FN Archimer Export Format
PT J
TI A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data
BT 
AF RICKER, Robert
   HENDRICKS, Stefan
   KALESCHKE, Lars
   TIAN-KUNZE, Xiangshan
   KING, Jennifer
   HAAS, Christian
AS 1:1,2;2:1;3:3;4:3;5:4;6:1,5;
FF 1:PDG-ODE-LOPS;2:;3:;4:;5:;6:;
C1 Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, Bussestr 24, D-27570 Bremerhaven, Germany.
   Univ Brest, CNRS, IFREMER, IRD,LOPS,IUEM, F-29280 Brest, France.
   Univ Hamburg, Inst Oceanog, Bundesstr 53, D-20146 Hamburg, Germany.
   Norwegian Polar Res Inst, Tromso, Norway.
   York Univ, Dept Earth & Space Sci & Engn, Toronto, ON, Canada.
C2 INST A WEGENER, GERMANY
   IFREMER, FRANCE
   UNIV HAMBURG, GERMANY
   NORWEGIAN POLAR RES INST, NORWAY
   UNIV YORK CANADA, CANADA
SI BREST
SE PDG-ODE-LOPS
UM LOPS
IN WOS Ifremer jusqu'en 2018
   DOAJ
   copubli-europe
   copubli-int-hors-europe
IF 4.524
TC 176
UR https://archimer.ifremer.fr/doc/00393/50443/51184.pdf
LA English
DT Article
AB Sea-ice thickness on a global scale is derived from different satellite sensors using independent retrieval methods. Due to the sensor and orbit characteristics, such satellite retrievals differ in spatial and temporal resolution as well as in the sensitivity to certain sea-ice types and thickness ranges. Satellite altimeters, such as CryoSat-2 (CS2), sense the height of the ice surface above the sea level, which can be converted into sea-ice thickness. Relative uncertainties associated with this method are large over thin ice regimes. Another retrieval method is based on the evaluation of surface brightness temperature (TB) in L-band microwave frequencies (1.4 GHz) with a thickness-dependent emission model, as measured by the Soil Moisture and Ocean Salinity (SMOS) satellite. While the radiometer-based method looses sensitivity for thick sea ice (> 1 m), relative uncertainties over thin ice are significantly smaller than for the altimetry-based retrievals. In addition, the SMOS product provides global sea-ice coverage on a daily basis unlike the altimeter data. This study presents the first merged product of complementary weekly Arctic sea-ice thickness data records from the CS2 altimeter and SMOS radiometer. We use two merging approaches: a weighted mean (WM) and an optimal interpolation (OI) scheme. While the weighted mean leaves gaps between CS2 orbits, OI is used to produce weekly Arctic-wide sea-ice thickness fields. The benefit of the data merging is shown by a comparison with airborne electromagnetic (AEM) induction sounding measurements. When compared to airborne thickness data in the Barents Sea, the merged product has a root mean square deviation (RMSD) of about 0.7m less than the CS2 product and therefore demonstrates the capability to enhance the CS2 product in thin ice regimes. However, in mixed first-year (FYI) and multiyear (MYI) ice regimes as in the Beaufort Sea, the CS2 retrieval shows the lowest bias. 
PY 2017
PD JUN
SO Cryosphere
SN 1994-0416
PU Copernicus Gesellschaft Mbh
VL 11
IS 4
UT 000405326000001
BP 1607
EP 1623
DI 10.5194/tc-11-1607-2017
ID 50443
ER

EF