On the origins of temporal power-law behavior in the global atmospheric circulation

被引:21
作者
Vyushin, Dmitry I. [1 ]
Kushner, Paul J. [1 ]
Mayer, Josh [1 ]
机构
[1] Univ Toronto, Dept Phys, Toronto, ON M5S 1A7, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
LONG-RANGE CORRELATIONS; NATURAL VARIABILITY; SURFACE-TEMPERATURE; MEMORY;
D O I
10.1029/2009GL038771
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Climate variations on timescales longer than a year are often characterized by temporal scaling ("power-law'') behavior for which spectral power builds up at low frequencies, in contrast to red-noise behavior for which spectral power saturates at low frequencies. Checks on the ability of climate prediction models to simulate temporal scaling behavior represent stringent performance tests on the models. We here estimate temporal power-law exponents ("Hurst exponents'') for the global atmospheric circulation of the stratosphere and troposphere during the 20th century. We show that current generation climate models generally simulate the spatial distribution of the Hurst exponents well. We then use simulations with different climate forcings to explain the Hurst exponent distribution and to account for discrepancies in scaling behavior between different observational products. We conclude that characterization of temporal power-law behavior provides a valuable tool for cross-validating low-frequency variability in various datasets, for elucidating the physical mechanisms underlying this variability, and for statistical testing of trends and periodicities in climate time series. Citation: Vyushin, D. I., P. J. Kushner, and J. Mayer (2009), On the origins of temporal power-law behavior in the global atmospheric circulation, Geophys. Res. Lett., 36, L14706, doi: 10.1029/2009GL038771.
引用
收藏
页数:5
相关论文
共 25 条
[1]   The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations [J].
Anderson, JL ;
Balaji, V ;
Broccoli, AJ ;
Cooke, WF ;
Delworth, TL ;
Dixon, KW ;
Donner, LJ ;
Dunne, KA ;
Freidenreich, SM ;
Garner, ST ;
Gudgel, RG ;
Gordon, CT ;
Held, IM ;
Hemler, RS ;
Horowitz, LW ;
Klein, SA ;
Knutson, TR ;
Kushner, PJ ;
Langenhost, AR ;
Lau, NC ;
Liang, Z ;
Malyshev, SL ;
Milly, PCD ;
Nath, MJ ;
Ploshay, JJ ;
Ramaswamy, V ;
Schwarzkopf, MD ;
Shevliakova, E ;
Sirutis, JJ ;
Soden, BJ ;
Stern, WF ;
Thompson, LA ;
Wilson, RJ ;
Wittenberg, AT ;
Wyman, BL .
JOURNAL OF CLIMATE, 2004, 17 (24) :4641-4673
[2]   Can climate trends be calculated from reanalysis data? [J].
Bengtsson, L ;
Hagemann, S ;
Hodges, KI .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2004, 109 (D11) :D111111-8
[3]   Influence of a discontinuity on the spectral and fractal analysis of one-dimensional data [J].
Berton, RPH .
NONLINEAR PROCESSES IN GEOPHYSICS, 2004, 11 (5-6) :659-682
[4]   Long time memory in global warming simulations [J].
Blender, R ;
Fraedrich, K .
GEOPHYSICAL RESEARCH LETTERS, 2003, 30 (14) :CLM7-1
[5]   Scaling of atmosphere and ocean temperature correlations in observations and climate models [J].
Fraedrich, K ;
Blender, R .
PHYSICAL REVIEW LETTERS, 2003, 90 (10) :4
[6]   Global climate models violate scaling of the observed atmospheric variability [J].
Govindan, RB ;
Vyushin, D ;
Bunde, A ;
Brenner, S ;
Havlin, S ;
Schellnhuber, HJ .
PHYSICAL REVIEW LETTERS, 2002, 89 (02)
[7]   Can local linear stochastic theory explain sea surface temperature and salinity variability? [J].
Hall, A ;
Manabe, S .
CLIMATE DYNAMICS, 1997, 13 (03) :167-180
[8]   STOCHASTIC CLIMATE MODELS .1. THEORY [J].
HASSELMANN, K .
TELLUS, 1976, 28 (06) :473-485
[9]   Links between annual, Milankovitch and continuum temperature variability [J].
Huybers, P ;
Curry, W .
NATURE, 2006, 441 (7091) :329-332
[10]   Detecting long-range correlations with detrended fluctuation analysis [J].
Kantelhardt, JW ;
Koscielny-Bunde, E ;
Rego, HHA ;
Havlin, S ;
Bunde, A .
PHYSICA A, 2001, 295 (3-4) :441-454