What is the ClusterTech Platform for Atmospheric Simulation?
The ClusterTech Platform for Atmospheric Simulation (CPAS) is a cloud-based service platform which implements Customizable Unstructured Mesh Generation (CUMG) and Hierarchical Time-Stepping (HTS) on Model for Prediction Across Scales - Atmosphere (MPAS-A (v6.3)) to better serve the computational needs of numerical atmospheric model users.
Background - CPAS is developed based on MPAS-A and WRF.
To achieve a balance between accuracy and computational cost, many Numerical Weather Prediction models (NWPs), such as Weather Research and Forecasting Model (WRF), adopt a set of rectangular grids where local refinement is achieved by nesting a high-resolution domain inside coarser grids. MPAS-A adopts spherical centroidal Voronoi tessellations (SCVTs) covering the globe, while local refinement is achieved using variable-resolution meshes. MPAS-A is a promising model for practical usages. However, MPAS-A uses a constant global timestep, determined by the size of the smallest mesh cell, which limits the resolution variability. This is because the existence of a high resolution region would make the computational resource requirements prohibitively large.
HTS - Arbitrary resolution variation
CPAS has relaxed this restriction by implementing an optional Hierarchical Time-Stepping (HTS) treatment in the MPAS-A (v6.3) dynamic core. Cells of different sizes can have different time step levels and hence the computational requirements are substantially reduced, particularly for large variations in resolution. This allows MPAS-A to be used for high-resolution regional/local forecast, instead of limited area models such as WRF (v3.9.1).
CUMG - 100% well-staggered mesh, zero obtuse Delaunay triangle
Bespoke mesh generation can be done by simply drawing polygons on a map panel and entering the resolutions. Our mesh generation algorithm have solved a well-known problem in generating SCVT with arbitrarily shaped refinement for MPAS’ use - no obtuse Delaunay triangle. We guarantee the resulting meshes have perfect SCVT staggering.
- First cloud-based service for meteorological model
- Freedom in “domain configuration”
- Automatic resolution boost for orography and coastline
- Optimized load-balancing and extreme scalability
- Multi-resolution geographical source data support
- Modified scale-aware features
1. Improve accuracy by releasing lateral boundary conditions
In contrast to WRF, CPAS doesn’t require lateral boundary conditions. As for dynamical downscaling using WRF, the synoptic-scale flows in the regional model are usually constrained as its lateral boundary conditions are forced by the global model. Moreover, the regional model suffers from the difference between global and regional model physics. Therefore, CPAS allows more freedom for the initial state to evolve which will greatly improve accuracy. Finally, unlike WRF, CPAS doesn’t require downloaded global forecast system (GFS) forecast data.
2. Save computation cost and boost efficiency
CPAS automatically assigns the optimal time steps according to resolution variation. You are free to design variable-resolution mesh configurations in a manner that is infeasible in the official MPAS-A release. Hierarchical time-stepping allows a variable-resolution global model like a nested-domain multi-resolution regional model. Computation is concentrated in regions of interest.
3. Save manpower and setup cost
No need to install any software. Computational experiments are done in the cloud. CPAS also provides an easy-to-use visualization system to inspect computational results in the cloud.
For more information, please visit CPAS’ official website: www.cpas.earth