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, 2023, Vol. 20, No. 6, pp. 336-345

Typhoon Hinnamnor (2022): Impact on the Far Eastern seas, Primorsky and Khabarovsk Krais based on active and passive microwave sensing data from space

L.M. Mitnik 1 , A.V. Baranyuk 1 , M.L. Mitnik 1 
1 V.I. Il'ichev Pacific Oceanological Institute FEB RAS, Vladivostok, Russia
Accepted: 06.12.2023
DOI: 10.21046/2070-7401-2023-20-6-336-345
The number of extreme weather events accompanied by gale force winds, heavy precipitation and flooding is increasing with global warming. The state of the sea surface, land cover and atmosphere as Typhoon Hinnamnor moved over the East China Sea, Sea of Japan, Sea of Okhotsk and the Far East region on September 5–9, 2022, was assessed using SAR images, brightness temperatures measured by AMSR2, GMI and MTVZA-GYa radiometers, radiosonde readings and meteorological station readings. To monitor floods and reduce damage, the space agencies of Korea on September 2 and Russia on September 4 activated the International Charter on Space and Major Disasters. Combining sensing data from various sensors over the disaster areas allowed reconstructing wind speed over the sea, precipitation intensity, atmospheric water vapor content, cloud liquid water content, flooding area and other parameters with spatial and temporal resolution unavailable from any single instrument.
Keywords: typhoon Hinnamnor, precipitation, flooding, SAR, Sentinel-1A, AMSR2, GPM, sea surface wind, cloud liquid water content, total atmospheric water vapor content, Amur basin, Primorsky Krai, Khabarovsk Krai
Full text

References:

  1. Gartzman B. I., Dozhdevye navodneniya na rekakh yuga Dal’nego Vostoka: metody raschetov, prognozov, otsenok riska (Rain floods on the rivers of the south of the Far East: methods of calculations, forecasts, risk assessments), Vladivostok: Dalnauka, 2008, 241 p. (in Russian).
  2. Danilov-Danilyan V. I., Gelfan A. N., Motovilov Yu. G., Kalugin A. S., Catastrophic flood of 2013 in the Amur River basin: formation conditions, repeatability assessment, modeling result, Water Resources, 2014, No. 2, pp. 111–122 (in Russian), DOI: 10.1134/S0097807814020055.
  3. Chernyavsky G. M., Mitnik L. M., Kuleshov V. P. et al., Brightness temperature modeling and first results derived from the MTVZA-GY radiometer of the Meteor-M No. 2-2 satellite, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 3, pp. 51–65 (in Russian), DOI: 10.21046/2070-7401-2020-17-3-51-65.
  4. Benoudjit A., Guida R., A novel fully automated mapping of the flood extent on SAR images using a supervised classifier, Remote Sensing, 2019, Vol.11, Article 779, 22 p., DOI: 10.3390/rs11070779.
  5. Chen R., Bennartz R. J., Sensitivity of 89–190-GHz microwave observations to ice particle scattering, J. Applied Meteorology and Climatology, 2020, Vol.59, No.7, pp.1195–1215, https://doi.org/10.1175/JAMC-D-19-0293.1.
  6. Katsaros K. B., Mitnik L. M., Black P. G., Microwave instruments for observing tropical cyclones, In: Typhoon Impacts and Crisis Management, Springer, 2014, pp.5–61, DOI: 10.1007/978-3-642-40695-9_2.
  7. Kubota T., Aonashi K., Ushio T. et al., Global Satellite Mapping of Precipitation (GSMaP) products in the GPM era, In: Satellite Precipitation Measurement, Springer, 2020, pp.355–373, https://doi.org/10.1007/978-3-030-24568-9_20.
  8. Manavalan R., SAR image analysis techniques for flood area mapping — literature survey, Earth Science Information, 2017, Vol.10, pp.1–14, https://doi.org/10.1007/s12145-016-0274-2.
  9. Mitnik L. M., Mitnik M. L., Zabolotskikh E. V., Microwave sensing of the atmosphere-ocean system with ADEOS-II AMSR and Aqua AMSR-E, J. Remote Sensing Society of Japan, 2009, Vol.29, No.1, pp.156–165.
  10. Mitnik L. M., Kuleshov V. P., Mitnik M. L. et al., Microwave radiometer MTVZA-GY on new Russian satellite Meteor-M No. 2-2 and sudden stratospheric warming over Antarctica, IEEE J. Selected Topics of Applied Remote Sensing, 2022, Vol.15, pp.820–830, DOI: 10.1109/JSTARS.2021.3133425.
  11. Tay C. W. J., Yun S. H., Chin S. T. et al., Rapid flood and damage mapping using synthetic aperture radar in response to Typhoon Hagibis, Japan, Scientific Data, 2020, Vol.7, Article 100, https://doi.org/10.1038/s41597-020-0443-5.
  12. Tupas M. E., Roth F., Bauer-Marschallinger B., Wagner W., An intercomparison of Sentinel-1 based change detection algorithms for flood mapping, Remote Sensing, 2023, Vol.15, Article 1200, https://doi.org/10.3390/rs1505120.