Distribution of most probable temperature of daily average temperature records in China and the slowing down of warming trend

Zhong-Hua, Qian; Feng, Guolin; Gong, Zhiqiang

doi:10.7498/aps.59.7498

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…[11−13] However, this hypothesis could bring many defects into practical data analysis. Therefore using the Box-Cox transformation to improve the normality of data, we obtained the probability density function of abnormal temperature distribution by theoretical derivation, i.e., a skewed distribution function p(x), [14] p…”

Section: Methods and Datamentioning

confidence: 99%

Characteristics of the spatiotemporal distribution of daily extreme temperature events in China: Minimum temperature records in different climate states against the background of the most probable temperature

Qian¹,

Jia²,

Feng³

et al. 2012

Chinese Phys. B

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Based on the skewed function, the most probable temperature is defined and the spatiotemporal distributions of the frequencies and strengths of extreme temperature events in different climate states over China are investigated, where the climate states are referred to as State I, State II and State III, i.e., the daily minimum temperature records of 1961–1990, 1971–2000, and 1981–2009. The results show that in space the frequency of high temperature events in summer decreases clearly in the lower and middle reaches of the Yellow River in State I and that low temperature events decrease in northern China in State II. In the present state, the frequency of high temperature events increases significantly in most areas over China except the north east, while the frequency of low temperature events decreases mainly in north China and the regions between the Yangtze River and the Yellow River. The distributions of frequencies and strengths of extreme temperature events are consistent in space. The analysis of time evolution of extreme events shows that the occurrence of high temperature events become higher with the change in state, while that of low temperature events decreases. High temperature events are becoming stronger as well and deserve to be paid special attention.

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Section: Methods and Datamentioning

confidence: 99%

Characteristics of the spatiotemporal distribution of daily extreme temperature events in China: Minimum temperature records in different climate states against the background of the most probable temperature

Qian¹,

Jia²,

Feng³

et al. 2012

Chinese Phys. B

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Detecting abrupt change on the basis of skewness: numerical tests and applications

Wan

Jiang

et al. 2012

Intl Journal of Climatology

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An abrupt change occasionally occurs when the dynamical system suddenly shifts from one stable state to a new state, which can take place in many complex systems, such as climate, ecosystem, social system, and so on. In order to detect abrupt change, this article presents a novel method -sliding transformation parameter (STP) on the basis of skewness change and the Box-Cox transformation. Tests on model time series and 1000 simulated daily precipitation data show the ability of the present method to identify and detect abrupt change of probability density function. The applications of STP in daily precipitation data show that there is an abrupt climate change between 1979 and 1980 in the selected observational stations, which is almost the same with the result obtained by approximate entropy (ApEn). Furthermore, it is found that the sample sizes of sliding windows have some influence on the Lambda parameter of the Box-Cox transformation, but it does not significantly affect the varying trend of the parameter and the identification of the change point in annual or interannual time scale. Comparing STP with the coefficient of skewness and kurtosis, ApEn, and some statistics approaches (e.g. percentiles and annual maxima), we find that the performance of the present method is much better than that of these methods.

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The characteristics of clusters of weather and extreme climate events in China during the past 50 years

杨萍¹,

侯威²,

封国林³

2012

Chinese Phys. B

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The pick-up algorithm by the k-th order cluster for the closest distance is used in the fields of weather and climactic events, and the technical terms clustered index and high clustered region are defined to investigate their temporal and spatial distribution characteristics in China during the past 50 years. The results show that the contribution of extreme high-temperature event clusters changed in the period from the 1960s to the 1970s, and its strength was enhanced. On the other hand, the decreasing trend in the clusters of low-temperature extremes can be taken as a signal for warmer winters to follow in the decadal time scale. Torrential rain and heavy rainfall clusters have both been lessened in the past 50 years, and have different cluster characteristics because of their definitions. Regions with high clustered indexes are concentrated in southern China. The spatial evolution of the heavy rainfall clusters reveals that clustered heavy rainfall has played an important role in the rain-belt pattern over China during the last 50 years.

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Distribution of most probable temperature of daily average temperature records in China and the slowing down of warming trend

Cited by 5 publications

References 22 publications

Characteristics of the spatiotemporal distribution of daily extreme temperature events in China: Minimum temperature records in different climate states against the background of the most probable temperature

Characteristics of the spatiotemporal distribution of daily extreme temperature events in China: Minimum temperature records in different climate states against the background of the most probable temperature

Detecting abrupt change on the basis of skewness: numerical tests and applications

The characteristics of clusters of weather and extreme climate events in China during the past 50 years

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