How to translate climate model projections into actionable, industry-oriented risk assessment becomes significantly important to address potential local climate impacts, resilience planning, adaptive management, and future investment for public and private sectors. Argonne National Laboratory, in collaboration with AT&T, has recently developed inland and costal flood prediction datasets using hydrologic (WRF-hydro) and storm surge (ADCIRC) models based on Argonne Dynamically Downscaled Data Archive (ADDA) at 12km resolution (version 1) from GCMs for North America and tropical cyclone synthetic datasets. We will present the methodology to project flood hazard risks and generate national datasets, the results of probabilistic predictions driven by extreme coastal storm surges and inland floods, and actionable risk information for supporting adaptive management of the utility systems and local community resilience planning.
