Based on seven sets of reanalysis data, this paper analyzed the spatio-temporal characteristics of global temperature change and the temperature change of major countries from 1981 to 2019 by using climate tendency rate and spatial interpolation. Key scientific method to reveal the spatial difference of global temperature change and toĪchieve a common global climate change. The determination of temperature changes in major countries since the 1980s is a This paper takes the view that there was no global warming hiatus over the period 1998–2019.
Since the 1980s, there have been 4, 34 and 68 countries with levels of global warming above 2.0☌, 1.5☌ and 1.0☌, respectively, accounting statistically for 2.740%, 23.288% and 46.575% of the countries examined. 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. 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☌/10a. Greenland, Ukraine, and Russia had the highest rates of increase in the mean annual temperature in particular, Greenland experienced a rate of 0.654☌/10a. The global land surface air temperature displayed an increasing trend, with more than 80% of the land surface showing a significant increase. 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 mean annual land air temperature in the northern and southern hemispheres varied at rates of 0.362☌/10a and 0.147☌/10a, respectively, displaying significantly increasing trends with cumulative increases of 0.828☌ and 0.874☌, respectively. The results revealed that the global land air temperature from the 1980s to 2019 varied at a rate of 0.320☌/10a, and exhibited a significantly increasing trend, with a cumulative increase of 0.835☌. 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 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. JRA-55 is slightly better in detecting the extremely cold years, while NCEP/NCAR R1 is slightly worse in biases but performs well in high-temperature years reproduction. ERA5 and 20CRv3 perform better than the other reanalysis datasets, with relatively small deviation, their warming trends are closer to the observation results, and the appearance of extreme temperature years are also more consistent with the observed, and CERA-20C is the next. The results reflect that the above reanalysis datasets have reasonable representativeness of global temperature change. Based on the newly released version of China Merged global Surface Temperature data set, Interim version (CMST-Interim), the performance of 5 reanalysis datasets (ERA5, NCEP/NCAR R1, JRA-55, CERA-20C, and 20CRv3), covering more than 50 years, is compared in terms of long-term variation bias, warming trend and the consistency of the extreme temperature years from the period 1958 to 2010. However, because of the limitations of data assimilation and model performance in the reanalysis datasets, it is essential to evaluate the quality of the reanalysis datasets.
Reanalysis data is widely used to investigate long-term surface temperature changes due to insufficient spatial coverage of observational data.
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