A novel method for detecting abrupt dynamic change based on the changing Hurst exponent of spatial images

He, Wenping; Liu, Qunqun; Gu, Bin; Zhao, Shanshan

doi:10.1007/s00382-016-2983-0

Cited by 13 publications

(21 citation statements)

References 46 publications

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“…The preflood season, which is the most important rainy season over South China, indicates the period prior to the East Asian summer monsoon onset. During the preflood season (April 1 to June 30), there are three major branches of water vapour transport over South China that have decisive influences on precipitation (Zhou and Yu, ; Li et al ., ; Li et al ., ; Chu et al ., ; He et al ., ). The robust southwesterly water vapour transport occurs during the Indian summer monsoon, which carries moisture from the Bay of Bengal, the Arabian Sea and the tropical Indian Ocean (Xue et al ., ; Fan, ; Fan et al ., ).…”

Section: Introductionmentioning

confidence: 99%

The roles of moisture transports in intraseasonal precipitation during the preflood season over South China

Chu

Wang

Feng

2019

Intl Journal of Climatology

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The roles of moisture sources and transport in intraseasonal precipitation variabilities during the preflood season over South China are complex and different. In this paper, ERA‐Interim reanalysis data that were collected four times daily from 1979 to 2017 are used to analyse the variation and influence of moisture transport in intraseasonal precipitation during the preflood season over South China. Using the Hybrid Single‐Particle Lagrangian Integrated Trajectory model, fixed atmospheric moisture sources are defined: land area source (LD source), Indian Ocean source (IO source), Pacific Ocean source (PO source), South China Sea source (SCS source), and South China source (SC source). Sea source moisture transport accounts for more than 75% of the total precipitation during the preflood season, which is the most important moisture source in South China. For April, southeasterly moisture transport, which includes PO source and SCS source moisture transports, is the major moisture transport over South China. Then, the IO source and SCS source precipitation increased significantly during May. During June, the IO source precipitation accounted for 43.75% of the total precipitation, thus dominating precipitation over South China. In addition, there is a significant difference in the interdecadal variation in the preflood season precipitation before and after the Indian summer monsoon onset. Before the Indian summer monsoon onset, the land‐sea thermal contrast decreased, which led to a significant interdecadal reduction in the IO source, PO source, and SCS source moisture transports. After the Indian summer monsoon onset, the increase in IO source moisture transport is the primary cause of the interdecadal increase in precipitation over South China.

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Section: Introductionmentioning

confidence: 99%

The roles of moisture transports in intraseasonal precipitation during the preflood season over South China

Chu

Wang

Feng

2019

Intl Journal of Climatology

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“…Gu et al (2006) proposed a two-dimensional DFA (TD-DFA) method and used it to extract long-range correlation signals from spatial images. In view of the climate system as a dynamical system with spatiotemporal evolution characteristics and an interacting nature, He et al (2016) present a new method for abrupt dynamic change detection, namely, moving TD-DFA (MTD-DFA). The performance of the MTD-DFA has been tested based on the coupled Henon map.…”

Section: Introductionmentioning

confidence: 99%

Detecting abrupt dynamic change based on changes in the fractal properties of spatial images

Liu

et al. 2016

Theor Appl Climatol

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Many abrupt climate change events often cannot be detected timely by conventional abrupt detection methods until a few years after these events have occurred. The reason for this lag in detection is that abundant and long-term observational data are required for accurate abrupt change detection by these methods, especially for the detection of a regime shift. So, these methods cannot help us understand and forecast the evolution of the climate system in a timely manner. Obviously, spatial images, generated by a coupled spatiotemporal dynamical model, contain more information about a dynamic system than a single time series, and we find that spatial images show the fractal properties. The fractal properties of spatial images can be quantitatively characterized by the Hurst exponent, which can be estimated by twodimensional detrended fluctuation analysis (TD-DFA). Based on this, TD-DFA is used to detect an abrupt dynamic change of a coupled spatiotemporal model. The results show that the TD-DFA method can effectively detect abrupt parameter changes in the coupled model by monitoring the changing in the fractal properties of spatial images. The present method provides a new way for abrupt dynamic change detection, which can achieve timely and efficient abrupt change detection results.

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“…Previous studies have examined precipitation variations on interannual and decadal time scales in the NA based on different approaches (He et al, ; He et al, ). Huang et al .…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have examined precipitation variations on interannual and decadal time scales in the NA based on different approaches (He et al, 2008;He et al, 2016). Huang et al (2012) suggested that the summer precipitation decreased significantly over Northeast and North China, around the late-1990.…”

Section: Introductionmentioning

confidence: 99%

Assessment and correction of BCC_CSM's performance in capturing leading modes of summer precipitation over North Asia

Gong

Dogar

Qiao

et al. 2017

Intl Journal of Climatology

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This article examines the ability of Beijing Climate Center Climate System Model (BCC_CSM) in demonstrating the prediction accuracy and the leading modes of the summer precipitation over North Asia (NA). A dynamic‐statistic combined approach for improving the prediction accuracy and the prediction of the leading modes of the summer precipitation over NA is proposed. Our results show that the BCC_CSM can capture part of the spatial anomaly features of the first two leading modes of NA summer precipitation. Moreover, BCC_CSM regains relationships such that the first and second mode of the empirical orthogonal function (EOF1 and EOF2) of NA summer precipitation, respectively, corresponds to the development of the El Niño and La Niña conditions in the tropical East Pacific. Nevertheless, BCC_CSM exhibits limited prediction skill over most part of NA and presents a deficiency in reproducing the EOF1's and EOF2's spatial pattern over central NA and EOF2's interannual variability. This can be attributed as the possible reasons why the model is unable to capture the correct relationships among the basic climate elements over the central NA, lacks in its ability to reproduce a consistent zonal atmospheric pattern over NA, and has bias in predicting the relevant Sea Surface Temperature (SST) modes over the tropical Pacific and Indian Ocean regions. Based on the proposed dynamic‐statistic combined correction approach, compared with the leading modes of BCC_CSM's original prediction, anomaly correlation coefficients of corrected EOF1/EOF2 with the tropical Indian Ocean SST are improved from 0.18/0.36 to 0.51/0.62. Hence, the proposed correction approach suggests that the BCC_CSM's prediction skill for the summer precipitation prediction over NA and its ability to capture the dominant modes could be certainly improved by choosing proper historical analogue information.

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A novel method for detecting abrupt dynamic change based on the changing Hurst exponent of spatial images

Cited by 13 publications

References 46 publications

The roles of moisture transports in intraseasonal precipitation during the preflood season over South China

The roles of moisture transports in intraseasonal precipitation during the preflood season over South China

Detecting abrupt dynamic change based on changes in the fractal properties of spatial images

Assessment and correction of BCC_CSM's performance in capturing leading modes of summer precipitation over North Asia

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