Climatic Jump: A Hypothesis in Climate Diagnosis

Yamamoto, Ryo; Iwashima, Tatsuya; Kazadi, Sanga-Ngoie; Hoshiai, Makoto

doi:10.2151/jmsj1965.63.6_1157

Cited by 56 publications

(32 citation statements)

References 9 publications

(8 reference statements)

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“…Considering that in some cases the MK test failed to yield step change point for a time series (Yamamoto et al, 1985), the MTT and Yamamoto methods were further employed in the same data sets of PCBs and OCPs at the four arctic monitoring sites to verify the MK test results and to increase the confidence of detected step change points by the MK test. Figures …”

Section: Step Change Points Identified By Mtt and Yamamoto Methodsmentioning

confidence: 99%

“…In climate and hydrological studies, three statistical methods have been widely used to identify abrupt climate change points. These are the Mann-Kendall (MK) test (Mann, 1945;Kendall, 1955), the moving t test (MTT) technique (Moraes, et al, 1998), and the Yamamoto method (Yamamoto et al, 1985).…”

Section: Statistical Test For Pop Trends and Step Changementioning

confidence: 99%

“…The Yamamoto method is somewhat similar to the MTT approach, defined by a signal-to-noise ratio (S/N, Yamamoto et al, 1985):…”

Section: Statistical Test For Pop Trends and Step Changementioning

confidence: 99%

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Step changes in persistent organic pollutants over the Arctic and their implications

et al. 2015

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Abstract. While some persistent organic pollutants (POPs) have been declining globally due to their worldwide ban since the 1980s, the declining trends of many of these toxic chemicals become less significant and in some cases their ambient air concentrations, e.g., polychlorinated biphenyls (PCBs), showed observable increase during the 2000s, disagreeing with their declining global emissions and environmental degradation. As part of the efforts to assess the influences of environmental factors on the long-term trend of POPs in the Arctic, step change points in the time series of ambient POP atmospheric concentrations collected from four arctic monitoring sites were examined using various statistical techniques. Results showed that the step change points of these POP data varied in different years and at different sites. Most step change points were found in 2001-2002 and 2007-2008. In particular, the step change points of many PCBs for 2007-2008 were coincident with the lowest arctic sea ice concentration occurring during the 2000s. The perturbations of air concentration and water-air exchange fluxes of several selected POPs averaged over the Arctic, simulated by a POP mass balance perturbation model, switched from negative to positive during the early 2000s, indicating a tendency for reversal of POPs from deposition to volatilization which coincides with a positive to negative reversal of arctic sea ice extent anomalies from 2001. Perturbed ice-air exchange flux of PCB 28 and 153 showed an increasing trend and a negative to positive reversal in 2007, the year with the lowest arctic sea ice concentration. On the other hand, perturbed ice-air exchange flux of α-hexachlorocyclohexane decreased over the period of 1995 to 2012, likely owing to its lower Henry's law constant which indicates its relatively lower tendency for volatilization from ice to air.

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Section: Step Change Points Identified By Mtt and Yamamoto Methodsmentioning

confidence: 99%

Section: Statistical Test For Pop Trends and Step Changementioning

confidence: 99%

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Step changes in persistent organic pollutants over the Arctic and their implications

et al. 2015

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“…The abrupt climate change is described as the system transitioning from one stable state to another (Thom, 1972;Tong et al, 2014), i.e., the system swings between different states (Lorenz, 1976;Charney and DeVore, 1979), and it also has been verified in the climate system (Dai et al, 2012;Baker and Charlson, 1990;Wang et al, 2012;Alley et al, 2003;Xiao et al, 2011). Detection methods (Wan and Zhang, 2008;Fu and Wang, 1992;Yamamoto et al, 1986) have been greatly developed. Since the abrupt change theory was developed, increasing numbers of research (Goossens and Berger, 1986;Feng et al, 2008Feng et al, , 2011Stefan, 2002) studies have been launched.…”

Section: Introductionmentioning

confidence: 99%

A novel method for analyzing the process of abrupt climate change

Yan

Feng

Hou

2015

Nonlin. Processes Geophys.

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Abstract.A climate system which is transitioning from one state to another is known as an abrupt climate change. Most of the recent studies regarding abrupt climate change have focused on the changes occurring before and after the abrupt change point, while little attention has been given to the "transition process" which occurs when the system breaks away from the original state to a new state. In this study, a novel method for analyzing the process of abrupt climate change was presented. By using the mathematical model based on the logistic model, the process of the abrupt change could be analyzed and divided into different phases which include start moment, end moment, stable state, and unstable transition state. Meanwhile, the method was confirmed to be effective by testing in a study of Pacific decadal oscillation (PDO) time sequence, and the results of this study specify that this abrupt change process (ACP) of PDO has a relationship with global warming.

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“…The detection results of traditional methods for detecting abrupt change, such as Moving t-test, Cramer method, Mann-Kendall test (Mann, 1945;Kendall and Charles, 1975) and Yamamoto method (Yamamoto et al, 1985), all highly depend on the length of subseries, namely analysed timescales (He et al, 2008). However, the timeinstant of abrupt dynamic change does not have certain relations with specific timescales.…”

Section: Introductionmentioning

confidence: 99%

A new method for abrupt dynamic change detection of correlated time series

He¹,

Feng²,

Wu³

et al. 2011

Intl Journal of Climatology

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On the basis of detrended fluctuation analysis (DFA), a new method, moving cut data-DFA (MC-DFA), was presented to detect abrupt dynamic change in correlated time series. The numerical tests show the capability of the presented method to detect abrupt change time-instants in model time series generated by Logistic map. Moving DFA (MDFA) and approximate entropy (ApEn) can provide some information such as a single time-instant of abrupt dynamic change, but both of them cannot exactly detect all of the abrupt change regions. Some traditional methods, such as moving t-test, Cramer method, Mann-Kendall test and Yamamoto method, even cannot provide any information of abrupt dynamic change in these model time series. Meanwhile, results showed that windows sizes and strong noise have some less effect on the MC-DFA results. In summary, MC-DFA provides a reliable measure to detect the abrupt dynamic change in correlated time series, and perfectively make up the deficiencies of MDFA and ApEn. The applications in daily surface air pressure records further verify the validity of the present method.

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Climatic Jump: A Hypothesis in Climate Diagnosis

Cited by 56 publications

References 9 publications

Step changes in persistent organic pollutants over the Arctic and their implications

Step changes in persistent organic pollutants over the Arctic and their implications

A novel method for analyzing the process of abrupt climate change

A new method for abrupt dynamic change detection of correlated time series

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