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\u0426\u0435\u043b\u044c \u0440\u0430\u0431\u043e\u0442\u044b<\/strong> \u2013 \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u044c \u0438 \u0441\u043e\u043f\u043e\u0441\u0442\u0430\u0432\u0438\u0442\u044c \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u044c \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0432 \u0437\u0430\u0434\u0430\u0447\u0435 \u043e\u0431\u043d\u0430\u0440\u0443\u0436\u0435\u043d\u0438\u044f \u0438 \u043e\u0442\u0441\u043b\u0435\u0436\u0438\u0432\u0430\u043d\u0438\u044f \u043a\u043e\u043d\u0432\u0435\u043a\u0442\u0438\u0432\u043d\u044b\u0445 \u044f\u0447\u0435\u0435\u043a \u043d\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f\u0445 \u0440\u0430\u0434\u0438\u043e\u043b\u043e\u043a\u0430\u0446\u0438\u043e\u043d\u043d\u044b\u0445 \u043e\u0431\u0437\u043e\u0440\u043e\u0432.<\/p>\n\n\n\n

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\u00a9   \u0428\u0430\u043f\u043e\u0432\u0430\u043b\u043e\u0432 \u0412. \u0410., \u0410\u0434\u0436\u0438\u0435\u0432\u0430 \u0410. \u0410., \u0410\u0445\u043c\u0430\u0442\u043e\u0432 \u041c. \u041c., \u0425\u0438\u0442\u0438\u0435\u0432\u0430 \u0410. \u0416., 2026<\/p>\n\n\n\n

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\u0421\u043f\u0438\u0441\u043e\u043a \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u044b<\/strong><\/summary>\n
    \n
  1. WMO-No. 1198. Guidelines for Nowcasting Techniques. Geneva, 2017. 184 p.<\/li>\n\n\n\n
  2. \u0410\u0431\u0448\u0430\u0435\u0432 \u041c. \u0422., \u0410\u0431\u0448\u0430\u0435\u0432 \u0410. \u041c., \u041c\u0430\u043b\u043a\u0430\u0440\u043e\u0432\u0430 \u0410. \u041c., \u0416\u0430\u0440\u0430\u0448\u0443\u0435\u0432 \u041c. \u0412.<\/em> \u0410\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u0430\u044f \u0440\u0430\u0434\u0438\u043e\u043b\u043e\u043a\u0430\u0446\u0438\u043e\u043d\u043d\u0430\u044f \u0438\u0434\u0435\u043d\u0442\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u044f, \u0438\u0437\u043c\u0435\u0440\u0435\u043d\u0438\u0435 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u043e\u0432 \u0438 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u044f \u043a\u043e\u043d\u0432\u0435\u043a\u0442\u0438\u0432\u043d\u044b\u0445 \u044f\u0447\u0435\u0435\u043a \u0434\u043b\u044f \u0446\u0435\u043b\u0435\u0439 \u0437\u0430\u0449\u0438\u0442\u044b \u043e\u0442 \u0433\u0440\u0430\u0434\u0430 \u0438 \u0448\u0442\u043e\u0440\u043c\u043e\u043e\u043f\u043e\u0432\u0435\u0449\u0435\u043d\u0438\u044f \/\/ \u041c\u0435\u0442\u0435\u043e\u0440\u043e\u043b\u043e\u0433\u0438\u044f \u0438 \u0433\u0438\u0434\u0440\u043e\u043b\u043e\u0433\u0438\u044f. 2010. \u2116 3. \u0421. 36\u201345.<\/li>\n\n\n\n
  3. \u0421\u0430\u0440\u0430\u0439\u043a\u0438\u043d \u0410. \u0410., \u0427\u0430\u0439\u043a\u043e\u0432\u0441\u043a\u0438\u0439 \u0412. \u041c.<\/em> \u041f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u043e\u0439 \u0441\u0435\u0442\u0438 \u0432 \u043c\u0435\u0442\u0435\u043e\u0440\u043e\u043b\u043e\u0433\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0440\u0430\u0434\u0438\u043e\u043b\u043e\u043a\u0430\u0446\u0438\u0438 \/\/ \u0418\u0437\u0432\u0435\u0441\u0442\u0438\u044f \u0432\u0443\u0437\u043e\u0432. \u041f\u043e\u0432\u043e\u043b\u0436\u0441\u043a\u0438\u0439 \u0440\u0435\u0433\u0438\u043e\u043d. \u0422\u0435\u0445\u043d\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043d\u0430\u0443\u043a\u0438. 2024. \u2116 1(69). \u0421. 83\u201390.<\/li>\n\n\n\n
  4. \u0428\u0430\u043f\u043e\u0432\u0430\u043b\u043e\u0432 \u0412. \u0410., \u0422\u0443\u043c\u0433\u043e\u0435\u0432\u0430 \u0425. \u0410. <\/em>\u0420\u0430\u0441\u043f\u043e\u0437\u043d\u0430\u0432\u0430\u043d\u0438\u0435 \u0438 \u0441\u043e\u043f\u0440\u043e\u0432\u043e\u0436\u0434\u0435\u043d\u0438\u0435 \u043e\u0431\u043b\u0430\u0447\u043d\u044b\u0445 \u043a\u043e\u043d\u0432\u0435\u043a\u0442\u0438\u0432\u043d\u044b\u0445 \u044f\u0447\u0435\u0435\u043a \u0441 \u0446\u0435\u043b\u044c\u044e \u0442\u0435\u043a\u0443\u0449\u0435\u0433\u043e \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0430 \u043e\u043f\u0430\u0441\u043d\u044b\u0445 \u043f\u043e\u0433\u043e\u0434\u043d\u044b\u0445 \u044f\u0432\u043b\u0435\u043d\u0438\u0439 \/\/ \u0418\u0437\u0432\u0435\u0441\u0442\u0438\u044f \u042e\u0424\u0423. \u0422\u0435\u0445\u043d\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043d\u0430\u0443\u043a\u0438. 2018. \u2116 3. \u0421. 58\u201367. DOI: 10.23683\/2311-3103-2018-3-58-67<\/li>\n\n\n\n
  5. Bournas A., Baltas E. <\/em>Development of a Storm-Tracking Algorithm for the Analysis of Radar Rainfall Patterns in Athens, Greece. Water. 2024. No. 16(20). P. 2905. DOI: 10.3390\/w16202905<\/li>\n\n\n\n
  6. Lagerquist R., McGovern A., Gagne D. J.<\/em> Deep Learning for Spatially Explicit Prediction of Synoptic-Scale Fronts. Weather and Forecasting. 2019. Vol. 34. No. 4. Pp. 1137\u20131160. DOI: 10.1175\/WAF-D-18-0183.1<\/li>\n\n\n\n
  7. Dixon M., Wiener G.<\/em> TITAN: Thunderstorm identification, tracking, analysis, and nowcasting \u2013 Radar-based methodology. Journal of Atmospheric and Oceanic Technology. 1993. Vol. 10. No. 6. Pp. 785\u2013797. DOI: 10.1175\/1520-0426(1993)010<0785:TTITAA>2.0.CO;2<\/li>\n\n\n\n
  8. Johnson J.T., MacKeen P.L., Witt A. et al.<\/em> The storm cell identification and tracking algorithm: an enhanced WSR-88D Algorithm. Weather and Forecasting. 1998. Vol. 13. No. 2. Pp. 263\u2013276. DOI: 10.1175\/1520-0434(1998)013<0263: TSCIAT>2.0.CO;2<\/li>\n\n\n\n
  9. Pulkkinen S., Nerini D., P\u00e9rez Hortal A.A. et al.<\/em> Pysteps: an open-source Python library for probabilistic precipitation nowcasting, including an ensemble of extrapolation, autoregressive and more advanced methods. Geoscientific Model Development. 2019. Vol. 12. Pp. 4185\u20134219. DOI: 10.5194\/gmd-12-4185-2019<\/li>\n\n\n\n
  10. Jung S.-H., Lee G.<\/em> Radar-based cell tracking with fuzzy logic approach. Meteorological Applications. 2015. Vol. 22. No. 4. Pp. 716\u2013730. DOI: 10.1002\/met.1509<\/li>\n\n\n\n
  11. Jergensen G.E., McGovern A., Lagerquist R., Smith T.<\/em> Classifying convective storms using machine learning. Weather and Forecasting. 2020. Vol. 35, No. 2. Pp. 537\u2013556.<\/li>\n\n\n\n
  12. Veillette M.S., Kurdzo J.M., Stepanian P.M. et al.<\/em> A benchmark dataset for tornado detection and prediction using full-resolution polarimetric weather radar data (TorNet). Artificial Intelligence for the Earth Systems. 2024. Vol. 4. No. 1. DOI: 10.1175\/AIES-D-24-0006.1<\/li>\n\n\n\n
  13. Nan G., Chen M., Qin R. et al.<\/em> Identification, tracking and classification method of mesoscale convective system based on radar composite reflectivity mosaic and deep learning. Acta Meteorologica Sinica. 2021. Vol. 79(6). Pp. 1002\u20131021. DOI: 10.11676\/qxxb2021.062<\/li>\n\n\n\n
  14. Ayzel G., Scheffer T., Heistermann M.<\/em> RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting. Geoscientific Model Development. 2020. Vol. 13. No. 6. Pp. 2631\u20132644. DOI: 10.5194\/gmd-13-2631-2020<\/li>\n\n\n\n
  15. Han L., Sun J., Zhang W.<\/em> convolutional neural network for convective storm nowcasting using 3-d doppler weather radar data. IEEE Transactions on Geoscience and Remote Sensing. Vol. 58. No. 2. Pp. 1487\u20131495. DOI: 10.1109\/TGRS.2019.2948070<\/li>\n\n\n\n
  16. Albu A.-I., Czibula G., Mihai A. et al.<\/em> NeXtNow: A convolutional deep learning model for the prediction of weather radar data for nowcasting purposes. Remote Sens. 2022. No. 14. P. 3890. DOI: 10.3390\/rs14163890<\/li>\n\n\n\n
  17. Ritvanen J., Pulkkinen S., Moisseev D., Nerini D.<\/em> Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall. Geoscientific Model Development. 2025. Vol. 18. Pp. 1851\u20131878. DOI: 10.5194\/gmd-18-1851-2025<\/li>\n\n\n\n
  18. Ranganayakulu S.V., Subrahmanyam K.V., Niranjan A.<\/em> A novel algorithm for convective cell identification and tracking based on optical character recognition neural network. Journal of Electromagnetic Waves and Applications. 2021. Vol. 35. No. 16. Pp. 2239\u20132255. DOI: 10.1080\/09205071.2021.1941299<\/li>\n\n\n\n
  19. Liu J., Zhang Q.<\/em> A novel algorithm for detecting convective cells based on h-maxima transformation using satellite images. Atmosphere. 2025. Vol. 16. No. 11. P. 1232. DOI: 10.3390\/atmos16111232<\/li>\n\n\n\n
  20. Wang X., Liao R., Li J. et al<\/em>. Thunderstorm identification algorithm research based on simulated airborne weather radar reflectivity data. EURASIP Journal on Wireless Communications and Networking. 2020. ID: 37. DOI: 10.1186\/s13638-020-1651-6<\/li>\n\n\n\n
  21. Wang Y., Long M., Wang J. et al.<\/em> PredRNN: Recurrent neural networks for predictive learning using spatiotemporal LSTMs. Advances in Neural Information Processing Systems. Vol. 30. Pp. 1\u201310.<\/li>\n\n\n\n
  22. Shi X., Chen Z., Wang H. et al.<\/em> Convolutional LSTM Network: A machine learning approach for precipitation nowcasting. Advances in Neural Information Processing Systems (NIPS). 2015. Vol. 28. Pp. 802\u2013810.<\/li>\n\n\n\n
  23. Shi X., Gao Z., Lausen L. et al.<\/em> Deep Learning for precipitation nowcasting: a benchmark and a new model. Advances in Neural Information Processing Systems (NIPS). 2017. Vol. 30. Pp. 5617\u20135627.<\/li>\n\n\n\n
  24. Gao Z., Shi X., Wang H., et al.<\/em> Earthformer: exploring space-time transformers for earth system forecasting. Advances in Neural Information Processing Systems (NeurIPS). 2022. Vol. 35. Pp. 25390\u201325403. arXiv:2207.05833<\/li>\n\n\n\n
  25. Hu J., Rosenfeld D., Zrni\u0107 D. et al.<\/em> Tracking and characterization of convective cells through their maturation into stratiform storm elements using polarimetric radar and lightning detection. Atmospheric Research. 2019. Vol. 226. Pp. 192\u2013207.<\/li>\n\n\n\n
  26. Xiao H., Wang Y., Zheng Y. et al.<\/em> Convective-gust nowcasting by a deep learning algorithm. Geoscientific Model Development. 2023. Vol. 16. Pp. 3611\u20133628. DOI: 10.5194\/gmd-16-3611-2023<\/li>\n\n\n\n
  27. Ravuri S., Lenc K., Willson M. et al.<\/em> Skilful precipitation nowcasting using deep generative models of radar. Nature. 2021. Vol. 597. Pp. 672\u2013677. DOI: 10.1038\/s41586-021-03854-z<\/li>\n<\/ol>\n\n\n\n

    <\/p>\n<\/details>\n\n\n\n

    \u0418\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044f \u043e\u0431 \u0430\u0432\u0442\u043e\u0440\u0430\u0445<\/strong><\/summary>\n

    \u0428\u0430\u043f\u043e\u0432\u0430\u043b\u043e\u0432 \u0412\u0438\u0442\u0430\u043b\u0438\u0439 \u0410\u043b\u0435\u043a\u0441\u0430\u043d\u0434\u0440\u043e\u0432\u0438\u0447<\/strong>, \u0434-\u0440 \u0444\u0438\u0437.-\u043c\u0430\u0442. \u043d\u0430\u0443\u043a, \u0441\u0442\u0430\u0440. \u043d\u0430\u0443\u0447. \u0441\u043e\u0442\u0440., \u0412\u044b\u0441\u043e\u043a\u043e\u0433\u043e\u0440\u043d\u044b\u0439 \u0433\u0435\u043e\u0444\u0438\u0437\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0438\u043d\u0441\u0442\u0438\u0442\u0443\u0442;
    360030, \u0420\u043e\u0441\u0441\u0438\u044f, \u0433. \u041d\u0430\u043b\u044c\u0447\u0438\u043a, \u043f\u0440\u043e\u0441\u043f\u0435\u043a\u0442 \u041b\u0435\u043d\u0438\u043d\u0430, 2;
    vet555_83@mail.ru, ORCID: https:\/\/orcid.org\/0000-0002-9701-6820, SPIN-\u043a\u043e\u0434: 6938-9800 \u0410\u0434\u0436\u0438\u0435\u0432\u0430 \u0410\u0438\u0434\u0430 \u0410\u043d\u0430\u0442\u043e\u043b\u044c\u0435\u0432\u043d\u0430<\/strong>, \u0434-\u0440 \u0444\u0438\u0437.-\u043c\u0430\u0442. \u043d\u0430\u0443\u043a, \u043f\u0440\u043e\u0444\u0435\u0441\u0441\u043e\u0440 \u043a\u0430\u0444\u0435\u0434\u0440\u044b \u00ab\u0412\u044b\u0441\u0448\u0430\u044f \u043c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u043a\u0430 \u0438 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb, \u041a\u0430\u0431\u0430\u0440\u0434\u0438\u043d\u043e-\u0411\u0430\u043b\u043a\u0430\u0440\u0441\u043a\u0438\u0439 \u0433\u043e\u0441\u0443\u0434\u0430\u0440\u0441\u0442\u0432\u0435\u043d\u043d\u044b\u0439 \u0430\u0433\u0440\u0430\u0440\u043d\u044b\u0439 \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442 \u0438\u043c\u0435\u043d\u0438 \u0412. \u041c. \u041a\u043e\u043a\u043e\u0432\u0430;
    360030, \u0420\u043e\u0441\u0441\u0438\u044f, \u0433. \u041d\u0430\u043b\u044c\u0447\u0438\u043a, \u043f\u0440\u043e\u0441\u043f\u0435\u043a\u0442 \u041b\u0435\u043d\u0438\u043d\u0430, 1\u0432;
    aida-adzhieva@mail.ru, ORCID: https:\/\/orcid.org\/0000-0002-1047-8417, SPIN-\u043a\u043e\u0434: 4128-9520
    \u0410\u0445\u043c\u0430\u0442\u043e\u0432 \u041c\u0443\u0445\u0430\u0434\u0438\u043d \u041c\u0430\u0433\u043e\u043c\u0435\u0434\u043e\u0432\u0438\u0447<\/strong>, \u043a\u0430\u043d\u0434. \u0444\u0438\u0437.-\u043c\u0430\u0442. \u043d\u0430\u0443\u043a, \u0434\u043e\u0446\u0435\u043d\u0442, \u0434\u043e\u0446\u0435\u043d\u0442 \u043a\u0430\u0444\u0435\u0434\u0440\u044b \u00ab\u0412\u044b\u0441\u0448\u0430\u044f \u043c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u043a\u0430 \u0438 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb, \u041a\u0430\u0431\u0430\u0440\u0434\u0438\u043d\u043e-\u0411\u0430\u043b\u043a\u0430\u0440\u0441\u043a\u0438\u0439 \u0433\u043e\u0441\u0443\u0434\u0430\u0440\u0441\u0442\u0432\u0435\u043d\u043d\u044b\u0439 \u0430\u0433\u0440\u0430\u0440\u043d\u044b\u0439 \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442 \u0438\u043c\u0435\u043d\u0438 \u0412. \u041c. \u041a\u043e\u043a\u043e\u0432\u0430;
    360030, \u0420\u043e\u0441\u0441\u0438\u044f, \u0433. \u041d\u0430\u043b\u044c\u0447\u0438\u043a, \u043f\u0440\u043e\u0441\u043f\u0435\u043a\u0442 \u041b\u0435\u043d\u0438\u043d\u0430, 1\u0432;
    m_ahmatov@mail.ru, ORCID: https:\/\/orcid.org\/0009-0003-2941-7459, SPIN-\u043a\u043e\u0434: 3620-2852
    \u0425\u0438\u0442\u0438\u0435\u0432\u0430 \u0410\u043c\u0438\u043d\u0430\u0442 \u0416\u0430\u0433\u0430\u0444\u0430\u0440\u043e\u0432\u043d\u0430<\/strong>, \u043a\u0430\u043d\u0434. \u044d\u043a\u043e\u043d. \u043d\u0430\u0443\u043a, \u0434\u043e\u0446\u0435\u043d\u0442, \u0434\u043e\u0446\u0435\u043d\u0442 \u043a\u0430\u0444\u0435\u0434\u0440\u044b \u00ab\u0412\u044b\u0441\u0448\u0430\u044f \u043c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u043a\u0430 \u0438 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb, \u041a\u0430\u0431\u0430\u0440\u0434\u0438\u043d\u043e-\u0411\u0430\u043b\u043a\u0430\u0440\u0441\u043a\u0438\u0439 \u0433\u043e\u0441\u0443\u0434\u0430\u0440\u0441\u0442\u0432\u0435\u043d\u043d\u044b\u0439 \u0430\u0433\u0440\u0430\u0440\u043d\u044b\u0439 \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442 \u0438\u043c\u0435\u043d\u0438 \u0412. \u041c. \u041a\u043e\u043a\u043e\u0432\u0430;
    360030, \u0420\u043e\u0441\u0441\u0438\u044f, \u0433. \u041d\u0430\u043b\u044c\u0447\u0438\u043a, \u043f\u0440\u043e\u0441\u043f\u0435\u043a\u0442 \u041b\u0435\u043d\u0438\u043d\u0430, 1\u0432;
    aminkahitieva@mail.ru, ORCID: https:\/\/orcid.org\/0009-0004-6847-6328, SPIN-\u043a\u043e\u0434: 8085-7236<\/p>\n\n\n\n

    <\/p>\n\n\n\n

    <\/p>\n\n\n\n

    <\/p>\n\n\n\n

    <\/p>\n<\/details>\n\n\n\n

    \u0424\u0438\u043d\u0430\u043d\u0441\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435<\/strong><\/summary>\n

    \u0418\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u0440\u043e\u0432\u0435\u0434\u0435\u043d\u043e \u0431\u0435\u0437 \u0441\u043f\u043e\u043d\u0441\u043e\u0440\u0441\u043a\u043e\u0439 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u043a\u0438.<\/p>\n<\/details>\n\n\n\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

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