Analysis of L-band radiometric measurements conducted over the North Sea during the CoSMOS-OS airborne campaign

Transcription

1 Analysis of L-band radiometric measurements conducted over the North Sea during the CoSMOS-OS airborne campaign Nicolas Reul*, Joseph Tenerelli** & Sebastien Guimbard * *IFREMER ** BOOST Technologies, Brest, France With the contributions from Catherine Bouzinac ESA Niels Skou TUD Estel Cardhellac IEEC Many Other Folks from IFREMER, ESA, TUD, TKK, NERSC, IEEC

2 Outline I. CoSMOS-OS campaign main objectives II. III. IV. Overall campaign presentation Instrumentation Site and Flight types Overview of geophysical conditions Data Processing Observation and model validation results Wind speed & roughness dependencies Sunglint Azimuthal signatures V. Summary

3 CoSMOS-OS Objectives Support validation of the SMOS Level 2 prototype processor critical sub forward models: Sea surface Roughness impacts Galactic and sun glints contaminations L-band Multi-angular dependencies over the sea Investigate physical sources for reported azimuthal wiggles in the previously measured Tb azimuthal signals (LOSAC, JPL,..): Original hypothesis for the wiggles: rough sea surface scattering of galactic reflections, signatures of spatial heterogeneities in surface roughness (internal wave signatures, mesoscale activity due to wave interaction with current or bathymetry, slicks,..)

4 The aircraft: HUT Skyvan -Specs- Typical airspeed range km/h ( knots). Maximum/Cruising speed278 km/h (150 knots). Max. range: 1200 km, (980 km + 45 min reserve). Flight max. duration: 4 hours (3h 15 min + 45 min reserve). Maximum altitude 3000 m standard, 6000 m with oxygen (5500 m recommended) Max. take off weight 5670 kg. Payload: 1800 kg (700 kg with full tank). Max. payload on rear cargo ramp 180 kg. Max. payload in rear cargo area 450 kg. Navigation unit for measurement flights: DGPS, 2 m accuracy, independent recording. GPS/INS Output rate 10hzAccuracy: 1 mrad (attitude), 1.5 mrad (heading).

5 CoSMOS onboard instruments GOLD-RTR GPS reflectometry system on aircraft. σ o (L-band), L-band mss IR radiometer on aircraft:.=>sst

6 Experiment Area and why?

7 Experiment Area and why? 110 km apart from 2 oil rigs along a Ferry Box line Crossing strong SSS front 3-4 psu then reaching homogeneous area Mean 3.5 psu Ferry measured SSS front

8 Baseline for the 12 Flights 8 night-time flights, focus on circle patterns performed over the target area between Ekofisk and SleipnerA, exhibiting maximally uniform SSS & SST conditions. => flights dedicated to galactic glint, wiggles and roughness impact studies 4 day-light morning flights: dives+ circle patterns in the same area than night-time circles =>flights dedicated to sunglint impact study Wing and nose wags patterns conducted at each night-time flight => dedicated to antenna specification post-calibration 6 Flights over 12 (3 night-time and 3 day time) were best co-located with ENVISAT/ASAR overpasses. Make use of the numerous straight-line flight legs from Stavenger to circle flight site to tentatively retrieve the SSS front from averaging procedure

9 Auxilliary Data and Overview of Geophysical conditions during CoSMOS

10 Auxilliary Data & Sources SleipnerA: MIROS wave radar. (scanning radar providing information on directional distribution of spectrum)+météorological station: wind, waves, meteo Ekofisk: WaMoS radar, vertical radar, waverider buoy. wind, waves, meteo, SST FerryBox System: low-cost opportunity observations on commercial ships. Norwegian Institute for Water Research=> SSS, SST ENVISAT/ASAR data flights coordinates with overpasses: σ o (C-band), wind, waves, currents Hycom model daily data (SSS, SST & currents at 5x5 km) GOLD-RTR GPS reflectometry system on aircraft. σ o (L-band), L-band mss Met data from Norwegian Meteorological Institute (Hirlam, rain radar ) wind, meteo, rain Dedicated CoSMOS Merged & analysed Satelitte (SST) Solar Fluxes at 1.4GHz (NODC)

11 Consistency Surface between Salinity various and Temperature SSS & SST during products CoSMOS MEAN SSS Mean SST 2.5 psu Hycom not reproducing the high spatial variability in SSS observed by the Ferry Show a smaller SSS dynamic =>front strongly smoothed out by Hycom Constant bias of about 1 C during the whole campaign between Ferry and SAT SST. Hycom consistent with SAT Aircraft IR data not yet considered

12 Impact of SSS & SST products uncertainties on Flat sea Tbs Uncertainties in SSS & SST from aux data have: little impact less than 0.2 K In circle flight area For both antenna Potential ~1K impact in coastal current zone

13 Wind products for CoSMOS-OS HIRLAM 6 hourly EKOFISK SLEIPNER NCEP 6 hourly ASAR ±2m/s

14 Mean Wind Conditions encountered for each CoSMOS flight Wind speed Wind direction Wind speed ranged from about 1 m/s to ~15 m/s during the acquisitions most acquisitions at moderate winds between 4 and 10 m/s 19 th & 29 th are calm wind days < 4 m/s 9 th & 22 nd are windy days > 11 m/s Dominant (North) Westerly winds

15 The CoSMOS-OS Data Processor Terrestrial Radiometry Airborne Package: TRAP-0.1

16 Analysis Methods Calculation of observation geometry for each -3dB antenna lobe along track from the INU/GPS data Collocation with auxilliary data: (using the Ferry box data as «a priori» SSS) Application of forward models at surface levels: Dielectric constant (Klein and swift) Emissivity of order 0 (flat sea) Delta of emissivity due to roughness:spm/ssa, Kirchhoff, 2-scale Delta of emissivity due to foam Transport surface-> antenna Atmospheric attenuation Celestial contributions : galactic & solar radiation scattering Polarization mixing from surface to antenna basis Weighting by antenna gain patterns Transport measured and model antenna Tbs to surface projected at boresight Comparison Tbmes-Tbmodel Scientific Analysis

17 Geometry of the problem

18 Theoretical gain patterns for CoSMOS pottern horns

19 Baseline Grid and Gain Pattern for Forward Modeling System

20 FORWARD modeling at sea target level At each line of sight targets of the discretized antenna patterns: =>Application of SMOS L2PP forward models at surface levels: Dielectric constant (Klein and Swift) Emissivity of order 0 (flat sea) Delta of emissivity due to «roughness»:ssa/spm & two-scale models Delta of emissivity due to «foam» Scatterered (+flat) SUN «Sunglint» Scattered (+flat) GALACTIC «Galactic glint» + Reflected Downwelling atmospheric contributions using Liebe model applied to 3D NCEP fields +direct sun & moon

21 Transport model results from sea target to antenna level Integration over pattern

22 Transformation of both data and model results derived at antenna level To surface level Projected at boresight: pseudo Surface Stokes pseudo Stokes=antenna measurements & models expressed in an earth basis reference frame

23 The Wags Post-Calibration

24 Analysis of Wing and nose wags patterns Antenna viewing geometry Incidence scans From 0 to 60 having both antennas With overlaps But limited ranges in azimuths

25 Analysis of Wing and nose wags patterns Inconsistent 2 branch behaviour in nadir antenna Developped specific calibration procedure (see report & ppt of ESTEC 27/02 meetin +4 K constant offset adjustement on Qxy=Ty-Tx, i.e.: Ty+2 & Tx-2 for the nadir ant

26 Both antenna data (after post-calibration at low winds) for all night-time wags Data (colors) L2PP model (black curves) Model-free Calibration results look consistent and robust Very important to consider impact of antenna pattern smoothing in V- pol at large incidences (~5 K!)

27 Science Results

28 I. Roughness dependencies

29 Two antennas & Wags=>Full Mutli-incidence L-band sensing from a classical airborne radiometer system! Observed Wind Speed & incidence dependencies All wags DATA Wind Speed m/s

30 Detailed Measured Wind Speed & incidence dependencies Wind Speed dependencies H-pol V-pol 2 roughness regimes at nadir at both polarization: 1) Almost roughness independence for U10< ~7-8 m/s 2) leveling off for U10> ~7-8 m/s V-pol =>dtb/du slopes are a STRONG function of wind speed interval & incidence angle => Assumed Linear dependencies from 0-12 m/s are wrong models

31 Detailed Measured Wind Speed & incidence dependencies Wind Speed dependencies H-pol V-pol 3 roughness regimes at moderate incidences growth< 6-7 m/s Plateau or for 6-7<U10<8-9 m/s leveling off 0 for U10> ~9-10 m/s V-pol Polarization independent at 15 but not at 40

32 Comparison with L2PP fowards roughness emissivity models Two-scale All wags SSA/SPM DATA model Wind Speed m/s To small dynamic in the L2PP roughness forward models?

33 Comparisons wind speed linear slopes over 0-12 m/s Interpolated linear slopes dtb/du between 0 and 12 m/s K/(m/s) Apparent underestimation Of the roughness impact by the SSA/SPM Rough surface emissivity model Data H-pol Data V-pol SSA/SPM 2 scale model predictions agrees better in H- pol but not at V-pol and incidences >30 2-scale

34 K/(m/s) Detailed Comparison with L2PP roughness models Light to moderate winds 0-7 m/s: SSA/SPM better than 2-scale which overestimates in the range 0-20 Both models underestimate for incidences > 20, 2-scale better Moderate winds 4-11 m/s SSA/SPM ok almost everywhere for incidences <60 2-scale overstimate in the range 0-60 Higher winds > 8 m/s Both models strongly underestimate roughness impact at all incidences: SSA/SPM by a factor ~3; 2-scale by a factor ~2 Foam impact?

35 Overall roughness dependencies 1) Sensitivities to wind speed (dtb/du slopes) are observed to be STRONG functions of wind speed interval & incidence angle 2) Assumed Linear dependencies with U10 from 0-12 m/s are wrong models And shall not be used for forward model validation 3) Interesting roughness independence for U10< ~7-8 m/s & incidences < 20 SSA-SPM model in better agreement than 2-scale which overestimates in that range 4) For low to moderate winds < 8 m/s, Both models underestimate H-pol for incidences > 20, 2-scale better than SSA- SPM model but large dispersion in data 5) For higher winds > 8 m/s Both models strongly underestimate roughness impact at moderate to high winds and at all incidences. Problem with Foam Impact? RFI?

36 II. Sunglint contamination

37 Sunglint contamination Circle and Dives patterns from the view point of bistatic scattering

38 1.4 GHz Brightness Temperature of the Sun from NODC 1 s Fluxes Learmonth( Australia) exhibit K consistently higher Tsun by ~33% Compared to San Vito (ITalia) = K & Sagammore (USA)

39 Sunglint contamination Circles Azimuth angle scans through the bistatic glint at ~10 off specula Max at the Right location: Correct Geometry! Galactic glint

40 Sunglint contamination From the sunglint point of view, The Kirchhoff model is systematically underestimating the glint within the specular regime Too high scattering Attenuation: Too high mss? Too low Tsun?

41 Sunglint contamination Dives scans through the bistatic glint incidence plane Wind speed m/s Wind speed m/s Data Data Model Model Circles Sun specular The scattering model is systematically underestimating the glint every where in the incidence plane both in H & V =>Too much reflectivity spreading & attenuation: pb with scattering model, surface model, Tsun?

42 Sunglint contamination Sunglint assuming flat sea Data Data Data indicate significant roughness impact vs flat sea contribution, =>adjustement to make for improving bistatic is in a plausible physical range around specular (0-15 ) Scattering model Roughness model: non gaussianity? Far from specular (15-30 ), even the flat surface is not sufficient

43 Sunglint contamination To get a better estimate of sunglint residual: make use of the data alone: => Empirical fits through data during dives with antenna pointing 180 from the sun

44 Sunglint New sunglint residuals contamination V-pol H-pol

45 Sunglint contamination Better agreement model with data but there are still problems : two small mss to get match and keep consistency with GPS retrievals & lack of peakidness in the model! => Non gaussianity in the surface scatterer statistics at L-band?

46 Sunglint contamination Conclusions on sunglint models: Sunglint Kirchhoff/SSA-1 scattering model consistently overestimates roughness impact The model clearly lack peakidness Weak impact of choosing 2 different spectral models Difficult interpretation due to strong impact of antenna pattern smoothing & potential errors on the sun Tb However, non gaussian surface statistics applied to GO model gives acceptable match up if one assume there are 30-40% offsets in the sun brightness temperature estimates: Are scattering wave slopes pdf non gaussian at L-band in the general case?

47 III.Azimuthal variations, Wiggles & Galactic Glint issues

48 Observed Wiggles Dominant Wiggles (wags) Small Wiggles (circles) Dominant wiggles from few k to about 70 K amplitudes due to large Incidence angle variations within +/-20 arond nominal incidence Well reproduced by model but may be small residual errors in geometry Small wiggles from Less than 0.5 K: roughness? galactic glint? Other Some Consistency from one circle to the other

49 Galactic Glint and Wiggles small winds & cold sky sources bright spots «Flat Surface Glitter model» ok Although residual wiggles ~0.2 K still there but not consistently At bright spots, and strong winds accounting for the roughness impact in galactic glint is needed, Assumming flat sea=> overestimation ~0.5 K

50 Galactic Glint and Wiggles Linear polarization Low wind Significant problems In restituting V- polarized Signatures High wind

51 Azimuthal variations L2PP Model predictions

52 Azimuthal variations SSA-SPM-data: strong residual azimuthal wind direction dependence!

53 Azimuthal variations 2scale-data: much weaker residual azimuthal wind direction dependence!

54 Azimuthal variations Data alone: no wind direction dependent signature Only galactic glint signature SSA/SPM clearly overestimate azimuthal variations at L-band: problem with spectrum model

55 Azimuthal variations, Wiggles & Galactic Glint issues Conclusions Small residual wiggles < 0.5 K mostly due to HF incidence angle changes Galactic glint model working well at low & high winds & cold and hot spots for First stokes But problems in dual pol contributions Clear overestimations of azimuthal variations <0.5 K by ssa/spm model Two-scale much better Data do not exhibit azimuthal wind direction dependent signals but only galactic glint signatures

56 VI. Summary, Conclusions & perspectives

57 Summary and conclusions CoSMOS Data Analysis results 1) Analysis of multi-auxilliary data for Synergetic analysis of CoSMOS campaign data 2) Complete aircraft L-band data Processor mimiking L2PP built up: => Can be used for future (or past) aircraft data (re-)analysis 3) Post-calibration of antenna data methodology developped Model free and only concepts-based method using Q and I Stokes parameters Emphasize the strong interest of having both Nadir and aft-looking antenna 4) Demonstration of strong interest for using Two airborne antennas & Wags patterns =>very usefull for Full Mutli-incidence L-band sensing and therefore SMOS calibration/validation

58 Summary Roughness Impact and L2PP forward models validatio 1) Sensitivities to wind speed (dtb/du slopes) are observed to be STRONG functions of wind speed interval & incidence angle 2) Assumed Linear dependencies with U10 from 0-12 m/s are wrong models And shall not be used for forward model validation 3) Interesting roughness independence for U10< ~7-8 m/s & incidences < 20 SSA-SPM model in better agreement than 2-scale which overestimate in that range 4) For low to moderate winds < 8 m/s, Both models underestimate H-pol for incidences > 20, 2-scale better than SSA- SPM model but large dispersion in data 5) For higher winds > 8 m/s Both models strongly underestimate roughness impact at moderate to high winds and at all incidences. Problem with Foam Impact? RFI? 6) GPS and Radiometer data show consistency with respect to model results

59 Summary Sunglint contamination 1) Sunglint Kirchhoff/SSA-1 scattering model systematically overestimates roughness impact Problems in surface description for long waves (spectrum, non gaussianity)? Likely also associated with Tsun estimate 2) Apparent contradiction with surface emissivity model mss dependence which tends to show too small model mss However, emissivity is small scale dependent while partial reflectivity is much more long waves dependent: Problems on modeling the scale distribution of roughness (Hs =1 m)? Problems on the directional distribution of roughness? ) Need for dedicated measurements with much narrower antenna beam

60 Summary Galactic Glint, wiggles & azimuthal signatures 1) Total power model does not always exhibit systematic «wiggeling» differences with Data 2) Wiggles are however observed in linear polarization: H-pol data exhibit higher amplitude wiggles than model V-pol data exhibit lower amplitude wiggles than model Potential hypothesis: (i) (ii) (iii) (iv) (v) sky sources polarization issues Roughness patchniness Small Errors in geometry angles Antenna pattern anisotropy Polarization ports cross-talking 3) Galactic glint corrections need to account for roughness impact at bright spots Proposed Model seems ok In cold sky =>flat sea surface model ok

61 Galactic Glint, wiggles & azimuthal signatures 3) Clear overestimations of azimuthal variations due to surface anisotropy by ~0.5 K by ssa/spm model Two-scale much better 4)Data do not exhibit azimuthal wind direction dependent signals but only galactic glint directional signatures

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63 V. SSS front signatures?

64 We Considered separatly inbound and outbound flight legs across the Norvegian Coastal current front

65 Consistency between various SSS & SST products MEAN SSS Mean SST 1.5 psu 3.5 psu Hycom not reproducing the high spatial variability in SSS observed by the Ferry Show a smaller SSS dynamic ~1.5 psu =>front strongly smoothed out by Hycom? => Expected ~2 K impact on 1 st Stokes Constant bias of about 1 C during the whole campaign between Ferry and SAT SST. Hycom consistent with SAT Front about 1 C as well => Expected ~0.5 K impact on 1 st Stokes

66 Roughness across the fronts observed by ASAR Highly variable roughness!

67 Roughness across the fronts: different predictions Results depend on wind speed auxilliary data used But Depend also on Forward model used!

68 Overall Modelled Tb contributions across the fronts

69 Fronts residual signatures in Tbs when assuming SSS hycom in forward emissivity model 04/10: consistent inbound/outbound with some indication of front east of 4.5 deg. 04/13: consistent inbound/outbound bet 3.8 E and 4.2 E. 04/16: another clean signal.

70 Fronts residual signatures in Tbs when assuming SSS hycom in forward emissivity model (SSA/SPM)

71 Summary SSS Fronts signatures 1) The SSS front is very sharp and the implied total power jump is only up to a few K, which we _consistently_ see in the crossings: the front is clearly in the brightness temperature data. => 5 flights/7 analyzed with consistently detected fronts consistent with FerryBox data 04/10: consistent inbound/outbound with some indication of front east of 4.5 deg. 04/13: consistent inbound/outbound bet 3.8 E and 4.2 E. 04/16: another clean signal. 04/19: low wind; consistent inbound/outbound 04/25: a good case with light winds and strong SSS signal 2) However Inbound and outbound results are not always consistent. 04/22: very windy; inconsistent inbound outbound; inbound crazy (wind impact swamps SSS signal) 04/29: as on 04/22; inconsistent inbound/outbound; no SAR; look at HIRLAM winds RFI seems to be a big problem, especially for outbound legs. The median filter removes some of this contamination but not all. Some of the inbound/outbound inconsistency may be related to roughness patches moving by.

72 Sources for polarized wiggles? Potential hypothesis: (i) sky sources polarization issues The Low-Resolution DRAO Survey of Polarized Emission at 1.4 GH Polarized Intensity Map V-polarized problem With Lewis An absolutely calibrated survey of polarized emission from the northern sky at 1.4 GHz M. Wolleben, T.L. Landecker, W. Reich, R. Wielebinski A&A, 2006, Vol. 448, pp Sampled Cosmos Area for the previous figures

73 Sources for polarized wiggles? Potential hypothesis: (ii) Roughness Patchniness?

74 Sources for polarized wiggles? Potential hypothesis: (iii) polarization ports cross talking AFT ANTENNA H-pol Aft antenna Roll=+15 Roll =-15 =>Systematic bias±1k as function of roll for the aft-antenna Nadir antenna

75 Sources for polarized wiggles? Potential hypothesis: (iii) antenna polarization mixing problems V U V

76 Potential hypothesis: (iii) antenna polarization mixing problems One calibration concern is non-zero Fourth Stokes parameter: May influence Third Stokes parameter which we want to use for antenna pointing calibration.

77 Third and Fourth Stokes parameters may become mixed due to port phase offset imperfection. Assuming no phase shift error we normally have or

78 The phase calibration method involves assuming non-random phase shift error added to random phase shift between ports: This leads to a rotation relationship between desired and actual Stokes 3 and 4: and so or

79 Here is the resulting phase shift error as function of aircraft roll for wags:

80 Impact on Third Stokes parameter:

81 Impact on the Yueh polarization rotation angle:

82 RFI issues

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