Microwave
- the SMOS Mission
Prof. Bob Su
prepared by
Monday 29 June 2009, D1L3a
Part 1 SMOS – MIRAS
• SMOS - Soil Moisture
Ocean Salinity
• MIRAS - Microwave
Imaging Radiometer
using Aperture Synthesis
• “Passive” microwave 2-D
interferometric radiometer
(L-Band, 1.4GHz, 21cm).
SMOS – MIRAS Movie
SMOS – MIRAS: to provide global & regional measurements
of soil moisture, ocean salinity and ice
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One of the Earth Explorer’s missions (see
also lecture D1L1)
1st space borne global measurement of
salinity – currently only complex model
output is available
Launch scheduled for April to July 2009
Simulated seasonal (winter) sea-surface salinity
map. The units are in practical salinity units (psu)
Simulated seasonal soil moisture map
(winter) of Europe and Africa. The units are
'cubic metre of water per cubic metre of soil'
Measurement of Soil Moisture in the Surface Zone
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Soil moisture (SM) is a measure of the
amount of water within a given volume
of soil and is usually expressed as a
percentage.
How measured in the surface zone?
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Ground measurements
Networks (GEWEX)
SW, SWIR, ….
THIR….
Low frequency microwaves
– Active microwaves
• Vegetation, roughness
• Revisit
• Sensitivity
– Passive microwaves  antenna
issue
SMOS – MIRAS Soil Moisture Measurement Goals
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Multi-angular
Dual polarisation (H and V)
4 % volume 3 day revisit
(Vegetation 7 day)
Better than 50 km resolution
Global products
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A new technique (2D
interferometry) to provide global
measurements from space of key
variables (SSS and SM) for the
first time
Pellarin et al.
Le Traon et al.
How will the Measurement Goals be Achieved?
Constraining models by global soil moisture and
ocean salinity observations estimated from dual-pol.,
multi-angular, L-band brightness temperature
measurement acquired by a 2D interferometer.
Instrument as proposed:
2-D Y-shaped interferometer 4.5m arms
Satellite
69 LICEF receivers will allow either H &V or
full polarisation acquisition
Full polarisation. mode is experimental and
utility will be reported as part of Cal/Val
experiments
Use of full pol. mode impacts on data
downlink volume (x2 compared to dual pol.)
Spacecraft
velocity
Earth
Swath
1000 km

m
dN
Local incidence
30°
angle 
 = 55°
Nadir path
Measuring Soil Moisture at L-band
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Negligible atmospheric
attenuation (at L-Band 99%
atmospheric transmission)
Attenuation from vegetation small
(for biomass < 5 kg m-2, which is
65% of the Earth’s land surface)
Emission from the Earth shows a
large contrast between water and
land (signal-to-noise ratio from dry
to wet soils) due to the large
difference between the dielectric
constant of water (ca 80) and dry
soil (ca 3.5)
Emissivity originates from deeper
surface soil layer (at L-band ~5
cm) than for shorter wavelengths
Jackson and Schmugge, 1989
Aperture Interferometry
At L-band classic radiometers
require large steerable antennae,
MIRAS offers an alternative design
that achieves the appropriate
resolution through interferometric
processing.
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Angular resolution
provided by separated
antennas
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Correlation products
s(1)*s(2)  Visibility
Functions V(D/l)
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Inverse F.T. on V  TB()
1
2
D
D'

l / D'

Space sampling requirement : every l/2 value at least one
time ; hence "thinning" possibilities.
SMOS – MIRAS Hexagonal Foot Print
• From an altitude of 763 km, the
antenna will view an area of almost
3000 km in diameter.
• However, due to the interferometry
principle and the Y-shaped antenna,
the field of view is limited to a
hexagon-like shape about 1000 km
across called the 'alias-free zone'.
• This area corresponds to observations
where there is no ambiguity in the
phase-difference.
• Due to orbit and foot print
configuration the coverage will be
global every 3 days
How Will Soil Moisture be Retrieved?
For bare soil surfaces
SM* = a0 + a1 PR +a2 (TBv-TBh) ; SM* retrieved Surface Soil Moisture
PR = (Tbv-TBh)/(TBv+TBh) ; Polarization ratio from MIRAS measurements
For vegetated surfaces
The retrieval of SM requires ancillary data to evaluate the effect caused by the
vegetation. The vegetation optical depth can be related to the amount of water
in vegetation which can be estimated from indices such as NDVI. BUT dualpolarised, multi-angle L-band data give the opportunity to retrieve both
soil moisture and vegetation optical depth.
SMOS SM and vegetation characteristics will be produced by an operational
SMOS Level 2 retrieval algorithm which is based on an iterative approach,
minimizing a cost function computed from the sum of squared weighted
differences between measured and modelled brightness temperature (TB)
data, for a variety of incidence angles.
Sources of Uncertainty in SM measurement
Instrumental errors
- Radiometric sensitivity, accuracy, calibration
stability
- Characterisation of system elements incomplete
- Interferometric image reconstruction
Surface characteristics
- Soil surface roughness (causes increase in
backscatter)
- Soil texture
- Land cover & surface heterogeneity
- Dew, intercept, snow
- Topography
- Litter effect
- Surface water
Radiofrequency Interference
Pixel heterogeneity
Due to area of footprint,
many types of land use can
be expected within a
resolution cell, for each
surface there will be a
different model
Cover Dependent Models Relating Emissivity to SM
Accounting for Uncertainties due to
Surface Characteristics
Pixel heterogeneity
- SMOS pixels are highly heterogeneous
- Processor distinguishes between three main types of
pixels: land, sea/water and mixed
- Land surfaces are classified into 12 categories,
aggregated from the ECOCLIMAP land cover map (dry
sand/desert, bare soils, natural low vegetation, cropland,
dense forest, moderately dense forests, snow covered
area, marshes, swamps, wetlands, rocky terrain,
maintains, ice, urban)
Auxiliary data for static characteristics
- Land/sea mask
- Water bodies, rivers
- Urban areas
- Topography: DEM
- Soil texture: FAO data set 5’x5’
- Surface roughness
ECOCLIMAP Land use map
Auxilliary data for dynamic characteristics
- Land use map (ECOCLIMAP)
- Snow cover extent and status
(MODIS-MERIS, ECMWF)
- Freezing (weather centres)
- Land surface temperature (AVHRR, MODIS)
- Atmospheric characteristics (weather centres)
How Homogeneous?
Forest vs. Non Forest LC fractions
In Conclusion
SM retrievals can be attempted in many areas with varying expected accuracy
SMOS Validation and
Retrieval Team (SVRT) – Soil Moisture
• For SM several sites and dedicated teams worldwide
• Supported by ground and airborne campaigns and Announcement of
Opportunity projects in 2005
• There will also be SMOS validation for Sea Surface Salinity
SVRT – Airborne System (AMIRAS)
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Similar configuration but smaller version of
MIRAS (three Y-shaped arms)
Being flown to provide SMOS simulations
and in support of CAL/VAL activities
Like MIRAS, this airborne instrument is
able to measure in horizontal as well as
vertical polarisations in both dual- and fullpolarisation modes.
Only 4 LICEF like receivers per arm,
MIRAS will carry a total of 69 receivers
AMIRAS Brightness temperature in the alias-free
field-of-view during its maiden flight over Pensaari
island in the Lohja lake west of Helsinki. The
brightness contrast between water and land is as
expected.
Credits: UPC (Polytechnic University of Catalonia)
AMIRAS on aircraft in SMOS
configuration, 24° from nadir
SVRT in China
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Workshop in 2008 in Beijing to bring SSS and SM teams together
In China Dragon 2 project id. 5252 will specifically address SMOS Soil
Moisture CAL/VAL
– Area centred on Takla Makan Sand Desert. The specified site is selected
for its homogeneity, stability, relatively easy to access and significant
accuracy from previous passive microwave studies.
– Area centred on Northwest of China will look at localisation of algorithms
for China
– Lead investigators are Dr. Weiguo Zhang (in photo right) & Prof. Yann Kerr
(centre of photo left)
courtesy PNRA
courtesy Y. Kerr, CESBIO
SVRT Ice (Antartica) and Land Surfaces (Europe)
Long-term observations of snow and ice-sheet
surfaces will be used for external calibration of
MIRAS as the ice sheets exhibit stable microwave
emission at 1.4 GHz.
An L-band radiometer operated near Toulouse,
France. Temporal measurements are used to
determine the effect of vegetation growth and
soil moisture on L-band emissivity.
Retrievals - Forward Modeling by
Iterative Minimisation
Aux
Auxdata
data
Instrument
Instrument
characteristics
characteristics
Decision
Decision
Tree
Tree
Submodels
/weighting
factors
observed
Field component
Initial
InitialSM/OS
SM/OS
Value
Value
modelled
Forward Model
TB
TBh(0°)
TBh(50°)
TBv(50°)
Land cover
Soil-type
Neural Network or other
(semi)empirical relationship
Output
Soil
Moisture
τ
Tsoil
SMOS Level-1 Products
Level 1A: SMOS reformatted and calibrated
observation and housekeeping data in engineering
units; physically consolidated in pole-to-pole timebased
segments;
“calibrated
visibilities”
Level 1B: output of image reconstruction of
SMOS observation measurements; consisting of
geo-located vectors of Fourier Component of TB
on antenna frame
L1C Sea product dual polarization snapshot:
Brightness temperature @ H-pol (ESA-ESRIN 2007)
Level 1C: Brightness temperatures Swath; Magnitudes are expressed at Top of
Atmosphere; Information is geo-located on a Discrete Global Grid (ISEA 4-9); L1c semiorbit product (pole to pole) split by Land and Sea grid point Two sets of information
available: pixel-wise and snapshot-wise
Snapshot-wise information
• Satellite position and attitude
• TEC magnitude
• IGRF magnetic vector
• Sun illumination angle
• Direct Sun corrected
magnitude Snapshot Overall
Radiometric Accuracy
Geo-located information
• grid point information: latitude, longitude,
altitude
• Number of measured values in grid point
• For each value:Flags (Polarization, Sun,
position in the Field of View), BT value,
radiometric accuracy, Incidence and Azimuth
Angle, Snapshot ID, Footprint size
SMOS Level-2 Products
Sea Surface Salinity (SSS) computed at each ISEA
grid point for a semi orbit (ascending or descending)
 Three SSS values (3 models, with uncertainties)
 Pseudo-dielectric constant retrieved
 Wind Speed and Sea Surface Temperature used in the
retrieval
 Polarized Tb at 42.5º incidence angle at surface and
antenna frame
 Flags and confidence and science descriptors
SMOS L2 SM retrieved over North Africa
(Cabot et al 2007)
Soil Moisture (SM) computed at each ISEA grid point for a semi orbit (ascending or
descending):
SM values, optical thickness, physical temperature, Polarized TB (surface and antenna frame at
42.5º) , and dielectric constants
 All quantities have related uncertainties
 Flags to indicate presence/absence of features/events of interest such as rocks, topography,
snow, RFI
 Descriptors to describe properties such as number of wild views and mean spatial resolution
Soil Moisture
Simulated Sea Surface Salinity
Levels 3 & 4 Daily and
Averaged Global SM &
SSS Maps
Simulated Seasonal Maps
Winter at top
• Level 3
– global, single instrument
• Level 4
– global root zone SM,
multi-instrument retrieval
with US missions 2010 on
– will be developed and
available through French
and Spanish national
programmes
SMOS Data Access
• SMOS data will be made available through the ESA category-1
procedure, either through dedicated AOs or registration service
online (http://eopi.esa.int).
• SMOS calibration & validation data will be available via the
SMOS Cal/Val portal:
http://calvalportal.ceos.org/CalValPortal/welcome.do
• Near-real time products will be available either from the WMOGTS network or the ESAC FTP server
• Soil Moisture in situ data will be made available via the SMOS
Soil Moisture Network Data Hosting under development at the
University of Lisbon
• ESA campaign data will be available via the campaign database
http://earth.esa.int/campaigns and via the SMOS CalVal portal