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
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