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Quantifying the urbanization effect on trends in climate extremes is important both for detection and attribution studies and for human adaptation; however, a fundamental problem is how to accurately estimate a trend and its statistical significance, especially for non-Gaussian and serially dependent data. In this paper, the choice of trend estimation and significance testing method is suggested as important for these kinds of studies, as illustrated by quantifying the urbanization effect on trends in seven hot-extreme indices for the megacity of Shanghai during 1961-2013. Both linear and nonlinear trend estimation methods were used. The trends and corresponding statistical significances were estimated by taking into account potential non-Gaussian and serial dependence in the extreme indices. A new method based on adaptive surrogate data is proposed to test the statistical significance of the ensemble empirical mode decomposition (EEMD) nonlinear trend. The urbanization contribution was found to be approximately 34 % (43 %) for the trend in the non-Gaussian distributed heat wave index based on nonparametric linear trend (EEMD nonlinear trend) estimation. For some of the other six hot-extreme indices analyzed, the urbanization contributions estimated based on linear and nonlinear trends varied greatly, with as much as a twofold difference between them. For the linear trend estimation itself, the ordinary least squares fit can give a substantially biased estimation of the urbanization contribution for some of the non-Gaussian extreme indices. [ABSTRACT FROM AUTHOR]

We investigate a record-breaking heat wave in southern China (SC) and explore its association with the South China Sea (SCS) summer monsoon (SCSSM), using station observations and various reanalysis products. This heat wave event started in mid-May 2018 and persisted more than 15 days, when the maximum air temperature anomaly exceeded 6 °C. Meanwhile, the onset of the SCSSM was extremely late in 2018, primarily due to the intrusion of easterly winds over the SCS. We show that the anomalous easterlies over the SCS associated with the delayed SCSSM could block the moisture transport from the tropical oceans to SC, which led to decreased rainfall, increased surface radiation, and elevated probability of heat wave in SC during May 2018. Further analysis reveals that both SC heat waves and SCSSM were significantly affected by the Pacific subtropical high (PSH). The westward extension of the PSH can hinder the establishment of SCSSM via inducing easterly anomalies over the SCS, which reduces SC rainfall and results in a drier surface condition. Moreover, the westward displacement of the PSH may cause anomalously high pressures, descending air motions, and divergent winds over SC, which triggers above-normal air temperatures that are conducive to the occurrences of SC heat waves. This study also underlines the importance of Eurasian planetary wave trains in bridging the upstream climate variability and the changes in PSH during boreal spring, which could be used to improve the intra-seasonal predictions of SC heat wave and SCSSM onset. [ABSTRACT FROM AUTHOR]

With the consideration of spatial extension of heatwave events, two kind of regional heatwaves using absolute and relative thresholds, namely RHWs-A and RHWs-R, are investigated during 1959-2013. The temperature data is derived from the daily maximum temperatures (DMTs) of 587 stations in China. Totally 298 RHWs-A and 374 RHWs-R are identified during the past 55 years, and both of them are growing more frequent since the mid-1980s. By utilizing the cluster analysis, several typical spatial distributions of RHWs-A/RHWs-R are obtained. For RHWs-A, there are three clusters covering the southeastern, northwestern China and the lower reaches of Yangtze River, of which the southeastern cluster groups the most heatwaves. For RHWs-R, there are seven clusters distributed throughout the whole regions of China. The clusters in the northwestern and northeastern China are more stable than others for both RHWs-A and RHWs-R, and the northern clusters are of larger intensity than that of the southern ones. All RHWs-A/RHWs-R are accompanied by the anomalous high systems along with the reduced soil moisture. The southern clusters are controlled by Northwestern Pacific subtropical high (WPSH), and the northern ones are influenced by the mid-latitude high systems. The influences of atmospheric circulations and soil moisture on regional heatwaves are further demonstrated by two case analyses of the severe RHW-A in 2003 and the RHW-R in 2013. [ABSTRACT FROM AUTHOR]