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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