Statistical physics in meteorology

Ausloos, Marcel

doi:10.1016/j.physa.2004.01.014

Cited by 6 publications

(4 citation statements)

References 62 publications

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“…Recent advances have shown us that we can use scaling arguments to analyse climatic data [1]- [29]. The ongoing discussion focuses on whether we can obtain a correlation between the scaling exponents obtained from these analyses and the geographic location of the weather stations [3,18,30,31].…”

Section: Introductionmentioning

confidence: 99%

“…Climate change is a major concern for everyone, and it is a focus of atmospheric research. The changes in properties of cloud cover influence the radiative feedback from the clouds and become one of the important players that effect the climate in general [29]. Considerable effort has been made to study the timescaling of fluctuations of cloud cover using detrended fluctuation analysis [19]- [22], [24]- [28].…”

Section: Introductionmentioning

confidence: 99%

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Detrended fluctuation analysis as a statistical tool to monitor the climate

Kurnaz

2004

J. Stat. Mech.: Theor. Exp.

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Detrended fluctuation analysis is used to investigate power law relationship between the monthly averages of the maximum daily temperatures for different locations in the western US. On the map created by the power law exponents, we can distinguish different geographical regions with different power law exponents. When the power law exponents obtained from the detrended fluctuation analysis are plotted versus the standard deviation of the temperature fluctuations, we observe different data points belonging to the different climates, hence indicating that by observing the long-time trends in the fluctuations of temperature we can distinguish between different climates.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detrended fluctuation analysis as a statistical tool to monitor the climate

Kurnaz

2004

J. Stat. Mech.: Theor. Exp.

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“…But as the longer timescales are governed by different processes like circulation patterns and global warming, defining long-term correlations becomes more difficult. Recently, scaling arguments have been used to analyze climatic data [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43].…”

Section: Introductionmentioning

confidence: 99%

“…The changes in properties of the cloud cover influence the radiative feedback from the clouds and become one of the important players that effect the climate in general [41]. Considerable effort has been made to study the time scaling of fluctuations of the cloud cover using DFA [31,32,33,34,36,37,38,39,40].…”

Section: Introductionmentioning

confidence: 99%

Climate Prediction through Statistical Methods

Akgun,

Isvan,

Tuter

et al. 2008

Preprint

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Climate change is a reality of today. Paleoclimatic proxies and climate predictions based on coupled atmosphere-ocean general circulation models provide us with temperature data. Using Detrended Fluctuation Analysis, we are investigating the statistical connection between the climate types of the present and these local temperatures. We are relating this issue to some well-known historic climate shifts. Our main result is that the temperature fluctuations with or without a temperature scale attached to them, can be used to classify climates in the absence of other indicators such as pan evaporation and precipitation.

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