FN Archimer Export Format
PT J
TI Inter-comparison and evaluation of Arctic sea ice type products
BT 
AF Ye, Yufang
   Luo, Yanbing
   Sun, Yan
   Shokr, Mohammed
   Aaboe, Signe
   GIRARD-ARDHUIN, Fanny
   Hui, Fengming
   Cheng, Xiao
   Chen, Zhuoqi
AS 1:1;2:1;3:1;4:2;5:3;6:4;7:1;8:1;9:1;
FF 1:;2:;3:;4:;5:;6:PDG-ODE-LOPS-SIAM;7:;8:;9:;
C1 School of Geospatial Engineering and Science, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
   Meteorological Research Division, Environment and Climate Change Canada, Toronto M3H5T4, Canada
   Department of Remote Sensing and Data Management, Norwegian Meteorological Institute, Tromso, Norway
   Laboratoire d'Océanographie Physique et Spatiale (LOPS), Ifremer-Univ. Brest-CNRS-IRD, IUEM, F-29280, Plouzané, France
C2 UNIV SUN YAT SEN, CHINA
   ENVIRONM & CLIMATE CHANGE CANADA, CANADA
   NORWEGIAN METEOROL INST MET, NORWAY
   IFREMER, FRANCE
SI BREST
SE PDG-ODE-LOPS-SIAM
UM LOPS
IN WOS Ifremer UMR
   DOAJ
   copubli-europe
   copubli-int-hors-europe
   copubli-sud
IF 5.2
TC 5
UR https://archimer.ifremer.fr/doc/00772/88397/94055.pdf
   https://archimer.ifremer.fr/doc/00772/88397/99843.pdf
LA English
DT Article
AB Arctic sea ice type (SIT) variation is a sensitive indicator of climate change. However, systematic inter-comparison and analysis for SIT products are lacking. This study analyzed nine SIT products from five SIT retrieval approaches covering the winters from 1999 to 2018. These SIT products were inter-compared towards sea ice age product and evaluated with Synthetic Aperture Radar images. Among all, the largest daily Arctic multiyear ice (MYI) extent difference reaches 4.5× 106 km2, while that in monthly data varies between 0.6× 103 km2 and 3.6× 106 km2. Overall speaking, the Zhang- and KNMI-SIT products based on Ku-band scatterometer perform the best. However, when using C-band scatterometer, KNMI-SIT shows overestimation of MYI in the early winter, and Zhang-SIT shows underestimation with anomalous fluctuations. C3S- and OSISAF-SIT show large daily variability. IFREMER-SIT generally underestimates MYI. Factors that could impact their performances are analyzed and summarized: (1) Ku-band scatterometer generally performs better than C-band scatterometer on SIT discrimination, while the latter sometimes identifies first-year ice (FYI) more accurately, especially when FYI and MYI are highly mixed. (2) Simple combination of scatterometer and radiometer data is not always beneficial, e.g. under circumstances with strong atmospheric influence on microwave signatures. (3) The representativeness of training data and efficiency of classification are crucial for SIT classification. Spatial and temporal variation of characteristic training dataset should be well accounted in the SIT method. Additionally, the change of separation pattern of microwave data could influence the adaptive classification method. (4) Post-processing corrections play important roles and should be considered with caution. 
PY 2023
PD JAN
SO Cryosphere
SN 1994-0416
PU Copernicus GmbH
VL 17
IS 1
UT 000918305600001
BP 279
EP 308
DI 10.5194/tc-17-279-2023
ID 88397
ER

EF