presentation_meissner.pptx

592 views

Published on

Published in: Technology, Business
  • Be the first to comment

  • Be the first to like this

presentation_meissner.pptx

  1. 1. IGARSS 2011<br />Vancouver, BC, Canada <br />July 26, 2011 <br />All-Weather Wind Vector Measurements from Intercalibrated Active and Passive Microwave Satellite Sensors<br />Thomas Meissner<br />Lucrezia Ricciardulli<br />Frank Wentz<br />
  2. 2. Outline<br />Passive (radiometer: WindSat) vs active (scatterometer: QuikSCAT) wind speed retrievals: <br />Surface emissivity versus radar backscatter.<br />Ocean Surface Emissivity Model.<br />Overview: RSS WindSat version 7 ocean products.<br />WindSat all-weather wind speeds.<br />Improved QuikSCAT Ku2011 geophysical model function.<br />Validation.<br />High winds.<br />Rain impact study. <br />Selected storm case: Hurricane Katrina.<br />Conclusion: active vs passive - strength +weaknesses.<br />
  3. 3. Passive vs Active Wind Speeds<br />Passive (radiometer)<br />Sees change in emissivity of wind roughened sea surface compared with specular surface<br />Low winds: Polarization mixing of large gravity waves.<br />High winds: Emissivity of sea foam.<br />Radiative Transfer Model (RTM) function for wind induced surface emissivity.<br />Active (scatterometer)<br />Sees backscatter from the Bragg-resonance of small capillary waves.<br />Geophysical Model Function (GMF) for wind induced radar backscatter. <br />Calibration<br />Ground truth:<br />Buoy, NWP wind speeds<br />
  4. 4. Challenge 1: High Wind Speeds (> 20 m/s)<br />Passive (radiometer)<br />Lack of reliable ground truth. (buoys, NWP) for calibration and validation.<br />Tropical cyclones: High winds correlated with rain (challenge 2).<br />Active (scatterometer)<br />Lack of reliable ground truth. (buoys, NWP) for calibration and validation.<br />Tropical cyclones: High winds correlated with rain (challenge 1).<br />Loss of sensitivity (GMF saturates).<br />
  5. 5. Challenge 2: Wind Speeds in Rain<br />Passive (radiometer)<br />Rainy atmosphere attenuates signal.<br />Emissivity from rainy atmosphere has similar signature than from wind roughened surface.<br />Scattering from rain drops is difficult to model.<br />Active (scatterometer)<br />Rainy atmosphere attenuates signal.<br />Backscatter from rainy atmosphere has similar signature than from wind roughened surface.<br />Scattering from rain drops is difficult to model.<br />Splash effect on surface.<br />Rain flagging difficult for single frequency sensor.<br />
  6. 6. Ocean Surface Emissivity Model<br />Crucial part of Radiative Transfer Model (RTM). <br />Physical basis of passive wind retrieval algorithm.<br />Dielectric constant of sea water.<br />Wind induced sea surface emissivity.<br />Derived from WindSat and SSM/I TB measurements.<br />Winds < 20 m/s:<br />Buoys.<br />NWP.<br />Scatterometer.<br />Winds > 20 m/s: <br />HRD wind analysis (hurricanes).<br />SFMR data.<br />T. Meissner + F. Wentz, IEEE TGRS 42(9), 2004, 1836 - 1849 <br />T. Meissner + F. Wentz, IEEE TGRS, under review<br />
  7. 7. Ocean Surface Emissivity Model (cont.)<br />Measured minus computed WindSat TB as function of SST (x-axis) and wind speed (y-axis).<br />
  8. 8. Overview: RSS Version 7 Ocean Products<br />Intercalibrated multi-platform suite.<br />100 years of combined satellite data.<br />Climate quality.<br />DMSP SSM/I, SSMIS<br />F8, F10, F11, F13, F14 ,F15, F16, F17<br />TRMM TMI<br />AMSR-E, AMSR-J<br />WindSat<br />V7 released<br />V7 release in progress<br />QuikSCAT<br />
  9. 9. RSS WindSat Version 7 Ocean Products<br />Optimized swath width by combining forand aft looks at each band.<br />
  10. 10. New in V7 Radiometer : Winds Through Rain<br />Version 6: Rain areas needed to be blocked out.<br />Version 7: Rain areas have wind speeds.<br />C-band (7 GHz) required: <br />WindSat, AMSR-E, GCOM<br /> Possible with only X-band (11 GHz): TMI, GMI.<br />Residual degradation in rain.<br />
  11. 11. WindSat Wind Speed Algorithms<br />No-rain algorithm (≥10.7 GHz, 32 km res.)<br />Physical algorithm.<br />Trained from Monte Carlo simulated TB. <br />Based on radiative transfer model (RTM).<br />Wind speed in rain algorithms (≥6.8 GHz, 52 km res.) <br />Statistical or hybrid algorithms<br />Trained from match-ups between measured TB and ground truth wind speeds in rainy conditions.<br />Utilizes spectral difference (6.8 GHz versus 10.7 GHz) in wind/rain response of measured brightness temperatures.<br />Same method is used by NOAA aircraft step frequency microwave radiometers (SFMR) to measure wind speeds in hurricanes.<br />Radiometer winds in rain: <br />T. Meissner + F. Wentz, IEEE TGRS 47(9), 2009, 3065 - 3083 <br />
  12. 12. WindSat All-Weather Wind Speeds<br />Blending between no-rain, global wind speed in rain and H-wind (tropical cyclones) algorithms. <br />Depends on SST, wind speed and cloud water.<br />Smooth transitions between zones.<br />L=0.2 mm<br />W=15 m/s<br />H-Wind Algo<br />(tropical cyclones)<br />No-Rain Algo<br />SST=28oC<br />SST<br />Global Rain Algo<br />Wind Speed<br />Liquid Water<br />
  13. 13. WindSat Wind Speed Validation<br />2-dimensional PDF: WindSat versus CCMP (cross-calibrated multi-platform) wind speed.<br />Rain free and with rain.<br />
  14. 14. WindSat Wind Validation at High Winds (1)<br />Renfrew et al. QJRMS 135, 2009, 2046 – 2066<br />Aircraft observations taken during the Greenland Flow Distortion Experiment, Feb + Mar 2007.<br />150 measurements during 5 missions.<br />Wind vectors measured by turbulence probe.<br />Adjusted to 10m above surface.<br />
  15. 15. Improved QuikSCAT Ku2011 GMF: Purpose<br />Improvement at high wind speeds.<br />When RSS Ku2001 was developed (Wentz and Smith, 1999), validation data at high winds were limited. <br />GMF at high winds had to be extrapolated. <br />Analyses showed Ku2001 overestimated high winds. <br />WindSat wind speeds have been validated.<br />Confident up to 30 – 35 m/s.<br />Emissivity does not saturate at high winds. Good sensitivity.<br />Excellent validation at low and moderate wind speeds < 20 m/s (Buoys, SSM/I, CCMP, NCEP,…), > 20 m/s: Aircraft flights.<br />WindSat can be used as ground truth to calibrate new Ku-band scatterometer GMF.<br />Produce a climate data record of ocean vector winds. <br />Combining QuikSCAT with other sensors using consistent methodology.<br />
  16. 16. Improved QuikSCAT Ku2011 GMF: Development<br />The GMF relates the observed backscatter ratio σ0 to wind speed w and direction φat the ocean’s surface.<br />To develop the new GMF we used 7 years of QuikSCAT σ0 collocated with WindSat wind speeds (90 min) and CCMP (Atlas et al, 2009) wind direction. <br />WindSat also measures rain rate, used to flag QuikSCAT σ0 when developing GMF. <br />We had hundreds of millions of reliable rain-free collocations, with about 0.2% at winds greater than 20 m/s.<br />
  17. 17. Ku2001 versus Ku2011<br />Greenland Aircraft Flights<br />Ku2001Ku2011<br />Ku2001Ku2011<br />A0<br />A2<br />
  18. 18. Rain Impact: WindSat/QuikSCAT vs Buoys<br />Table shows WindSat/QuikSCAT – Buoy wind speed as function of rain rate (5 years of data)<br />
  19. 19. Rain Impact: WindSat/QuikSCAT/CCMP<br />Figures show WindSat – CCMP and QuikSCAT – WindSat wind speeds as function of wind speed and rain rate.<br />5 years of data.<br />No rain correction for scatterometer has been applied yet.<br />With only single frequency (SF) scatterometer (QuikSCAT, ASCAT) it is very difficult to <br />Reliably flag rain events<br />Retrieve rain rate which is needed to perform rain correction<br />
  20. 20. Rain Impact on Scatterometer: Caveat<br />Rain impact depends on rain rate + wind speed:<br />At low wind speeds: QuikSCAT wind speeds too high in rain.<br />At high wind speeds: QuikSCAT wind speeds too low in rain.<br />Important: Correct GMF at high wind speeds.<br />Ku2001 wind speeds too high at high wind speeds.<br />Accidental error cancellation possible in certain cases.<br />
  21. 21. WindSat all-weather wind<br />QuikSCAT Ku 2011 wind<br />Hurricane Katrina08/29/2005 0:00 Z<br />HRD analysis wind<br />WindSat rain rate<br />
  22. 22. Active vs Passive - Strength + Weaknesses<br />WindSat and QuikSCAT V7 Data Sets available on www.remss.com<br />+ +very good<br />+ slightly degraded<br />strongly degraded / impossible<br />Assessment based on operating instruments:<br />Polarimetric radiometer (WindSat).<br />Single frequency scatterometer (QuikSCAT, ASCAT, Oceansat).<br />

×