Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions
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Published:2020-07-28
Issue:7
Volume:14
Page:2469-2493
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ISSN:1994-0424
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Container-title:The Cryosphere
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language:en
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Short-container-title:The Cryosphere
Author:
Kern StefanORCID, Lavergne ThomasORCID, Notz DirkORCID, Pedersen Leif ToudalORCID, Tonboe Rasmus
Abstract
Abstract. 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.
Publisher
Copernicus GmbH
Subject
Earth-Surface Processes,Water Science and Technology
Reference60 articles.
1. Burgard, C., Notz, D., Pedersen, L. T., and Tonboe, R. T.: The Arctic Ocean Observation Operator for 6.9 GHz (ARC3O) – Part 2: Development and evaluation, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-318, in review, 2020. 2. Cavalieri D. J., Gloersen, P., and Campbell, W. J.: Determination of Sea Ice
Parameters with the NIMBUS 7 SMMR. J. Geophys. Res., 89, 5355–5369,
1984. 3. Cavalieri, D. J., Crawford, J., Drinkwater, M., Emery, W. J., Eppler, D. T., Farmer, L.
D., Goodberlet, M., Jentz, R., Milman, A., Morris, C., Onstott, R.,
Schweiger, A., Shuchman, R., Steffen, K., Swift, C. T., Wackerman, C., and
Weaver, R. L.: NASA sea ice validation program for the DMSP SSM/I: final
report, NASA Technical Memorandum 104559, National Aeronautics and Space
Administration, Washington, DC, 126 pp., 1992. 4. Cavalieri, D. J., Burns, B. A., and Onstott, R. G.: Investigation of the
effects of summer let on the calculation of sea ice concentration using
active and passive microwave data, J. Geophys. Res., 95, 5359–5369,
1990. 5. Cavalieri, D. J., Parkinson, C. L., Gloersen, P., Comiso, J. C., and Zwally,
H. J.: Deriving long-term time series of sea ice cover from satellite
passive-microwave multisensor data sets, J. Geophys.
Res., 104, 15803–15814, https://doi.org/10.1029/1999JC900081, 1999.
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