On nonstationarity and antipersistency in global temperature series

Kärner, Olavi

doi:10.1029/2001jd002024

Cited by 31 publications

(34 citation statements)

References 37 publications

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“…An obvious scale break (i.e a change in empirically fitted H value) for various surface air temperature series has been detected between 10 and 30 days (provisionally 10 < Λ < 30) [8]. Recently, a similar scale break interval has been found also for the total solar irradiance at the top of the atmosphere (TOA) and the global mean tropospheric temperature time series [11]. The region τ < Λ is not of interest for the present study.…”

Section: Introductionmentioning

confidence: 80%

“…The latter directly reveals a leading role of correlations between the increments. The exponent is estimated on the basis of an updated version which is also about 3 years longer than that used in [11]. The updated data enables one to analyze also hemispheric and zonal mean anomaly series in addition to the global ones.…”

Section: Introductionmentioning

confidence: 99%

“…Brought to you by | MIT Libraries Authenticated Download Date | 5/13/18 3:53 AM ([8], [9], [10], [11]. They differ in accuracies [7] and can cause a remarkable bias in the results.…”

Section: Introductionmentioning

confidence: 99%

“…Mainly, the variability has been studied on the basis of monthly data (e.g [8], [16], [17], [18], [19]). The current study is a sequel to our earlier work [11]. Some modifications have been introduced: Firstly, H is estimated using the structure function.…”

Section: Introductionmentioning

confidence: 99%

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Some examples of negative feedback in the Earth climate system

Kärner

2005

Open Physics

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Temporal variability of daily time series for total solar irradiance at the top of the atmosphere, the Microwave Sounding Unit (MSU) based global, hemispherical and zonal average temperature for the lower troposphere and stratosphere together with 5 surface air temperature data, measured at various meteorological stations have been studied by means of the structure function. From the growth rate of the structure function in the time interval between 32 and 4096 days it follows that the variability of the series represents an anti-persistent (AP) behavior. This property in turn shows a domination of negative feedback in the physical system generating the lower tropospheric temperature variability. Distribution of the increments over various ranges and correlations between them are calculated in order to determine the quantitative characteristics describing temporal variability.

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Section: Introductionmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

“…Brought to you by | MIT Libraries Authenticated Download Date | 5/13/18 3:53 AM ([8], [9], [10], [11]. They differ in accuracies [7] and can cause a remarkable bias in the results.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Some examples of negative feedback in the Earth climate system

Kärner

2005

Open Physics

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“…Negative climate feedbacks have been documented in literature. Kärner (2002) carried out a statistical analysis for satellite-based global daily tropospheric (6-8 km depth) and stratospheric (15-19 km depth) temperature anomalies, from 1979 to 2001. He found antipersistency in the daily increments of the tropospheric temperature for scales longer than two months, pointing at a negative feedback governing the tropospheric variability.…”

Section: Multiplicative Noise: Stochastic Parameterization Of L↑mentioning

confidence: 99%

Analysis of the simulated global temperature using a simple energy balance stochastic model

Moreles

Martínez‐López

2016

ATM

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Este trabajo presenta un estudio de la respuesta de la variabilidad simulada de la temperatura global a parametrizaciones estocásticas aditivas y multiplicativas de flujos de calor, junto con una descripción de la variabilidad de largo plazo en términos de procesos autorregresivos simples. Para simular la temperatura global de la Tierra se utilizó un modelo climático de balance de energía promediado globalmente, acoplado a un modelo oceánico termodinámico. Se encontró que procesos autorregresivos simples explican la variabilidad de la temperatura en el caso de parametrizaciones aditivas; sin embargo, en el caso de parametrizaciones multiplicativas, la descripción de la variabilidad de la temperatura involucraría procesos autorregresivos de orden superior, lo cual sugiere la presencia de mecanismos complejos de retroefecto originados por el forzamiento multiplicativo. Asimismo, se encontró que las parametrizaciones multiplicativas produjeron una estructura compleja que emula de manera cercana procesos climáticos observados. Finalmente, se propone un nuevo enfoque para describir la estabilidad de un sistema estocástico general unidimensional en estado estacionario, a través de su función potencial. A partir de una expresión analítica de la función potencial se profundizó en la descripción de un sistema estocástico. ABSTRACTThis work presents a study of the response of the simulated global temperature variability to additive and multiplicative stochastic parameterizations of heat fluxes, along with a description of the long-term variability in terms of simple autoregressive processes. The Earth's global temperature was simulated using a globally averaged energy balance climate model coupled to a thermodynamic ocean model. It was found that simple autoregressive processes explain the temperature variability in the case of additive parameterizations; whereas in the case of multiplicative parameterizations, the description of the temperature variability would involve higher order autoregressive processes, suggesting the presence of complex feedback mechanisms originated by the multiplicative forcing. Also, it was found that multiplicative parameterizations produced a rich structure that emulates closely observed climate processes. Finally, a new approach to describe the stability in the steady state of a general one-dimensional stochastic system, through its potential function, was proposed. From an analytical expression of the potential function, further insight into the description of a stochastic system was provided.

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Simple statistical structure in time series for daily air flow characteristics

Post

Kärner

2007

Environmetrics

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SUMMARYThe structure function is used for quantifying of non-stationarity in time series for certain daily air flow characteristics (DAFC). The National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis 30 year (1968-97) dataset given over 5• × 10• latitude longitude grid is used to calculate the DAFC series for the Baltic Sea region. The quantification on the basis of the Hurst exponent H enables us to discriminate between the strong synoptic scale non-stationarity and a mild large-scale one. Presented examples show that the change of H is accompanied by a change of the distribution for the series' increments. Long-range increments for various DAFC appear to be approximately normally distributed with approximately constant variance independent of the increment length over a remarkably wide range. The property might be useful in describing a long-range variability of the air flow characteristics.

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On nonstationarity and antipersistency in global temperature series

Cited by 31 publications

References 37 publications

Some examples of negative feedback in the Earth climate system

Some examples of negative feedback in the Earth climate system

Analysis of the simulated global temperature using a simple energy balance stochastic model

Simple statistical structure in time series for daily air flow characteristics

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