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RAMMB Satellite Wind Algorithms: Possible Contributions to the GOES-R AWG

RAMMB Satellite Wind Algorithms: Possible Contributions to the GOES-R AWG. Mark DeMaria Regional and Mesoscale Meteorology Branch NOAA/NESDIS/ORA, Fort Collins, CO Presented at GOES-R Algorithm Working Group Meeting November 16, 2005 Falls Church, VA. Outline.

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RAMMB Satellite Wind Algorithms: Possible Contributions to the GOES-R AWG

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  1. RAMMB Satellite Wind Algorithms:Possible Contributions to the GOES-R AWG Mark DeMaria Regional and Mesoscale Meteorology Branch NOAA/NESDIS/ORA, Fort Collins, COPresented at GOES-R Algorithm Working Group Meeting November 16, 2005 Falls Church, VA

  2. Outline • 1. Stereo techniques for feature track winds • 2. Hurricane maximum wind estimation • Dvorak method • Hyperspectral eye sounding method • 3. Hurricane inner core wind field estimation algorithm • 4. Hurricane maximum wind forecast method

  3. 1. RAMMB Asynchronous Stereo Wind Studies • Utilize multiple images of same scene from different view angles in feature track wind algorithm • Improves height assignment • Utility of technique demonstrated experimentally • Emphasis on automation of target selection • Code provided to U.S. Air Force for operational implementation • Code provided to EUMETSAT for height assignment quality control • Comparison with CO2 slicing method • Code documented for use as RAMMB research tool

  4. GOES East + GOES West Because of the time sampling of GOES East and West it is not possible to use simultaneous stereo. The consistency of motion and height shows the technique is working. Automatic analysis of Visible GOES imagery at (19:30, 19:45 and 20:00 Feb 25, 1999)..

  5. Evaluation of Stereo Heights3 GOES Case: July 31, 2000 IR Technique Visible Technique GOES 10/11 GOES 8/11 GOES 8/10 GOES 8/10

  6. Stereo Heights vs. IR Brightness Temperature and CO2 Slicing Methods Stereo vs. IR BT Stereo vs. CO2 Slicing

  7. Stereo Wind Algorithms for GOES-R • Higher temporal resolution will make technique more synchronous • Higher spatial resolution will improve height assignment • Utility of multiple ABI visible channels

  8. 2. Hurricane Maximum Wind Estimation • Dvorak technique • Used for decades at global TC forecast centers • Visible technique • Subjective pattern matching with rules for each pattern • IR technique • Max winds based on warm eye pixel and cold ring eyewall temperature • Generalized and automated method developed by CIMSS (AODT) • Direct hydrostatic integration of hurricane eye soundings from GOES • Current GOES resolution limits utility

  9. Patterns of Visible Dvorak Technique 1. Curved Band 2. Shear Pattern 3. CDO 4. Eye 4a. Banded Eye

  10. Example Digital IR: Hurricane Erika 1515 UTC 8 September 1997 • Warmest eye pixel 16 °C • Warmest pixel 30 nmi (55 km) from center -57 °C • Nomogram gives max wind of 115 kt

  11. Eye - Environment Temperature Eye Sounding Environment Sounding Direct Hydrostatic Integration of Satellite Eye SoundingAIRS example from Isabel 2003 Integrate Hydrostatic Equation Downward from 100 hPa to Surface Environment Sounding: Ps = 1012 hPa Eye Sounding: Ps = 936 hPa Aircraft Recon: Ps = 933 hPa

  12. GOES-R Hurricane Maximum Wind Estimation Algorithms • Visible Dvorak technique with new ABI channels, resolution • Impact of horizontal resolution on IR techniques • Applications of HES eye soundings for direct intensity estimation

  13. Dvorak Resolution Sensitivity StatisticsUse AVHRR/MODIS to simulate ABI resolutionCompare cold ring/eye temperature difference between 4 and 2 km resolution

  14. 3. Hurricane Inner Core Wind Algorithm • Model wind field by sum of storm motion and symmetric • Assume Vmis know from Dvorak or other methods • Estimate x and Rm from IR imagery, Vm and latitude • Add wave number one asymmetry due to storm motion • Reduce to surface using standard reduction methods • Provides complete TC surface wind field from r=0 to 200 km Vm=100 kts, Rm=55 km, x=0.5

  15. Hurricane Dennis Example Motion: 8.6 kts Maxwind: 77 kts

  16. GOES-R TC Inner Core Wind Algorithm • Impact of horizontal resolution, new channels • Improved time continuity • Method involved temporal averaging • More general version being developed with CIMSS • Does not require parametric vortex

  17. 4. Hurricane Maximum Wind Forecast Algorithm • SHIPS model • Statistical TC intensity change forecast out to 120 hours • Input includes atmospheric and oceanic predictors • Most predictors from GFS model and Reynold’s SST • GOES predictors for inner core • Percent pixels colder than -20oC • Channel 4 Tb standard deviation (100 to 300 km) • EOF amplitudes of radial channel 4 Tb structure • Operational at NHC • Most skillful intensity forecast model since 2001 • Companion Rapid Intensity Index (RII) • Uses similar input to estimate probability of rapid intensification • GOES input is more important in RII than SHIPS

  18. GOES Data in SHIPS and the RII Percent Pixels < -20oC Standard Deviation of Tb EOF amplitudes Azimuthal Average

  19. GOES-R and TC Maximum Wind Forecast Algorithms • Inner core structure better resolved • EOFs may contain more information • Predictive information in new channels • Rapid intensification signals

  20. Summary of RAMMB Wind Algorithms 1. Stereo techniques for feature track winds 2. Hurricane maximum wind estimation - Dvorak method • Vis and IR - Hyperspectral eye sounding method 3. TC inner core wind field estimation algorithm - Parametric vortex and CIMSS general algorithm 4. Hurricane maximum wind forecast method - SHIPS and the Rapid Intensity Index

  21. RAMMB Resources • Experience with stereo and hurricane wind algorithms • Programming capabilities • GOES-R Proxy datasets • Synthetic • Mesoscale and radiative transfer models • Experimental satellites • Computing and mass storage

  22. Back-up Slides

  23. Infrared (IR) Technique • Can be used during night as well as during day • At times more objective than visible technique

  24. IR-Derived V at r=182 km (determines x) RMW

  25. Symmetric Wind Field

  26. Evolution of Dennis, 1999 Motion: 10.1 kts Maxwind: 77 kts

  27. Evolution of Dennis, 1999 Motion: 10.8 kts Maxwind: 72 kts

  28. The 2004 SHIPS Model • Statistical-dynamical intensity model (12-120 hr) • Developed from 1982-2003 sample • Empirical decay for portion of track over land • Track from adjusted 6-hour old NHC forecast • Version with satellite input operational for 2004 • SHIPS Input • Climatological: Julian Day • Atmospheric Environment: Shear, T200, 200, 850 • Oceanic Environment: SST, Ocean Heat Content • Storm Properties: Vm, dVm/dt, motion, PSL, lat, GOES Cold Pixel Count, GOES TB Std Dev • Most storm property inputs are indirect measurements

  29. GRIP Model Statistical Development • GRIP Predictors • EOF Version • SHIPS Forecast • Amplitudes of first four EOFs of GOES and Recon profiles (principal components) • Physical Version • SHIPS Forecast • 10 physical parameters from GOES and recon profiles • Final GRIP Model • EOF Version • SHIPS forecast, 2 recon PCs, 1 GOES PC • Physical Version • SHIPS forecast, 3 recon variables, 1 GOES variable • Both versions tested on 124 cases from 2004 Atlantic season

  30. 2005 GRIP Model • Add 2004 cases and re-derive the coefficients • ~20% increase in sample size • Consider combined EOF and physical variable version • Run in real time during 2005 season for further evaluation

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