Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Correcting weather and climate models by machine learning nudged historical simulations
Due to limited resolution and inaccurate physical parameterizations, weather and climate models consistently develop biases compared to the observed atmosphere. Using the FV3GFS model at coarse…
GridTools: A framework for portable weather and climate applications
Weather forecasts and climate projections are of tremendous importance for economical and societal reasons. Software implementing weather and climate models is complex to develop and hard to…
GFDL SHiELD: A Unified System for Weather-to-Seasonal Prediction
We present the System for High-resolution prediction on Earth-to-Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic…
Dawn: A high-level domain-specific language compiler toolchain for weather and climate applications
High-level programming languages that allow to express numerical methods and generate efficient parallel implementations are of key importance for the productivity of domain-scientists. The…