A positive finite-difference advection scheme
Journal of Computational Physics
Journal of Computational Physics
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Journal of Computational Physics
On numerical realizability of thermal convection
Journal of Computational Physics
Journal of Computational Physics
Partially implicit peer methods for the compressible Euler equations
Journal of Computational Physics
MCore: A non-hydrostatic atmospheric dynamical core utilizing high-order finite-volume methods
Journal of Computational Physics
Optimization principles for collective neighborhood communications
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Micro-applications for communication data access patterns and MPI datatypes
EuroMPI'12 Proceedings of the 19th European conference on Recent Advances in the Message Passing Interface
MPI datatype processing using runtime compilation
Proceedings of the 20th European MPI Users' Group Meeting
Journal of Computational Physics
Hi-index | 31.48 |
The sub-grid-scale parameterization of clouds is one of the weakest aspects of weather and climate modeling today, and the explicit simulation of clouds will be one of the next major achievements in numerical weather prediction. Research cloud models have been in development over the last 45 years and they continue to be an important tool for investigating clouds, cloud-systems, and other small-scale atmospheric dynamics. The latest generation are now being used for weather prediction. The Advanced Research WRF (ARW) model, representative of this generation and of a class of models using explicit time-splitting integration techniques to efficiently integrate the Euler equations, is described in this paper. It is the first fully compressible conservative-form nonhydrostatic atmospheric model suitable for both research and weather prediction applications. Results are presented demonstrating its ability to resolve strongly nonlinear small-scale phenomena, clouds, and cloud systems. Kinetic energy spectra and other statistics show that the model is simulating small scales in numerical weather prediction applications, while necessarily removing energy at the gridscale but minimizing artificial dissipation at the resolved scales. Filtering requirements for atmospheric models and filters used in the ARW model are discussed.