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September 7, 2006 LeRoy Spayd Chief, Operations and Requirements Division

Unidata Policy Committee NOAA/NWS Status. September 7, 2006 LeRoy Spayd Chief, Operations and Requirements Division Office of Climate, Water, and Weather Services NOAA’s National Weather Service. Outline. Storm-based Warnings Radiosonde vs Aircraft Water Vapor observations

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September 7, 2006 LeRoy Spayd Chief, Operations and Requirements Division

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  1. Unidata Policy Committee NOAA/NWS Status September 7, 2006 LeRoy Spayd Chief, Operations and Requirements Division Office of Climate, Water, and Weather Services NOAA’s National Weather Service

  2. Outline • Storm-based Warnings • Radiosonde vs Aircraft Water Vapor observations • Analysis of Record • Digital Services • NWS Budget

  3. From County-Based Warnings to Storm-Based Warnings Three simultaneous tornadoes within line of severe thunderstorms • More specific • Increased clarity • Supports newdissemination technology County-Based Tornado Warnings 8 Counties under warning Almost 1 million people warned Storm-Based Tornado Warnings 70% less area covered ~600,000 fewer people warned

  4. Storm-Based Warnings Provide Improved Service Strong circulation within line of severe thunderstorms Tornado warning area based on storm without regard to county boundaries In the current system, six full counties are warned. Storm-Based Tornado Warnings provide much improved service.

  5. Effective Storm-Based Warnings Can Avoid Unnecessary Warning of Population Centers “Storm-based warnings would save the public a minimum of $100 million dollars a year in reduction of the cost of sheltering” - Dr. Dan Sutter Professor of Economics Most of the Dallas/Fort Worth metroplex is correctly omitted from this Storm-Based tornado warning. New siren system selectively activated.

  6. Partner Acceptance of Storm-Based Tornado Warnings Screen capture of Brian Busby at the ABC affiliate in Kansas City, MO. WFO Kansas City/Pleasant Hill issued a Severe Thunderstorm Warning (blue) then upgraded to a Tornado Warning (red).

  7. Current County-Based Verification System • Tornado warning forCounties A, B, C, and D equals four warnings. • Tornado occurs in County A. • False alarms for Counties B, C, and D. County D County C County B County A ConfirmedTornado at 0030Z County-Based VerificationFalse Alarm Rate (FAR) = 75% Probability of Detection = 100%

  8. Tornado warning issued with lead time to first touchdown of 10 minutes. Lead time for County B of 20 minutes and County C of 25 minutes. LT = 25 min. County C County D Tornado Track County B County A LT = 20 min. Storm at TornadoWarning Issuance Tornado TouchdownLT = 10 minutes Current County-Based Verification System County-Based VerificationLead Time (LT) = 18.3 minutes (10+20+25 / 3) Probability of Detection = 100% False Alarm Rate = 25%

  9. Dissemination of Storm-Based Warnings • Those who access warnings via television, Internet, PDAs, and other GIS-enabled services will benefit. • A recent NSF study shows a majority of Americans obtain weather information via these sources. • We already use directional delimiters (based on the location of the storm) in verbal and text-based products. • “A Tornado Warning is in effect for Southwestern Montgomery County” • Planning ongoing to fully utilize these benefits in NOAA Weather Radio (NWR) and Emergency Alert System. • NWR Improvement Project specifies need for “geo-targeting” specific radio transmitters.

  10. Regional In Situ SoundingsRadiosonde/WV Aircraft Obs • In FY06-07: • Evaluate model response to water-vapor sensor derived data • Evaluate implications of • forecasters using different data source and, • reaction of broader US weather enterprise. • Use evaluation to develop plan for implementation • In FY08: Begin eliminating redundant capability for weather observations

  11. Future Directions: Commercial Aircraft Observations • Now: • 25 WVSSII sensors on United Parcel Service B-757 aircraft since March 2005 (NOAA) • 60 TAMDAR sensors on Mesaba Saab 340 Aircraft since January 2005 (NASA) • Sept 06: NOAA RFP for Water Vapor Data from Commercial Aircraft • FY07-08: NOAA Phase I contract for sensor installation and data collection • FY08-12: NOAA Phase II contract for expanded sensor installation and data collection • Bottom Line: • Potential for significant increase in atmospheric soundings from regional and larger airports; ex. Each Southwest Airlines has 450 B-737s, each aircraft has about 8 destinations per day or 16 soundings opportunities – 7200 soundings • Expansion of parameters from aircraft include water vapor, turbulence (EDR), and icing. Some proto-typing effort for air quality measurements (European MOZAIC Program) • Enhanced data monitoring/QA providing RMSE and bias by tail #

  12. Adaptive Sounding Strategy Notional Plan • Use alternative sounding from commercial aircraft if WV instrumented aircraft has a scheduled ascent or descent at an airport which is within: • XX miles of radiosonde site • YY minutes of radiosonde valid time • CONOPS: • Lead Meteorologist at closest WFO coordinates sounding strategy • Short (<3 hrs) and long term (6 month) public notices disseminated indicating product availability and associated WMO Heading and circuits • Soundings from aircraft publicly available in near real-time • Alternative sounding strategy limited to: • 1 of 2 sounding launches per radiosonde station (initially) • CONUS Non-GUAN stations • Outcomes: • $4M/yr in cost avoidance from radiosonde expendables • Redundant observations eliminated • Greater % of Data Requirements Achieved

  13. Adaptive Sounding Strategy: Weather Enterprise Input • A few questions… • How do you currently use radiosonde observations? • What do you know about atmospheric observations from commercial aircraft? • What transition issues might you have with use of aircraft observations as an alternative to radiosonde observations? • How can NOAA best communication data quality issues associated with aircraft observations? • How does the proposed adaptive sounding strategy timeline impact you? • How can we recruit Weather Enterprise contacts to answer these and other issues associated with the Adaptive Sounding Strategy???

  14. Questions and Comments: • David Helms • Office of Science and Technology • NOAA’s National Weather Service • Bldg: SSMC2, Rm: 15334 • Mail Code: W/OST12 • 1315 East-West Highway • Silver Spring, Maryland 20910 • Email: david.helms@noaa.gov • Phone: 301-713-3557 x193 AMDAR Observations 34K Reports in 12 Hours Radiosonde (purple) and WVSSII (black) Comparison April 26, 2005

  15. The Analysis of Record (AOR) • Analysis of Record • A comprehensive set of the best possible analyses of the atmospheric variables at high spatial and temporal resolution with attention placed on weather and climate conditions near the Earth’s surface.

  16. The Analysis of Record (AOR) Project Components • Phase I: Real-time Mesoscale Analysis (RTMA) • A quick analysis using few computer resources. • Proof of Concept for AOR. • NCEP EMC and GSD volunteered to build first phase. • Phase II: Analysis of Record (AOR) • A delayed, comprehensive truth analysis using late arriving data and more computer resources. • Phase III: The Reanalysis • A 30 year history of AORs analyzed using AOR system. • Apply the resulting analysis to local climate studies.

  17. The RTMA • Description • RTMA: A high-spatial resolution analyses of sensible weather variables disseminated to forecasters and external users. • Affordable application of a state-of-the-art analysis system. • Generated by NCEP’s 2DVar analysis. • Available to forecasters at HOUR + 43 min – goal is + 35 minutes • Production and Data • Initial set of variables produced hourly at 5 km resolution: temperature (2 m), dew point (2 m), wind direction (10 m), wind speed, precipitation estimate, sky cover estimate. • Analysis uncertainty of first four elements provided and expressed in same units as surface variables. • Distributed in GRIB 2 by AWIPS SBN as part of OB 7.2 upgrade. • Archived at NCDC. • Uses various data sources (e.g., surface, buoys, radar).

  18. The RTMAData Resources • NCEP obtains full compliment of observations • Conventional observations through the TOC. • Mesonets through MADIS at GSD. • MesoWest will be an alternate path to MADIS during AOR due to the ability to store and forward old data transmitted in bursts from some sites. • RTMA uses several thousand observations. • Analysis Verification • Cross-validation • Withhold small percentage of obs from analysis • Only way to verify analysis for analysis sake • Can withhold and internally compare analysis • Future performance metrics will be based on improvement over this Baseline

  19. The RTMAAnalysis Scheme • Reasons the RUC is used as a first guess for RTMA • Hourly mesoscale analysis. • Designed to fit observations. • Full-physics model. • Assimilation of full mesonet observations, except winds. • Generated by NCEP’s 2DVar analysis. • Downscaled from 13 to 5 km as an extra module at end of RUC post-processing code. • RUC 1-hour is used as RTMA background. • Why use a 2DVar solution? • 2DVar is a subset of NCEP’s 3DVar GSI (Grid-point Statistical Interpolation). • 2DVar is already running in NAM. • Anisotropy built into 2D-Var provides way to restrict influence of observations on elevation. • 2DVar is fast enough to run in NCEP production suite. • Produce an estimate of analysis uncertainty.

  20. The RTMA Schedule • Milestones and Project Schedule • Initial, experimental RTMA products generated routinely and transmitted through NOAAPort: August 2006 • RTMA survey results compiled and analyzed: Second Quarter FY 2007 • Operational testing and acceptance completed: Second Quarter FY 2007 • Start OCONUS development, if funding is available: First Quarter FY 2007 • Start development of additional meteorological parameters, if funding is available: First Quarter FY 2007 • Implement OCONUS RTMA, if funding is available: FY 2008. • Implement training: Second Quarter FY 2007

  21. RTMA 2 m Temperature Analysis

  22. RTMA Summary • RTMA provides an affordable solution for an NDFD-matching verification. • Enhanced analysis of surface weather variables available for situational awareness and other operational applications. • Provides a proof-of-concept for main AOR with applications for other NOAA offices. • Transfer of the RTMA to operational status will greatly increase the daily usage in operations and is the next important step in the RTMA evolution.

  23. Information Sources • RTMA Evaluation Web Site http://www.emc.ncep.noaa.gov/mmb/rtma/ • Established by EMC’s Geoff Manikin (January 2006) • 7 geographical sub-regions displayed: NE, DC, FL, MW, TX, NW and SW • RTMA experimental hourly sky product is displayed at http://www.orbit.nesdis.noaa.gov/smcd/opdb/goes/sdpi/html • RTMA precipitation estimate graphics are at http://wwwt.emc.ncep.noaa.gov/mmb/ylin/pcpanl/

  24. Experimental elements: QPF Snow Amount Sky Cover Significant Wave Height Wind gust – added 09/06/06 Operational elements: Maximum Temperature Minimum Temperature Temperature Dew Point Probability of Precipitation Weather Wind Direction Wind Speed Apparent Temperature * Relative Humidity * * Derived fields Current CapabilityNDFD Operational & experimental elements available for CONUS, Puerto Rico/ Virgin Islands, Hawaii, Guam

  25. HAWAII NDFD

  26. Alaska grids • New experimental elements for Alaska – added 09/06/06 • Max Temp • Min Temp • POP12 • Significant Wave Heights • Wind Speed • Wind Direction

  27. Probabilistic Winds – Operational • Graphical • Text • Experimental in the NDFD

  28. Probabilistic Storm Surge – Experimental Pre Katrina • www.weather.gov/mdl/psurge/ • Two choices: • Overall chance storm surges will be greater than 5 feet above normal tide levels during the next 2 days Mainland Mississippi Post Katrina • Storm surge heights, in feet above normal tide level, which have a 10 percent chance of being exceeded during the next 3 days

  29. Experimental storm surge

  30. Extreme Wind Warning • http://www.weather.gov/os/hurricane/eww.htm • Purpose • New for 2006 • Extreme Wind Warning Product for 2007 • Beyond 2007

  31. NWS Budget • FY06 enacted - $826M (cumulative shortfall of $ 51M in operations) • FY 07 PB - $ 882M • + $38 M for operations (shortfall reduced to $ 30M) • + $18 M for systems • FY 07 House Mark - $ 885 M • FY 07 Senate Mark - $ 927 M • Earmarks - $ 15 M • NDBC - $ 28 M

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