ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 1, pp. 27-38

Sea ice concentration retrieval from MTVZA GYa measurements

E.V. Zabolotskikh 1 , E.A. Balashova 1 , S.M. Azarov 1 
1 Russian State Hydrometeorological University, Saint Petersburg, Russia
Accepted: 29.11.2021
DOI: 10.21046/2070-7401-2022-19-1-27-38
Sea ice concentration (SIC) retrievals from measurements of the Russian microwave imager/sounder MTVZA GYa, based on polarization difference (PD) in the measurements of the sea ice – ocean – atmosphere system microwave radiation at frequencies of 10.6 and 36.7 GHz, are discussed. A joint analysis of the MTVZA GYa measurements and the measurements of the Japanese instrument Advanced Microwave Scanning Radiometer 2 (AMSR2) at similar frequencies over sea ice and open water is carried out. SIC satellite product based on polarization measurements of AMSR2 at 89 GHz is used to define the surface type. The possibility of classification of surface as sea ice or open water using PD values at 10.6 or 36.7 GHz has been demonstrated. The formulas are presented to calculate SIC from MTVZA GYa data using predetermined PD values at 10.6 and 36.7 GHz over open water and over sea ice (tie points). Experimental values of the gradient ratios in the measurements of vertically polarized radiation at 18.7, 23.8 and 36.5 GHz are determined to manage weather effects and remove spurious sea ice areas. The results of SIC retrievals from MTVZA GYa data are compared with the results of application of the SIC retrieval algorithm to the AMSR2 data for the Greenland, Barents and Kara Seas. Additional high-resolution satellite data are subjectively analyzed to confirm the adequateness of SIC fields and show that for some areas the MTVZA GYa SIC retrievals allow avoiding SIC underestimation by traditional algorithms based on measurements near 90 GHz.
Keywords: sea ice concentration, algorithms, Arctic, satellite microwave radiometers, MTVZA GYa, AMSR2
Full text


  1. Boldyrev V. V., Gorobets N. N., Ilgasov P. A., Nikitin O. V., Pantsov V. Yu., Prokhorov Yu. N., Strelnikov N. I., Streltsov A. M., Cherny I. V., Chernyavsky G. M., Yakovlev V. V., Satellite microwave scanner/sounder MTVZA GYa, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2008, Vol. 5, No. 1, pp. 243–248 (in Russian).
  2. Ermakov D. M., Kuzmin A. V., Mazurov A. A., Pashinov E. V., Sadovsky I. N., Sazonov D. S., Sterlyadkin V. V., Chernushich A. P., Cherny I. V., Streltsov A. M., The concept of streaming data processing of Russian satellite microwave radiometers of the MTVZA series based on the IKI-Monitoring Center for Collective Use, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2021, Vol. 18, No. 4, pp. 298–303 (in Russian), DOI: 10.21046/2070-7401-2021-18-4-298-303.
  3. Zabolotskikh E. V., Review of methods to retrieve sea ice parameters from satellite microwave radiometer data, Izvestiya RAN. Fizika atmosfery i okeana, 2019, Vol. 55, No. 1, pp. 128–151 (in Russian), DOI: 10.31857/S0002-3515551128-151.
  4. Zabolotskikh E. V., Balashova E. A., External calibration of MTVZA GYa measurements in the scanner channels using AMSR2 measurements. Part 2: experiment, Meteorologiya i gidrologiya, 2021, No. 11, pp. 50–57 (in Russian).
  5. Zabolotskikh E. V., Chapron B., Consideration of atmospheric effects for sea ice concentration retrieval from satellite microwave observations, Russian Meteorology and Hydrology, 2019, Vol. 44, No. 2, pp. 124–129.
  6. Zabolotskikh E. V., Balashova E. A., Chapron B., Advanced method for sea ice concentration retrieval from satellite microwave radiometer measurements at frequencies near 90 GHz, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 4, pp. 233–243 (in Russian), DOI: 10.21046/2070-7401-2019-16-4-233-243.
  7. Okeanografiya i morskoi led (Oceanography and sea ice), Frolov I. E., Ashik I. M., Timokhov L. A., Yulin A. V. (eds.), Moscow: Paulsen, 2011, 432 p. (in Russian).
  8. Tikhonov V. V., Repina I. A., Raev M. D., Sharkov E. A., Boyarskii D. A., Komarova N. Yu., New Algorithm Sea Ice Cover Reconstruction on the Basis of Passive Microwave Data, Issledovaniya Zemli iz kosmosa, 2014, No. 2, pp. 35–43 (in Russian), DOI: 10.7868/S0205961414020110.
  9. Asmus V. V., Uspenskiy A. B., Kozlov A. A., Kramchaninova E. K., Streltsov A. M., Chernyavsky G. M., Cherny I. V., Absolute calibration of Microwave Radiometer MTVZA-GY Atmospheric Sounding Channels, Issledovaniya Zemli iz kosmosa, 2016, No. 5, pp. 57–70 (in Russian), DOI: 10.7868/S0205961416050079.
  10. Breivik L., Eastwood S., Lavergne T., Use of C-band scatterometer for sea ice edge identification, IEEE Trans. Geoscience and Remote Sensing, 2012, Vol. 50, No. 7, pp. 2669–2677, DOI: 10.1109/TGRS.2012.2188898.
  11. Comiso J. C., Enhanced sea ice concentrations and ice extents from AMSR-E data, J. Remote Sensing Society of Japan, 2009, Vol. 29, No. 1, pp. 199–215.
  12. Comiso J. C., Cavalieri D. J., Markus T., Sea ice concentration, ice temperature, and snow depth using AMSR-E data, IEEE Trans. Geoscience and Remote Sensing, 2003, Vol. 41, No. 2, pp. 243–252, DOI: 10.1109/TGRS.2002.808317.
  13. 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, DOI: 10.1002/2017JC012768.
  14. Ivanova N., Pedersen L. T., Tonboe R. T., Kern S., Heygster G., Lavergne T., Sørensen A., Saldo R., Dybkjær G., Brucker L., Shokr M., Satellite passive microwave measurements of sea ice concentration: An optimal algorithm and challenges, Cryosphere, 2015, Vol. 9, pp. 1797–1817, DOI: 10.5194/tcd-9-1269-2015.
  15. 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, DOI: 10.1080/07038992.2001.10854892.
  16. Markus T., Cavalieri D. J., An enhancement of the NASA Team sea ice algorithm, IEEE Trans. Geoscience and Remote Sensing, 2000, Vol. 38, No. 3, pp. 1387–1398, DOI: 10.1109/36.843033.
  17. Rivas M. B., Otosaka I., Stoffelen A., Verhoef A. A., Scatterometer record of sea ice extents and backscatter: 1992–2016, The Cryosphere, 2018, Vol. 12, No. 9, pp. 2941–2953, DOI: 10.5194/tc-12-2941-2018.
  18. 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, DOI: 10.1109/TGRS.2008.2000624.
  19. Spreen G., Kaleschke L., Heygster G., Sea ice remote sensing using AMSR-E 89-GHz channels, J. Geophysical Research, 2008, Vol. 113, No. C2, DOI: 10.1029/2005JC003384.
  20. 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. No. 10, pp. 1479–1487, DOI: 10.1080/01431168708954790.
  21. Wentz F. J., A model function for ocean microwave brightness temperatures, J. Geophysical Research, 1983, Vol. 88, No. C3, pp. 1892–1908.
  22. Zakhvatkina N., Smirnov V., Bychkova I., Satellite SAR data-based sea ice classification: an overview, Geosciences, 2019, Vol. 9, No. 4, p. 152, 15 p., DOI: 10.3390/geosciences9040152.