Search

This paper reviews urban heat (UrHT) challenges following the SBAR (situation, background, assessment and recommendation) framework. The results indicate that heatwaves become more frequent, lasting and intense, especially after 1990s. Above 1960s level, heatwaves across China doubled in both magnitude and frequency by 2018. Jianghuai and Southern China underwent the largest magnitude and most widespread increases. Under 1.5 °C warming limit, the average heatwave days and duration across China will increase by 10.8 days and 3.9 days. Drought–heatwave co–occurrence is increasingly frequent at 7–11%/decade (from 1961 to 2018) and the co–occurrence leads to more intense heatwaves. UHIs are a common issue for almost all Chinese cities and UHIs have been aggravating annually. Daytime UHIs peak in summer, indicating the synergies with heatwaves. The synergies are prominent in southeastern cities for strong summer daytime UHIs in eastern cities and intense heatwaves in southern regions. UrHTs have not been recognised and there are no dedicated/mandatory plans. Mega–challenges of climate change, rapid urbanisation, carbon– and labour–intensive economic growth and demographic changes can potentially lock China into UrHT challenges. Addressing UrHT challenges is urgent in China not only for environmental, ecosystem, social and health consequences, but also for economic impacts relevant to labour, capital, and goods or services. Efforts are suggested in technical improvement, policy formulation, social participation, economic investment and co-benefit approach recognition. Overall, this paper provides a comprehensive understanding of heat–related challenges in China and can guide the creation of cool cities and communities in practice. [Display omitted] • Almost all cities in China are under the impacts of urban heat islands. • Heatwaves and urban heat islands can synergise, especially in Southeastern China. • China has not well recognised urban heat challenges and no dedicated plan. • UrHT affects economic productivity by affecting outputs, labour, capital and goods. • UrHT may drive population migrating out the extreme heat areas. [ABSTRACT FROM AUTHOR]

Abstract Vegetation-atmosphere interaction is thought to have significant impacts on modulating regional climate. The main purpose of this paper is to reveal the impact of vegetation change on regional climate simulation over Eastern China. Therefore, we have performed three 30-year simulations from 1982 to 2011 with the WRF model coupled with the Noah land surface model as follows: a control experiment with climatology green vegetation fraction (GVF) (CTL), a sensitive experiment with WRF default climatology GVF (CLMV), and a sensitive experiment with dynamic vegetation (DYNV). The climatology difference between the CTL and CLMV experiment points out that during 1982–2011 over Eastern China, the increase of vegetation causes the decrease of temperature; on the other hand, the increase of temperature often corresponds to the reduction of vegetation. In the meantime, the increase/decrease in GVF is quite consistent with the simulated increase/decrease in precipitation, which is caused by both circulations and water vapor distributions at lower levels. The difference in the temperature trend between the CTL and DYNV experiment is almost opposite to that between the DYNV and GVF trend, which means that the decreased/increased vegetation will increase/decrease the surface air temperature. However, the trend of precipitation variation shows no clear relation with that of GVF. In response to GVF change, the results show that in the vegetation-climate feedback the moisture feedback is dominant over the radiation and momentum feedback. Significant decrease in GVF and LAI is detected across the East China, which leads to the decrease in the latent heat flux and increase in the sensible heat flux. For extremes and heat waves, it is shown that DYNV leads to better stimulation on the maximum of daily maximum temperature (TXx), warm spell days (WSDI), heat wave days (HWNY) and the averaged heat wave duration (HWDU) than CTL does over most of the Southeast China, although it may introduce some new biases in the Eastern coastal regions as well as the Northeastern China. Highlights • Dynamic green vegetation fraction (GVF) data was used for simulation. • Studied the effect of vegetation variation on climate extremes. • The results are also compared with actual observations. [ABSTRACT FROM AUTHOR]