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Enhancing Winter Storm Forecasting with Adaptive Observations

Learn about the Winter Storm Reconnaissance program which uses adaptive observations to significantly improve forecast accuracy and reduce errors. Collaboration between university and gov’t agencies. Conducted since 1999. Future work includes verifying precipitation forecasts and expanding globally.

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Enhancing Winter Storm Forecasting with Adaptive Observations

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  1. Adaptive observations at NWS Lacey Holland, SAIC at EMC/NCEP/NWS Zoltan Toth, EMC/NCEP/NWS Acknowledgements: Dave Emmitt, Steve Lord, Sharan Majumdar, Jon Moskaitis, Craig Bishop http://wwwt.emc.ncep.noaa.gov/gmb/targobs/

  2. Outline • Introduction • Targeting for WSR • WSR Results • Future Work

  3. Winter Storm Reconnaissance (WSR) • Based on collaborative research between university and gov’t agencies. EMC/NCEP/NWS established the program in 1999. • Dropwinsonde observations taken over the Pacific by aircraft operated by NOAA’s Aircraft Operations Center (G-IV) and the US Air Force Reserve (C-130s). • Observations are adaptive – collected only prior to significant winter weather events in areas that influence the forecast the most. • Results show 60-80% improvement over forecast area • Operational since January 2001

  4. How WSR targeting happens… • Targets selected in areas where critical winter weather events with high forecast uncertainty may have a potentially large societal impact. • Sensitivity calculations performed using ETKF, and a decision is made (flight/no flight). • Observations are taken and used in operational analysis and forecast products by major NWP centers. • Verification is performed by comparing operational analyses/forecasts including the targeted data with analyses/forecasts excluding the targeted data.

  5. 54 Predetermined Flight Tracks

  6. Data Impact and Forecast Verification Flight track with initial impact Verification region with impact at 48-hrs Data impact Forecast improvement (red) and degradation (blue) Estimated forecast error variance reduction with possible flight tracks 48-hr verification

  7. Results from previous years of WSR Surface Pressure RMS Error Vector Wind RMS Error From Toth et al. (1999)

  8. Data Impact – WSR 2000

  9. Summary of WSR results • Overall, biggest improvement in surface pressure over verification region for 2002-2003 • Winds and temperature from dropsondes have the most impact, followed by winds only and temperature only • Dropsonde winds have greater positive impact than dropsonde temperatures in initial studies

  10. Future Work • Verify precipitation forecasts for all years of WSR; introduce new metric (storm track error) • Continue collaboration with LIDAR group (Emmitt et al.) in support of Atlantic and Pacific TOST or other campaigns • Test adaptive observations technique in OSSE environment, on global scales with simulated LIDAR measurements

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