geostationary surface albedo retrieval error estimation

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Geostationary surface albedo retrieval error estimation Y. Govaerts (1) and A. Lattanzio (2) (1) EUMETSAT, Germany (2) Makalumedia, Germany 2nd CEOS/WGCV/Land Product Validation (LPV) Workshop on Albedo Products April 27-28, 2005

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Geostationary surface albedo retrieval error estimation. Y. Govaerts (1) and A. Lattanzio (2). (1) EUMETSAT, Germany (2) Makalumedia, Germany. 2nd CEOS/WGCV/Land Product Validation (LPV) Workshop on Albedo Products April 27-28, 2005. METEOSAT MISSIONS STATUS. 6 bits data. 8 bits data. - PowerPoint PPT Presentation

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Page 1: Geostationary surface albedo retrieval error estimation

Geostationary surface albedo retrieval error estimation

Y. Govaerts(1) and A. Lattanzio(2)

(1) EUMETSAT, Germany(2) Makalumedia, Germany

2nd CEOS/WGCV/Land Product Validation (LPV) Workshop on Albedo Products

April 27-28, 2005

Page 2: Geostationary surface albedo retrieval error estimation

METEOSAT MISSIONS STATUS

Pre-operationalVIS 6 bits

OperationalVIS 8 bits

24 years of archive

Need to be consistently calibrated and navigated

6 bits data

8 bits data

The Meteosat mission has been conceived in the early seventies. The primary objective of VIS band data was the near real-time qualitative observation of meteorological systems (i.e., to take picture).

Page 3: Geostationary surface albedo retrieval error estimation

METEOSAT MISSIONS STATUSMajors drawbacks concerning the quantitative use of the VIS band concern:•The unreliable SSR characterization

Development of a SSR model to characterize the error

Govaerts, Y.M., Clerici, M., and Clerbaux, N. (2004) Operational Calibration of the Meteosat Radiometer VIS Band, IEEE TGARS, 42, 1900-1914.

Page 4: Geostationary surface albedo retrieval error estimation

METEOSAT MISSIONS STATUSMajors drawbacks concerning the quantitative use of the VIS band concern:•The unreliable SSR characterization•The width of the VIS band (surface changes, WV absorption, …) Surface reflectance

Aerosol transmittance (τ=0.4)Gaseous transmittance

Page 5: Geostationary surface albedo retrieval error estimation

METEOSAT MISSIONS STATUSMajors drawbacks concerning the quantitative use of the VIS band concern:•The unreliable SSR characterization•The width of the VIS band (surface changes, WV absorption, …)• Navigation problem in the eighties.

The proposed approach relies on a reliable estimation of the retrieved surface albedo retrieval error that explicitly accounts for the observation system uncertainties.

The Meteosat system has not been design to fulfil any climate monitoring requirements

Page 6: Geostationary surface albedo retrieval error estimation

METEOSAT-7 VIS Band Calibration

Estimated calibration errorTarget characterisation error : 4.1%SSR error contribution : 3.8%Random error : 1.6%Total calibration error : 6% The SSR error should increase in time

The loss of transmittance depends on the wavelength

Desert

Sea

Govaerts, Y.M.   Clerici, M.   Clerbaux, N., 2004, Operational calibration of the Meteosat radiometer VIS band, IEEE TGARS, 42, 1900- 1914

Page 7: Geostationary surface albedo retrieval error estimation

Surface Albedo from Geostationary Obs.The Reciprocity Principle is applicable at a

spatial scale of a few km

Absorbing atmosphere

Scattering atmosphere

Assumptions•Atmosphere is composed of one absorbing gas layer and one scattering layer

•US76 atmospheric profile•Continental aerosol type•Atmospheric and surface scattering properties are constant along the day

•Surface scattering properties can be represented by the RPV BRF model

Model :•ozone (TOMS)•Total column water vapour (ECMWF)

State variables

Retrieved :•aerosol optical thickness (1)•surface reflectance level (1)•surface anisotropy (2)

Pinty, B., Roveda, F., Verstraete, M.M., Gobron, N., Govaerts, Y., Martonchik, J.V., Diner, D.J., and Kahn, R.A. (2000) Surface albedo retrieval from Meteosat: Part 1: Theory, Journal of Geophysical Research, 105, 18099-18112.

Page 8: Geostationary surface albedo retrieval error estimation

INVERSION

GEOSTATIONARY SURFACE ALBEDO

Absorbing atmosphere

Scattering atmosphere

Inversion of the forward model

2

2 )ˆ(

y

m xyy

Page 9: Geostationary surface albedo retrieval error estimation

INVERSION : Nile delta (winter)

GEOSTATIONARY SURFACE ALBEDO

τ = 0.1, DHR = 0.17

Page 10: Geostationary surface albedo retrieval error estimation

INVERSION : Nile delta (summer)

GEOSTATIONARY SURFACE ALBEDO

τ = 0.4, DHR = 0.21

Page 11: Geostationary surface albedo retrieval error estimation

Meteosat -2/7 Albedo Comparison

Meteosat-7Launch date : 1997Sub-satellite point : 0o Repeat cycle (archive) : 30 minDigitalisation : 8 bitsCalibration accuracy : 6%Daily Rad. Noise : 7-9%

Meteosat-2Launch date : 1981Sub-satellite point : 0o Repeat cycle (archive) : 30/60 minDigitalisation : 6 bitsCalibration accuracy : 15%Daily Rad. Noise : 12%

5.915.3TOTAL

1.61.2Random

3.814.2SSR. Error

4.14.1Rad. Transfer.

72Meteosat

5.915.3TOTAL

1.61.2Random

3.814.2SSR. Error

4.14.1Rad. Transfer.

72Meteosat

Calibration error budget

Page 12: Geostationary surface albedo retrieval error estimation

Meteosat -2/7 Albedo Comparison

Met-2: 1-10 May 1984 Met-7: 1-10 May 2004

Page 13: Geostationary surface albedo retrieval error estimation
Page 14: Geostationary surface albedo retrieval error estimation
Page 15: Geostationary surface albedo retrieval error estimation

SURFACE ALBEDO COMPARISON OVER STABE DESERT

Min prob.: 90%Max albedo rel. error: 10%

6.8%

5.0%

MET-2 has more high values

Page 16: Geostationary surface albedo retrieval error estimation

DETECTION OF SIGNIFICANT CHANGES

1. Remove the pixels with a QI (probability of the goodness of the fit) lower than 90%

Page 17: Geostationary surface albedo retrieval error estimation

SOLUTION PROBABILITY

Met-2 Met-7

Page 18: Geostationary surface albedo retrieval error estimation

DETECTION OF SIGNIFICANT CHANGES

1. Remove the pixels with a QI (probability of the goodness of the fit) lower than 90%

2. Analyse the albedo difference with respect to the retrieval error

Page 19: Geostationary surface albedo retrieval error estimation

RADIOMETRIC RELATIVE ERROR

Met-2 Met-7

Page 20: Geostationary surface albedo retrieval error estimation

SURFACE ALBEDO RELATIVE ERROR

Met-2 Met-7

Page 21: Geostationary surface albedo retrieval error estimation

DETECTION OF SIGNIFICANT CHANGES

1. Remove the pixels with a QI (probability of the goodness of the fit) lower than 90%

2. Analyse the albedo difference with respect to the retrieval error

3. Keep only differences larger than the respective error (including calibration error):

22

2727 || AAAA

Page 22: Geostationary surface albedo retrieval error estimation

DETECTION OF SIGNIFICANT CHANGES

-75%< <+75%

(A2-A7)/A7

A2 : 1-10 May 1984A7 : 1-10 May 2004

Page 23: Geostationary surface albedo retrieval error estimation

CONCLUSION•Geostationary observations offer a decisive advantage

to retrieve surface albedo climate data set thanks to the frequent daily sampling used to estimate the surface anisotropy and to the duration of the archive (+20 years).

•Met-2 and Met-7 agrees within 6% over desert area. It should be possible to detect significant (15%) temporal surface albedo changes from the Meteosat archive.

•Uncertainty in the SSR characterization is the major limiting factor.

Page 24: Geostationary surface albedo retrieval error estimation

GLOBAL SURFACE ALBEDO

Broadband (0.3 – 3.0µm) surface albedo derived from GOES-8/10, MET-5/7 and GMS-5 in 1-10 May 2001