The prediction of storm surge is an important part of risk analysis for hurricanes because storm surge is the cause of a significant amount of hurricane damage. Although still debated, the effects of climate change on hurricanes may lead to an increase in storm surge occurrences and in the related damages. Consequently, there is the need to analyze the possible consequences of climate change for several possible scenarios. However, the available models for storm surge analyses are either too computationally expensive or incapable of accounting for climate change effects. This paper proposes a random field model for storm surge predictions based on the Improved Latent Space Approach. Contrary to models available in the literature, the presented metamodel can be trained with both data coming from high-fidelity simulations and observations from historical records.