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Trace gas column retrieval from IR nadir spectra – a model study for SCIAMACHY
Advances in Space Research 34 (2004) 734–738 www.elsevier.com/locate/asr
Trace gas column retrieval from IR nadir spectra – a model study for SCIAMACHY R. de Beek *, M. Buchwitz, V.V. Rozanov, J.P. Burrows Institute of Environmental Physics, University of Bremen, FB 1, D-28334 Bremen, Germany Received 6 January 2003; received in revised form 16 June 2003; accepted 19 June 2003
Abstract The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) is part of the European satellite ENVISAT launched at 1st March 2002. It is a follow-on instrument of the Global Ozone Monitoring Experiment (GOME) flying on ERS-2 and, compared to GOME, has extended capabilities. Using measurements of the direct extra-terrestrial solar spectrum and sun-light reflected and scattered by the earth atmosphere or surface SCIAMACHY detects atmospheric absorption of several trace species absorbing in spectral regions from the ultraviolet to the near infrared (240–2380 nm). Vertical columns of H2 O, N2 O, CO, and CH4 can be retrieved using SCIAMACHY Channel 8 near-infrared nadir measurements. In this study, selected atmospheric and instrument specific errors relevant for the retrieval are analysed. Spectral windows of Channel 8 are considered, which are currently used for the operational near-real-time processing. For this purpose, spectral error patterns have been simulated as well as sun-normalised model radiances for nadir scanning mode, the latter using the radiative transfer model SCIATRAN. Focus are the polarisation sensitivity and dark signals of the instrument. Further on, accuracy estimates for a number of different atmospheric scenarios are presented. Ó 2004 COSPAR. Published by Elsevier Ltd. All rights reserved. Keywords: Trace gas column retrieval; IR nadir spectra; Model study for SCIAMACHY; ENVISAT
1. Introduction The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) is a UV/ Vis/near-infrared spectrometer (Bovensmann et al., 1999). Total column amounts of the atmospheric trace gases CH4 , H2 O, CO, CO2 , and N2 O are operationally retrieved from near-infrared nadir radiance and solar irradiance spectral measurements of SCIAMACHY Channel 7 (1934–2043 nm) and Channel 8 (2259–2385 nm) in near-real-time using the BIAS algorithm (Spurr and Chance, 1998). For calibration purposes, polarisation sensitivity and dark signal corrections are part of the operational SCIAMACHY processing scheme. Investigations have been performed in the frame of the * Corresponding author. Tel.: +49-421-218-4475; fax: +49-421-2184555. E-mail address: [email protected] (R. de Beek).
ESA project SUPPRO (de Beek, 2003) in order to achieve first error estimates with respect to these two error sources using the WFM-DOAS algorithm under development at the University of Bremen (Buchwitz et al., 2000, 2004). The wavelength dependent polarisation sensitivity of the instrument characterised onground prior to flight is used for correction. In case of inaccurate calibration, spectral polarisation characteristics will be mapped into the calibrated radiance, which lead to errors in trace gas total column retrievals. The relative dark signal contribution to the overall signal of the instrument can be large, especially for the case of a low ground albedo. Related inaccurate calibrations are therefore of special interest. Due to the principle similarities of the BIAS and WFM-DOAS methodologies similar responses of both algorithms to these error sources are assumed. Due to discretisation, inaccurate atmospheric and geometric parameters applied for the radiance and weighting function look-up table generation lead to
0273-1177/$30 Ó 2004 COSPAR. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.asr.2003.06.041
R. de Beek et al. / Advances in Space Research 34 (2004) 734–738
735
errors in total column retrieval. For selected cases, specific errors due to the discretisation of the look-up table scheme of the WFM-DOAS algorithm (Buchwitz et al., 2000) are estimated. Spectral fitting windows of Channel 8 as currently in use for SGP have been selected: 2269–2275 and 2360– 2366 nm, chosen for fittings of N2 O and CO, respectively. Simultaneously fitted CH4 and H2 O total columns have also been considered.
2. Polarisation correction In order to correct for instrumentally induced polarisation structures during SCIAMACHY operational data processing radiances are multiplied by polarisation correction factors (PCF), which are calculated using retrieved polarisation state parameters Q and U (Stokes parameters) and the pre-flight spectral characteric function of the instrumental polarisation sensitivity. For the simulation of erroneous PCF Cpolerr , failures in operational Q and U processing have been assumed using various polarisation states. As a reference, a radiance spectrum Rad has been simulated. Corruption of the radiance spectrum by multiplication with PCE ¼ (Cpolerr /Cpol) yields the erroneous radiance Raderr , where Cpol is the ideal PCF for the state considered. Retrieved trace gas columns using Raderr with respect to that achieved using the uncorrupted radiance Rad (hereinafter called ‘‘perfect fit’’) give percentage error estimates. Erroneous PCF have been simulated for various states of linear polarisation assuming errors in Q and U processing which are equally distributed within 0.15. This is on the order of observations during processor calibration closed-loop tests (de Beek, 2002). Retrievals applied resulted in a large data set of vertical column errors, which has been statistically analysed. Maximum errors and standard deviations are given in Table 1. Although the final operational polarisation state retrieval is expected to be at least accurate within the assumed range, single cases of complete failures in Q and U processing (examples of unphysical results, see e.g., de Beek, 2002) have also been tested. For illustration, an example of a simulated PCE spectrum for such
Fig. 1. As an example for un-polarised light (Q ¼ U ¼ 0, Cpol ¼ 1.0), a simulated polarisation calibration error (PCE) spectrum is shown for SCIAMACHY Channel 8. For this example, PCE has been generated assuming Qerr ¼ l and Uerr ¼ )1 (complete processing failure). This has been multiplied to the reference radiance to give the erroneous calibrated radiance. For the case of such errors, spectral structures as seen in panels 2 and 3, which origin is the spectral shape of instrumental polarisation sensitivity, are transfered into calibrated radiances and lead to errors in the retrieval (see Table 1).
a case is shown in Fig. 1. The sun-normalised radiance fitted using the CO-window is shown in Fig. 2.
3. Dark signal correction Dark signal contributions to SCIAMACHY measurements, which mainly arise from instrumental noise and thermal background emission, have to be corrected for. Due to the large contribution of dark signals relative
Table 1 Percentage errors with respect to vertical columns obtained from the perfect fit Error source !
DarkSigErr (%)
PolCorrErr (%) MaxErr
StdDev
ProcFail
2269–2275 nm
CH4 N2 O
0.06 0.15
0.02 0.06
0.3 1.1
)4.3 )6.0
2360–2366 nm
H2 O CH4 CO
0.31 0.44 0.15
0.11 0.15 0.06
)1.9 0.7 2.6
)21.9 )11.1 10.9
PolCorrErr: errors due to erroneous PCF, MaxErr and StdDev: maximum errors and standard deviations of the considered data, ProcFail: maximum errors due to processing failures (see Fig. 1), DarkSigErr: errors due to inaccurate dark signal correction.
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Fig. 2. WFM-DOAS as applied to a model sun-normalised radiance. The reference model radiance has been multiplied by PCE to give the corrupted radiance. Panels 2–3 show fitted weighting functions of the considered trace gases. The fit to the corrupted radiance (diamonds) results in vertical column errors. Residuals are small compared to dark signal case. Correlation between weighting functions and PCE is small, i.e., the introduced PCE characteristics can be recognised in the residual structure, except for H2 O around 2364 nm.
to the overall signal the sensitivity of the retrieval algorithm to inaccurate calibration can be significant. As an example for illustration, 1% of a measured dark signal spectrum has been added to the reference radiance as remaining dark signal error spectrum. Errors of )6% for N2 O and more than 10% for CO obtained for this case emphasise the high sensitivity to errors in dark signal corrections. As an example, residuals are shown in Fig. 3. The vertical column errors due to the considered perturbation are given in Table 1.
4. Discretisation of the look-up table The WFM-DOAS algorithm uses a set of atmospheric radiances and weighting functions calculated for various geometric and atmospheric parameters like solar zenith angle, ground albedo, and atmospheric trace gas concentration profiles (US-standard atmosphere), e.g., different H2 O concentrations (H2 O profile scaled) (Buchwitz et al., 2004). The fast look-up table (LUtable) scheme introduces errors in vertical columns de-
Fig. 3. As Fig. 2 but using radiance corrupted by adding dark signal according to a calibration inaccurate by 1%. This leads to errors in the vertical column retrieval as given in Table 1, e.g., for H2 O of )21.9%, which can be clearly seen as difference in line depth between the perfect fit reference and the fit to erroneous radiance (third panel).
pending on the degree of discretisation of the geometrical and atmospheric parameters used. Such errors have been estimated for H2 O, CH4 , N2 O, and CO for measurements, simulated using RTM parameters which vary from those used to generate the algorithm LU-table. The sensitivity of the WFM-DOAS algorithm to these dedicated variations are given as percentage error estimates in Table 3. As an example, for the LU-table generation a relative azimuth of 0° and a solar zenith angle of 30.0° were used. As variations of geometrical parameters, the relative azimuth used for the simulations has taken to be 25° and the solar zenith angle has been changed to 32.5°. For this assumptions, Table 3 gives maximum percentage errors with respect to climatology vertical columns used for the simulations. Another example is the use of temperature and trace gas profiles different from those represented by the LU-table, e.g., using a tropical atmosphere (Temperature at 0 km: 299.7 K, H2 O column: 4.18 g/cm2 ) instead of US-standard atmosphere settings (Temperature at 0 km: 288.1 K, H2 O column: 1.43 g/ cm2 ). A list of all cases considered is given in Table 2. Errors are about 1.0% for most of the cases considered. Water vapour retrieval is slightly stronger affected by ground albedo variations ()4.2% error). For tropical and mid-latitude summer atmospheres considered,
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Table 2 Variations with respect to LU-table settings used for the sensitivity study of the WFM-DOAS algorithm Abreviation
Item
Reference setting for LU-table
Changes considered
Geom SurfEl Albedo EnhAer NoAer EnhWat RedWat TropAtm MidLtSum EnhCH4Bl
Geometrical parameters Surface elevation Ground albedo Enhanced aerosol No aerosol Enhanced water vapor Reduced water vapor Tropical atmosphere Mid-latitude summer Enhanced CH4 in boundary layer
RAA 0°; SZA 30.0° 0m 0.1 Maritim boundary aerosola Background aerosol US-standard US-standard US-standard US-standard US-standard
RAA 25°; SZA 32.5° 750 m 0.025, 0.05, 0.4 Rural boundary aerosola Aerosol switched off Enhanced by factor 1.8 Reduced by factor 0.6 Tropical atmosphere settings Mid-latitude summer settings Vertical column enhanced by 6%
a
RAA: relative azimuth angle, SZA: solar zenith angle. LOWTRAN/MODTRAN aerosol parametrisation.
Table 3 Percentage errors with respect to climatology vertical columns used for the simulations (see also Table 2 for explanation) Error source ! 2269–2275 nm 2360–2366 nm
Geom (%) CH4 N2 O H2 O CH4 CO
Error source ! 2269–2275 nm 2360–2366 nm
CH4 N2 O H2 O CH4 CO
)1.0 )0.9 )1.8 )1.2 )1.2
SurfEl (%) )0.9 )1.0 )1.9 )1.2 )1.1
)0.4 )1.4 )0.1 )0.5 )1.0
Albedo (%) )0.5 )1.4 )0.8 )0.1 )1.5
)0.7 0.5 )4.2 )1.0 )0.9
0.7 0.5 )4.2 )0.9 )1.0
EnhAer (%)
NoAer (%)
)0.7 )0.5 )0.7 )0.5 )0.5
)0.7 )0.6 )0.3 )0.5 )0.5
)0.7 )0.5 )0.6 )0.6 )0.4
)0.7 )0.6 )0.1 )0.5 )0.3
EnhWat (%)
RedWat (%)
TropAtm (%)
MidLtSum (%)
EnhCH4Bl (%)
0.0 0.0 )0.2 )0.1 0.0
0.0 0.0 )1.0 )0.1 0.0
)1.2 )0.7 16.4 )6.8 27.1
)0.3 0.0 12.1 )4.6 14.7
0.7 )0.6 )0.1 0.0 )0.3
0.0 0.0 )0.1 0.0 )0.1
0.0 0.0 )1.1 0.0 )0.1
)0.4 )0.4 )1.1 2.7 )15.6
)0.6 0.7 1.3 1.4 )3.7
0.8 )0.8 0.0 )0.1 )0.2
For numbers of the right side of each column an additional temperature profile fit parameter has been used.
except for CO, large errors can be strongly reduced by using a temperature profile shift fit parameter (see Table 2, right column for each case). Errors given should only be related to the WFM-DOAS algorithm, i.e., to the extension of the used reference look-up tables. Further testing with respect to fitting windows and LU-table optimisation is foreseen.
5. Conclusions The sensitivities of trace gas retrieval in SCIAMACHY Channel 8 to simulated errors in polarisation and dark signal corrections as performed within the SCIAMACHY operational calibration processing have been investigated using the WFM-DOAS retrieval algorithm. The current SCIAMACHY operational fit window settings have been used. The sensitivity of WFM-DOAS vertical columns of H2 O, CO, N2 O, and CH4 to incorrect dark signal corrections is strong, which for the considered case of 1% error in dark signal correction leads to errors of )21.9%, 10.9%, )6.0%, and )4.3%, respectively. Errors in Q and U processing around 0.1, which have similarly shown up in processor calibration closed-
loop tests (de Beek, 2002), lead to negligible errors in trace gas vertical columns. For selected simulated cases considered assuming even unphysical polarisation parameters, maximum errors of about 2% in vertical columns have been obtained for CO. As fit windows currently used in the SCIAMACHY operational processing test phase and a method similar to those of the SCIAMACHY processor have been applied, errors presented could be taken as rough estimates for operational products. For the WFM-DOAS algorithm, LU-table discretisation errors are about 1.0% for most of the cases considered. Water vapour retrieval is slightly stronger affected by ground albedo variations (maximum case: )4.2% error). For tropical and mid-latitude summer atmospheres considered, except for CO, large errors can be strongly reduced by using a temperature profile shift fit parameter.
Acknowledgements This work has been funded by ESA (ESA/ESTEC Contract 13594/99/NL/PR) and by the University and the State of Bremen.
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References Bovensmann, H., Burrows, J.P., Buchwitz, M., et al. SCIAMACHY – Mission objectives and measurement modes. J. Atmos. Sci. 56, 125–150, 1999. Buchwitz, M., Rozanov, V., Burrows, J. A near-infrared optimized DOAS method for the fast global retrieval of atmospheric CH4 , CO, CO2 , H2 O, and N2 O total column amounts from SCIAMACHY Envisat-1 nadir radiances. J. Geophys. Res. 105 (D12), 15231–15245, 2000. Buchwitz, M., No€el, S., Bramstedt, K., et al. Retrieval of trace gas vertical columns from SCIAMACHY/ENVISAT near-infrared
nadir spectra: first preliminary results. Adv. Space Res., this issue, 2004, doi:10.1016/j.asr.2003.05.054. de Beek, R. SCIAMACHY Level 0-to-1 Processor Closed-Loop Tests, Technical Report. ESA/ESTEC, Envisat-1 Program, Contract 13594/99/NL/PR, 2002. de Beek, R. SUPPRO Final Report, Technical Report. ESA/ESTEC, Envisat-1 Program, Contract 13594/99/NL/PR, 2003. Spurr, R., Chance, K. BIAS: an algorithm for the retrieval of trace gas vertical column amounts from near-infrared earthshine measurements by the SCIAMACHY spectrometer, in: Proceedings of the IGARSS Conference, Seattle, 1998.
Trace gas column retrieval from IR nadir spectra – a model study for SCIAMACHY R. de Beek *, M. Buchwitz, V.V. Rozanov, J.P. Burrows Institute of Environmental Physics, University of Bremen, FB 1, D-28334 Bremen, Germany Received 6 January 2003; received in revised form 16 June 2003; accepted 19 June 2003
Abstract The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) is part of the European satellite ENVISAT launched at 1st March 2002. It is a follow-on instrument of the Global Ozone Monitoring Experiment (GOME) flying on ERS-2 and, compared to GOME, has extended capabilities. Using measurements of the direct extra-terrestrial solar spectrum and sun-light reflected and scattered by the earth atmosphere or surface SCIAMACHY detects atmospheric absorption of several trace species absorbing in spectral regions from the ultraviolet to the near infrared (240–2380 nm). Vertical columns of H2 O, N2 O, CO, and CH4 can be retrieved using SCIAMACHY Channel 8 near-infrared nadir measurements. In this study, selected atmospheric and instrument specific errors relevant for the retrieval are analysed. Spectral windows of Channel 8 are considered, which are currently used for the operational near-real-time processing. For this purpose, spectral error patterns have been simulated as well as sun-normalised model radiances for nadir scanning mode, the latter using the radiative transfer model SCIATRAN. Focus are the polarisation sensitivity and dark signals of the instrument. Further on, accuracy estimates for a number of different atmospheric scenarios are presented. Ó 2004 COSPAR. Published by Elsevier Ltd. All rights reserved. Keywords: Trace gas column retrieval; IR nadir spectra; Model study for SCIAMACHY; ENVISAT
1. Introduction The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) is a UV/ Vis/near-infrared spectrometer (Bovensmann et al., 1999). Total column amounts of the atmospheric trace gases CH4 , H2 O, CO, CO2 , and N2 O are operationally retrieved from near-infrared nadir radiance and solar irradiance spectral measurements of SCIAMACHY Channel 7 (1934–2043 nm) and Channel 8 (2259–2385 nm) in near-real-time using the BIAS algorithm (Spurr and Chance, 1998). For calibration purposes, polarisation sensitivity and dark signal corrections are part of the operational SCIAMACHY processing scheme. Investigations have been performed in the frame of the * Corresponding author. Tel.: +49-421-218-4475; fax: +49-421-2184555. E-mail address: [email protected] (R. de Beek).
ESA project SUPPRO (de Beek, 2003) in order to achieve first error estimates with respect to these two error sources using the WFM-DOAS algorithm under development at the University of Bremen (Buchwitz et al., 2000, 2004). The wavelength dependent polarisation sensitivity of the instrument characterised onground prior to flight is used for correction. In case of inaccurate calibration, spectral polarisation characteristics will be mapped into the calibrated radiance, which lead to errors in trace gas total column retrievals. The relative dark signal contribution to the overall signal of the instrument can be large, especially for the case of a low ground albedo. Related inaccurate calibrations are therefore of special interest. Due to the principle similarities of the BIAS and WFM-DOAS methodologies similar responses of both algorithms to these error sources are assumed. Due to discretisation, inaccurate atmospheric and geometric parameters applied for the radiance and weighting function look-up table generation lead to
0273-1177/$30 Ó 2004 COSPAR. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.asr.2003.06.041
R. de Beek et al. / Advances in Space Research 34 (2004) 734–738
735
errors in total column retrieval. For selected cases, specific errors due to the discretisation of the look-up table scheme of the WFM-DOAS algorithm (Buchwitz et al., 2000) are estimated. Spectral fitting windows of Channel 8 as currently in use for SGP have been selected: 2269–2275 and 2360– 2366 nm, chosen for fittings of N2 O and CO, respectively. Simultaneously fitted CH4 and H2 O total columns have also been considered.
2. Polarisation correction In order to correct for instrumentally induced polarisation structures during SCIAMACHY operational data processing radiances are multiplied by polarisation correction factors (PCF), which are calculated using retrieved polarisation state parameters Q and U (Stokes parameters) and the pre-flight spectral characteric function of the instrumental polarisation sensitivity. For the simulation of erroneous PCF Cpolerr , failures in operational Q and U processing have been assumed using various polarisation states. As a reference, a radiance spectrum Rad has been simulated. Corruption of the radiance spectrum by multiplication with PCE ¼ (Cpolerr /Cpol) yields the erroneous radiance Raderr , where Cpol is the ideal PCF for the state considered. Retrieved trace gas columns using Raderr with respect to that achieved using the uncorrupted radiance Rad (hereinafter called ‘‘perfect fit’’) give percentage error estimates. Erroneous PCF have been simulated for various states of linear polarisation assuming errors in Q and U processing which are equally distributed within 0.15. This is on the order of observations during processor calibration closed-loop tests (de Beek, 2002). Retrievals applied resulted in a large data set of vertical column errors, which has been statistically analysed. Maximum errors and standard deviations are given in Table 1. Although the final operational polarisation state retrieval is expected to be at least accurate within the assumed range, single cases of complete failures in Q and U processing (examples of unphysical results, see e.g., de Beek, 2002) have also been tested. For illustration, an example of a simulated PCE spectrum for such
Fig. 1. As an example for un-polarised light (Q ¼ U ¼ 0, Cpol ¼ 1.0), a simulated polarisation calibration error (PCE) spectrum is shown for SCIAMACHY Channel 8. For this example, PCE has been generated assuming Qerr ¼ l and Uerr ¼ )1 (complete processing failure). This has been multiplied to the reference radiance to give the erroneous calibrated radiance. For the case of such errors, spectral structures as seen in panels 2 and 3, which origin is the spectral shape of instrumental polarisation sensitivity, are transfered into calibrated radiances and lead to errors in the retrieval (see Table 1).
a case is shown in Fig. 1. The sun-normalised radiance fitted using the CO-window is shown in Fig. 2.
3. Dark signal correction Dark signal contributions to SCIAMACHY measurements, which mainly arise from instrumental noise and thermal background emission, have to be corrected for. Due to the large contribution of dark signals relative
Table 1 Percentage errors with respect to vertical columns obtained from the perfect fit Error source !
DarkSigErr (%)
PolCorrErr (%) MaxErr
StdDev
ProcFail
2269–2275 nm
CH4 N2 O
0.06 0.15
0.02 0.06
0.3 1.1
)4.3 )6.0
2360–2366 nm
H2 O CH4 CO
0.31 0.44 0.15
0.11 0.15 0.06
)1.9 0.7 2.6
)21.9 )11.1 10.9
PolCorrErr: errors due to erroneous PCF, MaxErr and StdDev: maximum errors and standard deviations of the considered data, ProcFail: maximum errors due to processing failures (see Fig. 1), DarkSigErr: errors due to inaccurate dark signal correction.
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Fig. 2. WFM-DOAS as applied to a model sun-normalised radiance. The reference model radiance has been multiplied by PCE to give the corrupted radiance. Panels 2–3 show fitted weighting functions of the considered trace gases. The fit to the corrupted radiance (diamonds) results in vertical column errors. Residuals are small compared to dark signal case. Correlation between weighting functions and PCE is small, i.e., the introduced PCE characteristics can be recognised in the residual structure, except for H2 O around 2364 nm.
to the overall signal the sensitivity of the retrieval algorithm to inaccurate calibration can be significant. As an example for illustration, 1% of a measured dark signal spectrum has been added to the reference radiance as remaining dark signal error spectrum. Errors of )6% for N2 O and more than 10% for CO obtained for this case emphasise the high sensitivity to errors in dark signal corrections. As an example, residuals are shown in Fig. 3. The vertical column errors due to the considered perturbation are given in Table 1.
4. Discretisation of the look-up table The WFM-DOAS algorithm uses a set of atmospheric radiances and weighting functions calculated for various geometric and atmospheric parameters like solar zenith angle, ground albedo, and atmospheric trace gas concentration profiles (US-standard atmosphere), e.g., different H2 O concentrations (H2 O profile scaled) (Buchwitz et al., 2004). The fast look-up table (LUtable) scheme introduces errors in vertical columns de-
Fig. 3. As Fig. 2 but using radiance corrupted by adding dark signal according to a calibration inaccurate by 1%. This leads to errors in the vertical column retrieval as given in Table 1, e.g., for H2 O of )21.9%, which can be clearly seen as difference in line depth between the perfect fit reference and the fit to erroneous radiance (third panel).
pending on the degree of discretisation of the geometrical and atmospheric parameters used. Such errors have been estimated for H2 O, CH4 , N2 O, and CO for measurements, simulated using RTM parameters which vary from those used to generate the algorithm LU-table. The sensitivity of the WFM-DOAS algorithm to these dedicated variations are given as percentage error estimates in Table 3. As an example, for the LU-table generation a relative azimuth of 0° and a solar zenith angle of 30.0° were used. As variations of geometrical parameters, the relative azimuth used for the simulations has taken to be 25° and the solar zenith angle has been changed to 32.5°. For this assumptions, Table 3 gives maximum percentage errors with respect to climatology vertical columns used for the simulations. Another example is the use of temperature and trace gas profiles different from those represented by the LU-table, e.g., using a tropical atmosphere (Temperature at 0 km: 299.7 K, H2 O column: 4.18 g/cm2 ) instead of US-standard atmosphere settings (Temperature at 0 km: 288.1 K, H2 O column: 1.43 g/ cm2 ). A list of all cases considered is given in Table 2. Errors are about 1.0% for most of the cases considered. Water vapour retrieval is slightly stronger affected by ground albedo variations ()4.2% error). For tropical and mid-latitude summer atmospheres considered,
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Table 2 Variations with respect to LU-table settings used for the sensitivity study of the WFM-DOAS algorithm Abreviation
Item
Reference setting for LU-table
Changes considered
Geom SurfEl Albedo EnhAer NoAer EnhWat RedWat TropAtm MidLtSum EnhCH4Bl
Geometrical parameters Surface elevation Ground albedo Enhanced aerosol No aerosol Enhanced water vapor Reduced water vapor Tropical atmosphere Mid-latitude summer Enhanced CH4 in boundary layer
RAA 0°; SZA 30.0° 0m 0.1 Maritim boundary aerosola Background aerosol US-standard US-standard US-standard US-standard US-standard
RAA 25°; SZA 32.5° 750 m 0.025, 0.05, 0.4 Rural boundary aerosola Aerosol switched off Enhanced by factor 1.8 Reduced by factor 0.6 Tropical atmosphere settings Mid-latitude summer settings Vertical column enhanced by 6%
a
RAA: relative azimuth angle, SZA: solar zenith angle. LOWTRAN/MODTRAN aerosol parametrisation.
Table 3 Percentage errors with respect to climatology vertical columns used for the simulations (see also Table 2 for explanation) Error source ! 2269–2275 nm 2360–2366 nm
Geom (%) CH4 N2 O H2 O CH4 CO
Error source ! 2269–2275 nm 2360–2366 nm
CH4 N2 O H2 O CH4 CO
)1.0 )0.9 )1.8 )1.2 )1.2
SurfEl (%) )0.9 )1.0 )1.9 )1.2 )1.1
)0.4 )1.4 )0.1 )0.5 )1.0
Albedo (%) )0.5 )1.4 )0.8 )0.1 )1.5
)0.7 0.5 )4.2 )1.0 )0.9
0.7 0.5 )4.2 )0.9 )1.0
EnhAer (%)
NoAer (%)
)0.7 )0.5 )0.7 )0.5 )0.5
)0.7 )0.6 )0.3 )0.5 )0.5
)0.7 )0.5 )0.6 )0.6 )0.4
)0.7 )0.6 )0.1 )0.5 )0.3
EnhWat (%)
RedWat (%)
TropAtm (%)
MidLtSum (%)
EnhCH4Bl (%)
0.0 0.0 )0.2 )0.1 0.0
0.0 0.0 )1.0 )0.1 0.0
)1.2 )0.7 16.4 )6.8 27.1
)0.3 0.0 12.1 )4.6 14.7
0.7 )0.6 )0.1 0.0 )0.3
0.0 0.0 )0.1 0.0 )0.1
0.0 0.0 )1.1 0.0 )0.1
)0.4 )0.4 )1.1 2.7 )15.6
)0.6 0.7 1.3 1.4 )3.7
0.8 )0.8 0.0 )0.1 )0.2
For numbers of the right side of each column an additional temperature profile fit parameter has been used.
except for CO, large errors can be strongly reduced by using a temperature profile shift fit parameter (see Table 2, right column for each case). Errors given should only be related to the WFM-DOAS algorithm, i.e., to the extension of the used reference look-up tables. Further testing with respect to fitting windows and LU-table optimisation is foreseen.
5. Conclusions The sensitivities of trace gas retrieval in SCIAMACHY Channel 8 to simulated errors in polarisation and dark signal corrections as performed within the SCIAMACHY operational calibration processing have been investigated using the WFM-DOAS retrieval algorithm. The current SCIAMACHY operational fit window settings have been used. The sensitivity of WFM-DOAS vertical columns of H2 O, CO, N2 O, and CH4 to incorrect dark signal corrections is strong, which for the considered case of 1% error in dark signal correction leads to errors of )21.9%, 10.9%, )6.0%, and )4.3%, respectively. Errors in Q and U processing around 0.1, which have similarly shown up in processor calibration closed-
loop tests (de Beek, 2002), lead to negligible errors in trace gas vertical columns. For selected simulated cases considered assuming even unphysical polarisation parameters, maximum errors of about 2% in vertical columns have been obtained for CO. As fit windows currently used in the SCIAMACHY operational processing test phase and a method similar to those of the SCIAMACHY processor have been applied, errors presented could be taken as rough estimates for operational products. For the WFM-DOAS algorithm, LU-table discretisation errors are about 1.0% for most of the cases considered. Water vapour retrieval is slightly stronger affected by ground albedo variations (maximum case: )4.2% error). For tropical and mid-latitude summer atmospheres considered, except for CO, large errors can be strongly reduced by using a temperature profile shift fit parameter.
Acknowledgements This work has been funded by ESA (ESA/ESTEC Contract 13594/99/NL/PR) and by the University and the State of Bremen.
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