Publications by authors named "Sam Hatfield"

Article Synopsis
  • General circulation models (GCMs) are essential for weather and climate predictions, combining physics-based simulations with small-scale process representations like cloud formation.
  • Recently, machine learning models have shown they can compete with GCMs for short-term weather forecasting but lack stability for long-term predictions.
  • The newly developed NeuralGCM merges a differentiable atmospheric dynamics solver with machine learning, achieving competitive forecasts for both weather and climate while being more computationally efficient than traditional GCMs.
View Article and Find Full Text PDF

Tumor hypoxia, resulting from rapid tumor growth and aberrant vascular proliferation, exacerbates tumor aggressiveness and resistance to treatments like radiation and chemotherapy. To increase tumor oxygenation, we developed solid oxygen gas-entrapping materials (O-GeMs), which were modeled after clinical brachytherapy implants, for direct tumor implantation. The objective of this study was to investigate the impact different formulations of solid O-GeMs have on the entrapment and delivery of oxygen.

View Article and Find Full Text PDF

Most Earth-system simulations run on conventional central processing units in 64-bit double precision floating-point numbers Float64, although the need for high-precision calculations in the presence of large uncertainties has been questioned. Fugaku, currently the world's fastest supercomputer, is based on A64FX microprocessors, which also support the 16-bit low-precision format Float16. We investigate the Float16 performance on A64FX with ShallowWaters.

View Article and Find Full Text PDF

We assess the value of machine learning as an accelerator for the parameterization schemes of operational weather forecasting systems, specifically the parameterization of nonorographic gravity wave drag. Emulators of this scheme can be trained to produce stable and accurate results up to seasonal forecasting timescales. Generally, networks that are more complex produce emulators that are more accurate.

View Article and Find Full Text PDF