IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA Calibration of localization biases for SMOS François Cabot 1 , Yann Kerr 1 , Philippe Richaume 1 and Philippe Waldteufel 2 (1) CESBIO, 18, Av E Belin 31401 TOULOUSE CEDEX 9 FRANCE (2) IPSL/SA, 91371 Verrières le Buisson, FRANCE
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FR1.L10.2: CALIBRATION OF LOCALIZATION BIASES FOR SMOS
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IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
Calibration of localization biases for SMOS
François Cabot1, Yann Kerr1, Philippe Richaume1 and Philippe Waldteufel2
(1) CESBIO, 18, Av E Belin 31401 TOULOUSE CEDEX 9 FRANCE(2) IPSL/SA, 91371 Verrières le Buisson, FRANCE
IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
Outline
System level performances as assessed during commissioningGeolocation biases assessment – Best Fit Plane calibration
although higher bias than expected, calibration has been achieved up to required accuracy
Geolocation accuracy – impact at soil moisture levelpreliminary assessment shows we are moving in the right direction, but thorough cal/val results will be needed for final analysis
Equivalent Array Factor – spatial resolution confirmationIn close agreement with expectations, and validated making use of RFI
Radiometric accuracy verification for Land scenesConsistent with theory, and used as such for soil moisture retrieval
Absolute accuracy of brigthness temperaturesDome C results extremely promising, finer analysis still needed.
Instrumental model used for geolocation assessment includes Blackman rmax parameter.
Retrieved parameter compares well with theoretical resolution, as computed at L1C:
Retrievals proved to be very stable with time.
(km) rmax
std(rmax)
Semi axis (-3dB)
Semi axis in L1C
Ascending
46.7 3.1 18.9 22.0
Descending
45.6 2.0 18.4 19.2
IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
Ground resolution from RFI sourcesMadagascar results can be cross validated making use of
RFI (assumed to be point sources)
A1 (km)
A2(km)
From L1C
45.6 24.8
36.5 23.1
From RFI source
43.5 22
31.5 25
IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
Geolocation impact on Soil Moisture
Same product processed with/without biases correction
Brightness temperature impact less than 3K
SM impact low on average
Coastal zones and high surface variations show higher impacts
Overall statistics suggest better retrieval. Finer analysis over anchor sites still on-going.
Mialon A., 2010
IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
Antarctica around Dome Concordia
• Antarctic plateau around Dome C appears a very good candidate for stability monitoring and across fov consistency check
IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
System level performances
• Average brightness temperature over Antarctic Plateau
IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
System level performances
• Noise level consistent with expectations
pre launch simulations
IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
Antarctica around Dome Concordia
Dome C only, Hallikainen model (one layer, Tsnow=-54)
Tv Domex-2 operative 2009
Th Domex-2 operative 2009
Th Domex-2 Initial 2009
Tv Domex-2 Initial 2009
Tv domex2010
th domex2010
DomeX data, G. Macelloni
IGARSS 2010 – 25/30 july 2010, Honolulu, HI, USA
Summary
System level performances as assessed during commissioningGeolocation biases assessment – Best Fit Plane calibration
although higher bias than expected, calibration has been achieved up to required accuracy
Geolocation accuracy – impact at soil moisture levelpreliminary assessment shows we are moving in the right direction, but thorough cal/val results will be needed for final analysis. Long-term trends will be monitored.
Equivalent Array Factor – spatial resolution confirmationIn close agreement with expectations, and validated making use of RFI
Radiometric accuracy verification for Land scenesConsistent with theory, and used as such for soil moisture retrieval
Absolute accuracy of brightness temperaturesDome C results extremely promising, finer analysis still needed.