Cloud properties over the Tibetan Plateau (TP) and their underlying dynamics play a crucial
role in the energy balance and regional water cycle of the climate system. In this review, we …

Modern climate projections lack adequate spatial and temporal resolution due to
computational constraints. A consequence is inaccurate and imprecise predictions of critical …

Results from the new Department of Energy super‐parameterized (SP) Energy Exascale
Earth System Model (SP‐E3SM) are analyzed and compared to the traditionally …

Accurately representing mesoscale convective systems (MCSs) is crucial to simulating the
energy and water cycles in global climate models. Using a novel MCS identification and …

Supercomputers are the most powerful computing machines available to society. They play
a central role in economic, industrial, and societal development. While they are used by …

Modern climate projections lack adequate spatial and temporal resolution due to
computational constraints, leading to inaccuracies in representing critical processes like …

We introduce a machine learned surrogate model from high-resolution simulation data to
capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural …

Clouds play an important role in the Earth's energy budget, and their behavior is one of the
largest uncertainties in future climate projections. Satellite observations should help in …

The advent of Exascale computing invites an assessment of existing best practices for
developing application readiness on the world's largest supercomputers. This work details …

Modern climate projections often suffer from inadequate spatial and temporal resolution due
to computational limitations, resulting in inaccurate representations of sub-grid processes. A …