smos ocean salinity retrieval level 2 marco talone, jérôme gourrion, fernando martin porqueras,...

SMOS Ocean Salinity RetrievalSMOS Ocean Salinity RetrievalLevel 2Level 2

Marco Talone, Jérôme Gourrion, Fernando Martin Porqueras, Nicolas Reul, Joe Tenerelli, Marcos Portabella, and the SMOS

Barcelona Expert Centre (SMOS-BEC) Team

[email protected]

Course on Earth Observation Understanding of the Water CycleCourse on Earth Observation Understanding of the Water CycleFortaleza, BrasilFortaleza, Brasil, November 1-12, 2010, November 1-12, 2010

Course on Earth Observation Understanding of the Water Cycle Fortaleza, Brasil, November 1-12, 2010 2/46

Motivation


Ocean salinity monitoring: motivation/overviewOcean salinity monitoring: motivation/overview

• SSS variations governed by:• E-P balance • freezing/melting ice• freshwater run-off

• Key oceanographic parameter (density)• Thermohaline circulation and heat redistribution



Surface salinity distribution is closely tied to E-P patterns

10-m depth salinity field reconstructed from Argo floats data. There are still “holes” and spatial resolution is low

SSS time-series

Historical lack of SSS observations



Oceanographic models already assimilate SST and SSH from satellite data, while SSS is still climatologic

The absence of any specific treatment of salinity in ocean models can lead to significant errors:

• Near-surface currents errors [Acero-Schetzer et al., 1997]• Tropical dynamics [Murtugudde and Busalacchi, 1998] • Dynamic height difference [Maes et al., 1999; Ji et al., 2000] • Spurious convection [Troccoli et al., 2000]• ENSO predictions [Ballabrera-Poy et al., 2002]


SMOS, general features


SMOS satellite – general featuresSMOS satellite – general features

1.4 GHz, L-band (unique payload)• Optimum SSS sensitivity • Reasonable pixel dimension• Atmosphere almost transparent

• Full scene acquired every 2.4 s • Variable number of observations according to

the satellite sub-track distance • Different measurements of TB corresponding to

a single SSS under different incidence angles

• Synthetic Aperture Radiometer (MIRAS)• Sun-synchronous LEO orbit, 3 days revisit time• 69 elements array, Y-array: arms 120º apart• Field Of View (EAF FOV) about 1000 km • Dual-pol / Full-pol• Multi-angular capabilities• Spatial Resolution: 32 (boresight) - 100 km


SMOS satellite – Field Of ViewSMOS satellite – Field Of View

Radiometric Accuracy and Radiometric Sensitivity (quality of the measurement)

[calculated using SEPS]

Incidence Angle and Spatial Resolution [calculated using SEPS]

boresight

nadir


SMOS satellite – Field Of ViewSMOS satellite – Field Of View

Due to MIRAS geometry Nyquist criterion is not satisfied3 FOV can be defined:

• Hexagon resolved by MIRAS • Alias-Free FOV • Extended Alias-Free FOV

cossin sinsin


SMOS processing chain


SMOS processing chainSMOS processing chain

Level 1Level 0 Level 2 Level 3 Level 4

Data Assimilation

Measurements Observations Global map Data fusionRaw data


SMOS processing chainSMOS processing chain

Level 0 Raw dataLevel 1A Calibrated Visibilities

Level 1B TB Fourier components

Level 1C TB geocoded (ISEA4H9) Level 2 Salinity Maps (single-overpass)Level 3 Spatio-temporal averaged SSSLevel 4 Merged product

Scientific requirements for salinity retrieval

• Global Ocean Data Assimilation Experiment (GODAE, 1997) 0.1 psu, 200 km, 10 days

• Salinity and Sea Ice Working Group (SSIWG, 2000) 0.1 psu, 100 km, 30 days

• SMOS (Mission Requirements Document v5, 2002)0.1 psu, 200 km, 30 days

lower accuracy, higher resolution products (e.g. 100 km, 10 days or single passes) are useful for applications other than climate and large scale studies

ISEA DGGs (Discrete Global Grids)


From Level 1C to Level 3From Level 1C to Level 3

Level 1C Level 2 Level 3pre-

processingpost-

processing

quality control & filtering

SSSinversion

Level 1C

Level 1C


Level 1CLevel 1C

What does a radiometer measure?

Brecant kTTGV 0

G accounts for the receiver’s gain and the antenna pattern receiver temperature

Boltzmann constant

antT is the only term dependent on the observed scene

it is also referred as Apparent Temperature because sum of various contributions

appT


e

Level 1C - Forward Models Level 1C - Forward Models

APT

surface

atmosphere

ionosphere

BT COST UPTDNT e


Level 1C - Forward ModelsLevel 1C - Forward Models

flat sea contribution roughnesscontribution

Klein & Swift (1977) dielectric model at microwave frequenciesKlein & Swift (1977) dielectric model at microwave frequencies

TB sensitivity to SSS increases with SSTTB sensitivity to SSS increases with SSTThe total dynamic of TB is 2-4 KThe total dynamic of TB is 2-4 K

3 MODELS

Two-scale model IFREMER Brest, France

Small Slope Approximation (SSA) model LOCEAN, Paris, France

Empirical Model ICM, Barcelona, Spain

polTSSSSSTfRSSTpolT BrVHB ,,,,1,2

,


Level 1C - Forward ModelsLevel 1C - Forward Models

Brightness temperature as measured by SMOS

TXTY




processingpost-

processing


SSSinversion

Level 1Cpre-

processing

Level 2 pre-processing


Level 1C – Errors and inaccuraciesLevel 1C – Errors and inaccuracies

Several different phenomena contribute to the final

The main error sources for the SSS retrieval are:

antT

• The forward Tb models• The estimation of the antenna pattern• The estimation of the galactic noise• Radio Frequency Interference• Land contamination

Some of them are solved by pre- and post-processing techniques


Level 2 pre-processingLevel 2 pre-processing

Ocean Target TransformationOcean Target Transformation

Average instrumental spatial pattern spatial pattern against ocean target, to be subtracted from measurements prior to SSS retrieval.[J. Tenerelli, Tech Note, 2010]

orbithalfmodelSMOS TBTBOTT

)),(),((),(

• An accurate filtering of the snapshots must be applied to discard land land and/or Radio Frequency Interferences (RFIRFI) contaminations.

• Ascending Ascending and descending descending passes must be considered separately.

• Finally, many orbits many orbits are used to increase the robustness of the estimation.

INCLUDED IN THE CURRENT PROCESSING



Strong systematic patterns are found in SMOS TB measurements

Features are clearly associated to brightness temperature transition:Sky/LandAlias Free/Extended Alias Free Field of View



The use of a forward modelforward model can introduce error due to inaccuraciesinaccuracies in its definition

UnhomogeneitiesUnhomogeneities in the geophysical parametergeophysical parameter statistical distribution in the FOV affect the estimation of the OTT

Model-free OTT – X pol Model-free OTT – Y pol

INCLUDED IN THE NEXT REPROCESSING (july)



Histograms are calculated for all the pixel of the reconstructed brightness temperature image

(black lines).

A selection of the grid point used in the averaging is performed to homogenize all the histograms

the most internal one (red line)

Sea Surface Temperature

[°C]

Wind Speed

[m/s]



The average sea surface salinity, sea surface temperature, and wind speed inside the FOV are

shown for the standard OTT and the “homogenized” OTT.

STANDARD

HOMOGENIZED



STANDARD

MODEL-FREE

Model-free OTT – X pol

Model-free OTT – Y pol

Standard OTT – X pol

Standard OTT – Y pol

The difference between the “homogenized” and “no-homogenized” OTT.

1 - 2 °C for sea surface temperature

and 0.5 - 1 m/s for wind speed

up to 0.6 - 0.8 K (peak to peak) in the

estimation of the bias spatial pattern.



External Brightness Temperature CalibrationExternal Brightness Temperature Calibration

,))()(()( snapTBsnapTBsnapETB modelSMOS

Average instrumental temporal pattern temporal pattern (scene-dependent bias) against ocean target, to be subtracted from measurements prior to SSS retrieval.[Camps et al., Radio Science 2005]

IN TESTING PHASE



Radio Frequency Interference (RFI) Radio Frequency Interference (RFI)

Spurious stable or intermittent man-made interferences.Spurious stable or intermittent man-made interferences.

Receiver Co-Channel Interference + Receiver Adjacent Signal InterferenceReceiver Co-Channel Interference + Receiver Adjacent Signal Interference - the signal itself or its tails - the signal itself or its tails can fall within the receiver’s RF passband.can fall within the receiver’s RF passband.Receiver Out of Band InterferenceReceiver Out of Band Interference - the signal is outside the receiver’s RF passband, nevertheless - the signal is outside the receiver’s RF passband, nevertheless spurious signals due to the mixer stage. spurious signals due to the mixer stage. Transmitter Fundamental and Harmonic EmissionsTransmitter Fundamental and Harmonic Emissions - the Transmitter Transfer Function. - the Transmitter Transfer Function. Transmitter NoiseTransmitter Noise - thermal noise generated in the various stages of the processing. - thermal noise generated in the various stages of the processing. Transmitter IntermodulationTransmitter Intermodulation - local mixing of a transmitter’s output emission with that of another - local mixing of a transmitter’s output emission with that of another transmitter or any other component of the instrument. transmitter or any other component of the instrument.

Concerning SMOS the strongest interference come from Concerning SMOS the strongest interference come from WiFi networksWiFi networks and and RadarRadar

As expressed in the Technical Note on “L-band RFI detected in SMOS data over the world oceans” by As expressed in the Technical Note on “L-band RFI detected in SMOS data over the world oceans” by Nicolas Reul of IFREMER.Nicolas Reul of IFREMER.



By estimating the impulsional response of the RFI, this can be eliminated from the scene, as done for the Sun effects.

[Camps, 2010]INCLUDED IN THE NEXT

REPROCESSING (july)




processingpost-

processing


SSSinversion

Level 1Cpre-

processing Level 2


SSSinversion

Level 2


Quality control and filteringQuality control and filtering

Quality control is performed on both measurement and gridpoint Quality control is performed on both measurement and gridpoint basisbasis• Distance from the coast:

• Ice• Suspect ice• Heavy rain• Sea condition• Number of valid measurements• Sunglint• Moonglint• Galactic noise• position in the FOV:

• RFI

Land< 40 km40 km - 200 km> 200 km

AFEAFBorder FOVAliased FOV

OKRetrieved but FlaggedDiscarded


SSS InversionSSS Inversion

The problemThe problem

yobservationsobservations state variablesstate variables

forward modelforward model

nK x

The solutionThe solution

• exact algebraic solution,• relaxation,• least squares estimation,• truncated Eigenvalue expansion,• Bayes’ theorem,• etc …

– maximum likelihood,– maximum posteriori probability,– minimum variance,– minimum measurement error– etc …


SSS Inversion - theoretical backgroundSSS Inversion - theoretical background

APABPBAP

Bayesian approachBayesian approach

ttoot xPxyPyxP

knowledge about thestate variables

uncertainty of observations and forward model

tntfotonoofto dyxkyPyyPxkyPxyP

tnoofota xPxkyPyxPxP

ASSUMING AND INDEPENDENT (ERRORS UNCORRELATED) txPofP

posterior probability

xPa


SSS Inversion - theoretical backgroundSSS Inversion - theoretical background

Maximum Likelihood EstimationMaximum Likelihood EstimationErrors are generally assumed GaussianErrors are generally assumed Gaussian

xkyFOxkyxP no

Tnoa

1

2

1exp

1.1. Forward Model (GMF, Geophysical Model Function) Forward Model (GMF, Geophysical Model Function) is assumed perfect is assumed perfect

2.2. Errors are assumed uncorrelated Errors are assumed uncorrelated

0F

O is diagonalis diagonal

xPxP aa lnminmax

xkyFOxkyMLE noT

no 1

N

i meas

measmod

y

yy

NMLE

12

21


SMOS SSS InversionSMOS SSS Inversion

,

2

2

12

2

2

n p

priornn

N

i F

modi

measi

ni

ppFF

observables part part Background termBackground term

],,[ 10USSTSSSpn

SMOS Sea Surface Salinity Retrieval Cost FunctionSMOS Sea Surface Salinity Retrieval Cost Function

YB

XB

YB

XB

iTTI

TTF

/

is minimized iteratively2

02 ,, ppF priormeas pppF priormeas 02 ,,ppp 0 min

ppp 0

NO

YES

INITIALIZATION




processingpost-

processing


SSSinversion

Level 1Cpre-

processing Level 2


SSSinversion

post-processing Level 3

Level 2 post-processing


Level 2 post-processingLevel 2 post-processing

External Sea Surface Salinity CalibrationExternal Sea Surface Salinity Calibration

rec

situin

SSS

SSSCF

_

Correcting for the mean uncertainty introduced by the forward model inaccuracies as done for rain radar calibration (Seo and Breidenbach, 2002) using as ancillary in-situ database the ARGO array of buoys.[Talone et al., IEEE TGARS 2008]

reccorr SSSCFSSS

IN TESTING PHASE


Level 1C problems @Level2RFI

Galactic NoiseLand contamination


Level 1C problems @Level2 - RFILevel 1C problems @Level2 - RFI

North Pole case: RadarNorth Pole case: Radar

climatological SSS

Average SSS in April – ASCENDING PASSES Average SSS in April – DESCENDING PASSES

SOURCE anti-missile radar protection array from Alaska all along the Northern

Canada pointing to the horizon


Level 1C problems @Level2 Level 1C problems @Level2 - RFI- RFI

First Stokes’ parameter in brightness temperature (I=TX+TY). One-month averaging, only descending passes.

Retrieved SSS

Due to the signal processing in SMOS, a point strong source generates 60-degrees spaced tails60-degrees spaced tails, like a starstar.



Due to the signal processing in SMOS, a punctual strong source generates 60-degrees spaced 60-degrees spaced tailstails, like a starstar.

First Stokes’ parameter in brightness temperature, both the ascending and descending passes of the month of May



RFI has effects several kilometers from the source. Sources on land frequently affects SSS retrieval.

First Stokes’ parameter in brightness temperature, both the ascending and descending passes of the month of May


Galactic NoiseGalactic Noise

Very geographic, pass-type & incidence angle dependent

Scattering model for ocean surface reflection of downwelling celestial radiations

[Nicolas Reul, IFREMER, 2010]


Level 1C problems @Level2 – Land cont.Level 1C problems @Level2 – Land cont.

The image reconstruction algorithm in SMOS is almost a FFT. Any sharp transition introduce singularities and its inversion introduce errors. Land’s brightness temperature is 300 K, while the average sea surface brightness temperature is 120 K.


Level 2 Products


Level 2 ProductsLevel 2 Products

SMOS Level 2 User Data Product – UDP is available, one file per semi-orbit, on:

http://eopi.esa.int/esa/esa (a data request form must be filled first)

SM_OPER_MIR_OSUDP2_20101023T140558_20101023T145957_316_001_1.zip

SM_OPER_MIR_OSUDP2_20101023T140558_20101023T145957_316_001_1.HDRheader in XMLSM_OPER_MIR_OSUDP2_20101023T140558_20101023T145957_316_001_1.DBLbinary data file

startYYYYMMDDThhmmss

endYYYYMMDDThhmmss

procversion


Level 2 ProductsLevel 2 Products

Different programs are available to open, display, partially process, and export SMOS Level 2 data, among them:

BEAM software, including SMOS-box plug-in can be downloaded fromwww.brockmann-consult.de

Binary .DBL files can be read by using ad-hoc programs (C, Matlab, Fortran…), exported data can feed any program you are most used to (IDL, Matlab, ODV…)Details on DBL file structure can be found in the L2 Product Specification Document, on:www.smos-bec.csic.es


Level 2 ProductLevel 2 Product



• 3 retrieved SSS• 3 theoretical uncertainties associated to the 3 retrievals• Acard• theoretical uncertainty associated to the retrieval of Acard• Wind Speed • theoretical uncertainty associated to the retrieval of WS• Sea Surface Temperature• theoretical uncertainty associated to the retrieval of SST• Modeled Brightness Temperature at 42.5° pol H (surface)• theoretical uncertainty associated to TBH

• Modeled Brightness Temperature at 42.5° pol V (surface)• theoretical uncertainty associated to TBV

• Modeled Brightness Temperature at 42.5° pol X (antenna)• theoretical uncertainty associated to TBX

• Modeled Brightness Temperature at 42.5° pol Y (antenna)• theoretical uncertainty associated to TBY

• Control Flag: Several quality flags one for retrieval (4)• Dg_chi2: Retrieval fit quality index, one for retrieval (4)



• Dg_chi2_P: chi2 high value acceptability probability, one for retrieval (4)

• Dg_quality: Descriptor of SSS uncertainty, one for retrieval (4)

• Dg_num_iter: number of iterations until convergence, one for retrieval (4)

• Dg_num_meas_L1c: number of measurements at L1c• Dg_num_meas_valid: number of valid measurements

after discrimination• Dg_border_fov: number of grid-points at the border of the

FOV• Dg_eaf_fov: number of grid-points in the Extended

Alias-Free FOV• Dg_af_fov: number of grid-points in the Alias-Free FOV• Dg_sun_tails: number of grid-points affected by sun

reflection tails• Dg_sunglint_area: number of grid-points affected by sun

reflection• Dg_sunglint_fov: number of grid-points with reflected sun

in the FOV



• Dg_sunglint_L2: number of grid-points with reflected sun in the FOV, as computed at L2

• Dg_suspect_ice: number of grid-points with suspected ice • Dg_galactic_Noise_Error: number of grid-points affected by

galactic noise• Dg_galactic_Noise_Pol: number of grid-points affected by

polarized galactic noise• Dg_moonlight: number of grid-points with reflected

moonlight in the FOV• Science_Flags: several geophysical flags• Dg_sky: number of gridpoints with specular direction

toward a strong galactic source• Land_Sea_Mask: Land/Sea descriptor


SMOS Land Cover ToolSMOS Land Cover Tool

Tool from GMV to display and export SMOS product to Google Earth files



Exercise

Thank you!Thank you!

Course on Earth Observation Understanding of the Water CycleCourse on Earth Observation Understanding of the Water CycleFortaleza, BrasilFortaleza, Brasil, November 1-12, 2010, November 1-12, 2010

Marco Talone, Jérôme Gourrion, Fernando Martin Porqueras, Nicolas Reul, Joe Tenerelli, Marcos Portabella, and the SMOS

Barcelona Expert Centre (SMOS-BEC) Team

[email protected]


Interferometric Radiometer

The idea at the basis of interferometric radiometry is to synthesize a large antenna with a number of small ones. Output voltages of a pair of antennas (e.g. located at and ) is cross-correlated to obtain the so-called “visibility sample”:

11,YX 22 ,YX

tbtbGGBBk

vuVB

*21

2121 2

11,

The result is a potential degradation of the radiometric sensitivity in terms of a higher rms noise, on the otherhand a complete image is acquired in one snapshot, permitting to increase the integration time and improve the measurement quality. Nevertheless, the major advantage of interferometric radiometry is the multi-angular measurement: the output of an IR is, in fact, an image; this permits having several views under dierent incidence angles of the same point on the Earth before it exits from the Field of View

yxYYXXvu ,,, 12121123103806.1 HzJKkBwhere ,

B1 and B2 are the receivers' noise bandwidths, G1 and G2 the available power gains, and b1(t) and

b2(t) the signals measured by elements 1 and 2.

The complete set of the visibility samples is called a visibility map, and it is approximately the Fourier transform of the brightness temperature distribution of the scene. To invert this process the inverse Fourier transform can be applied as a first approximation (Camps et al., 1997) or a more sophisticated G-matrix inversion (Anterrieu and Camps (2008); Camps et al. (2008a))


RFI

FROM http://www.radioing.com/eengineer/rfi.html

1.0 Receiver Co-Channel Interference

This is defined as undesired signals with frequency components that fall within the receiver’s RF passband and are translated into the Intermediate Frequency (IF) passband via the mixer stage. The interfering signal frequency is equal to the sum of the receiver’s tuned frequency and one half of the narrowest IF bandwidth. These signals are amplified and detected through the same process as the desired signals; therefore, a receiver is very susceptible to these emissions even at lower levels.

Results: Receiver desensitization, signal masking, distortion.

2.0 Receiver Adjacent Signal Interference

This is defined as undesired signals with frequency components which fall within or near the receiver’s RF passband and are translated outside of the IF passband via the mixer stage. These signals must be of sufficient amplitude to produce non-linear effects within the receiver’s RF amplifier or mixer stages. Some of the resulting non-linear response signals may be converted to the IF passband frequency via the mixer stage where they are amplified and detected through the same process as the desired signals. These become similar to co-channel interference signals at this point. The undesired emissions which are translated outside of the IF passband may still pass through the remaining receiver stages, if at high enough levels to survive the out-of-passband attenuation. They may then be processed by the detector. The predominant response for this case is desensitization.

Results: Non linear effects in the RF or mixer stages producing receiver desensitization, intermodulation and cross modulation.


RFI


3.0 Receiver Out of Band Interference

This is defined as undesired signals with frequency components that are significantly removed from the receiver’s RF passband. High level signals may produce spurious responses in the receiver if mixed with local oscillator (LO) harmonics to produce a signal falling within the IF passband. The spurious responses result from the mixing of an undesired signal with the receiver’s LO. The amplitude of these responses is directly proportional to the level of the undesired signals prior to mixing with the LO. The spurious responses in a receiver usually occur at specific frequencies. Any other out of band signals are attenuated by the IF selectivity.

Results: An undesired response created by the mixing of an undesired signal with the LO. The undesired signals which mix with the LO and are capable of being translated to the IF stages are the spurious response frequencies. These frequencies and their interference power levels are a function of the receiver’s susceptibility to these responses.

4.0 Transmitter Fundamental Emissions

The transmitter’s fundamental output signal includes characteristics of the power distribution over a range of frequencies around the fundamental frequency. These are determined by the base-band modulation characteristics and are represented by a modulation envelope function. The primary parameter associated with the modulation envelope is the transmitter’s nominal bandwidth (3dB). This may be derived from the transmitter modulation characteristics (by Fourier analysis), measured, or from the manufacturer’s specifications. The power distribution in the modulation sidebands may be represented by a modulation envelope function showing the variation of power with frequency.


RFI


5.0 Transmitter Harmonic Emissions

The main concern with a transmitter’s harmonic emissions is the undesired signal outputs which are harmonically related to the fundamental signal rather than to other oscillator circuits. The relative power associated with the harmonic emissions may be modeled using data for the particular transmitter type. However, since harmonic output power can vary considerably from one transmitter to another for the same type and model, it should be represented statistically. Harmonic emission models may be derived from statistical summaries of measured data or from manufacturer’s equipment specifications. Transmitter spurious emission models for prediction of frequencies above the fundamental are based on harmonic emission levels. The modulation envelope must be represented for harmonics as was done for the fundamental.

6.0 Transmitter Noise

Transmitter noise includes the output spectrum that is a result of the thermal noise generated in the driver and final amplifier stages as well as the synthesizer noise from lower level stages. This is a broad-band noise; however, it usually does not cover the immediate modulation sidebands. The level may be specified as the power per bandwidth as a function of frequency (dBm/Hz).

7.0 Transmitter Intermodulation

These are the undesired signals that result from the local mixing of a transmitter’s output emission with that of another transmitter. The mixing usually occurs in the non-linear circuits of a transmitter whose antenna receives a high level of RF from another transmitter antenna in close proximity. The mixing products are radiated by the transmitter’s antenna as possible co-channel or adjacent signal interference signals

smos ocean salinity retrieval level 2 marco talone, jérôme gourrion, fernando martin porqueras,...

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