An accurate assessment of the physical states of the Earth system is an essential component
of many scientific, societal, and economical considerations. These assessments are …

The emergence of exascale computing and artificial intelligence offer tremendous potential
to significantly advance earth system prediction capabilities. However, enormous challenges …

Computing derivatives is key to many algorithms in scientific computing and machine
learning such as optimization, uncertainty quantification, and stability analysis. Enzyme is a …

It is the purpose of this paper to provide a comprehensive documentation of the new NCAR
(National Center for Atmospheric Research) version of the spectral element (SE) dynamical …

We present an algorithmic framework for matrix-free evaluation of discontinuous Galerkin
finite element operators. It relies on fast quadrature with sum factorization on quadrilateral …

Today's global Earth system models began as simple regional models of tropospheric
weather systems. Over the past century, the physical realism of the models has steadily …

In this work a non-conservative balance law formulation is considered that encompasses the
rotating, compressible Euler equations for dry atmospheric flows. We develop a semi …

Abstract This work presents IMplicit-EXplicit (IMEX) formulations for discontinuous Galerkin
(DG) discretizations of the compressible Euler equations governing non-hydrostatic …

High-order spectral element methods (SEM) for large-eddy simulation (LES) are still very
limited in industry. One of the main reasons behind this is the lack of robustness of SEM for …

In this study, we accelerated a microphysics scheme embedded within the Model for
Prediction Across Scales (MPAS), using OpenACC directives. As one of the most time …