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[email protected] PM4 04/2002
GOME2 Error Assessment Study
Error Budget, Error Mitigation and Proposal for Future Work
Mark Weber, Rüdiger de Beek, and John Burrows University of Bremen FB1
Institute of Environmental Physics
[email protected] PM4 04/2002
Overview
Topics
1 General Remarks2 Overall Error Budget3 Error Mitigation4 Conclusion5 Future Work
[email protected] PM4 04/2002
Error baseline is basic SNR for IT=0.1875 sec (80X40 km2 ground pixel)
A clear distinction between SC error and AMF error does not exist in error budgets assessed from simulated data („perfect a-priori knowledge“)
Trace gas column (VC) errors can be thus attributed to both slant column error and airmass factor error in the standard DOAS approach
1 General Remarks
VC SC AMFError Slant Column Air mass factor
SNR/diffuser X
Polarisation X (POLCOR) X (RTM)
Spatial aliassing X X
Resolution/undersampling
X X
RTM assumptions X
BRDF X
Pointing/geolocation X
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Contribution to SC and/or AMF error determines strategy for error mitigation
SC errors are mainly instrument related and may in addition require SC errors are mainly instrument related and may in addition require modifications in modifications in operational settingsoperational settings
AMF errors can be improved upon by AMF errors can be improved upon by modifying modifying algorithmic algorithmic and/or RTM and/or RTM approachesapproaches
Errors due to imperfect a-priori knowledge, e.g. use of certain trace gas profiles and other geophysical parameters in RTM (not derived from the retrieval itself), was not investigated in this error study. This adds mostly to AMF error.
Alternatives to standard DOAS should be considered, particularly in the case Alternatives to standard DOAS should be considered, particularly in the case of O3 UVof O3 UV
Modified DOAS (Serco GOME Tracegas Study, Diebel et al. 1996) Weighting function DOAS (Buchwitz et al. 2000)
Regardless of the algorithm used, good a-priori knowldge of the atmospheric Regardless of the algorithm used, good a-priori knowldge of the atmospheric state is needed by each of these methods (need for good climatologies!)state is needed by each of these methods (need for good climatologies!)
1 General Remarks
[email protected] PM4 04/2002
[email protected] PM4 04/2002
2 Overall error budget
2.1 Ozone UV and VIS
In UV (Channel 2) very strong absorption, thus very small SC error (<0.5%) at nominal noise at IT=0.1875 sec
Most other error sources except for spatial aliassing and pointing error are of same order of magnitude
Errors due to violation of weak absorber approximation is not accounted for in this budget
recommended use of modified DOAS and/or weighting function DOAS in UVrecommended use of modified DOAS and/or weighting function DOAS in UV
Visible window (450-497 nm) contains weaker absorption, however strong interference from other trace gases, e.g. water vapor, and albedo (gradient) effects
Standard DOAS more appropriate in VIS spectral range (O3 Chappuis band), slant column errors generally larger, AMF shows weaker wavelength dependence
Errors due to diffuser plate is still unknown, but may be of the same order (few tenth of a percent in UV and somewhat higher in VIS)
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2 Overall error budget
2.2 NO2
Error clearly dominated by diffuser plate signatures (50% error) and noise (<30%)
SNR can be improved by co-adding; increasing ground pixel size, however, hamper tropospheric retrieval (worse cloud statistics)
Strong benefits to be expected from open slit option as opposed to defocusing
Most other error sources are negligible compared to diffuser plate error
2.3 BrO
Similar arguments as for NO2 apply for BrO
Dominating error is SNR (<60%) and diffuser plate signature (70%)
Undersampling may cause huge errors (~80%)
Strong benefits from open slit
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2 Overall error budget
2.4 OClO
As photoactive species only retrievable under ozone hole condition and under twilight conditions
Error due to spectral noise dominates (~100%)
Co-adding may be needed to improve SNR, but OClO has strong gradients at the terminator
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3 Error Mitigation
3.1 Basic SNR
General improvements in error possible by coadding, this is, however, disadvantagous for tropospheric species (NO2, BrO, O3)
Recommendation: open slit and/or co-adding improves SNR, coadding not Recommendation: open slit and/or co-adding improves SNR, coadding not recommended for regions of tropospheric studies because of large pixel recommended for regions of tropospheric studies because of large pixel sizessizes
3.2 Diffuser plate structures Most significant error source for minor species
Recommendation: change to diffuser plate having spectral peak-to-peak Recommendation: change to diffuser plate having spectral peak-to-peak signatures below 10signatures below 10-4-4
3.3 Spatial aliassing
Small error coadding and/or reduction in read-out time (6msec) improves error statistics
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3 Error Mitigation
3.4 Spectral resolution and undersampling Defocussing leads to detoriation in precision; open slit significantly improves SNR Both defocussing and open slit option avoid undersampling error Saturation problems may be circumvented by decreasing IT/coadding options
Recommendation: open slit by a factor of two (0.48nm and 1nm spectral Recommendation: open slit by a factor of two (0.48nm and 1nm spectral resolution, respectively)resolution, respectively)
3.5 RTM assumption Spherical RTM to first order approximation is needed (particularly for O3 UV) Smallest error is found if viewing geometry at surface (Rayleigh layer) is used in plan-
paralell atmosphere of pseudo spherical RTM
Recommendation:Recommendation: use first order spherical RTM or optimised pseudo spherical model (cost use first order spherical RTM or optimised pseudo spherical model (cost
benefit)benefit) Use of appropriate climatologies of trace gases and, possibly, other Use of appropriate climatologies of trace gases and, possibly, other
geophysical parameters are also important for improving a-priori geophysical parameters are also important for improving a-priori informationinformation
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3 Error Mitigation
3.6 BRDF Small error even in case of sun glint, most significant for O3
RecommendationRecommendation Derive Lambertian equivalent reflectivity (LER) directly from the sun-Derive Lambertian equivalent reflectivity (LER) directly from the sun-
normalised radiance at absorption free wavelengths (e.g. 370-400 nm)normalised radiance at absorption free wavelengths (e.g. 370-400 nm)
3.7 Pointing accuracy
Errors are generally small
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3 Error Mitigation
LER Retrieval from GOME1
Relationship between LER and TOA reflectivity at 377nm for GOME Westpixels (~32° LOS)
Effect of altitude is included
TOA
IFR
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4 Conclusion
Major Issues (hardware/operation) for column retrieval
Replacement of diffuser plate is strongly recommended, otherwise minor trace gas retrieval will have large errors
Recommend opening the slit by degrading spectral resolution to 0.5 nm and 1.0 nm, respectively
IT of 0.1875 sec and lower shall be the baseline, depending of the needs co-adding by s/w option shall be done, reduction in read-out time
Reduction in read-out time only if IT gets shorter than 0.1875 sec
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5 Future Work
5.1 Use of CCD technology for GOME3 New observation strategyNew observation strategy Impact on trace gas retrievalImpact on trace gas retrieval Comparison to Reticon technologyComparison to Reticon technology
5.2 New ozone column retrieval strategies by combining UV and Visible windows Investigating feasibilty for separating tropospheric and stratospheric ozone Investigating feasibilty for separating tropospheric and stratospheric ozone
columncolumn Developing novel retrieval techniqueDeveloping novel retrieval technique
5.3 New ozone profile and total ozone climatology Improved a-priori statistics Improved a-priori statistics New AMF climatologyNew AMF climatology Separation in dynamical relevant regions (tropics, midlatitude, polar region) Separation in dynamical relevant regions (tropics, midlatitude, polar region)
rather than zonal meansrather than zonal means
5.4 Ring climatology Dependence on ozone profile shape at large solar zenith angleDependence on ozone profile shape at large solar zenith angle Developing a new extended Ring database Developing a new extended Ring database