Abstract
Near surface wind speed has significant impacts on ecological environment change and climate change. Based on the CN05.1 observation data (a gridded monthly dataset with the resolution of 0.25 latitude by 0.25 longitude over China), this study evaluated the ability of 25 Global Climate Models (GCMs) from Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating the wind speed in the Arid Region of Northwest China (ARNC) during 1971–2014. Then, the temporal and spatial variations in the surface wind speed of ARNC in the 21st century were projected under four Shared Socioeconomic Pathways (SSPs), SSP1-2.6, SSP2-4.5, SSP3-7.0, and SP5-8.5. The results reveal that the preferred-model ensemble (PME) can fairly evaluate the temporal and spatial distribution of surface wind speed with the temporal and spatial correlation coefficients exceeding 0.5 at the significance level of p = 0.05 when compared to the 25 single models and their ensemble mean. After deviation correction, the PME can reproduce the distribution characteristics of high wind speed in the east and low in the west, high in mountainous areas, and low in basins. Unfortunately, no models or model ensemble can accurately reproduce the decreasing magnitude of observed wind speed. In the 21st century, the surface wind speed in the ARNC is projected to increase under SSP1-2.6 scenario but will decrease remarkably under the other three scenarios. Moreover, the higher the emission scenarios, the more significant the surface wind speed decreases. Spatially, the wind speed will increase significantly in the west and southeast of Xinjiang, decrease in the north of Xinjiang and the south of Tarim Basin. What’s more, under the four scenarios, the surface wind speed will decrease in spring, summer and autumn, especially in summer, and increase in winter. The wind speed will decrease significantly in the north of Tianshan Mountains in summer, decrease significantly in the north of Xinjiang and the southern edge of Tarim Basin in spring and autumn, and increase in fluctuation with high values in Tianshan Mountains in winter.
Highlights
As an influencing factor of ecological environment change and climate change, surface wind speed has a significant impact on the wind energy industry, surface evapotranspiration, hydrological cycle and wind-related natural disasters [1,2,3,4,5]
The above six models are selected as the preferred models and formed the preferred-model ensemble (PME)
This study evaluated the performance of 25 Coupled Model Intercomparison Project phase 6 (CMIP6) models and 2 model ensembles (MME and PME) in simulating the surface wind speed in the Arid Region of Northwest China (ARNC) based on the CN05.1 observation data
Summary
As an influencing factor of ecological environment change and climate change, surface wind speed has a significant impact on the wind energy industry, surface evapotranspiration, hydrological cycle and wind-related natural disasters (such as sandstorm, tornados, and typhoons) [1,2,3,4,5]. Sensitive response to climate system change, and frequent sand and dust events, it is one of the areas richest in wind energy resources in China and has excellent potential for wind energy development. It has become one of the hotspot areas of wind resources research [14,15]. Many studies show that [16,17,18], over the past half-century, the change of surface wind speed in the ARNC is consistent with that of the whole of China and even the northern hemisphere, showing a decreasing trend with a larger magnitude than the whole China. The complexity of the terrain in the ARNC determines the regional differences in the temporal and spatial distribution of surface wind energy resources
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