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SeaWinds Scatterometer Data: Characteristics and Challenges

SeaWinds Scatterometer Data: Characteristics and Challenges. M. H. Freilich COAS 8 Feb 2005. Outline. What do scatterometers measure? SeaWinds: Instrument, processing, products Accuracy: The numbers Challenges: Coastal measurements Wind Retrieval Rain/extreme conditions.

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SeaWinds Scatterometer Data: Characteristics and Challenges

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  1. SeaWinds Scatterometer Data: Characteristics and Challenges M. H. Freilich COAS 8 Feb 2005

  2. Outline • What do scatterometers measure? • SeaWinds: Instrument, processing, products • Accuracy: The numbers • Challenges: • Coastal measurements • Wind Retrieval • Rain/extreme conditions

  3. What: Interpretation of Scatterometer Wind Estimates • Scatterometers measurebackscatter • From centimetric waves • Generated (primarily) by wind stress • Scatterometer winds are “xx km resolution, 10 m neutral stability wind velocity [speed and direction]” • Speed: scalar (spatial) average over the footprint • Direction: direction of the vector (spatial) mean • Essentially instantaneous (backscatter measurements acquired within minutes)

  4. What: Interpretation (cont.) • 10 m neutral stability wind???? • Wind speed and direction at 10 m height that would cause the observed surface stress if: • Atmosphere neutrally stratified • Motionless sea surface • No long waves Kelly et al., GRL, 2001

  5. 8/99-7/03 4-year Average Wind Stress Curl Chelton, Schlax, Freilich, Milliff, Science, 2004

  6. 8/99-7/03 4-year Average Wind Stress Curl Chelton, Schlax, Freilich, Milliff, Science, 2004

  7. QuikSCAT: Scatterometry Basics • Active microwave radar • Day and night • Clear-sky and clouds • Scattering from short waves • “Cats paws” • In equilibrium with wind • Backscatter depends on • wind speed, direction • Multiple measurement angles • Dual scanning pencil beam • Collocated backscatter measure- • ments used to solve for wind • speed and direction

  8. NOAA/NESDIS Storm Page (3 views) Ambiguities (2 deg grid) NOAA/NESDIS http://manati.orbit.nesdis.noaa.gov/cgi-bin/qscat_storm.pl Wind Vectors NRCS oV-pol forward

  9. QuikSCAT: SeaWinds Measurements

  10. SeaWinds: Dc and Swath Schematic

  11. QuikSCAT: Comparison with NCEP and ECMWF Chelton and Freilich, MWR, 2005

  12. Accuracy: QuikSCAT and NSCAT Buoy Comparisons Chelton and Freilich, MWR, 2005

  13. QuikSCAT/Buoy:NOFAR swath Spd RMS: 1.23 m/s Spd BIAS: 0.13 m/s 3-20 m/s: 19.1 deg (5.2 deg bias) 5-20 m/s: 16.0 deg (5.2 deg bias) 3-20 m/s: 25.3 deg (5.0 deg bias) 5-20 m/s: 19.6 deg (5.1 deg bias)

  14. L2B vs. DIRTH:Nadir swath 3-20 m/s: 23.5 deg (4.7 deg bias) 5-20 m/s: 20.7 deg (5.1 deg bias) 3-20 m/s: 19.6 deg (4.7 deg bias) 5-20 m/s: 16.3 deg (5.1 deg bias) 3-20 m/s: 27.8 deg (4.7 deg bias) 5-20 m/s: 23.0 deg (5.0 deg bias) 3-20 m/s: 23.3 deg (4.7 deg bias) 5-20 m/s: 18.6 deg (5.0 deg bias)

  15. QuikSCAT: Vector Wind Accuracy

  16. Outline • What do scatterometers measure? • SeaWinds: Instrument, processing, products • Accuracy: The numbers • Challenges: • Coastal measurements • Wind Retrieval • Rain/extreme conditions

  17. Summer CZCS Image of US West Coast Equatorward winds cause coastal upwelling -- Low SST near coast -- High productivity -- Complex air-sea interaction Pigment Temperature

  18. Effect of 30 km scatterometer land mask NO accurate wind data over the critical upwelling region High resolution winds will allow study of air-sea interaction in coastal upwelling areas Pigment Temperature

  19. 25 April 2001

  20. 12.5 km Hi-Res “MGDR-slice” Winds • Near-real-time product • 12.5 km backscatter measurements from QSCAT slices • “Composite2” processing to yield 4 so per retrieval • Standard MLE wind retrieval algorithm • Erroneous wind variability (noise) • Poor far-swath performance • Systematic spikes in wind speed histograms • In the 21st century, why must NOAA provide degraded products?

  21. 12.5 km Hi-Res “MGDR-slice” Winds (blue)

  22. New12.5 km Hi-Res “Research-Slice” Winds • Offline (non-real-time) product • 12.5 km backscatter measurements from QSCAT slices • No compositing: up to 16 so msmts per retrieval • Refined MLE wind retrieval algorithm • Cubic spline + log-log wind speed model function interpolation • Improved optimization algorithm for objective function extrema • Full 5+ year reprocessing complete

  23. Rain • Scatterometer wind measurement assumes: • Power minus noise comes from surface • Surface geometry is caused by wind • Rain violates the assumptions: • Scattering/attenuation (non-surface) • Rain-induced surface roughness (non-wind) • Multi-channel radiometers provide (some) independent data • Correction/elimination of rain-contaminated so msmts. • AMSR on ADEOS-2 • QSCAT challenge – combine limited data in unique ways to indicate presence of rain

  24. QuikSCAT Rain Detection Hurricane Floyd Tb • Noise measurements (minus signal) yield estimates of Tb (increases w/ rain rate) • Rain increases h-pol/v-pol ratio (esp. for low wind speed) • Rain increases backscatter variability • Tendency for retrieved direction to cross-track • NOF (Mears et al.) • Single-parameter, no QSCAT Tb • Best for low wind speeds (< 15 m/s) • MUDH (Huddleston and Stiles) • Table lookup, trained vs SSM/I 2 km*mm/hr • Includes QSCAT Tb D. G. Long, BYU W. L. Jones, UCF

  25. QuikSCAT & Buoy:Rain (direction distributions)

  26. Rain Contaminated 95 kt max GALE STORM HURCN FORCE WHITE- HURCN FORCE Joe Sienkiewicz - MPC

  27. QuikSCAT/Buoy:Rain vs. non-Rain (dir. edit) Spd RMS: 4.40 m/s Spd BIAS: 2.58 m/s Spd RMS: 1.23 m/s Spd BIAS: 0.13 m/s

  28. QuikSCAT/Buoy:Rain vs. non-Rain (dir. edit) Spd RMS: 4.40 m/s Spd BIAS: 2.58 m/s Spd RMS: 1.23 m/s Spd BIAS: 0.13 m/s

  29. DIRTH:Rain vs. non-Rain (dir. edit) Spd RMS: 4.46 m/s Spd BIAS: 2.90 m/s Spd RMS: 1.26 m/s Spd BIAS: 0.19 m/s

  30. DIRTH:Nadir vs. “Sweet” swath (dir. edit.) 3-20 m/s: 23.5 deg (4.7 deg bias) 5-20 m/s: 20.7 deg (5.1 deg bias) 3-20 m/s: 17.1 deg (5.2 deg bias) 5-20 m/s: 13.9 deg (5.1 deg bias) 3-20 m/s: 23.3 deg (4.7 deg bias) 5-20 m/s: 18.6 deg (5.0 deg bias) 3-20 m/s: 23.7 deg (5.0 deg bias) 5-20 m/s: 18.0 deg (4.9 deg bias)

  31. L2B vs. DIRTH:“Sweet” swath (dir. edit.) 3-20 m/s: 18.2 deg (5.3 deg bias) 5-20 m/s: 15.0 deg (5.2 deg bias) 3-20 m/s: 17.1 deg (5.2 deg bias) 5-20 m/s: 13.9 deg (5.1 deg bias) 3-20 m/s: 24.9 deg (5.1 deg bias) 5-20 m/s: 19.0 deg (5.1 deg bias) 3-20 m/s: 23.7 deg (5.0 deg bias) 5-20 m/s: 18.0 deg (4.9 deg bias)

  32. 3-20 m/s: 17.5 deg (5.1 deg bias) 5-20 m/s: 14.3 deg (5.1 deg bias) DIRTH:NOFAR swath Spd RMS: 1.23 m/s Spd BIAS: 0.13 m/s 3-20 m/s: 23.6 deg (4.9 deg bias) 5-20 m/s: 18.1 deg (4.9 deg bias)

  33. MUDH Rain Expected Performance vs. SSM/I Huddleston and Stiles, 2000

  34. QuikSCAT -- Buoy:Rain (direction distributions)

  35. QuikSCAT -- Buoy:Rain (speed distributions)

  36. QuikSCAT:Rain Fraction (%) at NDBC Locations

  37. Scatterometry: 2-Look Solutions

  38. Scatterometry: 4-Look Solution(s)

  39. QuikSCAT: Rain Flag • Absorption and scattering from rain • and heavy clouds degrades • wind velocity accuracy • Multi-Dimensional Histogram Rain Flag • Normalized beam difference • Measured speed • MLE misfit • Radiometer mode Tb (H,V) • Table-driven, trained with SSM/I • ~5% flag rate (approx. 2 km mm/hr) • Rain-free data has improved quality • 24% speed rms decrease, 3-7 m/s • Active/Passive environmental retrievals • will be possible with SWS and AMSR on • ADEOS-II

  40. QuikSCAT Radiometer Mode Hurricane Floyd Tb • QuikSCAT noise measurements contribute to autonomous rain flag capability • Careful calibration/analysis allows subtraction of signal energy from 1 MHz bandwidth noise measurements, and interpretation of noise measurements as brightness temperature • QSCAT radiometer mode data compare well with space/time collocated SSM/I rain rates and water contents D. G. Long, BYU W. L. Jones, UCF

  41. REMARKS: 262100Z1 POSITION NEAR 21.4N7 130.6E0. TROPICAL STORM (TS) 20W (PRAPIROON), LOCATED APPROXIMATELY 375 NM SOUTH-SOUTHEAST OF OKINAWA HAS TRACKED NORTH NORTHWESTWARD AT 20KNOTS OVER THE PAST 6 HOURS. THE WARNING POSITION IS BASED ON 261730Z9 INFRARED SATELLITE IMAGERY. THE WARNING INTENSITY IS BASED ON SATELLITE CURRENT INTENSITY ESTIMATES OF 30 AND 35 KNOTS AND A SHIP REPORT OF 35 KNOTS. ANIMATED ENHANCED INFRARED SATELLITE IMAGERY DEPICTS CONVECTION IS SHEARED 15 NM TO THE NORTH AND EAST OF A PARTIALLY EXPOSED LOW LEVEL CIRCULATION CENTER (LLCC). IMAGERY ALSO INDICATES CONVECTION HAS INCREASED IN INTENSITY OVER THE PAST 06 HOURS. UW-CIMSS ANALYSIS AND THE 200 MB ANALYSIS INDICATE OUTFLOW ALOFT CONTINUES TO IMPROVE AS THE TROPICAL UPPER-TROPOSPHERIC TROUGH (TUTT) TO THE WEST CONTINUES TO FILL. A 260916Z4 QUIKSCAT PASS INDICATED A WELL DEFINED LLCC WITH LIGHTER WINDS AROUND THE CENTER AND STRONGER WINDS ON THE PERIPHERY. THE SYSTEM IS FORECAST TO TRACK NORTHWESTWARD THROUGH 24 HOURS, THEN INCREASINGLY WEST-NORTHWESTWARD AS THE SUB-TROPICAL RIDGE BUILDS IN NORTH OF THE SYSTEM. THE 35 KNOT WIND RADII HAVE BEEN INCREASED BASED ON THE 260916Z4 QUIKSCAT PASS. QuikSCAT:Operational Applications National Weather Service Advisory National Weather Service Meteorological Data Assimilation Software Display QuikSCAT data has become a high priority data set for weather forecasters QuikSCAT data is a significant resource for a significant number of advisories issued Joe Sienkiewicz, Lead Forecaster, NWS Marine Prediction Center Jeff Hawkins, Naval Research Laboratory, Monterey, CA 93943

  42. WIND MEASUREMENTS: Mission Schedules

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