1. 1 Development of a convection- resolving CONUS ensemble system (aka: Warn on Forecast) Presented By: Lou Wicker (NSSL) Contributors Geoff DiMego (NCEP) Stan Benjamin (GSD) Jack Kain (NSSL)

2. 2 Potential Attribute(s) of the Planned Operational WOF System System NameAcronymAreal Coverage Horz Res Cycle Freq Fcst Length (hr) Warn on Forecast (v1) [1 km deterministic mean + 3 km ensemble] WoF-HRD (high-res determin) Sub-CONUS Nest 3 / 1 km 15 min 1-3 hr 2 Fcsts/hr Warn on Forecast (v2) [~0.5 km deterministic mean + ~1 km ensemble] WoF-HRE (high-res ens) Sub-CONUS Nest 0.5 / 1 km 5 min 1-3 hr 4 Fcsts/hr SystemAttributes WoF (v1) EnKF-Hybrid multi-res system having 1 km regional deterministic mean (uses HREF-RR or regional 3 km for fcst probabilities) WoF (v2) EnKF-Hybrid multi-res system having 0.5 km regional deterministic mean with 1 km regional ensemble. (uses IC/BCs from the HREF-RR) System Data Assimilation or Initialization Technique

3. 3 Why System(s) would be Operational  Primary stakeholders and requirement drivers  NWS offices, SPC, WPC, FAA, aviation/transportation, high-impact weather  What products are the models contributing to?  SPC short-term outlooks (new watches, MDs, 4-hour tornado fcsts)  Tornado/severe thunderstorm warnings, FF warn, terminal fcsts?  What product aspects are you trying to improve with your development plans?  WoF will extend severe weather lead times for local offices towards 1 hour  WoF will produce probabilistic guidance for multiple local weather threats  WoF could might be helpful in improving flash-flood forecasts  Top 3 System Performance Strengths  Convective storms hazards: tornadoes, hail, winds, QPF  Top 3 System Performance Challenges  Reduction of model errors to improve analysis and forecast accuracy  Still unclear whether current observational densities are sufficient for needed forecast accuracy at convective scales

4. 4 System Evolution Over the Next 5 Years  Major forcing factors  Weather Ready Nation Requirements  Increased societal awareness of high-impact weather events  Science and development priorities  Ens. assimilation of conventional and rapid-scan radar and satellite data  Reduction of model error: big need for improved parameterizations  Probabilistic guidance for severe weather  Hazardous event detection platform – collaboration with FACETs program to provide a seamless multi-scale threat-alert capability  What are your top challenges to evolving the system(s) to meet stakeholder requirements?  HPC for ensemble DA and forecasts for both research and operations.  QC and data latency (Radar data already has ~5 min latency!)  MADIS system not designed for RR applications (today ~30 min lat.)  GOES delivery will need to be improved (today ~15 min lat.)  Potential opportunities for simplification going forward  Unify all regional modeling applications with HREF & SREF consolidation, eventually including rapid refresh, hurricane, fire weather, AQ etc using a single-dycore HREF. Single ensemble DA including aerosols and even land-surface. Retain GSI extended to 4D for regional/global DA.

5. 5 Top 3 Things You Need From the UMAC 1.Consider moving NCEP’s operational atmospheric modeling systems toward 2 cores (global and regional) by 2020, and toward a unified core (global+regional) by 2025. In parallel, simplify the product suite (HREF & SREF consolidation). Both would improve NCEP’s ability to be agile and innovate. 2.Product suite is currently heavily weighted toward delivery time. Have user priorities changed since ~2000? Example: Would having the 00Z “GEFS” first yield a better 00Z HREF a bit later? Would forecasters “wait” for that improvement? Should relative priorities of timeliness and accuracy be revaluated? 3.NWP as a science has grown considerably in last 10 years, particularly for convective-scale NWP. Problem is now “too big” for any one group to solve alone. Should (and can?) NCEP and the U.S. weather research community agree to use established community modeling systems to increase R2O between various wx groups?