A method for predicting arrival of a wind event at an aeromechanical structure, comprising: repeatedly scanning, with lidar, a three-dimensional geometric surface in an atmospheric volume moving towards the aeromechanical structure to measure a time series of spatially distributed wind velocity measurements on the three-dimensional geometric surface, the three-dimensional geometric surface having fixed location relative to the aeromechanical structure, the method being characterized by: spatiotemporally propagating each of the wind velocity surface measurements temporally and spatially in a mutually consistent manner such that optimal consistency between the different time points of time series is ensured in order to determine a time evolution of the full volumetric wind field associated with atmospheric volume; evaluating at least one time point of the time evolution to detect the wind event; prior to arrival of the wind event at the aeromechanical structure, tracking the wind event through at least a portion of the time evolution to estimate arrival time of the wind event at the aeromechanical structure; and communicating feed-forward control data enabling adjustment of the aeromechanical structure in anticipation of the wind event, the method further comprising: in the step of spatiotemporally propagating, summarizing the time series of spatially distributed wind velocity as a corresponding time series of wind parameter surface maps, each of the wind parameter surface maps indicating at least one wind-field parameter for a plurality of sectors, each of the sectors being associated with several individual wind velocity measurements; in the step of evaluating, evaluating at least one of the wind parameter surface maps to detect the wind event and determine type of the wind event; and in the step of tracking, tracking propagation of the wind event through at least a portion of the time series of wind parameter surface maps to estimate the arrival time; and the method further comprising: determining, from the time series of wind parameter surface maps, (a) a wind parameter map of current values of the at least one wind-field parameter at a second geometric surface located at the aeromechanical structure, and (b) at least one wind field map of future values of the at least one wind-field parameter associated with the wind event at the second geometric surface, to provide feed-forward control data enabling adjustment of the aeromechanical structure in anticipation of the wind event. repeatedly scanning, with lidar, a three-dimensional geometric surface in an atmospheric volume moving towards the aeromechanical structure to measure a time series of spatially distributed wind velocity measurements on the three-dimensional geometric surface, the three-dimensional geometric surface having fixed location relative to the aeromechanical structure, the method being characterized by: spatiotemporally propagating each of the wind velocity surface measurements temporally and spatially in a mutually consistent manner such that optimal consistency between the different time points of time series is ensured in order to determine a time evolution of the full volumetric wind field associated with atmospheric volume; evaluating at least one time point of the time evolution to detect the wind event; prior to arrival of the wind event at the aeromechanical structure, tracking the wind event through at least a portion of the time evolution to estimate arrival time of the wind event at the aeromechanical structure; and communicating feed-forward control data enabling adjustment of the aeromechanical structure in anticipation of the wind event, the method further comprising: in the step of spatiotemporally propagating, summarizing the time series of spatially distributed wind velocity as a corresponding time series of wind parameter surface maps, each of the wind parameter surface maps indicating at least one wind-field parameter for a plurality of sectors, each of the sectors being associated with several individual wind velocity measurements; in the step of evaluating, evaluating at least one of the wind parameter surface maps to detect the wind event and determine type of the wind event; and in the step of tracking, tracking propagation of the wind event through at least a portion of the time series of wind parameter surface maps to estimate the arrival time; and the method further comprising: determining, from the time series of wind parameter surface maps, (a) a wind parameter map of current values of the at least one wind-field parameter at a second geometric surface located at the aeromechanical structure, and (b) at least one wind field map of future values of the at least one wind-field parameter associated with the wind event at the second geometric surface, to provide feed-forward control data enabling adjustment of the aeromechanical structure in anticipation of the wind event.