The study of temperature change in major countries of the world since the 1980s is a key scientific issue given that such data give insights into the spatial differences of global temperature change and can assist in combating climate change. Based on the reanalysis of seven widely accepted datasets, which include trends in climate change and spatial interpolation of the land air temperature data, the changes in the temperature of major countries from 1981 to 2019 and the spatial-temporal characteristics of global temperature change have been assessed. The results revealed that the global land air temperature from the 1980s to 2019 varied at a rate of 0.320°C/10a, and exhibited a significantly increasing trend, with a cumulative increase of 0.835°C. The mean annual land air temperature in the northern and southern hemispheres varied at rates of 0.362°C/10a and 0.147°C/10a, respectively, displaying significantly increasing trends with cumulative increases of 0.828°C and 0.874°C, respectively. Across the globe, the rates of change of the mean annual temperature were higher at high latitudes than at middle and low latitudes, with the highest rates of change occurring in regions at latitudes of 80°-90°N, followed by regions from 70°-80°N, then from 60°-70°N. The global land surface air temperature displayed an increasing trend, with more than 80% of the land surface showing a significant increase. Greenland, Ukraine, and Russia had the highest rates of increase in the mean annual temperature; in particular, Greenland experienced a rate of 0.654°C/10a. The regions with the lowest rates of increase of mean annual temperature were mainly in New Zealand and the equatorial regions of South America, Southeast Asia, and Southern Africa, where the rates were <0.15°C/10a. Overall, 136 countries (93%), out of the 146 countries surveyed, exhibited a significant warming, while 10 countries (6.849%) exhibited no significant change in temperature, of which 3 exhibited a downward trend. Since the 1980s, there have been 4, 34 and 68 countries with levels of global warming above 2.0°C, 1.5°C and 1.0°C, respectively, accounting statistically for

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We conducted three pairs of 21‐year (1980–2000) experiments using the Weather Research and Forecast (WRF) model. The paired two experiment members were identical, except for the underlying land use/cover data, which were from the early 1980s and 2000 (hereafter, EXP1980 and EXP2000), respectivley. The differences in EXP1980 and EXP2000 were primarily induced by the land use/cover change (LUCC) from the early 1980s to 2000. To minimize the effects of WRF model uncertainties, the ensemble mean of three couples was applied. We found that the modifications of LUCC on summer precipitation over eastern China exhibited inter‐annual variability rather than kept fixed through 1980 to 2000. Due to the LUCC, the precipitation in eastern China may be decreased in 1981, 1984, 1986, 1988, 1989, and 1998 (hereafter, LR years) while increased in 1983, 1985, 1993, 1994, 1995, and 1999 (hereafter, MR years). Due to large discrepancy of large‐scale circulation background between MR years and LR years, there are different modifications by the LUCC on surface energy budget and therefore also on temperature, air pressure, water vapour supply and, eventually, precipitation. In the MR years, the LUCC induced increased evapotranspiration (i.e., latent heat) and decreased sensible heat over the middle and north partitions of eastern China; hence, there was a cooling effect. This cooling effect led to a decline in surface air pressure, thereby intensifying the ocean‐land pressure gradient; as a result, ocean‐to‐land movement of water vapour increased. Eventually, this led to increased precipitation. In the LR years, the LUCC induced significantly more sensible heat and slightly more latent heat over the north partition of eastern China, resulting in a warming effect. Then, the modifications to the surface air pressure and ocean‐land pressure gradient, as well as the water vapour flux, were reversed to those of the MR years, eventually leading to decreased precipitation.

In the context of global warming, the frequency and intensity of extreme weather and climate events are increasing. However, the impact of these changes that is directly felt by people is the day-to-day temperature change. Extreme temperature changes between neighboring days (ETCNs) carry substantial disease risks and socioeconomic impacts. Evaluative studies of ETCN events with global circulation models (GCMs) remain unknown in China. This study quantitatively evaluates the performances of 36 GCMs and the multi-model ensemble (MME) of the Coupled Model Intercomparison Project 6 (CMIP6) in simulating the extreme cooling (EC) and extreme warming (EW) events of two consecutive days as defined by relative thresholds. Moreover, we select the optimal models in different regions at the seasonal and annual scales in China, providing theoretical support for the frequency projection and modeling improvement of ETCN events. The results showed that from 1981 to 2013, the annual average EW events and EC events in China showed increasing but not statistically significant trends, and the frequency of EW events was higher than that of EC events. EW events mostly occurred in spring, while EC events mostly occurred in autumn.Additionally, the performances of the CMIP6 models are quite different between EC and EW events.The simulations of EC events are generally more reliable than those of EW events, and the models can also capture the annual cycle of EC events well. Furthermore, the CMIP6 models overestimate the frequencies of EW and EC events but underestimate the frequency of EC events in autumn. The CMIP6 models exhibit poor performance in simulating the trend of and interannual variability in ETCN events and can only simulate the decreasing trend in autumn. Finally, according to the overall ranking of the CMIP6 models, GFDL-ESSM4 and EC-Earth3-Veg-LR achieve the best performance in simulating EW and EC events, respectively. The CMIP6 MME only effectively improved the capabilities of the models to simulate winter EC events in the WNW region. In terms of the trend of and interannual variability in ETCN events, individual models exhibited better performances than the CMIP6 ensemble.

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