The current work presents spatiotemporal analysis of areal windspeeds, using state-of-the-art Gaidai multivariate hazards evaluation approach. Environmental dynamic systems being challenging to forecast using existing reliability methods due to their high dimensionality and intricate nonlinear cross-correlations between different environmental system essential dimensions or components. Developing novel multivariate reliability methods for dynamic environmental systems may assist contemporary research on the global climate change effects. Multivariate Gaidai risks evaluation approach is especially well-suited for multi-dimensional structural and environmental dynamic systems, that have been monitored physically or numerically simulated across a representative time-lapse. The current study made use of raw in-situ windspeed data, collected by NOAA (i.e., National Oceanic and Atmospheric Administration) buoys near the Hawaiian Islands in the North Pacific. Resilient island communities/infrastructure can be designed, using advocated multivariate risk/hazard assessment methodology, particularly those that are close to the ocean and hence subject to extreme weather.As was demonstrated in this study, even given limited underlying dataset, it is feasible to conservatively estimate environmental system’s hazard risks. Novel non-parametric deconvolution extrapolation scheme has been utilized to accurately assess hazard risks.