Abstract: Concepts are proposed for augmenting a plurality of climate impact and hazard models. In particular, the plurality of climate impact and hazard models are modified/altered based on a user-specified requirement (i.e., a specified geographical location, temporal location or hazard type) and at least one intelligent (i.e., AI-enabled) workflow. Each modified climate impact and hazard model is then analyzed/processed using a machine learning model to identify model parameters which may improve the climate impact and machine learning model. An operation is then identified and executed based on the intelligent workflow, and model parameter. In this way, speed, efficiency and accuracy of climate impact and hazard models may be improved at scale.