF GLACIOLOGY, VOL 25, 1997: PAPERS FROM THE INTERNATIONAL SYMPOSIUM ON REPRESENTATION OF THE CRYOSPHERE IN CLIMATE AND HYDROLOGICAL MODELS HELD AT VICTORIA, BRITISH COLUMBIA, CANADA, 12-15 AUGUST 1996, 1997, 25 : 445 - 450
  • [23] Estimating Sea Ice Concentration From Microwave Radiometric Data for Arctic Summer Conditions Using Machine Learning
    Li, Xudong
    Xiong, Chuan
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62 : 1 - 18
  • [24] Comparison of Satellite Microwave and Visual Shipborne Data on Sea Ice Concentration
    T. A. Alekseeva
    V. V. Tikhonov
    S. V. Frolov
    M. D. Raev
    I. A. Repina
    Yu. V. Sokolova
    E. V. Afanasieva
    E. A. Sharkov
    S. S. Serovetnikov
    [J]. Izvestiya, Atmospheric and Oceanic Physics, 2019, 55 : 1292 - 1301
  • [25] Comparison of Satellite Microwave and Visual Shipborne Data on Sea Ice Concentration
    Alekseeva, T. A.
    Tikhonov, V. V.
    Frolov, S. V.
    Raev, M. D.
    Repina, I. A.
    Sokolova, Yu. V.
    Afanasieva, E. V.
    Sharkov, E. A.
    Serovetnikov, S. S.
    [J]. IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS, 2019, 55 (09) : 1292 - 1301
  • [26] Satellite Passive Microwave Sea Ice Concentration Retrieval Errors over the Russian Arctic Seas
    Zabolotskikh, E., V
    Zhivotovskaya, M. A.
    Balashova, E.
    Lvova, E.
    Chapron, B.
    [J]. 2022 PHOTONICS & ELECTROMAGNETICS RESEARCH SYMPOSIUM (PIERS 2022), 2022, : 797 - 800
  • [27] Evaluation of late summer passive microwave Arctic sea ice retrievals
    Markus, T
    Dokken, ST
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2002, 40 (02): : 348 - 356
  • [28] The Contribution of Sea-Ice Contamination to Inaccuracies in Sea-Ice Concentration Retrieval from Satellite Microwave Radiometry Data during the Ice-Melt Period
    T. A. Alekseeva
    J. V. Sokolova
    E. V. Afanasyeva
    V. V. Tikhonov
    M. D. Raev
    E. A. Sharkov
    S. M. Kovalev
    V. M. Smolyanitsky
    [J]. Izvestiya, Atmospheric and Oceanic Physics, 2022, 58 : 1470 - 1484
  • [29] Record low sea-ice concentration in the central Arctic during summer 2010
    Zhao, Jinping
    Barber, David
    Zhang, Shugang
    Yang, Qinghua
    Wang, Xiaoyu
    Xie, Hongjie
    [J]. ADVANCES IN ATMOSPHERIC SCIENCES, 2018, 35 (01) : 106 - 115
  • [30] The Contribution of Sea-Ice Contamination to Inaccuracies in Sea-Ice Concentration Retrieval from Satellite Microwave Radiometry Data during the Ice-Melt Period
    Alekseeva, T. A.
    Sokolova, J. V.
    Afanasyeva, E. V.
    Tikhonov, V. V.
    Raev, M. D.
    Sharkov, E. A.
    Kovalev, S. M.
    Smolyanitsky, V. M.
    [J]. IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS, 2022, 58 (12) : 1470 - 1484