ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 6, pp. 209-220

Spurious Arctic sea ice identification by satellite microwave radiometers under extreme weather conditions

M.A. Zhivotovskaia‎ 1 , E.V. Zabolotskikh 1 , B. Chapron 2, 1 
1 Russian State Hydrometeorological University, Saint Petersburg, Russia
2 Institut Français de Recherche pour l’Exploitation de la Mer, Plouzané, France
Accepted: 04.10.2019
DOI: 10.21046/2070-7401-2019-16-6-209-220
The appearance of spurious sea ice concentration (SSIC) areas in sea ice concentration (SIC) products was studied under extreme weather conditions associated with the development of polar lows (PLs) and extratropical cyclones (ECs). The SIC products are based on measurements of the Advanced Microwave Scanning Radiometer 2 (AMSR2). The database of the PLs and ECs in the Arctic was created for the period 2015–2018 and consists of optical and radar images of the ocean surface and sea ice maps of the Norwegian Meteorological Institute (NMI) and the Arctic and Antarctic Research Institute (AARI). Two satellite products were analyzed: daily average SIC, calculated with the ARTIST Sea Ice algorithm (ASI) and provided by the University of Bremen, and swath SIC of original time resolution calculated with the Bootstrap algorithm and provided by the Japan Aerospace Exploration Agency (JAXA). A comparison of the SIC fields with the NMI and AARI maps, as well as with optical and radar images, allowed us to identify SSIC areas for which the atmospheric water vapor content, cloud liquid water content, and sea surface wind speed were calculated from the AMSR2 data. The influence of these parameters on the appearance and characteristics of the SSIC areas was studied for both products. It was found that the reason of SSIC appearance in the product of the University of Bremen is mainly the atmospheric water, whereas in the JAXA product ― strong winds. The largest number of the SSIC cases was observed in the regions of the most frequent PLs and ECs. The areas of SSIC were estimated for both products, which proved to be almost the same in winter months but different in summer months.
Keywords: sea ice, Arctic, AMSR2, satellite products, extreme weather conditions
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References:

  1. Vasilyeva P. V., Zabolotskikh E. V., Chapron B., Sravnitel’nyi analiz kharakteristik vnetropicheskikh tsiklonov v severnoi Atlantike i severnoi chasti Tikhogo okeana po dannym reanaliza ERA-Interim i sputnikovogo radiometra AMSR-E (Comparative analysis of the North Atlantic and North Pacific extratropical cyclone characteristics retrieved from ERA-Interim reanalysis and AMSR-E data), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 4, pp. 236–248.
  2. Zabolotskikh E. V., Obzor metodov vosstanovleniya parametrov ledyanogo pokrova po dannym sputnikovykh mikrovolnovykh radiometrov (Review of Methods to Retrieve Sea Ice Parameters from Satellite Microwave Radiometer Data), Izvestiya rossiiskoi akademii nauk. Fizika atmosfery i okeana, 2019, Vol. 55, No. 1, pp. 128–151.
  3. Zabolotskikh E. V., Shapron B., Uchet atmosfernykh effektov pri vosstanovlenii splochennosti morskogo l’da po dannym sputnikovykh mikrovolnovykh radiometrov (Consideration of atmospheric effects for sea ice concentration retrieval from satellite microwave observations), Meteorologiya i gidrologiya, 2019, No. 2, pp. 57–65.
  4. Smirnov V. G., Bushuev A. V., Zakhvatkina N. Yu., Loshchilov V. S., Sputnikovyi monitoring morskikh l’dov (Satellite Monitoring of the Sea Ice), Problemy Arktiki i Antarktiki, 2010, Vol. 85, No. 2, pp. 62–76.
  5. Andersen S., Tonboe R., Kern S., Schyberg H., Improved retrieval of sea ice total concentration from spaceborne passive microwave observations using numerical weather prediction model fields: An intercomparison of nine algorithms, Remote Sensing of Environment, 2006, Vol. 104, No. 4, pp. 374–392.
  6. Cavalieri D. J., Gloersen P., Campbell W. J., Determination of sea ice parameters with the Nimbus 7 SMMR, J. Geophysical Research: Atmospheres, 1984, Vol. 89, pp. 5355–5369.
  7. Cavalieri D. J., Germain K. M.S., Swift C. T., Reduction of weather effects in the calculation of sea-ice concentration with the DMSP SSM/I, J. Glaciology, 1995, Vol. 41, No. 139, pp. 455–464.
  8. Comiso J. C., Sea ice effective microwave emissivities from satellite passive microwave and infrared observations, J. Geophysical Research: Ocean, 1983, Vol. 88, pp. 7686–7704.
  9. Comiso J. C., Meier W. N., Gersten R., Variability and trends in the Arctic Sea ice cover: Results from different techniques, J. Geophysical Research: Oceans, 2017, Vol. 122, No. 8, pp. 6883–6900.
  10. Gloersen P., Cavalieri D. J., Reduction of weather effects in the calculation of sea ice concentration from microwave radiances, J. Geophysical Research, 1986, Vol. 91, No. C3, pp. 3913–3919.
  11. Harold J. M., Bigg G. R., Turner J. M., Mesocyclone activity over the North-East Atlantic. Part 1 : Vortex distribution and variability, Intern. J. Climatology, 1999, Vol. 19, pp. 1187–1204.
  12. Ivanova N., Pedersen L. T., Tonboe R. T., Kern S., Heygster G., Lavergne T., Sørensen A., Saldo R., Dybkjær G., Brucker L., Shokr M., Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations, The Cryosphere, 2015, Vol. 9, No. 5, pp. 1797–1817.
  13. Kaleschke L., Lüpkes C., Vihma T., Haarpaintner J., Bochert A., Hartmann J., Heygster G., SSM/I sea ice remote sensing for mesoscale ocean-atmosphere interaction analysis, Canadian J. Remote Sensing, 2001, Vol. 27, No. 5, pp. 526–537.
  14. Shokr M., Lambe A., Agnew T., A New Algorithm (ECICE) to Estimate Ice Concentration From Remote Sensing Observations: An Application to 85-GHz Passive Microwave Data, IEEE Trans. Geoscience and Remote Sensing, 2008, Vol. 46, No. 12, pp. 4104–4121.
  15. Smirnova J. E., Golubkin P. A., Bobylev L. P., Zabolotskikh E. V., Chapron B., Polar low climatology over the Nordic and Barents seas based on satellite passive microwave data, Geophysical Research Letters, 2015, Vol. 42, No. 13, pp. 5603–5609.
  16. Spreen G., Kaleschke L., Heygster G., Sea ice remote sensing using AMSR-E 89-GHz channels, J. Geophysical Research, 2008, Vol. 113, pp. 1–14.
  17. Svendsen E., Kloster K., Farrelly K. B., Johannessen O. M., Johannessen J. A., Campbell W. J., Gloersen P., Cavalieri D. J., Matzler C., Norwegian Remote Sensing Experiment: Evaluation of the Nimbus 7 scanning multichannel microwave radiometer for sea ice research, J. Geophysical Research, 1983, Vol. 88, No. C5, pp. 2781–2792.
  18. Svendsen E., Matzler C., Grenfell T. C., A model for retrieving total sea ice concentration from a spaceborne dual-polarized passive microwave instrument operating near 90 GHz, Intern. J. Remote Sensing, 1987, Vol. 8, pp. 1479–1487.
  19. Zabolotskikh E. V., Chapron B., New Geophysical Model Function for Ocean Emissivity at 89 GHz Over Arctic Waters, IEEE Geoscience and Remote Sensing Letters, 2018, Vol. 16, No. 4, pp. 573–577.
  20. Zabolotskikh E. V., Mitnik L. M., Chapron B., New approach for severe marine weather study using satellite passive microwave sensing, Geophysical Research Letters, 2013, Vol. 40, No. 13, pp. 3347–3350.