Polarimetric Radiometer and Scatterometer Measurements Simon H. Yueh Jet Propulsion Laboratory Operational SVW Requirement Workshop, Miami 7 June 2006.

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Presentation transcript:

Polarimetric Radiometer and Scatterometer Measurements Simon H. Yueh Jet Propulsion Laboratory Operational SVW Requirement Workshop, Miami 7 June 2006

2 Outline Introduction Coastal Winds off Southern California Active and Passive Measurements for Hurricane Erika in 1997 Combined Polarimetric Measurements in Monterey Bay in 2000 WindSat Signals for High winds Summary

3 Coastal Wind off Southern California from POLSCAT/DC-8 on 17 Feb km

4 Coastal Wind off Southern California from POLSCAT on 17 Feb 2002 After about 4 hours, wind speed increased by about 4-5 m/s

5 Polarimetric Radiometry Microwave emission from sea surfaces is polarized and varies with ocean surface wind speed and direction Stokes vector describes the full polarization properties of polarized radiation Measurement techniques –Coherent Correlation measurements –Incoherent power measurements

6 Symmetry Properties of Polarimetric Radiometer Signals Tv and Th are symmetric with respect to wind direction. U and V are odd functions of wind direction

7 POLARIMETRIC SCATTEROMETRY VV VH HV HH Polarimetric Scattering Matrix Polarimetric Correlation Theoretical Predictions of Polarimetric Signature of Wind Direction  vv,  hh,  vh and  hhvv are cosine functions of wind direction  hhhv and  vvhv are sine functions  V H Wind Ocean Surface Radar

8 Significance of Polarimetry and Combined Active/Passive Measurements Inversion –From c2, we get φ, -φ, φ+180 and 180-φ –From s, we get two solutions, φ and 180-φ Polarimetry will reduce the number of directional solutions Will enhance the identification of circulation

9 NUSCAT/WINDRAD Data at 35 m/s Wind Speed in September 1997 Simultaneous 13 GHz radar and multi-frequency radiometer observations Radar and polarimetric radiometer data showed consistent wind direction. NASA P-3 FLIGHT OVER HURRICANE ERIKA IN SEPTEMBER 1997 (AVHRR INFRARED)

10 POLSCAT/WINDRAD ON NCAR C-130 OCEAN FLIGHTS NEAR MONTEREY, CA IN AUGUST 2000 AND JULY 2002 –STAR FLIGHT PATTERNS OVER MBARI MOORINGS POLSCAT Mooring PALSWINDRAD

11 Clear Wind Direction Signals in All Polarimetric Channles at 10 M/S Wind Speed  VV,  HH,  VH,  HV, and  VVHH are cosine functions  VVHV,  VVVH,  HHHV,  HHVH are sine functions Upwind POLSCAT DATA FROM ONE STAR FLIGHT PATTERN Over MBARI M2 Mooring on August 16, 2000

12 Polarimetric Scatterometer and Radiometer Measurements at 11 m/s on Aug 16, 2000 Upwind Crosswind

13 QuikSCAT and WindSat Matchup Hurricane Isabel DateQuikSCAT Rev WindSat RevBest Track Maximum Wind Speed (m/s) Sept 8, Sept Sept Sept Sept Sept Sept

14 WindSat 10 GHz Data for Hurricane Isabel Rev 3510 U data show circulation around eye

15 GMF FOR VERY HIGH WIND The Approach is based on Young’s technique (JGR 1993) for the estimate of Geosat Altimeter wind speed algorithm The same technique applied to the QuikSCAT data to develop the model function for very high winds WindSat Tb HOLLAND’S TC MODEL WIND Location Velocity of forward motion Central and ambient pressure Radius of maximum wind speed Angle of the maximum wind  b(W,  ) 5 m/s and 20 degree bins

16 Holland Model Direction Versus QuikSCAT Wind Direction for Isabel (QuikScat Rev 22012)

17 WindSat U and V Signals Versus Holland’s Directional Model for Rev 3510 The data from other revs have similar directional features.

18 Polarimetric WindSat Data Show Response to Hurricane Wind direction WindSat 10, 18 and 37 GHz data from hurricane Isabel respond to hurricane wind direction 10 GHz U 1 data show strong response at 50 m/s or higher wind speed

19 WindSat U Model Function and Comparison with Aircraft K-band Data WindSat U data agree well with aircraft data Observable passive directional signals for above 30 m/s

20 Summary Airborne scattermeter data frequently showed features with a few Km scale Scatterometer and polarimetric radiometer data show consistent directional signals for m/s Polarimetric scatterometer signals complement the directional characteristics of VV, HH and HV NRCS WindSat 10-GHz U data showed directional response to ocean wind direction for m/s winds. –There were anomalous directional features in V data near eye