Long-term high-resolution temperature data of the Compact Rayleigh Autonomous Lidar (CORAL) is used to evaluate temperature and gravity wave (GW) activity in ECMWF Integrated Forecasting System (IFS) over R\’io Grande (53.79$^{\circ}$S, 67.75$^{\circ}$W), which is a hot spot of stratospheric GWs in winter. Seasonal and altitudinal variations of the temperature differences between the IFS and lidar are studied for 2018 with a uniform IFS version. Moreover, interannual variations are considered taking into account updated IFS versions. We find monthly mean temperature differences $<2$~K at 20-40~km altitude. At 45-55~km, the differences are smaller than 4~K during summer. The largest differences are found during winter (4~K in May 2018 and -10~K in August 2018, July 2019 and 2020). The width of the difference distribution (15th/85th percentiles), the root mean square error, and maximum differences between instantaneous individual profiles are also larger during winter ($>\pm10$~K) and increase with altitude. We relate this seasonal variability to middle atmosphere GW activity. In the upper stratosphere and lower mesosphere, the observed temperature differences result from both GW amplitude and phase differences. The IFS captures the seasonal cycle of GW potential energy ($E_p$) well, but underestimates $E_p$ in the middle atmosphere. Experimental IFS simulations without damping by the model sponge for May and August 2018 show an increase in the monthly mean $E_p$ above 45~km from only $\approx10$~\% of the $E_p$ derived from the lidar measurements to 26~\% and 42~\%, respectively. GWs not resolved in the IFS are likely explaining the remaining underestimation of the $E_p$.