Scatterometer Calibration. Alex Fore

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Whitney Foster
5 years ago
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1 Scatterometer Calibration Alex Fore

2 Overview Bias correction factor Antenna pattern correction Faraday Rotation correction Future work

3 Bias Correction By comparison of our σ 0 model function to PALSAR HH model function we determined that we have an approximate 1.5 gain bias. Gain bias is the same for all beam. The 1.5 factor was introduced in the V1.2 data processing.

4 No Bias Correction Applied (V1.1) data Bias Correction Applied (V1.2) data

5 Antenna Pattern Correction Changes: V1.2 data includes an APC that was trained using the theory/simulated antenna patterns. V1.1 data used an APC based on the scale-model antenna patterns. APC Derivation: Make forward simulated data with nominal antenna model. Make forward simulated data where cross-talk explicitly set to zero in beam integration. (This was done in a way to conserve total σ 0 at level 2). Perform a least-squares fit of the HV σ 0 in the absence of cross-talk to a simple distortion model. Perform a second least-squares fit to determine how to distribute the remaining σ 0 into the co-polarized channels. Yields an explicit 3 parameter (α, β, γ) fit for each beam Simplified Distortion Model: σ noxtalk HV = σ xtalk HV + ασ xtalk xtalk HH + βσ VV A = 2 σ HV ( xtalk noxtalk σ ) HV σ noxtalk HH = σ xtalk HH + ( 1 γ)a σ noxtalk VV = σ xtalk VV + γa

6 Coupling Coefficients in Antenna Pattern Correction The APC derived from the theory patterns has significantly less coupling between co-pol and cross-pol than that derived from the scalemodel patterns. Coupling Coefficients used in APC correction matrix Scale-Model Theory/Simulated HV/HH HV/VV HV/HH HV/VV Beam db db db db Beam db db db db Beam db db db db

7 V1.1 Data

8 V1.2 Data

9 Faraday Rotation Correction Changes: V1.2 uses a scaled VTEC, obtained from the TEC data files. Constant scale factor 0.75 is used. V1.1 used all the TEC in the TEC data files. Inputs: Predicted Farday rotation angle. Observed HH, HV, VV σ 0. Estimated HHVV correlation; HV/VV and HV/HH ratios. Method Non-linear measurement model. Minimize cost function to solve for Faraday rotation corrected σ 0 (σ 0 true below). Obtain σ 0 HV via conservation of total σ 0. σ M HH Measurement Model: = σ true HH cos 4 θ F +σ true VV sin 4 θ F 2ρ HHVV cos 2 θ F sin 2 θ F σ true true VV σ HH Cost Function ( ) = # σ ipol J σ true true HH,σ VV ipol=hh,vv! # "! obs ln σ obs $ $ ipol # M " σ & & ipol %% 2 σ M VV = σ true HH sin 4 θ F +σ true VV cos 4 θ F 2ρ HHVV cos 2 θ F sin 2 θ F σ true true VV σ HH σ M HV true ( ) + σ true HH +σ VV = 1 2 f HHHVσ true HH + f VVHV σ VV true + 2ρ σ true σ true ( HHVV VV )cos 2 θ HH F sin 2 θ F

10 Contour plot of σ 0 HH ANT and TOA versus NCEP speed and predicted Faraday rotation angle. -V1.2 data -Ocean only data. -TOA quantities should only have residual correlation with Faraday rotation, given a constant wind speed. (such as to northern hemisphere/southern hemisphere geophysical differences, for example). -We see significant flattening of the iso-contour lines in the TOA data, indicating Faraday rotation correction is having the desired effect.

11 Contour plot of σ 0 VV ANT and TOA versus NCEP speed and predicted Faraday rotation angle. -V1.2 data -Ocean only data. -TOA quantities should only have residual correlation with Faraday rotation, given a constant wind speed. (such as to northern hemisphere/southern hemisphere geophysical differences, for example). -We see significant flattening of the iso-contour lines in the TOA data, indicating Faraday rotation correction is having the desired effect.

12 Contour plot of σ 0 HV ANT and TOA versus NCEP speed and predicted Faraday rotation angle. -V1.2 data -The HV channel is far more sensitive than the HH or VV channels to Faraday rotation due to much smaller geophysical signal in cross-pol. -We see some flattening of the iso-contour lines in the TOA data, indicating Faraday rotation correction is having the desired effect. -Clearly there are improvements that can be made.

13 Summary and Future Work Summary: We have shown that a multiplicative factor of 1.5 gives fairly good overall agreement with PALSAR for all 3 beams. We have improved the HV channels in the V1.2 dataset as compared to the V1.1 data. We have demonstrated that Faraday rotation correction has improved HH and VV NRCS significantly. Future Work: Bias Correction Possibly refine bias correction estimate per beam and polarization. Antenna Pattern Correction Verify that the APC based on theory patterns is improving the HV and VH channels. Faraday Rotation Correction Validate model-based TEC scale factor code. Validate faraday rotation correction model /assumptions used in model. Transition to radiometer based Faraday rotation angle estimate.

14 BACKUP SLIDES

15 L2 Processing Flow L1B geolocated, calibrated TOI σ 0 Average over block; filter by L1B Qual. Flags L2 (lon, lat) L2 σ TOI + KPC L2 σ TOA + KPC Cross-Talk + Faraday Rotation Ancillary Data: -ρ HHVV, f HHHV, f VVHV -Θ F (from rad or IONEX) Wind Retrieval L2 wind + σ wind Ancillary Data: -NCEP wind dir. ΔT B retrieval Ancillary Data: -PALS HIGHWINDS 2009 data L2 ΔT B + σ ΔTB

16 L2 Faraday and Cross-Talk Mitigation Process Flow TOI: (σ HH, σ HV, σ VV ) Cross-Talk Correction Explicit fit trained on antenna patterns Cross-Talk Corrected: (σ HH, σ HV, σ VV ) Ancillary Inputs: Faraday rotation angle -radiometer -IONEX PALS HIGHWINDS data 2d non-linear minimization problem Faraday Rotation Correction Assumptions: (ρ HHVV, f HHHV, f VVHV ) per beam. TOA: (σ HH, σ HV, σ VV )

Scatterometer Algorithm

Scatterometer Algorithm Algorithm Seattle Simon Yueh, Alex Fore, Adam Freedman, Julian Chaubell Aquarius Algorithm Team Outline Key Requirements Technical Approach Algorithm Development Status L1A-L1B L1B-L2A Post-Launch Cal/Val