Spatial and temporal coherence of quasi-periodic components of meteorological fields as a basis for long-term weather forecasts
https://doi.org/10.29235/1561-8323-2023-67-6-499-507
Abstract
A new method of teleconnections studding is proposed which is based on the identification of conjugate regions in the global meteorological fields of temperature and pressure by their characteristic coherent quasi-periodic oscillation. This method was implemented in order to select predictors of winter air temperature in Belarus with an advance of 2 months. The degree of coherence of sea level pressure and winter temperature in Belarus on a quasi-8-year cycle was considered as a criterion for the selection of predictors. The forecast was implemented using the advanced deep machine learning model TimesNet and showed rather high metrics of quality for seasonal meteorological forecasting: the correlation coefficient between actual and predicted temperature values was 0.66, and the weighted macro-average values of precision and recall of the forecast in the gradations “normal”, “above normal” and “below normal” were 0.61 and 0.56, respectively.
Keywords
Supporting agencies: The study was carried out with financial support from the Belarusian Republican Foundation for Fundamental Research (grant no. X23РНФ-122)
About the Authors
S. A. Lysenko
Institute of Nature Management of the National Academy of Sciences of Belarus
Belarus
Belarus
Lysenko Sergey A. – D. Sc. (Physics and Mathematics), Professor, Director.
10, F. Skorina Str., 220114, Minsk
V. F. Loginov
Institute of Nature Management of the National Academy of Sciences of Belarus
Belarus
Belarus
Loginov Vladimir F. – Academician, D. Sc. (Geography), Professor, Chief Researcher.
10, F. Skorina Str., 220114, Minsk
References
1. Vilfand R. M., Zaripov R. B., Kiktev D. B., Kruglova E. N., Kryjov V. N., Kulikova I. A., Tischenko V. A., Tolstych M. A., Khan V. M. Long-range forecasting at Hydrometeorological Center of Russia. Gidrometeorologicheskie issledovaniya i prognozy = Hydrometeorological Research and Forecasting, 2019, no. 4 (374), pp. 12–36 (in Russian).
2. Bagrov N. A., Kondratovich K. V., Ped D. A., Ugryumov A. I. Long-term meteorological forecasts. Leningrad, 1985. 248 p. (in Russian).
3. Wang Y., Gozolchiani A., Ashkenazy Y., Berezin Y., Guez O., Havlin Sh. Dominant imprint of Rossby waves in the climate network. Physical Review Letters, 2013, vol. 111, art. 138501. https://doi.org/10.1103/physrevlett.111.138501
4. Stan C., Straus D. M., Frederiksen J. S., Lin H., Maloney E. D., Schumacher C. Review of tropical-extratropical teleconnections on intraseasonal time scales. Reviews of Geophysics, 2017, vol. 55, no. 4, pp. 902–937. https://doi.org/10.1002/2016rg000538
5. Hardiman S. C., Dunstone N. J., Scaife A. A., Smith D. M., Ineson S., Lim J., Fereday D. The impact of strong El Niño and La Niña events on the North Atlantic. Geophysical Research Letters, 2019, vol. 46, no. 5, pp. 2874–2883. https://doi.org/10.1029/2018gl081776
6. Gastineau G., Frankignoul C. Influence of the North Atlantic SST variability on the atmospheric circulation during the twentieth century. Journal of Climate, 2015, vol. 28, no. 4, pp. 1396–1416. https://doi.org/10.1175/jcli-d-14-00424.1
7. Seip K. L., Grøn Ø., Wang H. The North Atlantic Oscillations: cycle times for the NAO, the AMO and the AMOC. Climate, 2019, vol. 7, no. 3, art. 43. https://doi.org/10.3390/cli7030043
8. Rahmstorf S. Ocean circulation and climate during the past 120,000 years. Nature, 2002, vol. 419, no. 12, pp. 207–214. https://doi.org/10.1038/nature01090
9. Polonsky A. B., Sukhonos P. A. North Atlantic Oscillation and upper layer heat balance in the North Atlantic. Fundamental’naya i prikladnaya klimatologiya = Fundamental and Applied Climatology, 2019, no. 4, pp. 67–100 (in Russian). https://doi.org/10.21513/0207-2564-2019-4-67-100
10. Jackson L. C., Peterson K. A., Roberts C. D., Wood R. A. Recent slowing of Atlantic overturning circulation as a recovery from earlier strengthening. Nature Geoscience, 2016, vol. 9, no. 7, pp. 518–522. https://doi.org/10.1038/ngeo2715
11. Fedorov A. M., Bashmachnikov I. L., Belonenko T. V. Localization of areas of deep convection in the Nordic seas, the Labrador sea and the Irminger sea. Vestnik SPbGU. Nauki o Zemle = Vestnik of Saint Petersburg University. Earth Sciences, 2018, vol. 63, no. 3, pp. 345–362 (in Russian). https://doi.org/10.21638/spbu07.2018.306
12. Årthun M., Eldevik T., Viste E., Drange H., Furevik T., Johnson H. L., Keenlyside N. S. Skillful prediction of northern climate provided by the ocean. Nature Communications, 2017, vol. 8, art. 15875. https://doi.org/10.1038/ncomms15875
13. Nesterov E. S. North Atlantic Oscillation: atmosphere and ocean. Moscow, 2013. 144 p. (in Russian).
14. Wang W., Anderson B. T., Kaufmann R. K., Myneni R. B. The Relation between the North Atlantic Oscillation and SSTs in the North Atlantic Basin. Journal of Climate, 2004, vol. 17, no. 24, pp. 4752–4759. https://doi.org/10.1175/jcli-3186.1
15. McCarthy G. D., Joyce T. M., Josey S. A. Gulf Stream variability in the context of quasi-decadal and multidecadal atlantic climate variability. Geophysical Research Letters, 2018, vol. 45, no. 20, pp. 11257–11264. https://doi.org/10.1029/2018gl079336
Review
Views: 200
Email this article 