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Adaptive observations at NWS

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/. Outline. Introduction Targeting for WSR WSR Results

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Adaptive observations at NWS

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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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