Wind is defined as the movement of air parcels in a particular direction. The wind speed detected by meteorological instruments increases or decreases suddenly as a result of the different amounts of kinetic energy carried by each air parcel. Peak wind gusts, defined as the maximum based on running mean wind speeds in a short sampling period, are a sudden increase in wind speed caused by air parcels with high kinetic energies (Huschke, 1959). Gusts are closely related to physical parameters such as the mean wind speed, the boundary layer turbulence, the roughness of the underlying surface and the atmospheric stability (Cheng et al., 2012;Letson et al., 2018;Vickery & Skerlj, 2005). Gust records are also affected by instrument characteristics and sample intervals (Holmes & Ginger, 2012).The World Meteorological Organization (WMO) (2018), has specified the mean wind speed as the average wind speed over 10 min and the gust wind speed as the maximum of 3-s running mean wind speed (WMO, Harper

Abstract. External forcing is the driving force of climate system, which has significant impact on long-term climate changes. Unlike in the Global Climate Models whose external forcing is clearly prescribed, whether or not to use spatial-temporal varying external forcing to force the Regional Climate Models (RCMs) is still lacking evaluations. Here we modify the regional climate model WRF v3.8.1 to include all kinds of spatial-temporal varying external forcing components, and further investigate the impact of dynamical forcing on the long-term simulation in China. The results showed that different external forcing configurations in WRF could result in a variation range of 0.08 °C/10a for annual temperature trend and 19.9 mm/10a for annual precipitation trend in Eastern China (EC), whose impact was stronger than parameterization schemes but was weaker than spectral nudging. The influence of spectral nudging on long-term trend also depended on the configuration of parameterization schemes and external forcing. The WRF model could reasonably reproduce the forcing response pattern of temperature, precipitation, and associated radiative and circulation anomaly changes. The forced annual temperature trend in China could be roughly explained by the linear superposition of GHGs and anthropogenic aerosols, while the forcing response pattern of summer precipitation trend was mainly determined by anthropogenic aerosols. Therefore, we recommend that when using RCMs for long-term simulations, one should first run a long-term preliminary test to determine whether or not to use nudging, and it is better to use all set of varying forcing components than to use varying GHGs only.