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M. Van Roozendael - One of the best experts on this subject based on the ideXlab platform.
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GDP 4.0 TRANSFER TO SGP 3.0 FOR SCIAMACHY NO 2 COLUMN PROCESSING: VERIFICATION WITH SDOAS / GDOAS PROTOTYPE ALGORITHMS AND DELTA-VALIDATION WITH NDACC / UV-VISIBLE NETWORK Data , F. Wittrock (14)
2020Co-Authors: J.-c Lambert, Christophe Lerot, M. Van Roozendael, P Gerard, J Granville, F Hendrick, S B Andersen, V Dorokhov, M Gil, F GoutailAbstract:ABSTRACT Until mid 2006, SCIAMACHY Data Processors for the operational retrieval of nitrogen dioxide (NO 2 ) column Data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO 2 Data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the offline SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric Data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO 2 Data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO 2 Data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous Processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant
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sixteen years of gome ers 2 total ozone Data the new direct fitting gome Data Processor gdp version 5 algorithm description
Journal of Geophysical Research, 2012Co-Authors: M. Van Roozendael, Dimitris Balis, Christophe Lerot, Walter Zimmer, Diego Loyola, R. Spurr, Jean-christopher Lambert, J. Van Gent, J. Van Geffen, M E KoukouliAbstract:[1] The Global Ozone Monitoring Instrument (GOME) was launched in April 1995 on ESA's ERS-2 platform, and the GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. We report on the new GDP5 spectral fitting algorithm used to reprocess the 16-year GOME Data record. Previous GDP total ozone algorithms were based on the DOAS method. In contrast, GDP5 uses a direct-fitting algorithm without high-pass filtering of radiances; there is no air mass factor conversion to vertical column amount. GDP5 includes direct radiative transfer simulation of earthshine radiances and Jacobians with respect to total ozone, albedo closure and other ancillary fitting parameters - a temperature profile shift, and amplitudes for undersampling and Ring-effect interference signals. Simulations are based on climatological ozone profiles extracted from the TOMS Version 8 Database, classified by total column. GDP5 uses the high-resolution Brion-Daumont-Malicet ozone absorption cross-sections, replacing older GOME-measured flight model Data. The semi-empirical molecular Ring correction developed for GDP4 has been adapted for direct fitting. Cloud preprocessing for GDP5 is done using updated versions of cloud-correction algorithms OCRA and ROCINN. The reprocessed GOME GDP5 record maintains the remarkable long-term stability of time series already achieved with GDP4. Furthermore, validation results show a clear improvement in the accuracy of the ozone product with reduced solar zenith angle and seasonal dependences, particularly in comparison with correlative observations from the ground-based network of Brewer spectrophotometers.
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six years of total ozone column measurements from sciamachy nadir observations
Atmospheric Measurement Techniques, 2009Co-Authors: Christophe Lerot, M. Van Roozendael, J. Van Gent, J. Van Geffen, C Fayt, Gunter Lichtenberg, Robert Spurr, A Von BargenAbstract:Abstract. Total O3 columns have been retrieved from six years of SCIAMACHY nadir UV radiance measurements using SDOAS, an adaptation of the GDOAS algorithm previously developed at BIRA-IASB for the GOME instrument. GDOAS and SDOAS have been implemented by the German Aerospace Center (DLR) in the version 4 of the GOME Data Processor (GDP) and in version 3 of the SCIAMACHY Ground Processor (SGP), respectively. The Processors are being run at the DLR processing centre on behalf of the European Space Agency (ESA). We first focus on the description of the SDOAS algorithm with particular attention to the impact of uncertainties on the reference O3 absorption cross-sections. Second, the resulting SCIAMACHY total ozone Data set is globally evaluated through large-scale comparisons with results from GOME and OMI as well as with ground-based correlative measurements. The various total ozone Data sets are found to agree within 2% on average. However, a negative trend of 0.2–0.4%/year has been identified in the SCIAMACHY O3 columns; this probably originates from instrumental degradation effects that have not yet been fully characterized.
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ten years of gome ers2 total ozone Data the new gome Data Processor gdp version 4 2 ground based validation and comparisons with toms v7 v8
Journal of Geophysical Research, 2007Co-Authors: Dimitris Balis, Pieter Valks, Diego Loyola, R. Spurr, M. Van Roozendael, Jean-christopher Lambert, Y Livschitz, V Amiridis, P Gerard, J GranvilleAbstract:[1] The atmospheric chemistry instrument Global Ozone Monitoring Experiment (GOME) was launched in April 1995 on the ERS-2 platform. The GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. With a Data record of over ten years, GOME has become important for ozone trend analysis. In 2004, GDP was upgraded to version 4.0, a new validation was performed, and the entire GOME Data record was reprocessed. In the preceding paper (Van Roozendael et al., 2006), the GDP 4.0 algorithm was described. In this paper, we deal with geophysical validation of the GDP 4.0 algorithm and the retrieved ozone products. We present results of a validation exercise involving comparisons of GDP 4.0 total ozone with the Network for Detection of Stratospheric Change (NDSC) and the World Meteorological Organization (WMO)/Global Atmospheric Watch (GAW) ground-based networks. We compare these results with similar validations of earlier GDP ozone products. We also present ground-based validation of TOMS versions 7 and 8 total ozone products, and we contrast these with GDP 4.0 values. On a global basis, GDP 4.0 total ozone results lie between −1% and +1.5% of ground-based values for solar zenith angles less than 70°; accuracy is now comparable to that obtainable from ground-based stations. At higher solar zenith angles in polar regions, larger discrepancies of up to +5% are found; in these regimes, errors on both satellite and ground-based measurements are higher. The validation also showed marked improvement in TOMS total ozone performance for the version 8 algorithm.
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sciamachy level 1b 2 Data processing update of off line Data Processor to version 3 0
Proceedings of the Third Workshop on the Atmospheric Chemistry Validation of Envisat (ACVE-3), 2007Co-Authors: A Von Bargen, A. A. Kokhanovsky, Heinrich Bovensmann, Christophe Lerot, M. Van Roozendael, Thomas Schroder, Adrian Doicu, Klaus Kretschel, Marco Vountas, Michael HessAbstract:Prasentation des Upgrades der Algorithmen zur operationellen Prozessierung von SCIAMACHY Messdaten
Diego Loyola - One of the best experts on this subject based on the ideXlab platform.
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validation of gome 2 metop a total water vapour column using reference radiosonde Data from the gruan network
Atmospheric Measurement Techniques, 2014Co-Authors: M Anton, Diego Loyola, Roberto Roman, H VomelAbstract:Abstract. The main goal of this paper is to validate the total water vapour column (TWVC) measured by the Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensor and generated using the GOME Data Processor (GDP) retrieval algorithm developed by the German Aerospace Centre (DLR). For this purpose, spatially and temporally collocated TWVC Data from highly accurate sounding measurements for the period January 2009–May 2014 at six sites are used. These balloon-borne Data are provided by the GCOS Reference Upper-Air Network (GRUAN). The correlation between GOME-2 and sounding TWVC Data is reasonably good (determination coefficient, R2, of 0.89) when all available radiosondes (1400) are employed in the inter-comparison. When cloud-free cases (544) are selected by means of the satellite cloud fraction (CF
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sixteen years of gome ers 2 total ozone Data the new direct fitting gome Data Processor gdp version 5 algorithm description
Journal of Geophysical Research, 2012Co-Authors: M. Van Roozendael, Dimitris Balis, Christophe Lerot, Walter Zimmer, Diego Loyola, R. Spurr, Jean-christopher Lambert, J. Van Gent, J. Van Geffen, M E KoukouliAbstract:[1] The Global Ozone Monitoring Instrument (GOME) was launched in April 1995 on ESA's ERS-2 platform, and the GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. We report on the new GDP5 spectral fitting algorithm used to reprocess the 16-year GOME Data record. Previous GDP total ozone algorithms were based on the DOAS method. In contrast, GDP5 uses a direct-fitting algorithm without high-pass filtering of radiances; there is no air mass factor conversion to vertical column amount. GDP5 includes direct radiative transfer simulation of earthshine radiances and Jacobians with respect to total ozone, albedo closure and other ancillary fitting parameters - a temperature profile shift, and amplitudes for undersampling and Ring-effect interference signals. Simulations are based on climatological ozone profiles extracted from the TOMS Version 8 Database, classified by total column. GDP5 uses the high-resolution Brion-Daumont-Malicet ozone absorption cross-sections, replacing older GOME-measured flight model Data. The semi-empirical molecular Ring correction developed for GDP4 has been adapted for direct fitting. Cloud preprocessing for GDP5 is done using updated versions of cloud-correction algorithms OCRA and ROCINN. The reprocessed GOME GDP5 record maintains the remarkable long-term stability of time series already achieved with GDP4. Furthermore, validation results show a clear improvement in the accuracy of the ozone product with reduced solar zenith angle and seasonal dependences, particularly in comparison with correlative observations from the ground-based network of Brewer spectrophotometers.
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ten years of gome ers2 total ozone Data the new gome Data Processor gdp version 4 2 ground based validation and comparisons with toms v7 v8
Journal of Geophysical Research, 2007Co-Authors: Dimitris Balis, Pieter Valks, Diego Loyola, R. Spurr, M. Van Roozendael, Jean-christopher Lambert, Y Livschitz, V Amiridis, P Gerard, J GranvilleAbstract:[1] The atmospheric chemistry instrument Global Ozone Monitoring Experiment (GOME) was launched in April 1995 on the ERS-2 platform. The GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. With a Data record of over ten years, GOME has become important for ozone trend analysis. In 2004, GDP was upgraded to version 4.0, a new validation was performed, and the entire GOME Data record was reprocessed. In the preceding paper (Van Roozendael et al., 2006), the GDP 4.0 algorithm was described. In this paper, we deal with geophysical validation of the GDP 4.0 algorithm and the retrieved ozone products. We present results of a validation exercise involving comparisons of GDP 4.0 total ozone with the Network for Detection of Stratospheric Change (NDSC) and the World Meteorological Organization (WMO)/Global Atmospheric Watch (GAW) ground-based networks. We compare these results with similar validations of earlier GDP ozone products. We also present ground-based validation of TOMS versions 7 and 8 total ozone products, and we contrast these with GDP 4.0 values. On a global basis, GDP 4.0 total ozone results lie between −1% and +1.5% of ground-based values for solar zenith angles less than 70°; accuracy is now comparable to that obtainable from ground-based stations. At higher solar zenith angles in polar regions, larger discrepancies of up to +5% are found; in these regimes, errors on both satellite and ground-based measurements are higher. The validation also showed marked improvement in TOMS total ozone performance for the version 8 algorithm.
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ten years of gome ers 2 total ozone Data the new gome Data Processor gdp version 4 1 algorithm description
Journal of Geophysical Research, 2006Co-Authors: M. Van Roozendael, Pieter Valks, Dimitris Balis, Diego Loyola, R. Spurr, Jean-christopher Lambert, Thomas Ruppert, Y Livschitz, P Kenter, C FaytAbstract:The Global Ozone Monitoring Instrument (GOME) was launched on European Space Agency's ERS-2 platform in April 1995. The GOME Data Processor (GDP) operational retrieval algorithm has generated total ozone columns since July 1995. In 2004 the GDP system was given a major upgrade to version 4.0, a new validation was performed, and the 10-year GOME level 1 Data record was reprocessed. In two papers, we describe the GDP 4.0 retrieval algorithm and present an error budget and sensitivity analysis (paper 1) and validation of the GDP total ozone product and the overall accuracy of the entire GOME ozone record (paper 2). GDP 4.0 uses an optimized differential optical absorption spectroscopy (DOAS) algorithm, with air mass factor (AMF) conversions calculated using the radiative transfer code linearized discrete ordinate radiative transfer (LIDORT). AMF computation is based on the TOMS version 8 ozone profile climatology, classified by total column, and AMFs are adjusted iteratively to reflect the DOAS slant column result. GDP 4.0 has improved wavelength calibration and reference spectra and includes a new molecular Ring correction to deal with distortion of ozone absorption features due to inelastic rotational Raman scattering effects. Preprocessing for cloud parameter estimation in GDP 4.0 is done using two new cloud correction algorithms: OCRA and ROCINN. For clear and cloudy scenes the precision of the ozone column product is better than 2.4 and 3.3%, respectively, for solar zenith angles up to 80°. Comparisons with ground-based Data are generally at the 1-1.5% level or better for all regions outside the poles.
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gome level 1 to 2 Data Processor version 3 0 a major upgrade of the gome ers 2 total ozone retrieval algorithm
Applied Optics, 2005Co-Authors: R. Spurr, Diego Loyola, M. Van Roozendael, Werner Thomas, Wolfgang Balzer, Eberhard Mikusch, Bernd Aberle, Sander Slijkhuis, Thomas Ruppert, Jean-christopher LambertAbstract:The global ozone monitoring experiment (GOME) was launched in April 1995, and the GOME Data Processor (GDP) retrieval algorithm has processed operational total ozone amounts since July 1995. GDP level 1-to-2 is based on the two-step differential optical absorption spectroscopy (DOAS) approach, involving slant column fitting followed by air mass factor (AMF) conversions to vertical column amounts. We present a major upgrade of this algorithm to version 3.0. GDP 3.0 was implemented in July 2002, and the 9-year GOME Data record from July 1995 to December 2004 has been processed using this algorithm. The key component in GDP 3.0 is an iterative approach to AMF calculation, in which AMFs and corresponding vertical column densities are adjusted to reflect the true ozone distribution as represented by the fitted DOAS effective slant column. A neural network ensemble is used to optimize the fast and accurate parametrization of AMFs. We describe results of a recent validation exercise for the operational version of the total ozone algorithm; in particular, seasonal and meridian errors are reduced by a factor of 2. On a global basis, GDP 3.0 ozone total column results lie between −2% and +4% of ground-based values for moderate solar zenith angles lower than 70°. A larger variability of about +5% and −8% is observed for higher solar zenith angles up to 90°.
Jean-christopher Lambert - One of the best experts on this subject based on the ideXlab platform.
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sixteen years of gome ers 2 total ozone Data the new direct fitting gome Data Processor gdp version 5 algorithm description
Journal of Geophysical Research, 2012Co-Authors: M. Van Roozendael, Dimitris Balis, Christophe Lerot, Walter Zimmer, Diego Loyola, R. Spurr, Jean-christopher Lambert, J. Van Gent, J. Van Geffen, M E KoukouliAbstract:[1] The Global Ozone Monitoring Instrument (GOME) was launched in April 1995 on ESA's ERS-2 platform, and the GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. We report on the new GDP5 spectral fitting algorithm used to reprocess the 16-year GOME Data record. Previous GDP total ozone algorithms were based on the DOAS method. In contrast, GDP5 uses a direct-fitting algorithm without high-pass filtering of radiances; there is no air mass factor conversion to vertical column amount. GDP5 includes direct radiative transfer simulation of earthshine radiances and Jacobians with respect to total ozone, albedo closure and other ancillary fitting parameters - a temperature profile shift, and amplitudes for undersampling and Ring-effect interference signals. Simulations are based on climatological ozone profiles extracted from the TOMS Version 8 Database, classified by total column. GDP5 uses the high-resolution Brion-Daumont-Malicet ozone absorption cross-sections, replacing older GOME-measured flight model Data. The semi-empirical molecular Ring correction developed for GDP4 has been adapted for direct fitting. Cloud preprocessing for GDP5 is done using updated versions of cloud-correction algorithms OCRA and ROCINN. The reprocessed GOME GDP5 record maintains the remarkable long-term stability of time series already achieved with GDP4. Furthermore, validation results show a clear improvement in the accuracy of the ozone product with reduced solar zenith angle and seasonal dependences, particularly in comparison with correlative observations from the ground-based network of Brewer spectrophotometers.
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ten years of gome ers2 total ozone Data the new gome Data Processor gdp version 4 2 ground based validation and comparisons with toms v7 v8
Journal of Geophysical Research, 2007Co-Authors: Dimitris Balis, Pieter Valks, Diego Loyola, R. Spurr, M. Van Roozendael, Jean-christopher Lambert, Y Livschitz, V Amiridis, P Gerard, J GranvilleAbstract:[1] The atmospheric chemistry instrument Global Ozone Monitoring Experiment (GOME) was launched in April 1995 on the ERS-2 platform. The GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. With a Data record of over ten years, GOME has become important for ozone trend analysis. In 2004, GDP was upgraded to version 4.0, a new validation was performed, and the entire GOME Data record was reprocessed. In the preceding paper (Van Roozendael et al., 2006), the GDP 4.0 algorithm was described. In this paper, we deal with geophysical validation of the GDP 4.0 algorithm and the retrieved ozone products. We present results of a validation exercise involving comparisons of GDP 4.0 total ozone with the Network for Detection of Stratospheric Change (NDSC) and the World Meteorological Organization (WMO)/Global Atmospheric Watch (GAW) ground-based networks. We compare these results with similar validations of earlier GDP ozone products. We also present ground-based validation of TOMS versions 7 and 8 total ozone products, and we contrast these with GDP 4.0 values. On a global basis, GDP 4.0 total ozone results lie between −1% and +1.5% of ground-based values for solar zenith angles less than 70°; accuracy is now comparable to that obtainable from ground-based stations. At higher solar zenith angles in polar regions, larger discrepancies of up to +5% are found; in these regimes, errors on both satellite and ground-based measurements are higher. The validation also showed marked improvement in TOMS total ozone performance for the version 8 algorithm.
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ten years of gome ers 2 total ozone Data the new gome Data Processor gdp version 4 1 algorithm description
Journal of Geophysical Research, 2006Co-Authors: M. Van Roozendael, Pieter Valks, Dimitris Balis, Diego Loyola, R. Spurr, Jean-christopher Lambert, Thomas Ruppert, Y Livschitz, P Kenter, C FaytAbstract:The Global Ozone Monitoring Instrument (GOME) was launched on European Space Agency's ERS-2 platform in April 1995. The GOME Data Processor (GDP) operational retrieval algorithm has generated total ozone columns since July 1995. In 2004 the GDP system was given a major upgrade to version 4.0, a new validation was performed, and the 10-year GOME level 1 Data record was reprocessed. In two papers, we describe the GDP 4.0 retrieval algorithm and present an error budget and sensitivity analysis (paper 1) and validation of the GDP total ozone product and the overall accuracy of the entire GOME ozone record (paper 2). GDP 4.0 uses an optimized differential optical absorption spectroscopy (DOAS) algorithm, with air mass factor (AMF) conversions calculated using the radiative transfer code linearized discrete ordinate radiative transfer (LIDORT). AMF computation is based on the TOMS version 8 ozone profile climatology, classified by total column, and AMFs are adjusted iteratively to reflect the DOAS slant column result. GDP 4.0 has improved wavelength calibration and reference spectra and includes a new molecular Ring correction to deal with distortion of ozone absorption features due to inelastic rotational Raman scattering effects. Preprocessing for cloud parameter estimation in GDP 4.0 is done using two new cloud correction algorithms: OCRA and ROCINN. For clear and cloudy scenes the precision of the ozone column product is better than 2.4 and 3.3%, respectively, for solar zenith angles up to 80°. Comparisons with ground-based Data are generally at the 1-1.5% level or better for all regions outside the poles.
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gome level 1 to 2 Data Processor version 3 0 a major upgrade of the gome ers 2 total ozone retrieval algorithm
Applied Optics, 2005Co-Authors: R. Spurr, Diego Loyola, M. Van Roozendael, Werner Thomas, Wolfgang Balzer, Eberhard Mikusch, Bernd Aberle, Sander Slijkhuis, Thomas Ruppert, Jean-christopher LambertAbstract:The global ozone monitoring experiment (GOME) was launched in April 1995, and the GOME Data Processor (GDP) retrieval algorithm has processed operational total ozone amounts since July 1995. GDP level 1-to-2 is based on the two-step differential optical absorption spectroscopy (DOAS) approach, involving slant column fitting followed by air mass factor (AMF) conversions to vertical column amounts. We present a major upgrade of this algorithm to version 3.0. GDP 3.0 was implemented in July 2002, and the 9-year GOME Data record from July 1995 to December 2004 has been processed using this algorithm. The key component in GDP 3.0 is an iterative approach to AMF calculation, in which AMFs and corresponding vertical column densities are adjusted to reflect the true ozone distribution as represented by the fitted DOAS effective slant column. A neural network ensemble is used to optimize the fast and accurate parametrization of AMFs. We describe results of a recent validation exercise for the operational version of the total ozone algorithm; in particular, seasonal and meridian errors are reduced by a factor of 2. On a global basis, GDP 3.0 ozone total column results lie between −2% and +4% of ground-based values for moderate solar zenith angles lower than 70°. A larger variability of about +5% and −8% is observed for higher solar zenith angles up to 90°.
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gome level 1 to 2 Data Processor version 3 0 a major upgrade of the gome ers 2 total ozone retrieval algorithm
Applied Optics, 2005Co-Authors: R. Spurr, Diego Loyola, M. Van Roozendael, Werner Thomas, Wolfgang Balzer, Eberhard Mikusch, Bernd Aberle, Sander Slijkhuis, Thomas Ruppert, Jean-christopher LambertAbstract:The global ozone monitoring experiment (GOME) was launched in April 1995, and the GOME Data Processor (GDP) retrieval algorithm has processed operational total ozone amounts since July 1995. GDP level 1-to-2 is based on the two-step differential optical absorption spectroscopy (DOAS) approach, involving slant column fitting followed by air mass factor (AMF) conversions to vertical column amounts. We present a major upgrade of this algorithm to version 3.0. GDP 3.0 was implemented in July 2002, and the 9-year GOME Data record from July 1995 to December 2004 has been processed using this algorithm. The key component in GDP 3.0 is an iterative approach to AMF calculation, in which AMFs and corresponding vertical column densities are adjusted to reflect the true ozone distribution as represented by the fitted DOAS effective slant column. A neural network ensemble is used to optimize the fast and accurate parametrization of AMFs. We describe results of a recent validation exercise for the operational version of the total ozone algorithm; in particular, seasonal and meridian errors are reduced by a factor of 2. On a global basis, GDP 3.0 ozone total column results lie between -2% and +4% of ground-based values for moderate solar zenith angles lower than 70 degrees. A larger variability of about +5% and -8% is observed for higher solar zenith angles up to 90 degrees.
R. Spurr - One of the best experts on this subject based on the ideXlab platform.
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sixteen years of gome ers 2 total ozone Data the new direct fitting gome Data Processor gdp version 5 algorithm description
Journal of Geophysical Research, 2012Co-Authors: M. Van Roozendael, Dimitris Balis, Christophe Lerot, Walter Zimmer, Diego Loyola, R. Spurr, Jean-christopher Lambert, J. Van Gent, J. Van Geffen, M E KoukouliAbstract:[1] The Global Ozone Monitoring Instrument (GOME) was launched in April 1995 on ESA's ERS-2 platform, and the GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. We report on the new GDP5 spectral fitting algorithm used to reprocess the 16-year GOME Data record. Previous GDP total ozone algorithms were based on the DOAS method. In contrast, GDP5 uses a direct-fitting algorithm without high-pass filtering of radiances; there is no air mass factor conversion to vertical column amount. GDP5 includes direct radiative transfer simulation of earthshine radiances and Jacobians with respect to total ozone, albedo closure and other ancillary fitting parameters - a temperature profile shift, and amplitudes for undersampling and Ring-effect interference signals. Simulations are based on climatological ozone profiles extracted from the TOMS Version 8 Database, classified by total column. GDP5 uses the high-resolution Brion-Daumont-Malicet ozone absorption cross-sections, replacing older GOME-measured flight model Data. The semi-empirical molecular Ring correction developed for GDP4 has been adapted for direct fitting. Cloud preprocessing for GDP5 is done using updated versions of cloud-correction algorithms OCRA and ROCINN. The reprocessed GOME GDP5 record maintains the remarkable long-term stability of time series already achieved with GDP4. Furthermore, validation results show a clear improvement in the accuracy of the ozone product with reduced solar zenith angle and seasonal dependences, particularly in comparison with correlative observations from the ground-based network of Brewer spectrophotometers.
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ten years of gome ers2 total ozone Data the new gome Data Processor gdp version 4 2 ground based validation and comparisons with toms v7 v8
Journal of Geophysical Research, 2007Co-Authors: Dimitris Balis, Pieter Valks, Diego Loyola, R. Spurr, M. Van Roozendael, Jean-christopher Lambert, Y Livschitz, V Amiridis, P Gerard, J GranvilleAbstract:[1] The atmospheric chemistry instrument Global Ozone Monitoring Experiment (GOME) was launched in April 1995 on the ERS-2 platform. The GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. With a Data record of over ten years, GOME has become important for ozone trend analysis. In 2004, GDP was upgraded to version 4.0, a new validation was performed, and the entire GOME Data record was reprocessed. In the preceding paper (Van Roozendael et al., 2006), the GDP 4.0 algorithm was described. In this paper, we deal with geophysical validation of the GDP 4.0 algorithm and the retrieved ozone products. We present results of a validation exercise involving comparisons of GDP 4.0 total ozone with the Network for Detection of Stratospheric Change (NDSC) and the World Meteorological Organization (WMO)/Global Atmospheric Watch (GAW) ground-based networks. We compare these results with similar validations of earlier GDP ozone products. We also present ground-based validation of TOMS versions 7 and 8 total ozone products, and we contrast these with GDP 4.0 values. On a global basis, GDP 4.0 total ozone results lie between −1% and +1.5% of ground-based values for solar zenith angles less than 70°; accuracy is now comparable to that obtainable from ground-based stations. At higher solar zenith angles in polar regions, larger discrepancies of up to +5% are found; in these regimes, errors on both satellite and ground-based measurements are higher. The validation also showed marked improvement in TOMS total ozone performance for the version 8 algorithm.
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ten years of gome ers 2 total ozone Data the new gome Data Processor gdp version 4 1 algorithm description
Journal of Geophysical Research, 2006Co-Authors: M. Van Roozendael, Pieter Valks, Dimitris Balis, Diego Loyola, R. Spurr, Jean-christopher Lambert, Thomas Ruppert, Y Livschitz, P Kenter, C FaytAbstract:The Global Ozone Monitoring Instrument (GOME) was launched on European Space Agency's ERS-2 platform in April 1995. The GOME Data Processor (GDP) operational retrieval algorithm has generated total ozone columns since July 1995. In 2004 the GDP system was given a major upgrade to version 4.0, a new validation was performed, and the 10-year GOME level 1 Data record was reprocessed. In two papers, we describe the GDP 4.0 retrieval algorithm and present an error budget and sensitivity analysis (paper 1) and validation of the GDP total ozone product and the overall accuracy of the entire GOME ozone record (paper 2). GDP 4.0 uses an optimized differential optical absorption spectroscopy (DOAS) algorithm, with air mass factor (AMF) conversions calculated using the radiative transfer code linearized discrete ordinate radiative transfer (LIDORT). AMF computation is based on the TOMS version 8 ozone profile climatology, classified by total column, and AMFs are adjusted iteratively to reflect the DOAS slant column result. GDP 4.0 has improved wavelength calibration and reference spectra and includes a new molecular Ring correction to deal with distortion of ozone absorption features due to inelastic rotational Raman scattering effects. Preprocessing for cloud parameter estimation in GDP 4.0 is done using two new cloud correction algorithms: OCRA and ROCINN. For clear and cloudy scenes the precision of the ozone column product is better than 2.4 and 3.3%, respectively, for solar zenith angles up to 80°. Comparisons with ground-based Data are generally at the 1-1.5% level or better for all regions outside the poles.
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gome level 1 to 2 Data Processor version 3 0 a major upgrade of the gome ers 2 total ozone retrieval algorithm
Applied Optics, 2005Co-Authors: R. Spurr, Diego Loyola, M. Van Roozendael, Werner Thomas, Wolfgang Balzer, Eberhard Mikusch, Bernd Aberle, Sander Slijkhuis, Thomas Ruppert, Jean-christopher LambertAbstract:The global ozone monitoring experiment (GOME) was launched in April 1995, and the GOME Data Processor (GDP) retrieval algorithm has processed operational total ozone amounts since July 1995. GDP level 1-to-2 is based on the two-step differential optical absorption spectroscopy (DOAS) approach, involving slant column fitting followed by air mass factor (AMF) conversions to vertical column amounts. We present a major upgrade of this algorithm to version 3.0. GDP 3.0 was implemented in July 2002, and the 9-year GOME Data record from July 1995 to December 2004 has been processed using this algorithm. The key component in GDP 3.0 is an iterative approach to AMF calculation, in which AMFs and corresponding vertical column densities are adjusted to reflect the true ozone distribution as represented by the fitted DOAS effective slant column. A neural network ensemble is used to optimize the fast and accurate parametrization of AMFs. We describe results of a recent validation exercise for the operational version of the total ozone algorithm; in particular, seasonal and meridian errors are reduced by a factor of 2. On a global basis, GDP 3.0 ozone total column results lie between −2% and +4% of ground-based values for moderate solar zenith angles lower than 70°. A larger variability of about +5% and −8% is observed for higher solar zenith angles up to 90°.
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gome level 1 to 2 Data Processor version 3 0 a major upgrade of the gome ers 2 total ozone retrieval algorithm
Applied Optics, 2005Co-Authors: R. Spurr, Diego Loyola, M. Van Roozendael, Werner Thomas, Wolfgang Balzer, Eberhard Mikusch, Bernd Aberle, Sander Slijkhuis, Thomas Ruppert, Jean-christopher LambertAbstract:The global ozone monitoring experiment (GOME) was launched in April 1995, and the GOME Data Processor (GDP) retrieval algorithm has processed operational total ozone amounts since July 1995. GDP level 1-to-2 is based on the two-step differential optical absorption spectroscopy (DOAS) approach, involving slant column fitting followed by air mass factor (AMF) conversions to vertical column amounts. We present a major upgrade of this algorithm to version 3.0. GDP 3.0 was implemented in July 2002, and the 9-year GOME Data record from July 1995 to December 2004 has been processed using this algorithm. The key component in GDP 3.0 is an iterative approach to AMF calculation, in which AMFs and corresponding vertical column densities are adjusted to reflect the true ozone distribution as represented by the fitted DOAS effective slant column. A neural network ensemble is used to optimize the fast and accurate parametrization of AMFs. We describe results of a recent validation exercise for the operational version of the total ozone algorithm; in particular, seasonal and meridian errors are reduced by a factor of 2. On a global basis, GDP 3.0 ozone total column results lie between -2% and +4% of ground-based values for moderate solar zenith angles lower than 70 degrees. A larger variability of about +5% and -8% is observed for higher solar zenith angles up to 90 degrees.
Dimitris Balis - One of the best experts on this subject based on the ideXlab platform.
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sixteen years of gome ers 2 total ozone Data the new direct fitting gome Data Processor gdp version 5 algorithm description
Journal of Geophysical Research, 2012Co-Authors: M. Van Roozendael, Dimitris Balis, Christophe Lerot, Walter Zimmer, Diego Loyola, R. Spurr, Jean-christopher Lambert, J. Van Gent, J. Van Geffen, M E KoukouliAbstract:[1] The Global Ozone Monitoring Instrument (GOME) was launched in April 1995 on ESA's ERS-2 platform, and the GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. We report on the new GDP5 spectral fitting algorithm used to reprocess the 16-year GOME Data record. Previous GDP total ozone algorithms were based on the DOAS method. In contrast, GDP5 uses a direct-fitting algorithm without high-pass filtering of radiances; there is no air mass factor conversion to vertical column amount. GDP5 includes direct radiative transfer simulation of earthshine radiances and Jacobians with respect to total ozone, albedo closure and other ancillary fitting parameters - a temperature profile shift, and amplitudes for undersampling and Ring-effect interference signals. Simulations are based on climatological ozone profiles extracted from the TOMS Version 8 Database, classified by total column. GDP5 uses the high-resolution Brion-Daumont-Malicet ozone absorption cross-sections, replacing older GOME-measured flight model Data. The semi-empirical molecular Ring correction developed for GDP4 has been adapted for direct fitting. Cloud preprocessing for GDP5 is done using updated versions of cloud-correction algorithms OCRA and ROCINN. The reprocessed GOME GDP5 record maintains the remarkable long-term stability of time series already achieved with GDP4. Furthermore, validation results show a clear improvement in the accuracy of the ozone product with reduced solar zenith angle and seasonal dependences, particularly in comparison with correlative observations from the ground-based network of Brewer spectrophotometers.
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ten years of gome ers2 total ozone Data the new gome Data Processor gdp version 4 2 ground based validation and comparisons with toms v7 v8
Journal of Geophysical Research, 2007Co-Authors: Dimitris Balis, Pieter Valks, Diego Loyola, R. Spurr, M. Van Roozendael, Jean-christopher Lambert, Y Livschitz, V Amiridis, P Gerard, J GranvilleAbstract:[1] The atmospheric chemistry instrument Global Ozone Monitoring Experiment (GOME) was launched in April 1995 on the ERS-2 platform. The GOME Data Processor (GDP) operational retrieval algorithm has produced total ozone columns since July 1995. With a Data record of over ten years, GOME has become important for ozone trend analysis. In 2004, GDP was upgraded to version 4.0, a new validation was performed, and the entire GOME Data record was reprocessed. In the preceding paper (Van Roozendael et al., 2006), the GDP 4.0 algorithm was described. In this paper, we deal with geophysical validation of the GDP 4.0 algorithm and the retrieved ozone products. We present results of a validation exercise involving comparisons of GDP 4.0 total ozone with the Network for Detection of Stratospheric Change (NDSC) and the World Meteorological Organization (WMO)/Global Atmospheric Watch (GAW) ground-based networks. We compare these results with similar validations of earlier GDP ozone products. We also present ground-based validation of TOMS versions 7 and 8 total ozone products, and we contrast these with GDP 4.0 values. On a global basis, GDP 4.0 total ozone results lie between −1% and +1.5% of ground-based values for solar zenith angles less than 70°; accuracy is now comparable to that obtainable from ground-based stations. At higher solar zenith angles in polar regions, larger discrepancies of up to +5% are found; in these regimes, errors on both satellite and ground-based measurements are higher. The validation also showed marked improvement in TOMS total ozone performance for the version 8 algorithm.
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ten years of gome ers 2 total ozone Data the new gome Data Processor gdp version 4 1 algorithm description
Journal of Geophysical Research, 2006Co-Authors: M. Van Roozendael, Pieter Valks, Dimitris Balis, Diego Loyola, R. Spurr, Jean-christopher Lambert, Thomas Ruppert, Y Livschitz, P Kenter, C FaytAbstract:The Global Ozone Monitoring Instrument (GOME) was launched on European Space Agency's ERS-2 platform in April 1995. The GOME Data Processor (GDP) operational retrieval algorithm has generated total ozone columns since July 1995. In 2004 the GDP system was given a major upgrade to version 4.0, a new validation was performed, and the 10-year GOME level 1 Data record was reprocessed. In two papers, we describe the GDP 4.0 retrieval algorithm and present an error budget and sensitivity analysis (paper 1) and validation of the GDP total ozone product and the overall accuracy of the entire GOME ozone record (paper 2). GDP 4.0 uses an optimized differential optical absorption spectroscopy (DOAS) algorithm, with air mass factor (AMF) conversions calculated using the radiative transfer code linearized discrete ordinate radiative transfer (LIDORT). AMF computation is based on the TOMS version 8 ozone profile climatology, classified by total column, and AMFs are adjusted iteratively to reflect the DOAS slant column result. GDP 4.0 has improved wavelength calibration and reference spectra and includes a new molecular Ring correction to deal with distortion of ozone absorption features due to inelastic rotational Raman scattering effects. Preprocessing for cloud parameter estimation in GDP 4.0 is done using two new cloud correction algorithms: OCRA and ROCINN. For clear and cloudy scenes the precision of the ozone column product is better than 2.4 and 3.3%, respectively, for solar zenith angles up to 80°. Comparisons with ground-based Data are generally at the 1-1.5% level or better for all regions outside the poles.
