LEAP Spring 2024 Lecture in Climate Data Science: IGNACIO LOPEZ-GOMEZ

*Please note that in-person space is limited.*

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Abstract: Probabilistic forecasting is crucial to decision-making under uncertainty about future weather. The dominant approach to quantify uncertainty in numerical weather prediction is to use an ensemble of forecasts. However, as the resolution of numerical models increases to meet the demand for highly accurate Digital Twins, generating ensembles will become even more computationally expensive than it is today. To overcome this issue, we propose to generate ensemble forecasts at scale by leveraging recent advances in generative artificial intelligence.

Our approach learns a data-driven probabilistic diffusion model from the 5-member ensemble GEFS reforecast dataset. The model can then be sampled efficiently to produce very large and realistic weather forecast ensembles, conditioned on a few members of the operational GEFS forecasting system. The generated ensembles have similar predictive skill as the full GEFS 31-member ensemble, evaluated against reanalysis, and emulate well the statistics of large physics-based ensembles. We also apply the same methodology to developing a diffusion model for generative post-processing: the model directly learns to correct biases present in the emulated forecasting system by leveraging reanalysis data as labels during training. Ensembles from this generative post-processing model show greater reliability and accuracy, particularly in extreme event classification. In general, they are more reliable and forecast the probability of extreme weather more accurately than the GEFS operational ensemble, even after the latter is post-processed. Our models achieve these results at a small fraction of the cost incurred by the operational GEFS system.

Bio: Ignacio Lopez-Gomez is a research scientist at Google Research. His research focuses on the development of data-driven weather forecasting systems, with an emphasis on extreme events, and on climate modeling and analysis. He holds a PhD in Environmental Science & Engineering from Caltech, where he developed models of atmospheric turbulence, convection and clouds for climate models, as well as methods for parameter estimation from indirect data.

IGNACIO LOPEZ-GOMEZ (Google)

Event Venue & Nearby Stays

LEAP, 2276 12th Ave, New York, United States