1 uni-bremen 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

2 uni-bremen 04/2002 Overview Topics 1General Remarks 2Overall Error Budget 3Error Mitigation 4Conclusion 5Future Work

3 uni-bremen 04/2002 Error baseline is basic SNR for IT= 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 ErrorSlant ColumnAir mass factor SNR/diffuserX PolarisationX (POLCOR)X (RTM) Spatial aliassingXX Resolution/ undersampling XX RTM assumptionsX BRDFX Pointing/geolocationX

4 uni-bremen 04/2002 Contribution to SC and/or AMF error determines strategy for error mitigation  SC errors are mainly instrument related and may in addition require modifications in operational settings  AMF errors can be improved upon by modifying algorithmic and/or RTM approaches 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 of 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 state is needed by each of these methods (need for good climatologies!) 1 General Remarks

5 uni-bremen 04/2002

6 uni-bremen 04/ 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= 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 UV Visible window ( 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)

7 uni-bremen 04/ 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

8 uni-bremen 04/ 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

9 uni-bremen 04/ 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 recommended for regions of tropospheric studies because of large pixel sizes 3.2 Diffuser plate structures Most significant error source for minor species  Recommendation: change to diffuser plate having spectral peak-to-peak signatures below Spatial aliassing Small error coadding and/or reduction in read-out time (6msec) improves error statistics

10 uni-bremen 04/ 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 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:  use first order spherical RTM or optimised pseudo spherical model (cost benefit)  Use of appropriate climatologies of trace gases and, possibly, other geophysical parameters are also important for improving a-priori information

11 uni-bremen 04/2002 3Error Mitigation 3.6 BRDF Small error even in case of sun glint, most significant for O3  Recommendation  Derive Lambertian equivalent reflectivity (LER) directly from the sun- normalised radiance at absorption free wavelengths (e.g nm) 3.7 Pointing accuracy Errors are generally small

12 uni-bremen 04/ Error Mitigation LER Retrieval from GOME1 Relationship between LER and TOA reflectivity at 377nm for GOME Westpixels (~32° LOS) Effect of altitude is included

13 uni-bremen 04/2002 4Conclusion 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 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 sec

14 uni-bremen 04/2002 5Future Work 5.1 Use of CCD technology for GOME3  New observation strategy  Impact on trace gas retrieval  Comparison to Reticon technology 5.2 New ozone column retrieval strategies by combining UV and Visible windows  Investigating feasibilty for separating tropospheric and stratospheric ozone column  Developing novel retrieval technique 5.3New ozone profile and total ozone climatology  Improved a-priori statistics  New AMF climatology  Separation in dynamical relevant regions (tropics, midlatitude, polar region) rather than zonal means 5.4 Ring climatology  Dependence on ozone profile shape at large solar zenith angle  Developing a new extended Ring database