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The Cryosphere, 12, 2005-2020, 2018
https://doi.org/10.5194/tc-12-2005-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
15 Jun 2018
Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice–ocean data assimilation system
Takuya Nakanowatari1, Jun Inoue1, Kazutoshi Sato1,a, Laurent Bertino2, Jiping Xie2, Mio Matsueda3, Akio Yamagami3, Takeshi Sugimura1, Hironori Yabuki1, and Natsuhiko Otsuka4 1National Institute of Polar Research, 10-3, Midori-cho, Tachikawa-shi, Tokyo, 190-8518, Japan
2Nansen Environmental and Remote Sensing Center, Thormøhlens gate 47, 5006 Bergen, Norway
3Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
4Arctic Research Center, Hokkaido University, Kita-21 Nishi-11 Kita-ku, Sapporo, 001-0021, Japan
apresent address: Kitami Institute of Technology, Kitami, 090-8507, Japan
Abstract. Accelerated retreat of Arctic Ocean summertime sea ice has focused attention on the potential use of the Northern Sea Route (NSR), for which sea ice thickness (SIT) information is crucial for safe maritime navigation. This study evaluated the medium-range (lead time below 10 days) forecast of SIT distribution in the East Siberian Sea (ESS) in early summer (June–July) based on the TOPAZ4 ice–ocean data assimilation system. A comparison of the operational model SIT data with reliable SIT estimates (hindcast, satellite and in situ data) showed that the TOPAZ4 reanalysis qualitatively reproduces the tongue-like distribution of SIT in ESS in early summer and the seasonal variations. Pattern correlation analysis of the SIT forecast data over 3 years (2014–2016) reveals that the early summer SIT distribution is accurately predicted for a lead time of up to 3 days, but that the prediction accuracy drops abruptly after the fourth day, which is related to a dynamical process controlled by synoptic-scale atmospheric fluctuations. For longer lead times ( >  4 days), the thermodynamic melting process takes over, which contributes to most of the remaining prediction accuracy. In July 2014, during which an ice-blocking incident occurred, relatively thick SIT ( ∼  150 cm) was simulated over the ESS, which is consistent with the reduction in vessel speed. These results suggest that TOPAZ4 sea ice information has great potential for practical applications in summertime maritime navigation via the NSR.
Citation: Nakanowatari, T., Inoue, J., Sato, K., Bertino, L., Xie, J., Matsueda, M., Yamagami, A., Sugimura, T., Yabuki, H., and Otsuka, N.: Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice–ocean data assimilation system, The Cryosphere, 12, 2005-2020, https://doi.org/10.5194/tc-12-2005-2018, 2018.
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Short summary
Medium-range predictability of early summer sea ice thickness in the East Siberian Sea was examined, based on TOPAZ4 forecast data. Statistical examination indicates that the estimate drops abruptly at 4 days, which is related to dynamical process controlled by synoptic-scale atmospheric fluctuations such as an Arctic cyclone. For longer lead times (> 4 days), the thermodynamic melting process takes over, which represents most of the remaining prediction.
Medium-range predictability of early summer sea ice thickness in the East Siberian Sea was...
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