It is well known that urban areas are typically hotter than the surrounding (vegetated) rural areas. However, the contribution of urbanization to the trends of extreme temperature events such as heat waves (HWs) is less understood. Using a homogenized meteorological dataset drawn from nearly 2,000 stations in China, we find that urban and rural areas have different HW trends and the urban-rural contrast of HW trends varies across climate regimes. In wet climates, the increasing trends of HWs in urban areas are greater than those in rural areas, suggesting a positive contribution of urbanization to HW trends. In arid regions, the urbanization contribution to HW trends is smaller and even negative. The stronger urbanization contribution to HW trends in wet climates is linked to the smaller variability of urban heat island intensity. This study highlights the important role of local hydroclimate in modulating the urbanization contribution to extreme temperatures.Plain Language Summary Extreme temperature events commonly known as heat waves (HWs) have profound impacts on human health. While it is well known that urban temperatures are usually higher than their rural counterparts (i.e., the urban heat island effect), whether and how the urbanization contribution to HW trends varies across different climate regimes over a large domain remains unclear. In this study, we explore the urban-rural contrast of HW characteristics over mainland China. Our analysis shows that while both urban and rural HWs are becoming more frequent, longer-lasting, and stronger in most parts of China, their trends are different. Interestingly, we find that the local hydroclimate modulates the variability of daily UHI intensity, thus affecting the contribution of urbanization to the frequency and magnitude of HWs. The stronger contrasts between urban and rural HW trends in wet climates are related to the larger increases in UHI intensity, but more importantly, the smaller variability of UHI intensity. As a result, the eastern, wet climate part of China, with the densest population and highest urbanization, will face severe heat risks in the future due to the combined effects of urbanization and global climate change.

Determining the timing (i.e. onset and withdrawal) of monsoon season precisely and objectively is an important yet difficult task. Conventional methods mainly define the monsoon timing as the date when the selected atmospheric variables (e.g. rainfall and wind) exceed an arbitrary threshold. These methods present little explicit justification and are subjective and sensitive to the fluctuation of the selected series. In this study, we propose an objective method to determine the onset and withdrawal of the South China Sea summer monsoon (SCSSM) using the cumulative low-level zonal wind. Our proposed approach provides an easy, objective, and applicable method that is recommended for the detection of the timing of monsoon season. On the basis of the proposed definition, the SCSSM onset and withdrawal are determined, and their accompanying processes are also examined in this paper. Both onset and withdrawal of SCSSM exhibit strong variability, and the El Niño-Southern Oscillation plays an important role. Via the modification of the western North Pacific subtropical high, a preceding El Niño (La Niña) event can delay (advance) the monsoon onset and advance (delay) the monsoon withdrawal.

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This study examines the spatio‐temporal changes of heat risk in South China and the possible effects of urbanization using a dynamic method for classifying urban and rural sites based on time‐varying DMSP‐OLS night‐time light images. Ten different indicators are analysed, which include daily means and consecutive heat wave (HW) measures at 86 stations in Guangdong Province from 1971 to 2014. Results show that these heat risk indicators have been intensifying across the study area, and the intensifying trends are more profound in urbanized and populated areas (e.g., the Pearl River Delta) than less urbanized inland areas. In addition, the mean of daily maximum, minimum, and mean temperatures in urban (rural) areas increased by 0.35 (0.24), 0.21 (0.11), and 0.23 (0.13) °C per decade, and urbanization contributes to 31, 48, and 43% of the total trends, respectively. We also estimate that the urbanization effects on (contributions to) the increasing hot days and warm nights are 2.52 (36%) and 4.21 days per decade (53%). Moreover, urbanization induces an additional increase in the frequency and participating days of HW by 0.44 events (49%) and 3.96 days (51%) per decade, respectively.

This study examines the impacts of El Niño–Southern Oscillation on the frequency, duration, magnitude, and timing of heat waves (HWs) in the Indochina Peninsula during 1979–2017. It is found that preceding winter El Niño (La Niña) events prominently amplify (weaken) the HWs in most areas of Indochina by increasing (decreasing) the occurrence of HW events and the number of participating HW days, prolonging (shortening) the duration, and elevating (reducing) the amplitude of such events. These influences are even stronger for severe HWs (i.e., longest and hottest events) than for regular ones with average duration and intensity. Further examinations show that the atmospheric circulation during El Niño events is featured by a weakened Walker circulation that is characterized by an anomalously sinking motion over the western North Pacific (WNP) and Asia and a rising motion over the eastern tropical Pacific. The anomalous subsidence over WNP/Asia is accompanied by suppressed precipitation, and the WNP anticyclone is also enhanced and moves more westward. These patterns are in accordance with the atmospheric controls of HWs in Indochina, thereby favoring the occurrence and sustenance of HW events in the peninsula. La Niña event causes the mostly opposite changes of El Niño, thus inhibiting the HW activities in Indochina.