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Application of interval approach to pattern recognition for identification of preceeding baric structures that determine extreme thermal modes in the South-Kuril area in summer

https://doi.org/10.26428/1606-9919-2021-201-470-483

Abstract

Patterns of atmosphere baric fields preceeded to development of extreme thermal modes in the South-Kuril area in summer are identified using the interval approach to their recogni tion. The best recognition rates are noted for the field of AT 500 hPa over the region of East Asia in February, March, May, and June. Extreme cold summer conditions in the South-Kuril area in summer were preceeded by development of AT 500 hPa trough and baric depression at the sea surface over East Asia in these winter and spring months. Warm summer conditions in the South-Kuril area were preceeded by opposite patterns, as AT 500 hPa ridge over the North-West Pacific and high pressure over the Okhotsk Sea, with positive anomalies of H500 height over the North-West Pacific and Kuril Islands.

About the Authors

T. A. Shatilina
VNIRO (TINRO)
Russian Federation

Shatilina Tatiana A., Ph.D., leading researcher, Pacific branch

4, Shevchenko Alley, Vladivostok, 690091



G. Sh. Tsitsiashvili
Institute of Applied Mathematics
Russian Federation

Tsitsiashvili Guram Sh., D.Math., professor, principal researcher

7, Radio Str., Vladivostok, 690041



T. V. Radchenkova
Institute of Applied Mathematics
Russian Federation

Radchenkova Tatyana V., junior researcher

7, Radio Str., Vladivostok, 690041



References

1. Berezhnaya, T.V., Golubev, A.D., and Parshina, L.N., Anomalous hydrometeorological phenomena on the territory of the Russian Federation in August 2016, Tr. Gidrometeorol. Nauchno-Issled. Tsentra Ross. Fed., 2016, no. 11, pp. 109–118.

2. Zavyalova, E.V., Morozova, S.V., and Polyanskaya, E.A.,Synoptic-statistical method of longterm forecast of anomally hot temperature conditions in the lower Volga Region, in Tr. 3-y Vseros. konf. «Gidrometeorologiya i ekologiya: dostizheniya i perspektivy razvitiya» (Proc. 3rd All-Russ. Conf. “Hydrometeorology and ecology: scientific and educational achievements and perspectives”), St. Petersburg: Khimizdat, 2019., pp. 358–362.

3. Multanovsky, B.P., The current state of the development of a method for long-term weather predictions in the USSR, Meteorol. vestn., 1933, no. 5, pp. 129–143.

4. Nalimov, V.V., Teoriya eksperimenta (Experiment theory), Moscow: Nauka, 1971.

5. Rostov, I.D., Dmitrieva, E.V., and Vorontsov, A.A., Tendencies of climatic changes for thermal conditions in the coastal areas of the Okhotsk Sea in last decades, Izv. Tikhookean. Nauchno-Issled. Inst. Rybn. Khoz. Okeanogr., 2017, vol. 191, pp. 176–195. doi 10.26428/1606-9919-2017-191-176-195

6. Tsitsiashvili, G.Sh., Shatilina, T.A., and Radchenkova, T.V., Surface water temperature variability in the Japan Sea and the North-West Pacific in 2000–2012 and the impact on saury fishing, Vopr. Promysl. Okeanologii, 2012, vol. 9, no. 2, pp. 96–116.

7. Shatilina, T.A., Analysis of errors in predicting water temperature in the South Kuril region, in Tezisy dokl. 6 Vseross. konf. probl. rybopromyslovogo prognozirovaniya (Proc. 6th All-Russ. Conf. Probl. Fish. Prediction), Murmansk: PINRO, 1995, p. 166.

8. Shatilina, T.A., Egorova, T.S., Krasikov, V.A., and Safin, V.I., Linear predictive models of water temperature by meteorological predictors in the South Kuril fishing area, Tekhnologii i sredstva modelirovaniya slozhnykh sistem (Technologies and tools for modeling complex systems), Vladivostok, 1992, pp. 130–141.

9. Shatilina, T.A., Tsitsiashvili, G.Sh., and Radchenkova, T.V., Complex assessment of variability for the sea surface temperature in the North-West Pacific in July-September 1950–2014, Izv. Tikhookean. Nauchno-Issled. Inst. Rybn. Khoz. Okeanogr., 2016, vol. 184, pp. 120–134.

10. Shatilina, T.A., Tsitsiashvili, G.Sh., and Radchenkova, T.V., Experience of using the method of interval recognition for predicting extreme ice coverage of the Tatar Strait (Sea of Japan), Tr. Gidrometeorol. Nauchno-Issled. Tsentra Ross. Fed., 2006, no. 10, pp. 65–73.

11. Shatilina, T.A., Tsitsiashvili, G.Sh., and Radchenkova, T.V., Features of the summer atmospheric force centers variability over the Far East and climatic extremes in the period 1980–2017, Uchenyye zapiski Rossiyskogo gosudarstvennogo gidrometeorologicheskogo universiteta, 2019, no. 56, pp. 61–80. doi 10.33933/2074-2762-2019-56-61-80

12. Efficient Algorithms of Time Series Processing and their Applications, Tsitsiashvili, G.Sh., ed., New York: Nova Science Publishers, Inc., 2009.

13. JMA: Japan Meteorological Agency. http://ds.data.jma.go.jp/gmd/goos/data/rrtdb/jma-pro.html. Cited September 20, 2019.

14. Vserossiyskiy nauchno-issledovatel’skiy institut gidrometeorologicheskoy informatsii — Mirovoy tsentr dannykh (All-Russian Research Institute of Hydrometeorological Information — World Data Center). http://meteo.ru. Cited September 20, 2019.


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For citations:


Shatilina T.A., Tsitsiashvili G.Sh., Radchenkova T.V. Application of interval approach to pattern recognition for identification of preceeding baric structures that determine extreme thermal modes in the South-Kuril area in summer. Izvestiya TINRO. 2021;201(2):470-483. (In Russ.) https://doi.org/10.26428/1606-9919-2021-201-470-483

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