The intermittent nature of wind resources is challenging for their integration into the electrical system. The identification of weather systems and the accurate forecast of wind ramps can improve wind-energy management. In this study, extreme wind ramps were characterized at four different geographical sites in terms of duration, persistence, and weather system. Mid-latitude systems are the main cause of wind ramps in Mexico during winter. The associated ramps last around 3 h, but intense winds are sustained for up to 40 h. Storms cause extreme wind ramps in summer due to the downdraft contribution to the wind gust. Those events last about 1 to 3 h. Dynamic downscaling is computationally costly, and statistical techniques can improve wind forecasting. Evaluation of the North American Mesoscale Forecast System (NAM) operational model to simulate wind ramps and two bias-correction methods (simple bias and quantile mapping) was done for two selected sites. The statistical adjustment reduces the excess of no-ramps (≤|0.5| m/s) predicted by NAM compared to observed wind ramps. According to the contingency table-derived indices, the wind-ramp distribution correction with simple bias method or quantile mapping method improves the prediction of positive and negative ramps.