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Since the Industrial Revolution, greenhouse gas emissions have caused global temperatures to rise gradually. The Paris Agreement aims to limit the global mean surface temperature increase to less than 2.0 °C relative to pre-industrial levels. China's land area accounts for ∼7% of the global land (65Ñ59S) area, and the arid area of China accounts for 12.41% of the total global arid area. Therefore, the degree of aridification/humidification in China is of great significance to climate change in China and the world. This paper evaluates the regional changes of drylands and humid lands in China based on the 1.5 °C and 2.0 °C increase targets for global mean surface warming(GMSW). We find a suitable warming target for China's climate from the perspective of aridification. The results show the following: 1) If the global mean surface temperature rises by 1.5 °C and 2.0 °C above pre-industrial levels, the mean surface temperature in China will increase by 2.0 °C and 2.8 °C, respectively. 2) Under the two GMSW targets, the degree of drought in some extremely arid areas in China was projected to decrease, which means that these areas may gradually be suitable for human habitation. 3) Regardless of which global surface temperature target is maintained, the humid lands in China will bear greater risks from warming than the drylands. Under these circumstances, the 1.5 °Ctargetwill lead to better outcomes for China than the 2.0 °C target. • The degree of drought in some extremely arid areas in China has decreased under global warming targets. • Humid lands in China will bear greater warming risks than the dry lands. • Global warming limited within 1.5 °C target for will lead to better outcomes for China than the 2.0 °C. [ABSTRACT FROM AUTHOR]

Near-surface temperature records show that China warmed by about 0.8 °C from 1950 to 2010. However, there exists an ongoing debate about whether this warming might have been partially due to urbanization bias. In fact, homogenization approaches may be inefficient in densely populated provinces that have experienced a significant urban development since the 1940s. This paper aims to complement previous research on the topic by showing that an alternative approach based on the analysis of the divergence between the minimum (Tmin) and maximum (Tmax) near-surface temperature records since the 1940s could be useful to clarify the issue because urban heat island (UHI) effects stress the warming of nocturnal temperatures more than the diurnal ones. Then, the significance of the divergence observed in the data could be evaluated against the expectations produced by the CMIP5 general circulation model simulations. From 1945–1954 to 2005–2014, on average and over China, these models predict that Tmin had to warm 0.19 ± 0.06 °C more than Tmax. However, during the same period, the climatic records show that Tmin warmed 0.83 ± 0.15 °C more than Tmax. A similar analysis demonstrates that the effect is more pronounced during the colder months from November–April than during the warmer ones from May to October. A comparison versus China urbanization records demonstrates that the regions characterized by a large Tmin-Tmax divergence are also the most densely populated ones, such as north-east China, that have experienced a diffused and fast urbanization since the 1940s. The results are significant and may indicate the presence of a substantial uncorrected urbanization bias in the Chinese climate records. Under the hypothesis that Tmax is a better metric for studying climatic changes than Tmean or Tmin, we conclude that about 50% of the recorded warming of China since the 1940s could be due to uncorrected urbanization bias. In addition, we also find that the Tmax record from May to October over China shows the 1940s and the 2000s equally warm, in contrast to the 1 °C warming predicted by the CMIP5 models. • Mean surface temperature in China has warmed by 0.8 °C since 1950. • Atmospheric boundary layer physics predicts higher UHI warming during night. • The divergence between Tmin and Tmax is used to detect urbanization biases. • The China regions with the strongest Tmin-Tmax divergence are also the most populated. • Thus, the temperature warming in China is partially due to UHI biases. [ABSTRACT FROM AUTHOR]