Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Correcting a 200 km Resolution Climate Model in Multiple Climates by Machine Learning From 25 km Resolution Simulations
Bretherton et al. (2022, https://doi.org/10.1029/2021MS002794) demonstrated a successful approach for using machine learning (ML) to help a coarse‐resolution global atmosphere model with real…
Impact of Warmer Sea Surface Temperature on the Global Pattern of Intense Convection: Insights From a Global Storm Resolving Model
Intense convection (updrafts exceeding 10 m s−1) plays an essential role in severe weather and Earth's energy balance. Despite its importance, how the global pattern of intense convection changes in…
Correcting a coarse-grid climate model in multiple climates by machine learning from global 25-km resolution simulations
Bretherton et al. (2022, https://doi.org/10.1029/2021MS002794) demonstrated a successful approach for using machine learning (ML) to help a coarse-resolution global atmosphere model with real…
Productive Performance Engineering for Weather and Climate Modeling with Python
Earth system models are developed with a tight coupling to target hardware, often containing highly-specialized code predicated on processor characteristics. This coupling stems from using…
Hallett‐Mossop Rime Splintering Dims Cumulus Clouds Over the Southern Ocean: New Insight From Nudged Global Storm‐Resolving Simulations
In clouds containing both liquid and ice with temperatures between −3°C and −8°C, liquid droplets collide with large ice crystals, freeze, and shatter, producing a plethora of small ice splinters.…
Correcting Coarse-Grid Weather and Climate Models by Machine Learning From Global Storm-Resolving Simulations
Global atmospheric `storm-resolving' models with horizontal grid spacing of less than 5~km resolve deep cumulus convection and flow in complex terrain. They promise to be reference models that could…
Tropical Cirrus in Global Storm‐Resolving Models: 2. Cirrus Life Cycle and Top‐of‐Atmosphere Radiative Fluxes
Cirrus clouds of various thicknesses and radiative characteristics extend over much of the tropics, especially around deep convection. They are difficult to observe due to their high altitude and…
Tropical Cirrus in Global Storm‐Resolving Models: 1. Role of Deep Convection
Pervasive cirrus clouds in the upper troposphere and tropical tropopause layer (TTL) influence the climate by altering the top‐of‐atmosphere radiation balance and stratospheric water vapor budget.…
Domain-Specific Multi-Level IR Rewriting for GPU: The Open Earth Comp
Most compilers have a single core intermediate representation (IR) (e.g., LLVM) sometimes complemented with vaguely defined IR-like data structures. This IR is commonly low-level and close to…
fv3gfs-wrapper: a Python wrapper of the FV3GFS atmospheric model
Simulation software in geophysics is traditionally written in Fortran or C++ due to the stringent performance requirements these codes have to satisfy. As a result, researchers who use…