«IZVESTIYA IRKUTSKOGO GOSUDARSTVENNOGO UNIVERSITETA». SERIYA «NAUKI O ZEMLE»
«THE BULLETIN OF IRKUTSK STATE UNIVERSITY». SERIES «EARTH SCIENCES»
ISSN 2073-3402 (Print)

List of issues > Series «Earth Sciences». 2024. Vol 50

Monitoring of Meteorological Conditions of State Aviation Flights Using Satellite Data

Author(s)
I. P. Rastorguev, I. Z. Denega, A. I. Rastorgueva
Abstract
There is a tendency for flights of all types of aircraft to depend on meteorological conditions. Meteorological support for state aviation requires an even larger volume of actual and expected weather data. In some cases, data from the terrestrial meteorological and aero logical network may be completely or partially unavailable. In this case, it is advisable to use satellite data. For their effective use, methods of meteorological interpretation of data from space should be developed. These methods should take into account the specifics of the aviation consumer of information. A methodology for the integrated use of regular thematic products and its adaptation to the tasks of state aviation is proposed. All meteorological factors limiting or excluding the use of State aviation have been identified. Samples of information products of developers of satellite meteorological maps are studied. Based on the comparison of influencing factors and thematic satellite products, a methodology for monitoring meteorological flight conditions has been developed. The verification of the methodology on the actual material showed acceptable for practical use in meteorological support of state aviation. A computer program has been developed to automate the implementation of the presented methodology.
About the Authors

Rastorguev Igor Polikarpovich, Candidate of Sciences (Geography), Associate Professor, Air Force Academy, 153/5, Krasnoznamennaya st., Voronezh, 394064, Russian Federation, e-mail: iprastor@yandex.ru

Denega Ivan Zinovievich, Postgraduate, Air Force Academy, 153/5, Krasnoznamennaya st., Voronezh, 394064, Russian Federation, e-mail: denega5190@mail.ru

Rastorgueva Anastasia Igorevna, Research Scientist, Air Force Academy, 153/5, Krasnoznamennaya st., Voronezh, 394064, Russian Federation, e-mail: airsuccess08@rambler.ru

For citation

Rastorguev I.P., Denega I.Z., Rastorgueva A.I. Monitoring of Meteorological Conditions of State Aviation Flights Using Satellite Data. The Bulletin of Irkutsk State University. Series Earth Sciences, 2024, vol. 50, pp. 112–125. https://doi.org/10.26516/2073-3402.2024.50.112 (in Russian)

Keywords
meteorological flight conditions, state aviation, meteorological spacecraft, satellite information, weather analysis and forecast.
UDC
551.50
DOI
https://doi.org/10.26516/2073-3402.2024.50.112
References

Akimov L.M., Rastorguev I.P., Neizhmak A.N. Diagnoz i prognoz tsiklogeneza po dannym sputnikovogo zondirovaniya atmosfery [Diagnosis and prognosis of cyclogenesis based on satellite sensing of the atmosphere]. Gidrometeorologicheskie issledovaniya i prognozy [Hydrometeorological research and forecasts], 2020, no. 2 (376), pp. 60-78. (in Russian)

Asmus V.V., Ioffe G.M., Kramareva L.S., Krovotyntsev V.A., Milekhin O.E., So-lov'eva I.A. Kosmicheskii monitoring opasnykh prirodnykh yavlenii na territorii Rossii. [Space monitoring of natural hazards in Russia]. Meteorologiya i gidrologiya. [Meteorology and hydrology] 2019. no 11. pp. 20-32. (in Russian)

Bloshchinskii V.D., Kramareva L.S., Shamilova Yu.A. Detektirovanie oblachnogo pokrova s ispolzovaniem neironnoi seti po dannym pribora MSU-GS kosmicheskogo apparata “Arktika-M” N 1 [Cloud cover detection using a neural network based on the data of the MSU-GS device of the Arktika-M spacecraft No. 1] Optika atmosfery i okeana. [Optics of the atmosphere and ocean], 2024. vol. 37, no. 2, (421). pp. 99-104. (in Russian)

Bolelov E. A. Meteorologicheskoe obespechenie poletov grazhdanskoi aviatsii: problemy i puti ikh resheniya [Meteorological support of civil aviation flights: problems and solutions]. Nauchnyi vestnik Moskovskogo gosudarstvennogo tekhnicheskogo universiteta grazhdanskoi aviatsii [Scientific Bulletin of the Moscow State Technical University of Civil Aviation], 2018, vol. 21, no. 5, pp. 117-129. (in Russian)

Bukharov M.V., Bukharov V.M. Analiz bystro rastushchei mezomasshtabnoi sistemy glubokoi konvektsii po kartam sputnikovogo diagnoza [Analysis of a rapidly growing mesoscale deep convection system based on satellite diagnosis maps]. Gidrometeorologicheskie is-sledovaniya i prognozy [Hydrometeorological research and forecasts], 2020, no. 2 (376), pp. 23-38. (in Russian)

Volkova E.V. O klassifikatsii tipov oblachnosti porogovym metodom po sput-nikovym IKdannym [On the classification of cloud types by the threshold method based on satellite IR data]. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa [Modern problems of remote sensing of the Earth from space], 2023, vol. 20, no. 1. pp. 271-286. (in Russian)

Nerushev A.F., Ivangorodskii R.V. Opredelenie zon turbulentnosti v verkhnei troposfere na osnove sputnikovykh izmerenii [Determination of turbulence zones in the upper troposphere based on satellite measurements]. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa [Modern problems of remote sensing of the Earth from space], 2019, vol. 16, no. 1. pp. 205-215. (in Russian)

Bukharov M.V., Mironova N.S., Losev V.M., Bukharov V.M., Misnik L.A. Prime-nenie kart sputnikovogo diagnoza dlya analiza meteorologicheskikh uslovii v raione aviatsionnogo proisshestviya [The use of satellite diagnosis maps for the analysis of meteorological conditions in the area of an aviation accident]. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa [Modern problems of remote sensing of the Earth from space], 2012, vol. 9, no. 3, pp. 285-292. Available at: http://d33.infospace.ru/d33_conf/sb2012t3/285-292.pdf (in Russian)

Rastorguev I.P., Akimov L.M., Bozhko A.S. Issledovanie mnogoletnei dinami-ki prostranstvenno-vremennogo raspredeleniya oblachnykh sistem po dannym spetsializirovannykh kosmicheskikh apparatov [Investigation of the long-term dynamics of the spatial and temporal distribution of cloud systems based on data from specialized spacecraft]. Vestnik Voronezhskogo gosudarstvennogo uni-versiteta. Seriya: Geografiya. Geoekologiya [Bulletin of the Voronezh State University. Series: Geography. Geo-ecology], 2022, no. 2, pp. 78-88. (in Russian)

Filei A.A., Andreev A.I., Shamilova Yu.A. Programmnyi kompleks vosstanovleniya parametrov oblachnosti po sputnikovym dannym VPO-SD [Software package for restoring cloud parameters based on satellite data VPO-SD]. Sovremennye pro-blemy distantsionnogo zondirovaniya Zemli iz kosmosa [Modern problems of remote sensing of the Earth from space], 2024, vol. 21, no. 1. pp. 106-121. (in Russian)

Shakina N.P., Gorlach I.A., Skriptunova E.N. Ispolzovanie sputnikovykh dan-nykh o konvektivnoi oblachnosti dlya analiza letnykh proisshestvii i ikh preduprezhdeniya [The use of satellite data on convective clouds for the analysis of flight accidents and their prevention]. Meteorologiya i gidrologiya [Meteorology and hydrology], 2021, no. 12, pp. 94-101. (in Russian)

Shakina N.P., Ivanova A.R. Prognozirovanie meteorologicheskikh uslovii dlya aviatsii. [Forecasting meteorological conditions for aviation]. Moscow, Triada Ltd. Publ., 2016, 312 p. (in Russian)

Berndt E., Molthan A., Vaughan W., Fuell K. Transforming satellite data into weather forecasts. Geophys, 2017, vol. 98. https://doi.org/10.1029/2017EO064449 (date of access: 03.03.2024).

Dim J.R., Takamura T. Alternative approach for satellite cloud classification: edge gradient application. Advances in Meteorology, 2013, Art. ID 584816. Available at: https://www.hindawi.com/journals/amete/2013/584816 (date of access: 03.03.2024).

Ellrod G.P., Gultepe I. Inferring low cloud base heights at night for aviation using satellite infrared and surface temperature data. Pure and Applied Geophysics, 2007, pp. 164, 1193–1205.

Gultepe I., Pagowski M., Reid J. Using surface data to validate a satellite-based fog detection scheme. Weather and Forecasting, 2007, vol. 22, pp. 444-456.

Huffman G. J., Levizzani V., Kidd C. [et al.] Integrated multi-satellite retrievals for the global precipitation measurement (GPM) mission (IMERG). Satellite Precipitation Measurement, 2020, vol. 67. pp. 343-353. https://doi.org/10.1007/978-3-030-24568-9_19

Jin W., Gong F., Zeng X., Fu R. Classification of clouds in satellite imagery using adaptive fuzzy sparse representation. Sensors, 2016, vol. 16, no. 12, art. no. 2153. https://doi.org/10.3390/s16122153

Kerdraon G., Le Glaue H. EUMETSAT NWC SAF Report to Nowcasting and very shortrange forecasting. Scientific and validation report for the cloud product processors of the NWC/GEO/NWC/CDOP3/GEOCMS/SCI/VR/Cloud, 2019, iss. 1, rev. 1, pp. 51.

Pavolonis M. J. GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document for Cloud Type and Cloud Phase, 2010, pp 86. Available at: https://www.star.nesdis.noaa.gov/goesr/docs/ATBD/Cloud_Phase.pdf (date of access: 03.03.2024).

Purbantoro B., Aminuddin J., Manago N. et al. Comparison of cloud type classification with split-window algorithm based on different infrared band combinations of Himawari-8 satellite. Remote Sensing, 2018, vol. 11 (24), art. no. 2944. https://doi.org/10.3390/rs11242944

Sadeghi M., Asanjan A.A., Faridzad M. et al. PERSIANN-CNN: Precipitation estimation from remotely sensed information using artificial neural networks – convolutional neural networks. J. Hydrometeorology, 2019, vol. 20, pp. 2273-2289. https://doi.org/10.1175/JHM-D-19-0110.1.

Smith W. L. Jr., Minnis P., Fleeger C. et al. Determining the Flight Icing Threat to aircraft with single-layer cloud parameters derived from operational satellite data. Journal of Applied Meteorology and Climatology, 2012, vol. 51, pp.1794–1810.

Veillette M., Samsi S., Mattioli C. Sevir: A storm event imagery dataset for deep learning applications in radar and satellite meteorology. Advances in Neural Information Processing Systems, 2020, vol. 33. pp. 22009-22019.

Wolfson, M., Clark, D. Advanced aviation weather forecasts. Lincoln laboratory journal, 2006, vol. 1, рp. 31-58.


Full text (russian)