A Multivariate Frequency-Domain Approach to Long-Lead Climatic Forecasting

Balaji Rajagopalan Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York

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Michael E. Mann Department of Geosciences, University of Massachusetts—Amherst, Amherst, Massachusetts

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Upmanu Lall Department of Civil and Environmental Engineering and Utah Water Research Laboratory, Utah State University, Logan, Utah

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Abstract

Guided by the increasing awareness and detectability of spatiotemporally organized climatic variability at interannual and longer timescales, the authors motivate the paradigm of a climate system that exhibits excitations of quasi-oscillatory eigenmodes with characteristic timescales and large-scale spatial patterns of coherence. It is assumed that any such modes are superposed on a spatially and temporally autocorrelated stochastic noise background. Under such a paradigm, a previously described (Mann and Park) multivariate frequency-domain approach is promoted as a particularly effective means of spatiotemporal signal identification and reconstruction, and an associated forecasting methodology is introduced. This combined signal detection/forecasting scheme exhibits significantly greater skill than conventional forecasting approaches in the context of a synthetic example consistent with the adopted paradigm. The example application demonstrates statistically significant skill at 5–10-yr lead times. Applications to operational long-range climatic forecasting are motivated and discussed.

Corresponding author address: Dr. Balaji Rajagopalan, 103 Oceanography, Lamont-Doherty Earth Observatory, Columbia University, P.O. Box 1000, Rt. 9W, Palisades, NY 10964-8000.

Email: rbala@rosie.ldgo.columbia.edu

Abstract

Guided by the increasing awareness and detectability of spatiotemporally organized climatic variability at interannual and longer timescales, the authors motivate the paradigm of a climate system that exhibits excitations of quasi-oscillatory eigenmodes with characteristic timescales and large-scale spatial patterns of coherence. It is assumed that any such modes are superposed on a spatially and temporally autocorrelated stochastic noise background. Under such a paradigm, a previously described (Mann and Park) multivariate frequency-domain approach is promoted as a particularly effective means of spatiotemporal signal identification and reconstruction, and an associated forecasting methodology is introduced. This combined signal detection/forecasting scheme exhibits significantly greater skill than conventional forecasting approaches in the context of a synthetic example consistent with the adopted paradigm. The example application demonstrates statistically significant skill at 5–10-yr lead times. Applications to operational long-range climatic forecasting are motivated and discussed.

Corresponding author address: Dr. Balaji Rajagopalan, 103 Oceanography, Lamont-Doherty Earth Observatory, Columbia University, P.O. Box 1000, Rt. 9W, Palisades, NY 10964-8000.

Email: rbala@rosie.ldgo.columbia.edu

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  • Barnston, A. G., 1994: Linear statistical short-term climate predictive skill in the Northern Hemisphere. J. Climate,7, 1513–1564.

    • Crossref
    • Export Citation
  • ——, and Coauthors, 1994: Long-lead seasonal forecasts—Where do we stand? Bull. Amer. Meteor. Soc.,75, 2097–2109.

    • Crossref
    • Export Citation
  • Cane, M., S. E. Zebiak, and S. C. Dolan, 1986: Experimental forecasts of El Niño. Nature,321, 827–832.

    • Crossref
    • Export Citation
  • Delworth, T., S. Manabe, and R. J. Stouffer, 1993: Interdecadal variations of the thermohaline circulation in a coupled ocean–atmosphere model. J. Climate,6, 1993–2011.

    • Crossref
    • Export Citation
  • Dettinger, M. D., M. Ghil, and C. K. Kepenne, 1995: Interannual and interdecadal variability in United States surface-air temperatures, 1910–1987. Climate Change,31, 33–66.

    • Crossref
    • Export Citation
  • Ghil, M., and R. Vautard, 1991: Interdecadal oscillations and the warming trend in global temperature time series. Nature,350, 324–327.

    • Crossref
    • Export Citation
  • Keppenne, C. L., and M. Ghil, 1992: Adaptive filtering and prediction of the Southern Oscillation index. J. Geophys. Res.,97, 20449–20454.

    • Crossref
    • Export Citation
  • ——, and U. Lall, 1996: Complex singular spectrum analysis and multivariate adaptive regression splines applied to forecasting the Southern Oscillation. Experimental Long Lead Forecast Bulletin, A. G. Barnston, Ed., NOAA/CPC, 54–56.

  • Kushnir, Y., 1994: Interdecadal variations in the North Atlantic sea surface temperature and associated atmospheric conditions. J. Climate,7, 141–157.

    • Crossref
    • Export Citation
  • Lall, U., and M. E. Mann, 1995: The Great Salt Lake: A barometer of low-frequency climatic variability. Water Resour. Res.,31, 2503–2515.

    • Crossref
    • Export Citation
  • ——, T. Sangoyomi, and H. D. I. Abarabanel, 1996: Nonlinear dynamics of the Great Salt Lake: Nonparametric short term forecasting. Water Resour. Res.,32, 975–985.

    • Crossref
    • Export Citation
  • Latif, M., and T. P. Barnett, 1994: Causes of decadal variability over the North Pacific and North America. Science,266, 634–637.

    • Crossref
    • Export Citation
  • Madden, R. A., 1981: A quantitative approach to long-range prediction. J. Geophys. Res.,86(C10), 9817–9825.

  • ——, D. J. Shea, G. W. Branstator, J. J. Tribbia, and R. O. Weber, 1993: The effects of imperfect spatial and temporal sampling on estimates of the global mean temperature: Experiments with model data. J. Climate,6, 1057–1066.

    • Crossref
    • Export Citation
  • Mann, M. E., and J. Park, 1993: Spatial correlations of interdecadal variation in global surface temperatures. Geophys. Res. Lett.,20, 1055–1058.

    • Crossref
    • Export Citation
  • ——, and ——, 1994: Global scale modes of surface temperature variability on interannual to century time scales. J. Geophys. Res.,99, 25819–25833.

    • Crossref
    • Export Citation
  • ——, and J. Lees, 1996: Robust estimation of background noise and signal detection in climatic time series. Climate Change,33, 409–445.

    • Crossref
    • Export Citation
  • ——, and J. Park, 1996: Joint spatiotemporal modes of surface temperature and sea level pressure variability in the Northern Hemisphere during the last century. J. Climate,9, 2137–2162.

    • Crossref
    • Export Citation
  • ——, U. Lall, and B. Saltzman, 1995a: Decadal-to-century scale climate variability: Insights into the rise and fall of the Great Salt Lake. Geophys. Res. Lett.,22, 937–940.

    • Crossref
    • Export Citation
  • ——, J. Park, and R. S. Bradley, 1995b: Global interdecadal and century-scale oscillations during the past five centuries. Nature,378, 266–270.

    • Crossref
    • Export Citation
  • Moon, Y., 1995: Large scale atmospheric variability and the Great Salt Lake. Ph.D. dissertation, Utah State University, 140 pp.

  • ——, and U. Lall, 1996: Interannual and interdecadal variability in the Great Salt Lake and selected atmospheric indices. ASCE J. Hydrologic Eng.,1(2), 55–62.

    • Crossref
    • Export Citation
  • Park, J., and K. A. Maasch, 1993: Plio-Pleistocene time evolution of the 100-kyr cycle in marine paleoclimate records. J. Geophys. Res.,92, 12675–12684.

    • Crossref
    • Export Citation
  • ——, and M. E. Mann, 1998: Interannual temperature events and shifts in global temperature: A multiple wavelet correlation approach. Earth Interactions, in press.

  • ——, C. R. Lindberg, and F. L. Vernon III, 1987: Multitaper spectral analysis of high-frequency seismograms. J. Geophys. Res.,92, 12675–12684.

    • Crossref
    • Export Citation
  • Preisendorfer, R. W., 1988: Principal Component Analysis in Meteorology and Oceanography. Elsevier, 425 pp.

  • Saltzman, B., A. Sutera, and A. Evenson, 1981: Structural stochastic stability of a simple autooscillatory climatic feedback system. J. Atmos. Sci.,38, 494–503.

    • Crossref
    • Export Citation
  • Sarda, H., G. Plaut, C. Pires, and R. Vautard, 1996: Statistical and dynamical long-range atmospheric forecasts: Experimental comparison and hybridization. Tellus,48A, 518–537.

    • Crossref
    • Export Citation
  • Schlesinger, M. E., and N. Ramankutty, 1994: An oscillation in the global climate system of period 65–70 years. Nature,367, 723–726.

    • Crossref
    • Export Citation
  • Thomson, D. J., 1982: Spectrum estimation and harmonic analysis. Proc. IEEE,70, 1055–1096.

    • Crossref
    • Export Citation
  • Trenberth, K. E., and J. W. Hurrell, 1994: Decadal atmosphere–ocean variations in the Pacific. Climate Dyn.,9, 303–319.

    • Crossref
    • Export Citation
  • Van den Dool H., and S. Saha, 1990: Frequency dependence in forecast skill. Mon. Wea. Rev.,118, 128–137.

    • Crossref
    • Export Citation
  • Vautard, R., P. Yiou, and M. Ghil, 1992: Singular spectrum analysis:A toolkit for short, noisy and chaotic series. Physica D,58, 95–126.

    • Crossref
    • Export Citation
  • ——, G. Plaut, and C. Pires, 1996: Long-range atmospheric predictability using space–time principal components. Mon. Wea. Rev.,124, 288–307.

    • Crossref
    • Export Citation
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