Creating ML benchmarks for climate problems


Google is looking to fund and actively engage with the research community, exploring opportunities and pathways to leverage Google’s expertise in machine learning (ML) and artificial intelligence (AI) to accelerate the development of data-driven solutions that inform climate action. ML and AI models depend on strong benchmarks that are used to evaluate their performance and track their improvement over time. A recent example is Google’s success in building a flood prediction tool for ungauged basins that uses weather forecasts and basin attributes to predict streamflow, with observed streamflow from thousands of gauges used as a benchmark.

We aim to support the development of ML benchmarks for the areas of interest listed below and the development of modeling tools that would facilitate the use of such benchmarks. In doing so, Google seeks to revolutionize our ability to track and mitigate climate change. We envision that funded projects will involve deep interactions between domain experts in climate and ML, both within Google and at funded institutions. In order to be considered responsive to this call, proposers must make a clear case for why ML and improved benchmarks are poised to be effective and impactful in addressing a given challenge.