The Hurst phenomenon and climate (solicited)

D. Koutsoyiannis, and T.A. Cohn, The Hurst phenomenon and climate (solicited), European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 11804, doi:10.13140/RG.2.2.13303.01447, European Geosciences Union, 2008.



Hurst's observation in 1950 that Nile streamflows exhibit persistent excursions from their mean value has plagued, entertained and humbled hydrologists for over half a century. The "Hurst phenomenon," sometimes denoted "long-term persistence (LTP)", has subsequently been recognized in countless natural and artificial processes. While LTP initially presented an analytical challenge, the concern was mostly academic: In many practical situations, calibration datasets were insufficiently long to reveal LTP; planning horizons were sufficiently short that other sources of variability and uncertainty dominated the effect of LTP; and the Hurst phenomenon seemed relevant, if at all, only to very large water projects. However, things have changed: Statistical tools and stochastic theory have improved, more data are available, and research now suggests that LTP is nearly ubiquitous when dealing with complex natural systems. Moreover, many of the problems we face today occur over the large spatial and temporal scales where LTP tends to emerge as a dominant component of natural processes evolving in continuous time or space. Under such circumstances, LTP must be taken into account when conducting statistical analyses and predictions. In particular, physical arguments and data indicate that LTP is likely a fundamental characteristic of global climate processes, and thus, when studying climate data, it would seem prudent to employ statistical methods that are robust to the presence of LTP.

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The title of the presentation changed to "Hurst-Kolmogorov pragmaticity and climate" (see full text)

Our works that reference this work:

1. D. Koutsoyiannis, A. Efstratiadis, N. Mamassis, and A. Christofides, On the credibility of climate predictions, Hydrological Sciences Journal, 53 (4), 671–684, doi:10.1623/hysj.53.4.671, 2008.
2. D. Koutsoyiannis, Older and modern considerations in the design and management of reservoirs, dams and hydropower plants (Solicited), 1st Hellenic Conference on Large Dams, Larisa, doi:10.13140/RG.2.1.3213.5922, Hellenic Commission on Large Dams, Technical Chamber of Greece, 2008.
3. D. Koutsoyiannis, C. Makropoulos, A. Langousis, S. Baki, A. Efstratiadis, A. Christofides, G. Karavokiros, and N. Mamassis, Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability, Hydrology and Earth System Sciences, 13, 247–257, doi:10.5194/hess-13-247-2009, 2009.
4. D. Koutsoyiannis, A. Montanari, H. F. Lins, and T.A. Cohn, Climate, hydrology and freshwater: towards an interactive incorporation of hydrological experience into climate research—DISCUSSION of “The implications of projected climate change for freshwater resources and their management”, Hydrological Sciences Journal, 54 (2), 394–405, doi:10.1623/hysj.54.2.394, 2009.
5. D. Koutsoyiannis, A. Paschalis, and N. Theodoratos, Two-dimensional Hurst-Kolmogorov process and its application to rainfall fields, Journal of Hydrology, 398 (1-2), 91–100, 2011.
6. Y. Markonis, and D. Koutsoyiannis, Climatic variability over time scales spanning nine orders of magnitude: Connecting Milankovitch cycles with Hurst–Kolmogorov dynamics, Surveys in Geophysics, 34 (2), 181–207, doi:10.1007/s10712-012-9208-9, 2013.
7. C. Pappas, S.M. Papalexiou, and D. Koutsoyiannis, A quick gap-filling of missing hydrometeorological data, Journal of Geophysical Research-Atmospheres, 119 (15), 9290–9300, doi:10.1002/2014JD021633, 2014.

Works that cite this document: View on Google Scholar or ResearchGate

Other works that reference this work (this list might be obsolete):

1. #Stockwell, D. R. B., and A. Cox, Structural break models of climatic regime-shifts: claims and forecasts, arXiv:0907.1650, 2009.
2. Bakker, A. M. R., and B. J. J. M. van den Hurk, Estimation of persistence and trends in geostrophic wind speed for the assessment of wind energy yields in Northwest Europe, Climate Dynamics, 39 (3-4), 767-782, 2012.

Tagged under: Hurst-Kolmogorov dynamics, Course bibliography: Stochastic methods, Climate stochastics