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Nonchaotic and globally synchronized short-term climatic variations and their origin

  • I. V. SerykhEmail author
  • D. M. Sonechkin
Original Paper
  • 20 Downloads

Abstract

Careful computations of atmospheric power spectra are done. These computations reveal that these spectra are continuous in the range of timescales from 2 days to 1 year, and so they confirm that weather variations are chaotic; however, the continuity of a part of the atmospheric power spectra, corresponding to the periods from 2 years to one decade is questioned. This part is prominent by the existence of several narrow bands of increased spectral density centered at the subharmonics 2:1, 3:1, and 4:1 of the Chandler wobble in the Earth’s pole motion (~ 1.2 years); the superharmonics 1:2, 1:3, and 1:4 of the Luni-Solar nutation of the Earth’s rotation axis (~ 18.6 years) as well as the superharmonics 1:2, 1:3, and 1:4 of the 11-year cycle of the Sun spots. The existence of similar bands in the El Niño–Southern Oscillation (ENSO) power spectra was recognized many years ago; however, it turns out that the above spectral bands also are seen in spectra of the atmospheric characteristics outside of tropics. Moreover, the respective climatic variations are globally synchronized. The synchronization takes place because the above-mentioned external periodicities must influence short-term climatic variations everywhere on the Earth. It is very probable that the periods of the external periodicities indicated are incommensurable with each other. Therefore, if these periodicities actually influence short-term climatic variations, they would have to do it discordantly. As a result, no resonances can exist which could make the affected climatic variations to be chaotic. A linear dependence of logarithms of serial numbers of the spectral bands on logarithms of the band magnitudes as well as a linear decrease of the accumulated sum of the squared autocorrelations of the respective atmospheric characteristics confirm that the dynamics of the interannual to decadal climatic variations are not chaotic.

Notes

Supplementary material

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References

  1. Allan RJ, Ansell TJ (2006) A new globally-complete monthly historical gridded mean sea level pressure data set (HadSLP2): 1850-2004. J Clim 19:5816–5846CrossRefGoogle Scholar
  2. Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Weather Rev 97:163–172CrossRefGoogle Scholar
  3. Blekhman II (1971) Synchronization of the dynamical systems. Nauka, Moscow 896 p. – in RussianGoogle Scholar
  4. Braganza K, Gergis JL, Power SB, Risbey JS, Fowler AM (2009) A multi-proxy index of the El Niño-southern oscillation, A.D. 1525–1982. J Geophys Res 114:D05106.  https://doi.org/10.1029/2008JD010896 CrossRefGoogle Scholar
  5. Bryson RA, Starr TB (1977) Chandler tides in the atmosphere. J Atmos Sci 34:1975–1986CrossRefGoogle Scholar
  6. Byshev VI, Neiman VG, Romanov YA, Serykh IV (2012) El Niño as a consequence of the global oscillation in the dynamics of the earth's climatic system. Dokl Earth Sci 446(Part 1):1089–1094CrossRefGoogle Scholar
  7. Byshev VI, Neiman VG, Romanov YA, Serykh IV, Sonechkin DM (2016) Statistical significance and climatic role of the global atmospheric oscillation. Oceanology 56(2):165–171CrossRefGoogle Scholar
  8. Chao BF (1985) Excitation of the Earth's Chandler Wobble by southern oscillation/El Nino, 1900–1979. National Aeronautics and Space Administration, Goddard Space Flight Center, Greenbelt 19 ppGoogle Scholar
  9. Climate Prediction Center (1989–2016) Climate Diagnostics Bulletin. NOAA/National Weather Service, Wash. (D.C.)Google Scholar
  10. Compo GP, Whitaker JS, Sardeshmukh PD, Matsui N, Allan RJ, Yin X, Gleason BE, Vose RS, Rutledge G, Bessemoulin P, Brönnimann S, Brunet M, Crouthamel RI, Grant AN, Groisman PY, Jones PD, Kruk MC, Kruger AC, Marshall GJ, Maugeri M, Mok HY, Nordli Ø, Ross TF, Trigo RM, Wang XL, Woodruff SD, Worley SJ (2011) The twentieth century reanalysis project. Q J R Meteorol Soc 137:1–28Google Scholar
  11. Desai SD (2002) Observing the pole tide with satellite altimetry. J Geophys Res 107(C11):3186.  https://doi.org/10.1029/2001JC001224 CrossRefGoogle Scholar
  12. Ding RQ, Li PJ, Zheng F, Feng J, Liu DQ (2015) Estimating the limit of decadal-scale climate predictability using observational data. Clim Dyn 46(5):1563–1580Google Scholar
  13. Eubanks TM, Stepp JA, Dickey JO (1986) Earth rotation: solved and unsolved problems. Springer, Dordrecht NATO ASI Series: Mathematical and Physical Sciences 187 ppGoogle Scholar
  14. Fedorov AV (2002) The response of the coupled tropical ocean – atmosphere to westerly wind bursts. Q J R Meteorol Soc 128:1–23CrossRefGoogle Scholar
  15. Fedorov AV, Filander SG (2000) Is El Nino changing? Science 288:1997–2002CrossRefGoogle Scholar
  16. Feudel U, Kuznetsov S, Pikovsky A (2006) Strange nonchaotic attractors. World Scientific, Singapore 228 pCrossRefGoogle Scholar
  17. Fraedrich K, Blender R, Zhu X (2009) Continuum climate variability: long-term memort, scaling, and 1/f-noise. Int J Mod Phys B 23:5403–5416CrossRefGoogle Scholar
  18. Ghil M (1985) Theoretical climate dynamics: an introduction. In: Ghil M, Benzi R, Parisi G (eds) Turbulence and predictability in geophysical fluid dynamics and climate dynamics. North Holland, New York, pp 347–402Google Scholar
  19. Gilman DL, Fuglister FJ, Mitchell JM (1963) On the power spectrum of “red noise”. J Atmos Sci 20:182–184CrossRefGoogle Scholar
  20. Grebogi C, Ott E, Pelikan S, Yorke JA (1984) Strange attractors that are not chaotic. Physica D 13:261–268CrossRefGoogle Scholar
  21. Harrison DE, Vecchi GA (1997) Westerly wind events in the tropical Pacific, 1986–95. J Clim 10:3131–3156CrossRefGoogle Scholar
  22. Hirahara S, Ishii M, Fukuda Y (2014) Centennial-Scale Sea surface temperature analysis and its uncertainty. J Clim 27:57–75CrossRefGoogle Scholar
  23. Huang B, Banzon VF, Freeman E, Lawrimore J, Liu W, Peterson TC, Smith TM, Thorne PW, Woodruff SD, Zhang HM (2015) Extended reconstructed sea surface temperature version 4 (ERSST.v4). Part I: upgrades and intercomparisons. J Clim 28(3):911–930CrossRefGoogle Scholar
  24. Huang B, Thorne PW, Banzon VF, Boyer T, Chepurin G, Lawrimore JH, Menne MJ, Smith TM, Vose RS, Zhang H (2017) Extended reconstructed sea surface temperature version 5 (ERSSTv5): upgrades, validations, and intercomparisons. J Clim 30:8179–8205.  https://doi.org/10.1175/JCLI-D-16-0836.1 CrossRefGoogle Scholar
  25. Huybers P, Curry W (2006) Links between annual, Milankovitch and continuum temperature variability. Nature 441(7091):329–332Google Scholar
  26. Ikeda K, Matsumoto K (1986) Study of a high-dimensional chaotic attractor. J Stat Phys 44(5/6):955–983CrossRefGoogle Scholar
  27. Ivashchenko NN, Kotlyakov VM, Sonechkin DM, Vakulenko NV (2013) On the nature of the Pliocene/Pleistocene glacial cycle lengthening. Global Perspective on Geography 1:9–20Google Scholar
  28. Ivashchenko NN, Kotlyakov VM, Sonechkin DM, Vakulenko NV (2014) On bifurcations inducing glacial cycle lengthening during Pliocene/Pleistocene epoch. Intern J Bifurcation Chaos 24(8):1440018 (8)CrossRefGoogle Scholar
  29. Jiang N, Neelin JD, Ghil M (1995) Quasi-quadrennial and quasi-biennial variability in the equatorial Pacific. Clim Dyn 12:101–112CrossRefGoogle Scholar
  30. Jin FF, Neelin JD, Ghil M (1994) El Nino on the devil’s: annual subharmonic steps to chaos. Science 264:70–72CrossRefGoogle Scholar
  31. Jones PD, Lister DH, Osborn TJ (2012) Hemispheric and large-scale land surface air temperature variations: an extensive revision and an update to 2010. J Geophys Res 117:D05127Google Scholar
  32. Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Leetmaa A, Reynolds R, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
  33. Kobayashi S, Ota Y, Harada Y et al (2015) The JRA-55 reanalysis: general specifications and basic characteristics. J Meteorol Soc Jpn 93(1):5–48CrossRefGoogle Scholar
  34. Li JP, Ding RQ (2011) Temporal-spatial distribution of atmospheric predictability limit by local dynamical analogues. Mon Weather Rev 139:3265–3283CrossRefGoogle Scholar
  35. Liu W, Huang B, Thorne PW, Banzon VF, Zhang HM, Freeman E, Lawrimore J, Peterson TC, Smith TM, Woodruff SD (2015) Extended reconstructed sea surface temperature version 4 (ERSST.v4): part II. Parametric and structural uncertainty estimations. J Clim 28(3):931–951CrossRefGoogle Scholar
  36. Lorenz EN (1984) A very narrow spectral band. J Stat Phys 36:1–14CrossRefGoogle Scholar
  37. Lorenz EN (2006) Predictability – a problem partly solved. In: Palmer T, Hagedorn R (eds) Predictability of weather and climate, pp 40–58CrossRefGoogle Scholar
  38. Lovejoy S (2018) Spectra, intermittency, and extremes of weather, macroweather and climate. Sci Rep 8:12697.  https://doi.org/10.1038/s41598-018-30829-4 CrossRefGoogle Scholar
  39. Lovejoy S, Schertzer D (2012) Low frequency weather and emergence of the climate. In: Sharma AS et al (eds) Extreme events and natural hazard. The complexity perspective. AGU, Washington, D.C., pp 231–254CrossRefGoogle Scholar
  40. Lovejoy S, Schertzer D (2013) The weather and climate: emergent laws and multifractal cascades. Cambridge Univ. Press, Cambridge 496 ppCrossRefGoogle Scholar
  41. Madden RA, Julian PR (1994) Observations of the 40-50 day tropical oscillation – a review. Mon Weather Rev 122:814–837CrossRefGoogle Scholar
  42. Maksimov IV (1952) On “pole tide” in seas and atmosphere of the Earth. Dokl Acad Sci 86:673–676 in RussianGoogle Scholar
  43. Maksimov IV (1955) “Polar tide” in the sea and the Earth's atmosphere. Trudy Instituta Okeanologii AN SSSR 8:92–118 in RussianGoogle Scholar
  44. Maksimov IV (1956) Nutation standing wave in the ocean and its geographical investigation. Izvestiya Akademii Nauk SSSR, ser. Geograficheskaya 1:14–34 in RussianGoogle Scholar
  45. McPhaden MJ, Busalacchi AJ, Cheney R, Donguy JR, Gage KS, Halpern D, Ji M, Julian P, Meyers G, Mitchum GT (1998) The Tropical Ocean-Global Atmosphere (TOGA) observing system: a decade of progress. J Geophys Res 103(14):169–14,240Google Scholar
  46. Monin AS, Yaglom AM (1975) Statistical fluid mechanics. Vol. II mechanics of turbulence. MIT Press, Cambridge 896 pGoogle Scholar
  47. Osprey SM, Ambaum MHP (2011) Evidence for the chaotic origin of northern annular mode variability. Geophys Res Lett 38:L15702.  https://doi.org/10.1029/2011GL048181 CrossRefGoogle Scholar
  48. Pelletier J (1998) The power-spectral density of atmospheric temperature from time scales of 10-2 to 106 yr. Earth Planet Sci Lett 158:157–164CrossRefGoogle Scholar
  49. Peng JB, Chen LT, Zhang QY (2014) The relationship between the El Niño/La Niña cycle and the transition chains of four atmospheric oscillations. Part I: the four oscillations. Adv Atmos Sci 31(2):468–479.  https://doi.org/10.1007/s00376-013-2275-0 CrossRefGoogle Scholar
  50. Philander SG (1999) A review of tropical ocean-atmosphere interactions. Tellus 51 A-B:71–90Google Scholar
  51. Pikovskii A, Rosenblum M, Kurths J (2001) Synchronization. A universal concept in dissipative systems. Cambridge Univ. Press, CambridgeGoogle Scholar
  52. Pikovsky A, Politi A (2016) Lyapunov exponents. A tool to explore complex dynamics. Cambrifge Univ Press, Cambridge 295 pCrossRefGoogle Scholar
  53. Rayner NA, Parker DE, Horton EB et al (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108(D14):4407CrossRefGoogle Scholar
  54. Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis for climate. J Clim 15:1609–1625CrossRefGoogle Scholar
  55. Romero-Centeno R, Zavala-Hidalgo J, Gallegos A, O’Brien JJ (2003) Isthmus of Tehuantepec wind climatology and ENSO signal. J Clim 16:2628–2639CrossRefGoogle Scholar
  56. Saffman PG (1967) The large scale structure of homogeneous turbulence. J Fluid Mech 27(3):581–593CrossRefGoogle Scholar
  57. Scoccimarro E, Gualdi S, Bellucci A, Sanna A, Fogli PG, Manzini E, Vichi M, Oddo P, Navarra A (2011) Effects of tropical cyclones on ocean heat transport in a high resolution coupled general circulation model. J Clim 24:4368–4384CrossRefGoogle Scholar
  58. Serykh IV (2017) A Comparison of the structure and dynamics of global atmospheric oscillation in reality and in the CMIP5 climate models // IOP conference series. Earth Environ Sci 96:012006Google Scholar
  59. Serykh IV, Sonechkin DM (2016) Confirmation of the oceanic pole tide influence on El Niño. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa 13(2):44–52CrossRefGoogle Scholar
  60. Serykh IV, Sonechkin DM (2017) Manifestations of motions of the Earth’s pole in the El Niño –Southern Oscillation rhythms. Dokl Earth Sci 472(2):256–259CrossRefGoogle Scholar
  61. Sidorenkov NS (2009) The interaction between Earth's rotation and geophysical processes. Wiley-VCH & Co. KCaA, Weinheim 305 pCrossRefGoogle Scholar
  62. Sonechkin DM, Ivashchenko NN (2001) On the role of a quasiperiodic forcing in the interannual and interdecadal climate variations. CLIVAR Exchanges 6(1):5–6Google Scholar
  63. SSALTO-DUACS (2015) Ssalto/Duacs user handbook: (M)SLA and (M)ADT near-real time and delayed time products, version 4 rev. 4, rep. SALP-MU-P-EA-21065-CLS. Aviso, Ramonville-St-Agne 74 ppGoogle Scholar
  64. Stickler A, Brönnimann S, Valente MA, Bethke J, Sterin A, Jourdain S, Roucaute E, Vasquez MV, Reyes DA, Allan R, Dee D (2014) ERA-CLIM: historical surface and upper-air data for future reanalyses. Bull Am Meteorol Soc 95(9):1419–1430CrossRefGoogle Scholar
  65. Tanaka Y, Yasuda I, Hasumi H (2012) Effects of the 18.6-yr modulation of tidal mixing on the north pacific bidecadal climate variability in a coupled climate model. J Clim 25(21):7625–7642.  https://doi.org/10.1175/JCLI-D-12-00051.1 CrossRefGoogle Scholar
  66. Taylor KE, Stouffer RJ, Meehl GA (2012) Overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498CrossRefGoogle Scholar
  67. Torrence C, Compo GP (1997) A practical guide to wavelet analysys. Bull Am Meteorol Soc 79(1):61–78CrossRefGoogle Scholar
  68. Trenberth KE (1976) Spatial and temporal variations of the southern oscillation. Q J R Meteorol Soc 102:639–653CrossRefGoogle Scholar
  69. Trenberth KE, Shea D (1987) On the evolution of the southern oscillation. Mon Weather Rev 115(12):3078–3096CrossRefGoogle Scholar
  70. Tziperman E, Stone L, Cane MA, Jarosh H (1994) El Nino chaos: overlapping of resonances between the seasonal cycle and the Pacific Ocean – atmosphere oscillator. Science 264:72–74CrossRefGoogle Scholar
  71. Tziperman E, Zebiak SE, Cane MA (1997) Mechanisms of seasonal – ENSO interaction. J Atmos Sci 54:61–71CrossRefGoogle Scholar
  72. Tziperman E, Cane MA, Zebiak SE et al (1998) Locking of El Nino’s peak time to the end of the calendar year in the delayed oscillator picture of ENSO. J Clim 9:2191–2199CrossRefGoogle Scholar
  73. Vakulenko NV, Sonechkin DM (2011) Evidence of the solar activity's effect on El Nino southern oscillation. Oceanology 51(6):935–939CrossRefGoogle Scholar
  74. Vakulenko NV, Ivashchenko NN, Kotlyakov VM, Sonechkin DM (2011) On periods of multiplying bifurcation of Early Pleistocene glacial cycles. Dokl Earth Sci 436(Part 2):245–248CrossRefGoogle Scholar
  75. Wahr JM (1985) Deformation induced by polar motion. J Geophys Res 90(B11):9363–9368CrossRefGoogle Scholar
  76. Webster PJ, Yang S (1992) Monsoon and ENSO: selectively interactive systems. Q J R Meteorol Soc 118:877–925CrossRefGoogle Scholar
  77. Welch PD (1967) The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust AU-15(2):70–73CrossRefGoogle Scholar
  78. Wirtki K (1975) El Niño - the dynamic response of the equatorial Pacific Ocean to atmospheric forcing. J Phys Oceanogr 5:572–584CrossRefGoogle Scholar
  79. Yasuda I (2009) The 18.6-year period moon-tidal cycle in Pacific decadal oscillation reconstructed from tree-rings in western North America. Geophys Res Lett 36:L05605.  https://doi.org/10.1029/2008GL036880 CrossRefGoogle Scholar

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© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Shirshov Institute of OceanologyRussian Academy of SciencesMoscowRussia

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