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

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

3. What: Interpretation of Scatterometer Wind Estimates Scatterometers measure backscatter – 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. Chelton, Schlax, Freilich, Milliff, Science, 2004 8/99-7/03 4-year Average Wind Stress Curl

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

7. QuikSCAT: Scatterometry Basics 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) Wind Vectors Ambiguities  o V-pol forward NRCS NOAA/NESDIS http://manati.orbit.nesdis.noaa.gov/cgi-bin/qscat_storm.pl (2 deg grid)

9. QuikSCAT: SeaWinds Measurements QuikSCAT: SeaWinds Measurements

10. SeaWinds:  and Swath Schematic SeaWinds:  and Swath Schematic

11. QuikSCAT: Comparison with NCEP and ECMWF 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 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 L2B vs. DIRTH: Nadir swath 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: 23.3 deg (4.7 deg bias) 5-20 m/s: 18.6 deg (5.0 deg bias) 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: 27.8 deg (4.7 deg bias) 5-20 m/s: 23.0 deg (5.0 deg bias)

15. QuikSCAT: Vector Wind Accuracy QuikSCAT: Vector Wind Accuracy

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

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

18. Temperature Pigment 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

19. 25 April 2001

22. 12.5 km Hi-Res “MGDR-slice” Winds Near-real-time product 12.5 km backscatter measurements from QSCAT slices “Composite 2 ” processing to yield 4  o per retrieval Standard MLE wind retrieval algorithm Erroneous wind variability (noise) Poor far-swath performance Systematic spikes in wind speed histograms In the 21 st century, why must NOAA provide degraded products?

23. 12.5 km Hi-Res “MGDR-slice” Winds (blue)

24. 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  o 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

25. 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  o msmts. – AMSR on ADEOS-2 QSCAT challenge – combine limited data in unique ways to indicate presence of rain

26. QuikSCAT Rain Detection Noise measurements (minus signal) yield estimates of T b (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 T b –Best for low wind speeds (< 15 m/s) MUDH (Huddleston and Stiles) –Table lookup, trained vs SSM/I 2 km*mm/hr – Includes QSCAT T b D. G. Long, BYU W. L. Jones, UCF TbTb Hurricane Floyd

27. QuikSCAT & Buoy: Rain (direction distributions) QuikSCAT & Buoy: Rain (direction distributions)

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

29. QuikSCAT/Buoy: Rain vs. non-Rain (dir. edit) 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

33. QuikSCAT/Buoy: Rain vs. non-Rain (dir. edit) 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

34. DIRTH: Rain vs. non-Rain (dir. edit) 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

35. DIRTH: Nadir vs. “Sweet” swath (dir. edit.) 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: 23.3 deg (4.7 deg bias) 5-20 m/s: 18.6 deg (5.0 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: 23.7 deg (5.0 deg bias) 5-20 m/s: 18.0 deg (4.9 deg bias)

36. L2B vs. DIRTH: “Sweet” swath (dir. edit.) 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: 24.9 deg (5.1 deg bias) 5-20 m/s: 19.0 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: 23.7 deg (5.0 deg bias) 5-20 m/s: 18.0 deg (4.9 deg bias)

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

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

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

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

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

45. Scatterometry: 2-Look Solutions Scatterometry: 2-Look Solutions

46. Scatterometry: 4-Look Solution(s) Scatterometry: 4-Look Solution(s)

47. QuikSCAT: Rain Flag 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

48. QuikSCAT Radiometer Mode 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 TbTb Hurricane Floyd

49. Joe Sienkiewicz, Lead Forecaster, NWS Marine Prediction Center 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. Jeff Hawkins, Naval Research Laboratory, Monterey, CA 93943 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 National Weather Service Advisory National Weather Service Meteorological Data Assimilation Software Display QuikSCAT: Operational Applications QuikSCAT: Operational Applications

50. WIND MEASUREMENTS: Mission Schedules WIND MEASUREMENTS: Mission Schedules

51. Wind Roughness Backscatter/ Emission Roughness

52. WIND MEASUREMENTS: (Wished) Mission Schedules

53. Model Function: Refinement Approach Model Function: Refinement Approach Objective is to use QSCAT  o measurements Exploit unique QSCAT scanning geometry – Single incidence angle for each polarization – Complete range of angular differences (“  ”) for collocated fore and aft measurements from each beam Collocated NCEP, ECMWF provide estimates of directional distributions for each (  U) bin NCEP and Interim QSCAT data yield  estimates of speed (“U”) for each collocated fore-aft pair

54. Sponsors: OPNAV N6 N096 NPOESS IPO Space Test Program Support Organizations: ONR (Executing Agent) NRL (Payload) Spectrum-Astro (S/C) Rationale: Validate Polarimetric Radiometry From Space to Develop Wind Vector Wind Direction is the Number One Unfilled Requirement of N096 Risk Reduction for NPOESS CMIS Benefits: 25 km Resolution Wind Vector 3x Improvement in Horizontal Resolution for Imagery (vs. SSMI) Tactical Downlink to the Fleet WindSat - Mission Description Overview: Measure Ocean Surface Wind Speed and Direction Titan II Launch (03/15/02) on STP’s Coriolis Satellite Bus Into a Sun-Synchronous Orbit (830 Km, 98.7 deg); 1100 km Forward Swath; 400 km Aft Swath 3 Year Mission Supports Calibration, Validation and Operational Users WindSat on Coriolis

55. Polarimetric Radiometry THTH T +45 TVTV T -45 T lc T rc Upwelling Microwave Emission Available from “Dual Polarization” Systems (SSM/I, SSMIS) New Capability Available from “Polarimetric” Systems (WindSat) Emission and Scattering Vary With Wind Vector (speed and direction) Wind Direction Dependence Arises From Anisotropic Distribution and Orientation of Wind Driven Waves Stokes Vector Polarization Properties of Emitted/Scattered Radiation Contains Directional Information Wind Direction signal is two orders of magnitude smaller than Wind Speed signal Two means of measuring Correlation of Primary Polarizations Direct measure of  45, LHC, RHC

56. (Wind Speed = 9 m/s; Vertical Lines Identify Upwind Direction)  T v, K  T u, K  T 4, K V-PolarizationH-Polarization 3rd Stokes Parameter4th Stokes Parameter  T h, K Comparison of 37 GHz A/C Data and NRL 2-Scale Model

57. 10.7, 18.7, 37 GHz: V/H, ±45, LCP/RCP 6.8, 23.8 GHz: V/H RF 29.6 rpmSpin Rate 350 Watts Power 675 lbs.Weight 8.25 ft.Width 10.5 ft. Height WindSat Payload Configuration Reflector Support Structure Warm Load Canister Top Deck and Electronics (Rotating) Bearing and Power Transfer Assembly (BAPTA) Launch Locks (4 Places) Spacecraft Interface Stationary Deck Feed Bench Feed Array Cold Load Main Reflector GPS Antenna

58. Transition Schedule Slopes indicate 10-90% need (NPOESS GAP 5b) CY 9900111213141516171803080910010207040506 Local Equatorial Crossing Time Earliest Availability Projected End of Life based on 50% Need S/C Deliveries S/C delivery interval driven by 15 month IAT schedule Mission Satisfaction 0530 1330 DMSP WindSat/Coriolis 0730 - 1030 NPOESS C3 POES EOS-Aqua NPOESS C2 or C1 N’ Earliest Need to back-up launch F20 NPOESS DMSP POES NPP EOS-Terra METOP NPOESS C1 or C2 F16 N M F17 F19 F15 F18 L (15) (Slide from NPOESS Climate brief, 1/25/01)

59. Model Function: Refinement Approach Model Function: Refinement Approach Objective is to use QSCAT  o measurements Exploit unique QSCAT scanning geometry – Single incidence angle for each polarization – Complete range of angular differences (“  ”) for collocated fore and aft measurements from each beam Collocated NCEP, ECMWF provide estimates of directional distributions for each (  U) bin NCEP and Interim QSCAT data yield  estimates of speed (“U”) for each collocated fore-aft pair