- International TOVS Study Conference XVIII, Toulouse, France, 21-27 March 2012 -
Land surface VIS/NIR BRDF module for
RTTOV-11: Model and Validation
against SEVIRI Land SAF Albedo
product
Jérôme Vidot1 and Eva Borbas2
1Centre
de Météorologie Spatiale, DP/Météo-France, Lannion, France
2SSEC/CIMSS, Madison, Wisconsin, USA
Introduction and methodology
Introduction
In the next version of RTTOV (version 11) there will be a possibility for the users to simulate clear-sky satellite observations in the visible and in the near infrared spectral regions.
In clear-sky situations over land, the major contribution to the signal simulated at the top of atmosphere comes from the surface. As for thermal or microwave spectral regions, the
surface optical properties exhibit strong spectral signatures based on the surface type. Furthermore, in the visible and near infrared spectral regions, the surface optical properties
also exhibit a strong geometrical dependency, which depends on the solar and on the satellite directions. To describe the spectral and the geometrical dependences of the surface,
the surface optical properties are represented by the Bidirectional Reflectance Distribution Function (BRDF). Additionally, the surface optical properties of vegetation-covered area
present a non-negligible seasonal dependency. This poster describes the scientific approach of the RTTOV-11 BRDF model that provides a global (at a spatial resolution of 0.1°) and
monthly mean land surface BRDF and quality index for any instrument with spectral response function between 0.4 and 2.5 µm. A preliminary validation of the model is shown by
comparison with the SEVIRI Land SAF Black-Sky Albedo (or Directional Hemispherical Reflectance ) product at 0.6 µm (Channel 1), 0.8 µm (Channel 2) and 1.6 µm (channel 3).
BRDF model
The BRDF is calculated by using the semi empirical linear model of Ross-Li (Ref. 1) that is given by:
BRDF(θ sat ,θ sol , ∆φ , λ ) = fiso (λ ) + fvol (λ ) Kvol (θ S ,θV , ∆φ ) + f geo (λ ) K geo (θ S ,θV , ∆φ )
where θsol, θsat and ∆φ are the solar zenith angle, the satellite zenith angle and the azimuth difference between satellite and solar
directions, respectively. λ is the wavelength. The three BRDF kernel model parameters fiso, fvol and fgeo are basically related to
isotropic scattering, to leaf canopies and to shadowing effect, respectively.
Methodology
The methodology is similar with the UWiremis infrared land surface emissivity module developed for RTTOV (Ref. 2):
⇒ The first Principal Components (PCs or eigenvectors) of 126 selected laboratory reflectance spectra from the USGS
database (Ref. 3) between 0.4 and 2.5 microns with wavelength resolution of 0.01 µm (Figure 1), were regressed against 7
hinge points corresponding to the central wavelength of MODIS channels (at 0.470 µm, 0.555 µm, 0.659 µm, 0.865 µm, 1.24 µm,
1.64 µm and 2.13 µm). The number of 6 PCs was found to be most optimal by giving the best agreement between the original
laboratory measurements and reconstructed spectra.
Figure 1. Reflectance spectra of the 126 selected USGS soils
and vegetations surfaces. Dotted lines represent the MODIS
channel central wavelengths.
⇒ Monthly means global BRDF kernel model parameters f were extracted from MODIS MCD43C1 product that allow to
constrain the reconstruction of a BRDF spectra, which are used next to interpolate the BRDF of any instrument.
BRDF validation with SEVIRI Land SAF Albedo product
80.
65.
0.50
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RTTOV
70.
Sensor Zenith Angle [Degrees]
0.70
0.60
75.
60.
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50.
45.
40.
35.
30.
25.
20.
15.
10.
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5.
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Land SAF
1
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0.70
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0.60
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0.60
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N = 93912
R = 0.957
BIAS = −0.0186
0.70
0.50
0.50
0.50
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Central Africa Ch03
0.70
0.60
0.70
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Land SAF
0.30
0.30
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0.20
N = 119144
R = 0.974
BIAS = −0.0206
Central Africa Ch02
0.10
N = 93912
R = 0.914
BIAS = −0.0127
0.40
0.20
0.20
Desert Good Quality Ch03
0.10
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0.10
0.10
0.70
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Black−Sky Albedo
RTTOV
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RTTOV
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RTTOV
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N = 119144
R = 0.966
BIAS = 0.0061
0.10
0.10
0.10
N = 93912
R = 0.929
BIAS = −0.0335
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Desert Good Quality Ch02
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0.70
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N = 832341
R = 0.987
BIAS = −0.0125
0.40
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0.30
0.10
Conclusion and perspectives
A BRDF model for land surfaces has been developed for RTTOV-11. It is based on a combination of USGS laboratory
hyperspectral measurements of soil and vegetation surfaces and the MODIS BRDF kernel parameters products. This
model allows the calculation of the BRDF for any instrument with channels between 0.4 and 2.5 µm. The model
provides a global and monthly mean BRDF at 0.1° spatial resolution. It also provides a quality index of the BRDF.
Comparison with one global SEVIRI Land SAF product show a good consistency between black-sky albedo, and better
for desert surfaces. It is found that RTTOV-11 BRDF model tends to slightly underestimate the albedo, especially in
areas where the presence of aerosols and/or persistent clouds reduce the quality of the MODIS BRDF retrieval. A
standard deviation of the BRDF will be implemented in the model and seasonal variability will be investigated.
0.30
Vegetated Good Quality Ch03
0.70
0.20
Figure 4. Scatterplots between
RTTOV and Land SAF BSA for
channels 1 to 3 and for the three
areas.
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3) Vegetated areas in Central Africa with mainly medium and filled quality index.
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Central Africa Ch01
channel 1 and 2 and RTTOV
lower by ~0.02 in channel 3.
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2) Desert areas in Northern Africa and Middle-East with good quality index.
0.20
Desert Good Quality Ch01
0.10
⇒ For desert areas, no bias in
0.40
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1) Vegetated areas in Europe, South Africa and South America with good quality
index.
If quality index is medium or
filled, RTTOV lower by 0.01–
0.03 (Fig. 4 bottom)
0.30
0.60
The quality index reveal an area in Central Africa where the quality of the MODIS
BRDF retrieval is reduced by the presence of aerosols and/or persistent clouds. For
the interpretation of the results, we then separated the SEVIRI full disk into three
parts (represented on Fig. 2):
0.10
N = 119144
R = 0.975
BIAS = −0.0085
0.70
Figure 2. Left: SEVIRI Land SAF Black-Sky Albedo product for the 25th August 2011 in channel
1 at 0.6 µm. Middle: RTTOV Black-Sky Albedo. Right: RTTOV BRDF quality index.
0.20
N = 832341
R = 0.972
BIAS = 0.0058
0.50
WATER
⇒ For vegetated areas:
If quality index is good, no
bias in channel 2, RTTOV
lower by ~0.01 in channels 1
and 3.
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1
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1
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GOOD
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areas with R>0.9
MEDIUM
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3
FILLED
in all
0.20
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N = 832341
R = 0.988
BIAS = −0.0134
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⇒ Good agreement
Vegetated Good Quality Ch02
Vegetated Good Quality Ch01
Results
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2
SNOW
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Black−Sky Albedo
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BAD
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Figure 3. Left: Scatterplot
between RTTOV and Land
SAF BSA for SEVIRI channel 1
on area 1. Right: Satellite
zenith angle.
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NO DATA
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RTTOV BRDF MASK
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RTTOV SEVIRI Ch01
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Land SAF SEVIRI Ch01
Vegetated Good Quality Ch01
0.10
N = 1646664
R = 0.933
BIAS = −0.0066
0.60
On Figure 2 is depicted the Land SAF BSA in channel 1 (at 0.6 µm, left), the RTTOV
BSA in channel 1 (middle) and the RTTOV quality index for August 2011 (right).
The scatterplot between RTTOV BSA and Land SAF BSA from Fig. 2 depicted in Fig. 3
show a lot of outliers. These outliers are explained by geometrical subsampling of the
SEVIRI observations at the edge of the disk. By removing data for satellite zenith angle
greater than 60°, the outliers are removed (compare with Fig. 4, top-left).
0.70
For the validation of the RTTOV BRDF module, we used SEVIRI Land SAF product
for the 25th August 2011 averaged at 0.1° spatial resolution from the SEVIRI
original spatial resolution. We were not able to validate directly the BRDF since the
BRDF is not an operational product from the Land SAF. We used the SEVIRI Land
SAF Directional Hemispherical Reflectance or Black-Sky Albedo (BSA) product. The
RTTOV BSA is calculated from the BRDF kernel model parameters (Ref. 1).
Effect of the SEVIRI geometrical observation subsampling
0.10
For any given location (in latitude and longitude), month, geometry and
instruments channel, the RTTOV-11 BRDF module provides the BRDF and a quality
index that is extracted from the original MODIS quality flags.
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Land SAF
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Land SAF
References:
(1) Lucht W., Schaaf C. B. and Strahler A. H., 2000: An Algorithm for the
retrieval of albedo from space using semiempirical BRDF models, IEEE
Transactions on Geoscience and Remote Sensing, Vol. 38, no. 2, pp. 977-998.
(2) Borbas, E. A. and Ruston B. C., 2010: The RTTOV UWiremis IR land surface
emissivity module, Report NWPSAF-MO-VS-042, 24 p.
(3) Clark R. N., Swayze G. A., Wise R., Livo E., Hoefen T.,
Kokaly R. and Sutley S. J., 2007: USGS digital spectral
library splib06a, U.S. Geological Survey, Digital Data
Series
231.
Available
at
http://speclab.cr.usgs.gov/spectral.lib06/ds231/.