1. Woody Roberts Tom LeFebvre Kevin Manross Paul Schultz Evan Polster Xiangbao Jing ESRL/Global Systems Division Application of RUA/RTMA to AWIPS and the Forecaster Decision Support Environment (FDSE) Sponsored by: Office of Central Processing National Weather Service, NOAA

2. FDSE - Origin NWS Weather Ready Nation Roadmap Infuse new science directly into forecaster environment Tools to improve situational knowledge, enhance short-term forecast efficiency, accuracy Reduce complexity of forecast creation/updates Expand use of probabilistic guidance Better impact information for decision-makers Viewing events in a climatological context Improve forecaster efficiency to better support Impact-based Decision Support Services

3. FDSE - Tasks Several tasks were funded through the FDSE project: Grid Monitor - Forecaster awareness tool that compares the current forecast to observations Short-term Update – Allows forecasters to quickly update the current forecasts using model blending Ensemble Tool – Provides better visualization of forecast ensembles, including frequency calculations for better decision support capability

4. FDSE – Grid Monitor Forecaster awareness tool Compares gridded forecasts to gridded observational analysis Allows forecasters to quickly assess the quality of any available forecast Can compare any model to observational analysis or any other model Customized algorithms and displays for each element

5. FDSE – Short-term Update Tool Updates the early (0-12 hr) period of the forecast by blending guidance hour by hour Blending weights assigned interactively by drawing a curve, other weights adjust automatically. Can update multiple elements at a time

6. Short-term Update Tool Future Work Suggestion of blending weights based on past model performance Potentially many choices – variety of weighting algorithms Users can accept as is, or adjust as needed User-defined verification period for weighting calculations Interpolate mode calculates fills in guidance in gaps before blending Auto-correct mode bias-corrects guidance in real-time using gridded Obs Forecaster chooses analysis grid: e.g., RTMA, Obs, LAPS

7. FDSE – Short-term Blending by Point Most WFOs employ blending tools to update the gridded forecast Most tools weight grids evenly in space and time Weights based on months old performance statistics Point by Point blending addresses these limitations: Weights vary by space and time Model performance evaluated in real-time using gridded observational analysis Complements National Blender project Fills gap in 0-12 hour forecast time frame Similar technique employed by National Blender

8. FDSE – Ensemble Tool Replicate AWIPS/ALPS capabilities with enhancements, initially

9. FDSE – Future Work Continue to solicit forecasters feedback on existing tools and implement suggested changes Blending by Point Continue testing and evaluation Investigate different weighting algorithms Deploy to NWS field offices Integrate Impacts Catalog information into AWIPS II Display overlay Forecaster awareness – Event alerts Forecaster Awareness Tool Data miner – scans for “interesting events” Large forecast differences – temporal, model High impact events Large ensemble spread

10. Summary New FDSE techniques increasingly used at forecast offices Feedback has been positive, but somewhat sparse Plans to better engage Rapid Prototype sites Challenge: Changing forecaster methodology Learning new techniques requires time, experience AWIPS II transition necessarily time-consuming Good foundation to advance IDSS goals

11. Questions?