The impacts of anthropogenic land use and land cover (LULC) changes on the spatiotemporal distribution of precipitation in megacities have been highlighted in studies on urban climate change. In this study, we conducted a quantitative analysis of urban growth on the impact on precipitation in Shanghai, China. We considered four periods of LULC data in 1979, 1990, 2000 and 2010, in addition to the long-term (1979–2010) trend of daily precipitation. The results indicate that the trend in precipitation exhibit different characteristics for urban (Ur), outskirt of urban (OUr) and outer suburb (OS) regions. Most Ur regions had an upward trend in annual and extreme precipitation during 1979–2010, while annual precipitation for the OUr and OS regions exhibited a decreasing trend. From 1979 to 2010, the areas of fastest expansion were located in the OUr region. The OS region, far away from the central area, had a relatively lower rate of change. In addition, OUr regions with rapid LULC changes exhibited higher increasing trends in annual and daily extreme precipitation, which is critical for the identification of frequent precipitation areas and the reliable projection of further changes.

As global warming continues to intensify, the relationship between diurnal temperature range (DTR) and vegetation productivity continues to change over time. However, the impact of DTR changes on vegetation activities remains uncertain. Thus, further study about how DTR changes affect the physiological activities of plants is also urgently needed. In this study, we employed copula function theory to analyze the impact of DTR on Normalized Difference Vegetation Index (NDVI) values during the spring, summer, and autumn seasons from 1982 to 2014 for various land types in the Inner Mongolia Plain (IMP), China. The results showed that the relationship between DTR and NDVI in the IMP was characterized by correlation at the upper tail and asymptotical independence at the lower tail. This demonstrated that the DTR had little effect on NDVI when they reached their minimum value. However, it has a significant impact on NDVI at its maximum values. This study provides valuable insight into the dynamic impact of monthly DTR on different land use types under climate change.