A Partnership to Develop, Conduct, and Evaluate Realtime High-Resolution Ensemble and Deterministic Forecasts for Convective-scale Hazardous Weather

 

Research Proposal Submitted To and Funded by

The National Oceanic and Atmospheric Administration (NOAA)

Collaborative Science, Technology, and Applied Research (CSTAR) Program

 

Kelvin Droegemeier1,2,3, Ming Xue1,2, Fanyou Kong1 and Michael Coniglio4

1Center for Analysis and Prediction of Storms (CAPS), 2School of Meteorology (SOM),

3Office of Vice President for Research

4Cooperative Institute for Mesoscale Meteorological Studies (CIMMS)

University of Oklahoma (OU)

National Weather Center, Suite 2500

120 David Boren Blvd, Norman OK 73072

 

$374,825 over 3 years. Project period: 5/1/2007 - 4/30/2010.

 

Accurate prediction of convective-scale hazardous weather continues to be a major challenge, because of the small spatial and temporal scales of the associated weather systems, and the inherent nonlinearity of their dynamics and physics. So far, the resolutions of operational numerical weather prediction (NWP) models remain too low to resolve explicitly convective-scale systems, which constitutes one of the biggest sources of uncertainty and inaccuracy of the quantitative prediction. These and other uncertainties as well as the high-nonlinearity of the weather systems at such scales render probabilistic forecast information afforded by high-resolution ensemble forecasting systems especially valuable to operational forecasting.

 

In this proposal, scientists from the SOM, CAPS and CIMMS at OU seek support from the NWS/CSTAR program to collaborate with scientists and forecasters from the Storm Prediction Center (SPC), the Aviation Weather Center (AWC), the Hydrometeorological Prediction Center (HPC), the Environmental Modeling Center (EMC), the National Severe Storms Laboratory (NSSL), the NWS Norman Weather Forecast Office (WFO), and the NWS Southern Region Headquarters to carry out the first ever realtime storm-scale convection-resolving ensemble forecast accompanied by an even higher-resolution deterministic forecast during the spring storm-seasons of 2007 through 2009. The system will be based on two WRF dynamic cores (ARW and NMM) and their physics packages, and in later years using enhanced (to include radar data assimilation capabilities) versions of the Grid-point Statistical Interpolation (GSI) data assimilation system of EMC/NCEP. Horizontal resolutions ranging from 1 to 4 km will be used by the ensemble and higher-resolution deterministic forecasts. Collaboration with EMC ensures that the ensemble system will be closely linked to the NOAA/NCEP operational short-range ensemble forecast (SREF) system by using EMC initial and boundary condition perturbations and similar model components whenever possible. In fact, the ensemble forecasting system developed and tested in this project will potentially serve as a prototype of the next-generation operational regional ensemble forecast system.

 

The proposed research and technology transfer activities will expand the many years of collaborations between OU research and academic units and the NOAA/NWS research and operational components, including the past SPC Spring Experiments, and leverage on the infrastructures and technologies developed or under development under the support of NSF (e.g., the NSF large ITR grant, Linked Environment for Atmospheric Discovery LEAD, and other grants for storm-scale data assimilation and NWP at CAPS), FAA, NASA and other agencies. Through collaboration with the SPC/NSSL Spring Experiment and the NOAA Hazardous Weather Testbed (HWT), 50-60 researchers and forecasters annually from around the nation will participate in the realtime assessment and evaluation of the forecast products and their impact on forecasting and warning. The project will take advantage of national supercomputing and future peta-scale computing resources acquired through CAPS.

 

The scientific findings of this project will provide guidance for the design of next-generation operational regional-scale ensemble forecast systems, and guidance to the NWS management concerning optimal R&D as well as computational resource allocations for the purpose of maximally enhancing public and aviation safety and American commerce as a whole.