An improved ARTSIST sea ice algorithm based on 19 GHz modified 91 GHz

Wu Zhankai; Wang Xingdong; Wang Xuemei

doi:10.1007/s13131-019-1482-7

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Article Navigation > Acta Oceanologica Sinica > 2019 > 38(10): 93-99

Wu Zhankai, Wang Xingdong, Wang Xuemei. An improved ARTSIST sea ice algorithm based on 19 GHz modified 91 GHz[J]. Acta Oceanologica Sinica, 2019, 38(10): 93-99. doi: 10.1007/s13131-019-1482-7

Citation:

Wu Zhankai, Wang Xingdong, Wang Xuemei. An improved ARTSIST sea ice algorithm based on 19 GHz modified 91 GHz[J]. Acta Oceanologica Sinica, 2019, 38(10): 93-99. doi: 10.1007/s13131-019-1482-7

Wu Zhankai, Wang Xingdong, Wang Xuemei. An improved ARTSIST sea ice algorithm based on 19 GHz modified 91 GHz[J]. Acta Oceanologica Sinica, 2019, 38(10): 93-99. doi: 10.1007/s13131-019-1482-7

Citation:

Wu Zhankai, Wang Xingdong, Wang Xuemei. An improved ARTSIST sea ice algorithm based on 19 GHz modified 91 GHz[J]. Acta Oceanologica Sinica, 2019, 38(10): 93-99. doi: 10.1007/s13131-019-1482-7

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An improved ARTSIST sea ice algorithm based on 19 GHz modified 91 GHz

doi: 10.1007/s13131-019-1482-7

1.
College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China
2.
College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China;Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

Received Date: 2018-06-19

Abstract

Abstract

An enhanced ARTSIST Sea Ice (ASI) algorithm is presented based on a data fusion method of calculating total sea ice concentration from high-frequency microwave data. Algorithms that use low-frequency data to calculate total sea ice concentration are less affected by atmosphere, but their spatial resolutions tend to be lower. In contrast, algorithms using high-frequency data have higher spatial resolution but are significantly influenced by atmosphere. Although errors can be eliminated using weather filters, the concentration of mixed pixels cannot be modified. Here, an enhanced ASI algorithm uses the 19 GHz polarization difference to modify the 91 GHz polarization difference, which is substituted into the ASI algorithm to calculate total sea ice concentration. Arctic total sea ice concentration results are obtained based on Special Sensor Microwave Imager Sounder (SSMIS) data on January 3, from 2008 to 2017. Total sea ice area and average concentration using the enhanced ASI algorithm are compared to traditional ASI and NASA Team results. In the Marginal Ice Zone, there is a considerable difference between the enhanced and traditional ASI algorithm results, with the former much closer to the NASA Team results. The proposed algorithm effectively modifies the concentration of the mixed pixels in the marginal zone.
- ASI algorithm|sea ice concentration|SSMIS|NASA Team algorithm

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References

Andersen S, Tonboe R, Kaleschke L, et al. 2007. Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice. Journal of Geophysical Research: Oceans, 112(C8): 207–220

Budikova D. 2009. Role of arctic sea ice in global atmospheric circulation: a review. Global and Planetary Change, 68(3): 149–163, doi: 10.1016/j.gloplacha.2009.04.001

Comiso J C. 1986. Characteristics of arctic winter sea ice from satellite multispectral microwave observations. Journal of Geophysical Research: Oceans, 91(C1): 975–994, doi: 10.1029/JC091iC01p00975

Comiso J C. 1995. SSM/I sea ice concentrations using the bootstrap algorithm. NASA Goddard Space Flight Center Ref. Publication, No. 1380. Washington: National Aeronautics and Space Administration

Gabarro C, Turiel A, Elosegui P, et al. 2017. New methodology to estimate Arctic sea ice concentration from SMOS combining brightness temperature differences in a maximum-likelihood estimator. The Cryosphere, 11(4): 1987–2002, doi: 10.5194/tc-11-1987-2017

Hollinger J P. 1989. DMSP Special Sensor Microwave/Imager Calibration/Validation. Final Report, Vol. I. Washington DC: Space Sensing Branch, Naval Research Laboratory

IPCC. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. New York: Cambridge University Press

Kaleschke L, Lüpkes C, Vihma T, et al. 2001. SSM/I sea ice remote sensing for mesoscale ocean-atmosphere interaction analysis. Canadian Journal of Remote Sensing, 27(5): 526–537, doi: 10.1080/07038992.2001.10854892

Kern S. 2004. A new method for medium-resolution sea ice analysis using weather-influence corrected Special Sensor Microwave/Imager 85 GHz data. International Journal of Remote Sensing, 25(21): 4555–4582, doi: 10.1080/01431160410001698898

Kern S, Heygster G. 2001. Sea-ice concentration retrieval in the antarctic based on the SSM/I 85.5 GHz polarization. Annals of Glaciology, 33(1): 109–114

Kern S, Kaleschke L, Clausi D A. 2003. A comparison of two 85-GHz SSM/I ice concentration algorithms with AVHRR and ERS-2 SAR imagery. IEEE Transactions on Geoscience and Remote Sensing, 41(10): 2294–2306, doi: 10.1109/TGRS.2003.817181

Kern S, Rösel A, Pedersen L T, et al. 2016. The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations. The Cryosphere, 10(5): 2217–2239, doi: 10.5194/tc-10-2217-2016

Korosov A A, Rampal P, Pedersen L T, et al. 2018. A new tracking algorithm for sea ice age distribution estimation. The Cryosphere, 12(6): 2073–2085, doi: 10.5194/tc-12-2073-2018

Li Peiji. 1996. The arctic sea ice and climate change. Journal of Glaciolgy and Geocryology (in Chinese), 18(1): 72–80

Markus T, Cavalieri D J. 2000. An enhancement of the NASA team sea ice algorithm. IEEE Transactions on Geoscience and Remote Sensing, 38(3): 1387–1398, doi: 10.1109/36.843033

NSIDC. 2010. Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) Global Gridded Products. Silver Spring: National Environmental Satellite, Data, and Information Service (NESDIS), NOAA

Schmidtko S, Heywood K J, Thompson A F, et al. 2014. Multidecadal warming of Antarctic waters. Science, 346(6214): 1227–1231, doi: 10.1126/science.1256117

Spencer R W, Goodman H M, Hood R E. 1989. Precipitation retrieval over land and ocean with the SSM/I: identification and characteristics of the scattering signal. Journal of Atmospheric and Oceanic Technology, 6(2): 254–273, doi: 10.1175/1520-0426(1989)006<0254:PROLAO>2.0.CO;2

Spreen G, Kaleschke L, Heygster G. 2008. Sea ice remote sensing using AMSR-E 89-GHz channels. Journal of Geophysical Research: Oceans, 113(C2): C02S03

Su Jie, Hao Guanghua, Ye Xinxin, et al. 2013. The experiment and validation of sea ice concentration AMSR-E retrieval algorithm in polar region. Journal of Remote Sensing (in Chinese), 17(3): 495–513

Svendsen E, Matzler C, Grenfell T C. 1987. A model for retrieving total sea ice concentration from a spaceborne dual-polarized passive microwave instrument operating near 90 GHz. International Journal of Remote Sensing, 8(10): 1479–1487, doi: 10.1080/01431168708954790

Swift C, Cavalieri D. 1985. Passive microwave remote sensing for sea ice research. Eos, Transactions American Geophysical Union, 66(49): 1210–1212, doi: 10.1029/EO066i049p01210

Tschudi M, Fowler C, Maslanik J, et al. 2016. Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 3. Boulder, Colorado, USA: NASA National Snow and Ice Data Center Distributed Active Archive Center, doi: https://doi.org/10.5067/O57VAIT2AYYY

Wang Huanhuan. 2009. Multiyear ice retrieval using passive microwave remote sensing radiometer AMSR-E 89GHz data (in Chinese) [dissertation]. Qingdao: Ocean University of China

Ye Yufang, Heygster G, Shokr M. 2016. Improving multiyear ice concentration estimates with reanalysis air temperatures. IEEE Transactions on Geoscience and Remote Sensing, 54(5): 2602–2614, doi: 10.1109/TGRS.2015.2503884

Zhang Shugang. 2012. Sea ice concentration algorithm and study on the physical process about sea ice and melt-pond change in Central Arctic (in Chinese) [dissertation]. Qingdao: Ocean University of China

Zhang Xiang, Wang Zhenzhan, Shen Hua. 2012. A sea ice concentration algorithm based on HY-2 scanning radiometer data. Remote Sensing Technology and Application (in Chinese), 27(6): 912–918

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