Standards & Transparency

There is a massive amount of data that practitioners can use to assess historical risk of natural perils. For future prediction, however, model design, simulation assumptions, and emissions scenarios can present a large range of potentially diverging outcomes. Divergent and potentially conflicting outcomes along with lack of transparency leads to lack of trust in predictions. In this project, we will design and implement the first phase of an industry standard-setting testbed for weather and climate models used by the insurance, reinsurance, and finance sector to predict natural perils. Utilize the testbed to develop standards and validate models, provide intercomparison, test novel methods.

Team: Cikanek (CUNY), Schlosser (MIT), Ortiz (GMU)