20 citations · 40 across the 5 of their papers we have counts for
6 papers
Suêtes: An end-to-end differentiable non-hydrostatic limited-area dynamical core
Tim Whittaker, Seth Taylor, Elsa Cardoso-Bihlo +2
We present Suêtes, a fully differentiable, non-hydrostatic, limited-area atmospheric dynamical core implemented in JAX. Suêtes includes both a semi-implicit semi-Lagrangian scheme…
Learning vertical coordinates via automatic differentiation of a dynamical core
Tim Whittaker, Seth Taylor, Elsa Cardoso-Bihlo +2
Terrain-following coordinates in atmospheric models often imprint their grid structure onto the solution, particularly over steep topography, where distorted coordinate layers can…
Constructing Extreme Heatwave Storylines with Differentiable Climate Models
Tim Whittaker, Alejandro Di Luca
Understanding the plausible upper bounds of extreme weather events is essential for risk assessment in a warming climate. Existing methods, based on large ensembles of physics-base…
Evaluating near-surface wind speeds simulated by the CRCM6-GEM5 model using AmeriFlux data over North America
Tim Whittaker, Alejandro Di Luca, Francois Roberge +1
We evaluate the performance of various configurations of the Canadian Regional Climate Model (CRCM6-GEM5) in simulating 10-meter wind speeds using data from 27 AmeriFlux stations a…
Turbulence Scaling from Deep Learning Diffusion Generative Models
Tim Whittaker, Romuald A. Janik, Yaron Oz
Complex spatial and temporal structures are inherent characteristics of turbulent fluid flows and comprehending them poses a major challenge. This comprehesion necessitates an unde…
Using machine learning to parametrize postmerger signals from binary neutron stars
Tim Whittaker, William E. East, Stephen R. Green +2
There is growing interest in the detection and characterization of gravitational waves from postmerger oscillations of binary neutron stars. These signals contain information about…