Monthly variation and correlation analysis of global temperature and wind resources under climate change

Abstract

Renewable energy is widely used as an alternative source of energy, and climate change has a significant impact on its variation and harnessing. This study conducted a monthly scale analysis of global temperature and wind-speed variations and their correlations using Theil–Sen’s median linear regression and Mann-Kendall test from 1989 to 2021. The results revealed that the global temperature averagely increased by 0.34 °C/10 a from 1989 to 2021, showing clearly increasing trends in most months but with significant differentiation in each month. The regions of East Europe Plain, Central Siberia, Central Asia, and Greenland showed the most significant increasing temperature trends ranging from 0.17 to 0.49 °C/10 a. Additionally, the regions in the East Europe Plain, Siberia, and North America showed distinctly decreasing temperature trends ranging from 0.27 to 0.51 °C/10 a. The global average wind speed changed slightly, with slopes of −0.026, −0.014, and 0.019 m/(s⋅10 a) for eastward, northward, and synthesis wind, respectively. However, the decreasing trends were relatively evident in regions across central Europe via the south of the Eastern European Plain to the north of Central Asia with slopes ranging from −0.13 to −0.3 m/(s⋅10 a). These monthly variations in eastward, northward, and synthesis wind speeds showed significant correlations with temperature, and the correlation coefficients (CCs) differed significantly for each month. For positive CCs higher than 0.34 and negative CCs lower than −0.35 (p < 0.05), the land coverage areas reached 72.3 million km2, accounting for 48% of the global land area. In addition, the synthesis wind speed showed significant positive and negative CCs with temperature, especially from November to March of the following year. The highly positive CCs of global temperature and synthesis wind speed are primarily distributed across land areas from Europe to Siberia, North America, and North Africa in the Northern Hemisphere. The areas with high negative CCs are distributed across South America, South Africa, and Australia in the Southern Hemisphere. Climate change has a substantial impact on wind-speed variation, which should be considered during wind source harnessing. Monthly variation analysis of global temperature and wind speed and their correlation could provide key scientific support for climate change adaptation and wind resource harnessing.