Special computational campaigns

The CISL production supercomputing environment supports special computational campaigns for ongoing and short-term computational projects, all via a priority-based and near-real-time job scheduling mechanism. These campaigns are managed to minimize the impact on the production computing delivered to NCAR, university, and CSL scientists.

The table below lists the special computational campaigns supported by CISL during FY2015. The efforts included support for two projects that involved demonstrating operational capabilities for improving weather and climate forecasting with NCAR flagship models.

FY2015 Special Campaign

Project Lead



MPAS global 3-km hindcasts for HIWPP

W. Skamarock



Testing and applying WRF-Solar for irradiance and solar power prediction

S. Haupt



Impacts of climate change on coral reef ecosystems of the Coral Triangle Region

J. Kleypas



Completion of atmospheric model development for CAM5.5 and the North American Multi-Model Ensemble hindcast suite

J. Tribbia



Real-time evaluation of extended guidance provided for SPC applications by a global convection-permitting model

W. Skamarock



A large-eddy simulation study of Southern Ocean boundary layers

P. Sullivan



The North American Multi-Model Ensemble (NMME) Phase II seasonal system

J. Tribbia



Regional climate ensembles project

C. Bruyère



Real-time high-resolution ensemble analyses and forecasts of high-impact weather with NCAR’s DART facility and WRF model

G. Romine



Special campaign usage
CISL works to accelerate scientific discovery through numerical simulation by providing a portion of the Yellowstone system to special campaigns. The image shows usage of Yellowstone for special computational campaigns during FY2015. 

Building on their demonstrated success producing real-time ensemble forecasts during the Mesoscale Predictability Experiment (MPEX) in 2013, the same team has begun conducting real-time 48-hr, 10-member, 3-km WRF-based ensemble forecasts over the entire contiguous United States for a full year, running daily on Yellowstone starting in April 2015. This data set will permit evaluation of high-resolution ensemble predictions across a variety of weather regimes including events not typically studied with convection-permitting ensembles, such as snowstorms. Thus, this data set will be useful to university researchers studying topics ranging from data assimilation to physical processes and predictability. The year-long aspect of this work will help WRF model developers understand seasonal WRF model climatology and biases. Furthermore, the team will objectively verify probabilistic ensemble forecasts and develop new methods to evaluate high-impact weather events ranging from supercell thunderstorms to winter-weather hazards. A system of this scope is unprecedented considering the scales involved. Limited-area continuously cycled ensemble data assimilation for a year-long period has never before been attempted, and this will be the only such high-resolution ensemble in the world.

In spring 2015, the MPAS team from the Mesoscale and Microscale Meteorology (MMM) lab used Yellowstone to produce extended-range convection-permitting forecasts in support of a collaborative effort with NOAA and the University of Oklahoma, part of the Next Generation Global Prediction System (NGGPS) project. Using the MPAS model and a variable mesh with 3-km resolution over the continental United States, the team produced five-day forecasts for the 2015-2016 Spring Forecast Experiments conducted at the NOAA Storm Prediction Center and evaluated these forecasts as part of ongoing efforts to provide extended range, five-day guidance for severe weather. The Yellowstone computations tested whether the use of a multi-scale global model provided more information about the potential, mode, and intensity of convective activity to storm forecasters for Day 2 and beyond, over and above what the current NCEP modeling suite provides. The 2015 NOAA/SPC Hazardous Weather Testbed spring experiment spanned five weeks in May and June, and the MPAS team conducted one 5-day forecast per day for the weekdays during those five weeks.

These special computing campaigns serve CISL’s computing imperative to provide on-demand and real-time services support for hardware cyberinfrastructure. This work is made possible through NSF Core funds, including CSL funding.