Effect of moisture exchange in the northern Atlantic on european Russia moistening and annual Volga runoff

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Abstract

The interaction between hydrological cycle components in the ocean–atmosphere–land system was considered. Calculations were made with the use of various reanalysis archives, and regularities in the interannual variability of evaporation and precipitation in the North Atlantic and their effect on the zonal transport of water vapor onto the European continent were considered. Statistical models of the annual average total moisture flow at the meridional section 5° E as a function of evaporation in the North Atlantic were constructed. The contribution of the zonal transport of water vapor at the meridian 5° E to the variance of the total precipitation over cold and warm seasons in the Volga basin was determined. Models with a small number of parameters were constructed for forecasting the annual runoff of the Volga as a function of precipitation by methods of multiple regression and decision trees.

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About the authors

V. N. Malinin

Russian State Hydrometeorological University

Author for correspondence.
Email: malinin@rshu.ru
Russian Federation, Saint-Petersburg

S. M. Gordeeva

Russian State Hydrometeorological University

Email: gordeeva@rshu.ru
Russian Federation, Saint-Petersburg

References

  1. Гордеева С.М., Малинин В.Н. Использование Data Mining в задаче гидрометеорологического прогнозирования // Уч. зап. РГГМУ. 2016. № 44. С. 30–44.
  2. Добровольский С.Г. Глобальные изменения речного стока. М.: ГЕОС, 2011. 660 с.
  3. Добровольский С.Г. Климатические изменения в системе “гидросфера–атмосфера”. М.: ГЕОС, 2002. 232 с.
  4. Ефремова Н.И. Месячные количества атмосферных осадков средние для районов Европейской территории СССР и северного Казахстана. Л.: Гидрометеоиздат, 1976. 112 с.
  5. Малинин В.Н. Влагообмен в системе океан–атмосфера. СПб.: Гидрометеоиздат, 1994. 197 с.
  6. Малинин В.Н. Проблема прогноза уровня Каспийского моря. СПб.: РГГМИ, 1994. 154 с.
  7. Малинин В.Н. Статистические методы анализа гидрометеорологической информации. СПб.: РГГМУ, 2008. 408 с.
  8. Малинин В.Н., Радикевич В.М., Гордеева С.М., Куликова Л.А. Изменчивость вихревой активности атмосферы над Северной Атлантикой. СПб.: Гидрометеоиздат, 2003. 171 с.
  9. Мировой водный баланс и водный ресурсы Земли. Л.: Гидрометеоиздат, 1974. 638 с.
  10. Многолетние ряды месячных сумм средних областных осадков за холодный период для основной сельскохозяйственной зоны СССР. Л.: Гидрометеоиздат, 1988. 288 с.
  11. Описание массива данных месячных сумм осадков на станциях России // Российский гидрометеорологический портал: ВНИИГМИ-МЦД. http://meteo.ru/data/158total-precipitation#описание-массива-данных, свободный
  12. Смирнов Н.П., Малинин В.Н. Водный баланс атмосферы как гидрологическая задача. Л.: Изд-во ЛГУ, 1986. 189 с.
  13. Специализированные массивы для климатических исследований // ВНИИГМИ-МЦД. http://aisori.meteo.ru/ClimateR
  14. Adler R.F. The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present) // J. Hydrometeor. 2003. V. 4. P. 1147–1167.
  15. Andersson A., Klepp C., Fennig K., Bakan S., Grassl H., Schulz J. Evaluation of HOAPS-3 Ocean Surface Freshwater Flux Components // J. Appl. Meteor. Climatol. 2011. V. 50. P. 379–398. Doi: http://dx.doi.org/10.1175/2010JAMC2341.1
  16. Bramer M. Principles of Data Mining. London: Springer-Verlag, 2007. 344 p. doi: 10.1007/978-1-84628-766-4.
  17. Breiman L., Friedman J., Olshen R., Stone C. Classification and Regression Trees. New York: Chapman and Hall, 1984. 358 p.
  18. Durre I., Vose R.S., Wuertz D.B. Overview of the Integrated Global Radiosonde Archive // J. Climate. 2006. V. 19. P. 53–68.
  19. Hilburn K.A. The Passive Microwave Water Cycle Product // REMSS Tech. Rpt. 072409. 2009. P. 1–30.
  20. Integrated Global Radiosonde Archive (IGRA) Version 2 // NCEI. NOAA. URL: ftp://ftp.ncdc.noaa.gov/pub/data/igra
  21. Interactive Trees (C&RT, CHAID): Statistica Help // StatSoft inc. URL:http://documentation.statsoft.com/STATISTICAHelp.aspx?path=Gxx/Indices/InteractiveTreesCRTCHAID_HIndex.
  22. Kalnay E.М., Kanamitsu M., Kistler R., Collins W., Deaven D., Gandin L., Iredell M., Saha S., White G., Woollen J., Zhu Y., Chelliah M., Ebisuzaki W., Higgins W., Janowiak J., Mo K.C., Ropelewski C., Wang J., Leetmaa A., Reynolds R., Jenne R., Joseph D. The NMC/NCAR 40-Year Reanalysis Project // Bull. Amer. Meteor. Soc. 1996. V. 77. P. 437−471.
  23. Kanamitsu M., Ebisuzaki W., Woollen J., Yang S.-K., Hnilo J.J., Fiorino M., Potter G.L. NCEP–DOE AMIP-II reanalysis (R-2) // Bul. of the Atmos. Met. Soc. 2002. V. 83. P. 1631–1643.
  24. Malinin V.N., Gordeeva S.M. Variability of Evaporation and Precipitation over the Ocean from Satellite Data // Izvestiya, Atmospheric and Oceanic Physics. 2017. V. 53. № 9. P. 934–944. doi: 10.1134/S0001433817090195
  25. NOAA NCEP-DOE Reanalysis-2: NCEP/DOE AMIP-II Reanalysis (Reanalysis-2) // NOAA. URL: http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NCEP-DOE/.Reanalysis-2/
  26. Trenberth K.E., Fasullo J.T., Mackaro J. Atmospheric moisture transports from ocean to land and global energy flows in reanalyses // J. Clim. 2011. V. 24. P. 4907–4924.
  27. Yu L., Jin X., Josey S., Lee T., Kumar A., Wen C., Xue Y. The Global Ocean Water Cycle in Atmospheric Reanalysis, Satellite, and Ocean Salinity // J. Climate. 2017. 30. Р. 3829–3852. doi: 10.1175/JCLI-D-16-0479.1
  28. Yu L.S., Weller R.A. Objectively analyzed air–sea heat fluxes for the global ice-free oceans (1981–2005) // Bull. Amer. Meteor. Soc. 2007. V. 88. P. 527–539.

Supplementary files

Supplementary Files
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2. Fig. 1. A conceptual diagram of the formation of interannual fluctuations of humidification at the ECHR [8].

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3. Fig. 2. The spatial distribution of the correlation coefficients between evaporation from the water area of ​​the SA and the first HA of the complete zonal moisture transfer in a meridional section of 5 ° E. for average annual conditions. The vertical line is a meridional section of zonal moisture transfer at 5 ° E. Negative values ​​of the correlation coefficient are depicted by dotted isolines.

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4. Fig. 3. The distribution of the coefficient of determination restored by the first three main components of the annual values ​​of the total zonal moisture flux in the section of 5 ° E

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5. Fig. 4. The spatial distribution of the coefficients of determination, showing the total contribution of the total zonal moisture fluxes at 13 points on the meridional section of 5 ° E in the formation of interannual variability of winter (October – March) (a) and summer (April – September) (b) precipitation in the flow-forming zone of the Volga Basin.

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6. Fig. 5. Comparison of actual and calculated values of the drain p. Volga near the city of Volgograd (1 - actual values of the flow; 2 - forecast of the flow according to model (4) on the dependent sample 1983–2008; 3 - forecast of the flow according to model (4) on the independent sample 2009–2013, 4 - the forecast of the flow of decision tree 5 on the dependent sample of 1983–2008; 5 - the forecast of the flow of decision tree 5 of the independent sample of 2009–2013).

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7. Fig. 6. The distribution of the test price on the training (dependent) sample (1) and the price of the cross-test error (2) depending on the number of tree nodes in identifying the relationship between the annual flow of the Volga and the precipitation in the catchment area for the two previous years.

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8. Fig. 7. Decision Tree 5, describing the formation of the annual runoff (m3 / s) of the Volga (Volgograd) in year i, depending on winter and summer precipitation (mm / year) in i – 1 and i – 2 years at meteorological stations located in the basin, for the period of 1983–2008.

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