Study of observed changes in the first harmonic amplitude of the daily precipitation amount series in the territory of Russia

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Using the data from weather observation stations, an assessment of the statistical significance of the first harmonic amplitude of the average long-term daily precipitation amount series in Russia in 1961–2020 and their changes in 1991–2020 compared to 1961–1990 is made. It is shown that at most stations the first harmonic has a reliable value different from the noise, except for eleven stations in the southern regions of the European Part of Russia. It is revealed that, on average, there is a significant decrease in the first harmonic amplitudes of the daily precipitation series across Russia. An analysis of the spatial distribution of the studied quantities is performed and the presence of large areas with their homogeneous character is demonstrated.

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作者简介

I. Popov

Yu. A. Izrael Institute of Global Climate and Ecology; Institute of Geography, Russian Academy of Sciences

编辑信件的主要联系方式.
Email: igor_o_popov@mail.ru
俄罗斯联邦, Moscow; Moscow

E. Popova

Institute of Geography, Russian Academy of Sciences

Email: en_popova@mail.ru
俄罗斯联邦, Moscow

参考

  1. Strangeways I. Precipitation. Theory, Measurement and Distribution. Cambridge University Press. 2007. doi: 10.1017/CBO9780511535772.
  2. Хромов С. П., Петросянц М. А. Метеорология и климатология. М.: Издательство Московского Университета, 2012. 582 с.
  3. Markham C. G. Seasonality of Precipitation in the United States // Annals of the Association of American Geographers. 1970. T. 60. V. 3. P. 593–597.
  4. Imteaz M. A., Hossain I. Climate Change Impacts on ‘Seasonality Index’ and its Potential Implications on Rainwater Savings // Water Resource Manage. 2023. V. 37. P. 2593–2606. doi: 10.1007/s11269-022-03320-z.
  5. Лайонс Р. Цифровая обработка сигналов. М.: “Бином”, 2006. 656 с.
  6. Nasser R. A., Hedayat F. Rainfall Forecasting Using Fourier Series // Journal of Civil Engineering and Architecture. 2012. V. 6. № 9. P. 1258–1262. doi: 10.17265/1934-7359/2012.09.019.
  7. Villarreal F. J. G., Mendoza V. I. M. Fast Fourier transform analysis of precipitation data for the Colorado river basin // Proceedings of the 37th IAHR World Congress (Kuala Lumpur, Malaysia, August 13–18, 2017). P. 5639–5645.
  8. Ussalu J. L. M., Bassrei A. Climate dynamics of southern region of Mozambique: statistics and Fourier analysis // Revista Brasileira de Climatologia. 2021. V. 29. P. 134–156. DOI: http://dx.doi.org/10.5380/rbclima.v29i0.75088
  9. Morales J. E., Poveda G. Diurnally driven scaling properties of Amazonian rainfall fields: Fourier spectra and order-q statistical moments // Journal of Geophysical Research. 2009. V. 114. P. 1–10. D11104, doi: 10.1029/2008JD011281
  10. Marshall G. J. On the annual and semi-annual cycles of precipitation across Antarctica // International Journal of Climatology. 2009. V. 29. № 15. P. 2298–2308. doi: 10.1002/joc.1810.
  11. Третий оценочный доклад об изменениях климата и их последствиях на территории Российской Федерации / под ред. В.М. Катцова; Росгидромет. СПб.: “Наукоемкие технологии”, 2022. 676 с.
  12. Popova E. N., Popov I. O., Semenov S. M. Assessment of Variations in the Annual Sum of Active Temperatures and Total Precipitation during the Vegetation Period in Russia and Neighboring Countries // Russian Meteorology and Hydrology. 2018. V. 43. № 6. P. 412–417.
  13. Золина О. Г., Булыгина О. Н. Современная климатическая изменчивость характеристик экстремальных осадков в России // Фундаментальная и прикладная климатология. 2016. Т. 1. С. 84–103. doi: 10.21513/2410-8758-2016-1-84-103
  14. Aleshina M. A., Semenov V. A, Chernokulsky A. V. A link between surface air temperature and extreme precipitation over Russia from station and reanalysis data // Environmental Research Letters. 2021. V. 16. № 10. 105004. doi: 10.1088/1748-9326/ac1cba.
  15. Попов И. О., Попова Е. Н. Анализ изменения режима осадков на территории Российской Федерации во второй половине 20–начале 21 века с применением байесовской оценки параметров марковской цепи // Доклады Российской Академии наук. Науки о Земле. 2022. Т. 502. № 1. С. 38–44. doi: 10.31857/S2686739722010054.
  16. Zolina O., Simmer C., Gulev S. K., Kollet S. Changing structure of European precipitation: Longer wet periods leading to more abundant rainfalls // Geophysical Research Letters. 2010. V. 37. L06704. doi: 10.1029/2010GL042468.
  17. Pruscha H. Statistical Analysis of Climate Series. Berlin; Heidelberg: Springer, 2013. 176 p. doi: 10.1007/978-3-642-32084-2.
  18. Brockwell P. J., Davis R. A. Time Series: Theory and Methods. New York, N.Y.: Springer, 1991. 580 p. doi: 10.1007/978-1-4419-0320-4.
  19. Roe G. H. Orographic Precipitation // Annual Review of Earth and Planetary Sciences. 2005. V. 33. P. 645–671. doi: 10.1146/annurev.earth.33.092203.122541.
  20. Wang B., Li X., Huang Y., Zhai G. Decadal trends of the annual amplitude of global precipitation // Atmospheric Science Letters. 2016. V. 17. P. 96–101. doi: 10.1002/asl2.631.

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2. Fig. 1. Graphs of the annual course of average long-term daily precipitation amounts for the period 1961–2020 (blue line) and the course of the first harmonic (orange line). Data for stations: (a) WMO 22324 (Umba, 66°41ʹ N, 34°21ʹ E), (b) WMO 27037 (Vologda, 59°19ʹ N, 39°55ʹ E), (c) WMO 34866 (Yashkul, 46°11ʹ N, 45°21ʹ E), (d) WMO 23867 (Laryak, 61°06ʹ N, 80°15ʹ E), (d) WMO 29974 (Olenya Rechka, 52°48ʹ N, 93°14ʹ E), (e) WMO 31909 (Terney, 45°0ʹ N, 136°36ʹ E). The abscissa axis shows the beginning dates of the corresponding months.

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3. Fig. 2. Spatial distribution of the first harmonic amplitude values ​​of the series of average long-term daily precipitation amounts for the period 1961–2020. Legend: 1 – stations with statistically significant amplitude, 2 – stations with statistically insignificant amplitude.

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4. Fig. 3. (a) – histograms (1, 2) and kernel estimates (3, 4) of the distributions of the first harmonic amplitude values ​​of the series of long-term average daily precipitation amounts for the periods 1961–1990 (1, 3) and 1991–2020 (2, 4). (b) – histogram (1) and kernel estimate (2) of the distribution of changes in the first harmonic amplitude values ​​of long-term average daily precipitation amounts for the period 1991–2020 compared to the period 1961–1990.

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5. Fig. 4. Spatial distribution of the values ​​of the differences in the amplitudes of the first harmonic of the series of long-term average daily precipitation amounts for the periods 1991–2020 and 1961–1990. Legend: 1 – stations with a statistically significant increase in amplitude, 2 – stations with a statistically significant decrease in amplitude, 3 – stations with a statistically significant amplitude of the first harmonic for the period 1961–2020, 4 – stations with a statistically insignificant amplitude of the first harmonic for the period 1961–2020.

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