Assessment of CMIP6 Model Performance for Wind Speed in China

Xiaolin Liu,Yuyang Guo,Lijun Zhao,Bo Wang,Zongpeng Song,Ju Hu,Shuanglong Jin

doi:10.3389/fclim.2021.735988

Abstract

As the major renewable energy, wind can greatly reduce carbon emissions. Following the “carbon neutral” strategy, wind power could help to achieve the realization of energy transformation and green development. Based on ERA5 reanalysis data and the multi-ensemble historical and scenario simulations of the Coupled Model Intercomparison Project Phase 6 (CMIP6), a variety of statistical analyses are used to evaluate the performance of CMIP6 simulating the wind speed in China. The conclusions are as follows: spatial patterns of the nine CMIP6 models are similar with ERA5, but BCC-CSM2-MR and MRI-ESM2-0 highly overestimate the wind speed in northwest China. CESM2-WACCM, NorESM2-MM, and HadGEM3-GC31-MM behave better than the other six CMIP6 models in four specific regions are chosen for detailed study. CESM2-WACCM, NorESM2-MM, and HadGEM3-GC31-MM tend to simulate a larger wind speed than ERA5 except the yearly averaged wind speed in region II and region IV. CESM2-WACCM and NorESM2-MM simulate a large monthly mean wind speed, but the value is relatively close with ERA5 in the summer. HadGEM3-GC31-MM overestimates wind speed in region I and region II from April to October, but gets closer with ERA during winter. CESM2-WACCM, NorESM2-MM, and HadGEM3-GC31-MM simulate an increasing trend in Tibetan Plateau and Xinjiang in the next 100 years, while NorESM2-MM projects rising wind speed in the eastern part of Inner Mongolia, and HadGEM3-GC31-MM simulates increasing wind speed in the northeast and central China. The future wind speed in three models is projected to decline in region I, and the value of HadGEM3-GC31-MM is much larger. In region II, wind speed simulated by three models is projected to decrease, but the wind speed from HadGEM3-GC31-MM in region III and modeled wind speed in region IV from NorESM2-MM would climb with the slope equal to 0.0001 and 0.0012, respectively. This study indicates that the CMIP6 models have certain limitations to perform realistic wind changes, but CMIP6 could provide available reference for the projection of wind in specific areas.

Highlights

Renewable energy, energy efficiency, and electrification are three drivers of deep de-carbonization, and developing renewable energy is an important measure for global climate governance and achieving the goal of carbon neutrality
Spatial patterns of the nine Coupled Model Intercomparison Project Phase 6 (CMIP6) models are similar with ERA5 shown in Figure 1, but the wind speed in north China is larger and the wind speed in the Sichuan Basin is much smaller
Spatial patterns of the nine CMIP6 models are similar with ERA5, but BCC-CSM2-MR and MRI-ESM2-0 highly overestimate the wind speed in northwest China

Summary

Introduction

Energy efficiency, and electrification are three drivers of deep de-carbonization, and developing renewable energy is an important measure for global climate governance and achieving the goal of carbon neutrality. A significant decreasing trend of wind speed is reported in numerous studies. Near-surface wind speed over the globe is dropping at 5–15% since 1960, which is called as global stilling (Pryor et al, 2009). There was a decreasing wind speed trend with −0.005 m/s/a in the USA (Hobbins, 2004). The declining wind speed trend across the Australia has reached 0.009 m/s/a since 2006 (McVicar et al, 2008). A significant declining wind speed of −0.017 m/s/a is showed in western Canada (Tuller, 2004; Wan et al, 2010). The downward change of wind speed in Italy is −0.013 m/s/a, while the falling trend is −0.026 m/s/a before 1975 and decreased to −0.002 m/s/s after 1975 (Pirazzoli and Tomasin, 2003)

Methods

Results

Conclusion