Climate change, the Hurst phenomenon, and hydrological statistics

Koutsoyiannis, Demetris

doi:10.1623/hysj.48.1.3.43481

Cited by 373 publications

(295 citation statements)

References 19 publications

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“…This is manifested by the Hurst behaviour of hydroclimatic processes, herein referred to as Hurst-Kolmogorov (HK) climate, after Hurst (1951) who studied it in natural processes and Kolmogorov (1940) who devised its stochastic representation as a mathematical tool for the research of turbulence (see also Shiryaev, 1989;Koutsoyiannis & Cohn, 2008). Koutsoyiannis & Montanari, as well as Koutsoyiannis (2003Koutsoyiannis ( , 2005Koutsoyiannis ( , 2006a and have provided empirical evidence and theoretical support of the HK behaviour of climate, and have shown that climatic variability is very much higher in HK processes than in purely random or Markov-type processes. Specifically, in a HK climate, the uncertainty at a climatic (30-year) scale proves to be only slightly lower than that at the annual one , in contrast to the classical approach, which yields significant reduction as we proceed from the annual to the climatic scale and justifies different perception of climatic and finer scale views of processes.…”

Section: Justification Of the Methodologymentioning

confidence: 95%

“…These excursions demonstrate the large variability at long time scales, which is an essential element for our testing framework: indeed, it is vital to evaluate whether the modelled series are able to reproduce the observed over-year "trends", which would be a powerful indicator of their potential to generate realistic climatic behaviours in their future projections. A well-recognized metric of long-term fluctuations is the Hurst coefficient (H), which is estimated for the annual time scale and longer (Koutsoyiannis, 2003). All records but two have Hurst coefficients larger than 0.50, i.e.…”

Section: Long-term Variability Of Historical Time Seriesmentioning

confidence: 99%

See 1 more Smart Citation

On the credibility of climate predictions

Koutsoyiannis

Efstratiadis

Mamassis

et al. 2008

Hydrological Sciences Journal

140

100

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Geographically distributed predictions of future climate, obtained through climate models, are widely used in hydrology and many other disciplines, typically without assessing their reliability. Here we compare the output of various models to temperature and precipitation observations from eight stations with long (over 100 years) records from around the globe. The results show that models perform poorly, even at a climatic (30-year) scale. Thus local model projections cannot be credible, whereas a common argument that models can perform better at larger spatial scales is unsupported.Key words climate models; general circulation models; falsifiability; climate change; Hurst-Kolmogorov climate De la crédibilité des prévisions climatiquesRésumé Des prévisions distribuées dans l'espace du climat futur, obtenues à l'aide de modèles climatiques, sont largement utilisées en hydrologie et dans de nombreuses autres disciplines, en général sans évaluation de leur confiance. Nous comparons ici les sorties de plusieurs modèles aux observations de température et de précipitation de huit stations réparties sur la planète qui disposent de longues chroniques (plus de 100 ans). Les résultats montrent que les modèles ont de faibles performances, y compris à une échelle climatique (30 ans). Les projections locales des modélisations ne peuvent donc pas être crédibles, alors que l'argument courant selon lequel les modèles ont de meilleures performances à des échelles spatiales plus larges n'est pas vérifié.

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Section: Justification Of the Methodologymentioning

confidence: 95%

Section: Long-term Variability Of Historical Time Seriesmentioning

confidence: 99%

On the credibility of climate predictions

Koutsoyiannis

Efstratiadis

Mamassis

et al. 2008

Hydrological Sciences Journal

140

100

View full text Add to dashboard Cite

show abstract

“…The idea was introduced more than 50 years ago by Hurst [1951], and has been debated ever since [Mandelbrot and Wallis, 1968;Klemeš, 1974;Potter and Walker, 1981;Hosking, 1984;Loucks et al, 1981;Koutsoyiannis, 2000Koutsoyiannis, , 2003]. Hurst's fundamental finding has neither been discredited nor universally embraced, but persuasive arguments have been presented (for discussion and additional references, see Koutsoyiannis [2003]). Given the LTP-like patterns we see in longer HC records, however, such as the periods of multidecadal drought that occurred during the past millennium and our planet's geologic history of ice ages and sea level changes, it might be prudent to assume that HC processes could possess LTP.…”

Section: Discussionmentioning

confidence: 99%

Nature's style: Naturally trendy

Cohn

Lins

2005

Geophysical Research Letters

339

310

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Hydroclimatological time series often exhibit trends. While trend magnitude can be determined with little ambiguity, the corresponding statistical significance, sometimes cited to bolster scientific and political argument, is less certain because significance depends critically on the null hypothesis which in turn reflects subjective notions about what one expects to see. We consider statistical trend tests of hydroclimatological data in the presence of long‐term persistence (LTP). Monte Carlo experiments employing FARIMA models indicate that trend tests which fail to consider LTP greatly overstate the statistical significance of observed trends when LTP is present. A new test is presented that avoids this problem. From a practical standpoint, however, it may be preferable to acknowledge that the concept of statistical significance is meaningless when discussing poorly understood systems.

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“…Another approach that might be useful for planning proactive plans is the use of Hurst-Kolmogorov (HK) stochastic dynamics (Hurst, 1975;Montanari et al, 1997;Koutsoyiannis, 2003Koutsoyiannis, , 2006Cohn and Lins, 2005;Fraedrich and Blender, 2003;Blender and Fraedrich, 2006, and references therein). Results here presented, in fact, are consistent with HK dynamics since the SPI time series appear to be not stationary and characterized by multi-scale fluctuations.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Observed drought and wetness trends in Europe: an update

Bordi

Fraedrich

Sutera

2009

Hydrol. Earth Syst. Sci.

131

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Abstract. Linear and nonlinear trends of drought and wetness are analysed in terms of the gridded Standardized Precipitation Index (SPI) determined from monthly precipitation in Europe (NCEP/NCAR). In characterizing the meteorological and hydrological aspects, the index is computed on a seasonal and on a bi-annual time scale. Two datasets are compared: one from 1949 to 1997 and the other one includes the update of the last decade (to February 2009). The following results are noted: (i) time series of drought and wetness area coverage (number of grid points above/below the severity threshold) show a remarkable linear trend until about the end of the last century, which is reversed in the last (update) decade. This recent trend reversal is an indication of a nonlinear trend, which is more pronounced on the hydrological time scale. (ii) A nonlinear trend analysis is performed based on the time series of the principal component (PC) associated to the first spatial SPI-eigenvector after embedding it in a time delay coordinate system using a sliding window of 70 months (singular spectrum analysis). Nonlinearity appears as a clear feature on the hydrological time scale. (iii) The first spatial EOF-patterns of the shorter and the longer (updated) SPI time series fields show similar structure. An inspection of the SPI time behaviour at selected grid points illustrates the spatial variability of the detected trends.

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Climate change, the Hurst phenomenon, and hydrological statistics

Cited by 373 publications

References 19 publications

On the credibility of climate predictions

On the credibility of climate predictions

Nature's style: Naturally trendy

Observed drought and wetness trends in Europe: an update

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