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Diego Loyola - One of the best experts on this subject based on the ideXlab platform.

  • the use of qbo enso and nao perturbations in the evaluation of gome 2 metop a Total Ozone measurements
    Atmospheric Measurement Techniques, 2019
    Co-Authors: K Eleftheratos, M E Koukouli, Pieter Valks, Dimitris Balis, Christophe Lerot, Diego Loyola, C S Zerefos, Melanie Coldeweyegbers, J Kapsomenakis, S M Frith
    Abstract:

    In this work we present evidence that quasi-cyclical perturbations in Total Ozone (quasi-biennial oscillation – QBO, El Nino–Southern Oscillation – ENSO, and North Atlantic Oscillation – NAO) can be used as independent proxies in evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A (GOME-2A) satellite Total Ozone data, using ground-based (GB) measurements, other satellite data, and chemical transport model calculations. The analysis is performed in the frame of the validation strategy on longer time scales within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF) project, covering the period 2007–2016. Comparison of GOME-2A Total Ozone with ground observations shows mean differences of about −0.7±1.4 % in the tropics (0–30∘), about +0.1±2.1 % in the mid-latitudes (30–60∘), and about +2.5±3.2 % and 0.0±4.3 % over the northern and southern high latitudes (60–80∘), respectively. In general, we find that GOME-2A Total Ozone data depict the QBO–ENSO–NAO natural fluctuations in concurrence with the co-located solar backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential Climate Variable (GTO-ECV; composed of Total Ozone observations from GOME, SCIAMACHY – SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI – Ozone monitoring instrument, combined into one homogeneous time series), and ground-based observations. Total Ozone from GOME-2A is well correlated with the QBO (highest correlation in the tropics of +0.8) in agreement with SBUV, GTO-ECV, and GB data which also give the highest correlation in the tropics. The differences between deseazonalized GOME-2A and GB Total Ozone in the tropics are within ±1 %. These differences were tested further as to their correlations with the QBO. The differences had practically no QBO signal, providing an independent test of the stability of the long-term variability of the satellite data. Correlations between GOME-2A Total Ozone and the Southern Oscillation Index (SOI) were studied over the tropical Pacific Ocean after removing seasonal, QBO, and solar-cycle-related variability. Correlations between Ozone and the SOI are on the order of +0.5, consistent with SBUV and GB observations. Differences between GOME-2A and GB measurements at the station of Samoa (American Samoa; 14.25∘ S, 170.6∘ W) are within ±1.9 %. We also studied the impact of the NAO on Total Ozone in the northern mid-latitudes in winter. We find very good agreement between GOME-2A and GB observations over Canada and Europe as to their NAO-related variability, with mean differences reaching the ±1 % levels. The agreement and small differences which were found between the independently produced Total Ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as additional tool for monitoring the long-term stability of satellite–ground-truth biases.

  • the gome type Total Ozone essential climate variable gto ecv data record from the esa climate change initiative
    Atmospheric Measurement Techniques, 2015
    Co-Authors: Melanie Coldeweyegbers, M E Koukouli, Diego Loyola, M. Van Roozendael, J Granville, Dimitris Alis, Jeanchristophe Lambe, T Verhoels, Christophe Lero, R Spu
    Abstract:

    Abstract. We present the new GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record which has been created within the framework of the European Space Agency's Climate Change Initiative (ESA-CCI). Total Ozone column observations – based on the GOME-type Direct Fitting version 3 algorithm – from GOME (Global Ozone Monitoring Experiment), SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY), and GOME-2 have been combined into one homogeneous time series, thereby taking advantage of the high inter-sensor consistency. The data record spans the 15-year period from March 1996 to June 2011 and it contains global monthly mean Total Ozone columns on a 1°× 1° grid. Geophysical ground-based validation using Brewer, Dobson, and UV–visible instruments has shown that the GTO-ECV level 3 data record is of the same high quality as the equivalent individual level 2 data products that constitute it. Both absolute agreement and long-term stability are excellent with respect to the ground-based data, for almost all latitudes apart from a few outliers which are mostly due to sampling differences between the level 2 and level 3 data. We conclude that the GTO-ECV data record is valuable for a variety of climate applications such as the long-term monitoring of the past evolution of the Ozone layer, trend analysis and the evaluation of chemistry–climate model simulations.

  • gome 2 Total Ozone columns from metop a metop b and assimilation in the macc system
    Atmospheric Measurement Techniques, 2014
    Co-Authors: M E Koukouli, Antje Inness, Pieter Valks, Dimitris Balis, I Zyrichidou, Michel Van Roozendael, Christophe Lerot, Walter Zimmer, Diego Loyola, Ray Spurr
    Abstract:

    Abstract. The two Global Ozone Monitoring Instrument (GOME-2) sensors operated in tandem are flying onboard EUMETSAT's (European Organisation for the Exploitation of Meteorological Satellites) MetOp-A and MetOp-B satellites, launched in October 2006 and September 2012 respectively. This paper presents the operational GOME-2/MetOp-A (GOME-2A) and GOME-2/MetOp-B (GOME-2B) Total Ozone products provided by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). These products are generated using the latest version of the GOME Data Processor (GDP version 4.7). The enhancements in GDP 4.7, including the application of Brion–Daumont–Malicet Ozone absorption cross sections, are presented here. On a global scale, GOME-2B has the same high accuracy as the corresponding GOME-2A products. There is an excellent agreement between the Ozone Total columns from the two sensors, with GOME-2B values slightly lower with a mean difference of only 0.55±0.29%. First global validation results for 6 months of GOME-2B Total Ozone using ground-based measurements show that on average the GOME-2B Total Ozone data obtained with GDP 4.7 are slightly higher than, both, Dobson observations by about 2.0±1.0% and Brewer observations by about 1.0±0.8%. It is concluded that the Total Ozone columns (TOCs) provided by GOME-2A and GOME-2B are consistent and may be used simultaneously without introducing systematic effects, which has been illustrated for the Antarctic Ozone hole on 18 October 2013. GOME-2A Total Ozone data have been used operationally in the Copernicus atmospheric service project MACC-II (Monitoring Atmospheric Composition and Climate – Interim Implementation) near-real-time (NRT) system since October 2013. The magnitude of the bias correction needed for assimilating GOME-2A Ozone is reduced (to about −6 DU in the global mean) when the GOME-2 Ozone retrieval algorithm changed to GDP 4.7.

  • optical property dimensionality reduction techniques for accelerated radiative transfer performance application to remote sensing Total Ozone retrievals
    Journal of Quantitative Spectroscopy & Radiative Transfer, 2014
    Co-Authors: Dmitry S Efremenko, Diego Loyola, Adrian Doicu, Thomas Trautmann
    Abstract:

    In this paper, we introduce several dimensionality reduction techniques for optical parameters. We consider the principal component analysis, the local linear embedding methods (locality pursuit embedding, locality preserving projection, locally embedded analysis), and discrete orthogonal transforms (cosine, Legendre, wavelet). The principle component analysis has already been shown to be an effective and accurate method of enhancing radiative transfer performance for simulations in an absorbing and a scattering atmosphere. By linearizing the corresponding radiative transfer model, we analyze the applicability of the proposed methods to a practical problem of Total Ozone column retrieval from UV-backscatter measurements.

  • comparison of profile Total Ozone from sbuv v8 6 with gome type and ground based Total Ozone for a 16 year period 1996 to 2011
    Atmospheric Measurement Techniques, 2013
    Co-Authors: E W Chiou, Christophe Lerot, Pawan K. Bhartia, Diego Loyola, M. Van Roozendael, R Spurr, R D Mcpeters, Melanie Coldeweyegbers, Vitali Fioletov, S M Frith
    Abstract:

    Abstract. This paper describes the comparison of the variability of Total column Ozone inferred from the three independent multi-year data records, namely, (i) Solar Backscatter Ultraviolet Instrument (SBUV) v8.6 profile Total Ozone, (ii) GTO (GOME-type Total Ozone), and (iii) ground-based Total Ozone data records covering the 16-year overlap period (March 1996 through June 2011). Analyses are conducted based on area-weighted zonal means for 0–30° S, 0–30° N, 50–30° S, and 30–60° N. It has been found that, on average, the differences in monthly zonal mean Total Ozone vary between −0.3 and 0.8 % and are well within 1%. For GTO minus SBUV, the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean Total Ozone vary between 0.6–0.7% and 2.8–3.8% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.4–0.6% and 2.2–3.5%. The standard deviations and ranges of the differences ground-based minus SBUV regarding both monthly zonal means and anomalies are larger by a factor of 1.4–2.9 in comparison to GTO minus SBUV. The ground-based zonal means demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences GTO minus SBUV and ground-based minus SBUV are found to vary between −0.04 and 0.1% yr−1 (−0.1 and 0.3 DU yr−1). These negligibly small trends have provided strong evidence that there are no significant time-dependent differences among these multi-year Total Ozone data records. Analyses of the annual deviations from pre-1980 level indicate that, for the 15-year period of 1996 to 2010, all three data records show a gradual increase at 30–60° N from −5% in 1996 to −2% in 2010. In contrast, at 50–30° S and 30° S–30° N there has been a levelling off in the 15 years after 1996. The deviations inferred from GTO and SBUV show agreement within 1%, but a slight increase has been found in the differences during the period 1996–2010.

Dimitris Balis - One of the best experts on this subject based on the ideXlab platform.

  • the use of qbo enso and nao perturbations in the evaluation of gome 2 metop a Total Ozone measurements
    Atmospheric Measurement Techniques, 2019
    Co-Authors: K Eleftheratos, M E Koukouli, Pieter Valks, Dimitris Balis, Christophe Lerot, Diego Loyola, C S Zerefos, Melanie Coldeweyegbers, J Kapsomenakis, S M Frith
    Abstract:

    In this work we present evidence that quasi-cyclical perturbations in Total Ozone (quasi-biennial oscillation – QBO, El Nino–Southern Oscillation – ENSO, and North Atlantic Oscillation – NAO) can be used as independent proxies in evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A (GOME-2A) satellite Total Ozone data, using ground-based (GB) measurements, other satellite data, and chemical transport model calculations. The analysis is performed in the frame of the validation strategy on longer time scales within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF) project, covering the period 2007–2016. Comparison of GOME-2A Total Ozone with ground observations shows mean differences of about −0.7±1.4 % in the tropics (0–30∘), about +0.1±2.1 % in the mid-latitudes (30–60∘), and about +2.5±3.2 % and 0.0±4.3 % over the northern and southern high latitudes (60–80∘), respectively. In general, we find that GOME-2A Total Ozone data depict the QBO–ENSO–NAO natural fluctuations in concurrence with the co-located solar backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential Climate Variable (GTO-ECV; composed of Total Ozone observations from GOME, SCIAMACHY – SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI – Ozone monitoring instrument, combined into one homogeneous time series), and ground-based observations. Total Ozone from GOME-2A is well correlated with the QBO (highest correlation in the tropics of +0.8) in agreement with SBUV, GTO-ECV, and GB data which also give the highest correlation in the tropics. The differences between deseazonalized GOME-2A and GB Total Ozone in the tropics are within ±1 %. These differences were tested further as to their correlations with the QBO. The differences had practically no QBO signal, providing an independent test of the stability of the long-term variability of the satellite data. Correlations between GOME-2A Total Ozone and the Southern Oscillation Index (SOI) were studied over the tropical Pacific Ocean after removing seasonal, QBO, and solar-cycle-related variability. Correlations between Ozone and the SOI are on the order of +0.5, consistent with SBUV and GB observations. Differences between GOME-2A and GB measurements at the station of Samoa (American Samoa; 14.25∘ S, 170.6∘ W) are within ±1.9 %. We also studied the impact of the NAO on Total Ozone in the northern mid-latitudes in winter. We find very good agreement between GOME-2A and GB observations over Canada and Europe as to their NAO-related variability, with mean differences reaching the ±1 % levels. The agreement and small differences which were found between the independently produced Total Ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as additional tool for monitoring the long-term stability of satellite–ground-truth biases.

  • evaluating a new homogeneous Total Ozone climate data record from gome ers 2 sciamachy envisat and gome 2 metop a
    Journal of Geophysical Research, 2015
    Co-Authors: M E Koukouli, Dimitris Balis, I Zyrichidou, Michel Van Roozendael, Christophe Lerot, Florence Goutail, Jean Pierre Pommereau, J C Lambert, J Granville, Melanie Coldeweyegbers
    Abstract:

    The European Space Agency's Ozone Climate Change Initiative (O3-CCI) project aims at producing and validating a number of high-quality Ozone data products generated from different satellite sensors. For Total Ozone, the O3-CCI approach consists of minimizing sources of bias and systematic uncertainties by applying a common retrieval algorithm to all level 1 data sets, in order to enhance the consistency between the level 2 data sets from individual sensors. Here we present the evaluation of the Total Ozone products from the European sensors Global Ozone Monitoring Experiment (GOME)/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A produced with the GOME-type Direct FITting (GODFIT) algorithm v3. Measurements from the three sensors span more than 16 years, from 1996 to 2012. In this work, we present the latest O3-CCI Total Ozone validation results using as reference ground-based measurements from Brewer and Dobson spectrophotometers archived at the World Ozone and UV Data Centre of the World Meteorological Organization as well as from UV-visible differential optical absorption spectroscopy (DOAS)/Systeme D′Analyse par Observations Zenithales (SAOZ) instruments from the Network for the Detection of Atmospheric Composition Change. In particular, we investigate possible dependencies in these new GODFIT v3 Total Ozone data sets with respect to latitude, season, solar zenith angle, and different cloud parameters, using the most adequate type of ground-based instrument. We show that these three O3-CCI Total Ozone data products behave very similarly and are less sensitive to instrumental degradation, mainly as a result of the new reflectance soft-calibration scheme. The mean bias to the ground-based observations is found to be within the 1 ± 1% level for all three sensors while the near-zero decadal stability of the Total Ozone columns (TOCs) provided by the three European instruments falls well within the 1–3% requirement of the European Space Agency's Ozone Climate Change Initiative project.

  • gome 2 Total Ozone columns from metop a metop b and assimilation in the macc system
    Atmospheric Measurement Techniques, 2014
    Co-Authors: M E Koukouli, Antje Inness, Pieter Valks, Dimitris Balis, I Zyrichidou, Michel Van Roozendael, Christophe Lerot, Walter Zimmer, Diego Loyola, Ray Spurr
    Abstract:

    Abstract. The two Global Ozone Monitoring Instrument (GOME-2) sensors operated in tandem are flying onboard EUMETSAT's (European Organisation for the Exploitation of Meteorological Satellites) MetOp-A and MetOp-B satellites, launched in October 2006 and September 2012 respectively. This paper presents the operational GOME-2/MetOp-A (GOME-2A) and GOME-2/MetOp-B (GOME-2B) Total Ozone products provided by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). These products are generated using the latest version of the GOME Data Processor (GDP version 4.7). The enhancements in GDP 4.7, including the application of Brion–Daumont–Malicet Ozone absorption cross sections, are presented here. On a global scale, GOME-2B has the same high accuracy as the corresponding GOME-2A products. There is an excellent agreement between the Ozone Total columns from the two sensors, with GOME-2B values slightly lower with a mean difference of only 0.55±0.29%. First global validation results for 6 months of GOME-2B Total Ozone using ground-based measurements show that on average the GOME-2B Total Ozone data obtained with GDP 4.7 are slightly higher than, both, Dobson observations by about 2.0±1.0% and Brewer observations by about 1.0±0.8%. It is concluded that the Total Ozone columns (TOCs) provided by GOME-2A and GOME-2B are consistent and may be used simultaneously without introducing systematic effects, which has been illustrated for the Antarctic Ozone hole on 18 October 2013. GOME-2A Total Ozone data have been used operationally in the Copernicus atmospheric service project MACC-II (Monitoring Atmospheric Composition and Climate – Interim Implementation) near-real-time (NRT) system since October 2013. The magnitude of the bias correction needed for assimilating GOME-2A Ozone is reduced (to about −6 DU in the global mean) when the GOME-2 Ozone retrieval algorithm changed to GDP 4.7.

  • geophysical validation and long term consistency between gome 2 metop a Total Ozone column and measurements from the sensors gome ers 2 sciamachy envisat and omi aura
    Atmospheric Measurement Techniques, 2012
    Co-Authors: M E Koukouli, Pieter Valks, Dimitris Balis, Michel Van Roozendael, Christophe Lerot, Walter Zimmer, Diego Loyola, J C Lambert, Ray Spurr
    Abstract:

    The main aim of the paper is to assess the consistency of five years of Global Ozone Monitoring Experiment-2/Metop-A [GOME-2] Total Ozone columns and the long-term Total Ozone satellite monitoring database already in existence through an extensive inter-comparison and validation exercise using as reference Brewer and Dobson ground-based measurements. The behaviour of the GOME-2 measurements is being weighed against that of GOME (1995–2011), Ozone Monitoring Experiment [OMI] (since 2004) and the Scanning Imaging Absorption spectroMeter for Atmospheric CartograpHY [SCIAMACHY] (since 2002) Total Ozone column products. Over the background truth of the ground-based measurements, the Total Ozone columns are inter-evaluated using a suite of established validation techniques; the GOME-2 time series follow the same patterns as those observed by the other satellite sensors. In particular, on average, GOME-2 data underestimate GOME data by about 0.80%, and underestimate SCIAMACHY data by 0.37% with no seasonal dependence of the differences between GOME-2, GOME and SCIAMACHY. The latter is expected since the three datasets are based on similar DOAS algorithms. This underestimation of GOME-2 is within the uncertainty of the reference data used in the comparisons. Compared to the OMI sensor, on average GOME-2 data underestimate OMI_DOAS (collection 3) data by 1.28%, without any significant seasonal dependence of the differences between them. The lack of seasonality might be expected since both the GOME data processor [GDP] 4.4 and OMI_DOAS are DOAS-type algorithms and both consider the variability of the stratospheric temperatures in their retrievals. Compared to the OMI_TOMS (collection 3) data, no bias was found. We hence conclude that the GOME-2 Total Ozone columns are well suitable to continue the long-term global Total Ozone record with the accuracy needed for climate monitoring studies.

  • 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, 2012
    Co-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 Koukouli
    Abstract:

    [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.

R D Mcpeters - One of the best experts on this subject based on the ideXlab platform.

  • comparison of profile Total Ozone from sbuv v8 6 with gome type and ground based Total Ozone for a 16 year period 1996 to 2011
    Atmospheric Measurement Techniques, 2013
    Co-Authors: E W Chiou, Christophe Lerot, Pawan K. Bhartia, Diego Loyola, M. Van Roozendael, R Spurr, R D Mcpeters, Melanie Coldeweyegbers, Vitali Fioletov, S M Frith
    Abstract:

    Abstract. This paper describes the comparison of the variability of Total column Ozone inferred from the three independent multi-year data records, namely, (i) Solar Backscatter Ultraviolet Instrument (SBUV) v8.6 profile Total Ozone, (ii) GTO (GOME-type Total Ozone), and (iii) ground-based Total Ozone data records covering the 16-year overlap period (March 1996 through June 2011). Analyses are conducted based on area-weighted zonal means for 0–30° S, 0–30° N, 50–30° S, and 30–60° N. It has been found that, on average, the differences in monthly zonal mean Total Ozone vary between −0.3 and 0.8 % and are well within 1%. For GTO minus SBUV, the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean Total Ozone vary between 0.6–0.7% and 2.8–3.8% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.4–0.6% and 2.2–3.5%. The standard deviations and ranges of the differences ground-based minus SBUV regarding both monthly zonal means and anomalies are larger by a factor of 1.4–2.9 in comparison to GTO minus SBUV. The ground-based zonal means demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences GTO minus SBUV and ground-based minus SBUV are found to vary between −0.04 and 0.1% yr−1 (−0.1 and 0.3 DU yr−1). These negligibly small trends have provided strong evidence that there are no significant time-dependent differences among these multi-year Total Ozone data records. Analyses of the annual deviations from pre-1980 level indicate that, for the 15-year period of 1996 to 2010, all three data records show a gradual increase at 30–60° N from −5% in 1996 to −2% in 2010. In contrast, at 50–30° S and 30° S–30° N there has been a levelling off in the 15 years after 1996. The deviations inferred from GTO and SBUV show agreement within 1%, but a slight increase has been found in the differences during the period 1996–2010.

  • solar backscatter uv sbuv Total Ozone and profile algorithm
    Atmospheric Measurement Techniques, 2013
    Co-Authors: P K Bhartia, R D Mcpeters, S L Taylor, L E Flynn, N A Kramarova, S Frith, Bradford Fisher, Matthew T Deland
    Abstract:

    Abstract. We describe the algorithm that has been applied to develop a 42 yr record of Total Ozone and Ozone profiles from eight Solar Backscatter UV (SBUV) instruments launched on NASA and NOAA satellites since April 1970. The Version 8 (V8) algorithm was released more than a decade ago and has been in use since then at NOAA to produce their operational Ozone products. The current algorithm (V8.6) is basically the same as V8, except for updates to instrument calibration, incorporation of new Ozone absorption cross-sections, and new Ozone and cloud height climatologies. Since the V8 algorithm has been optimized for deriving monthly zonal mean (MZM) anomalies for Ozone assessment and model comparisons, our emphasis in this paper is primarily on characterizing the sources of errors that are relevant for such studies. When data are analyzed this way the effect of some errors, such as vertical smoothing of short-term variability, and noise due to clouds and aerosols diminish in importance, while the importance of others, such as errors due to vertical smoothing of the quasi-biennial oscillation (QBO) and other periodic and aperiodic variations, become more important. With V8.6 zonal mean data we now provide smoothing kernels that can be used to compare anomalies in SBUV profile and partial Ozone columns with models. In this paper we show how to use these kernels to compare SBUV data with Microwave Limb Sounder (MLS) Ozone profiles. These kernels are particularly useful for comparisons in the lower stratosphere where SBUV profiles have poor vertical resolution but partial column Ozone values have high accuracy. We also provide our best estimate of the smoothing errors associated with SBUV MZM profiles. Since smoothing errors are the largest source of uncertainty in these profiles, they can be treated as error bars in deriving interannual variability and trends using SBUV data and for comparing with other measurements. In the V8 and V8.6 algorithms we derive Total column Ozone by integrating the SBUV profiles, rather than from a separate set of wavelengths, as was done in previous algorithm versions. This allows us to extend the Total Ozone retrieval to 88° solar zenith angle (SZA). Since the quality of Total column data is affected by reduced sensitivity to Ozone in the lower atmosphere by cloud and Rayleigh attenuation, which gets worse with increasing SZA, we provide our best estimate of these errors, as well as the kernels that can be used to test the sensitivity of the derived columns to long-term changes in Ozone in the lower atmosphere.

  • validation of omi toms and omi doas Total Ozone column using five brewer spectroradiometers at the iberian peninsula
    Journal of Geophysical Research, 2009
    Co-Authors: M Anto, J. Molina Vilaplana, M. López, R D Mcpeters, M Kroo, M Ano, A Serrano
    Abstract:

    [1] This article focuses on the comparison of the Total Ozone column data from the Ozone Monitoring Instrument (OMI) flying aboard the NASA EOS-Aura satellite platform with ground-based measurement recorded by Brewer spectroradiometers located at five Spanish remote sensing ground stations between January 2005 and December 2007. The satellite data are derived from two algorithms: OMI Total Ozone Mapping Spectrometer (OMI-TOMS) and OMI Differential Optical Absorption Spectroscopy (OMI-DOAS). The largest relative differences between these OMI Total Ozone column estimates reach 5% with a significant seasonal dependence. The agreement between OMI Ozone data and Brewer measurements is excellent. Total Ozone columns from OMI-TOMS are on average a mere 2.0% lower than Brewer data. For OMI-DOAS data the bias is a mere 1.4%. However, the relative difference between OMI-TOMS and Brewer measurements shows a notably lower seasonal dependence and variability than the differences between OMI-DOAS and ground-based data. For both OMI Ozone data products these relative differences show significant dependence on the satellite ground pixel solar zenith angle for cloud-free cases as well as for cloudy conditions. However, the OMI Ozone data products are shown to reveal opposite behavior with respect to the two antagonistic sky conditions. No significant dependency of the ground-based to satellite-based differences with respect to the satellite cross-track position is seen for either OMI retrieval algorithm.

  • comparing omi toms and omi doas Total Ozone column data
    Journal of Geophysical Research, 2008
    Co-Authors: M Kroon, J. Pepijn Veefkind, Pawan K. Bhartia, R D Mcpeters, Maarten Sneep, P F Levelt
    Abstract:

    [1] The Ozone Monitoring Instrument (OMI) project team uses two Total Ozone retrieval algorithms in order to maintain the long-term record established with Total Ozone Mapping Spectrometer (TOMS) data as well as to improve the Ozone column estimate using the hyperspectral capability of OMI. The purpose of this study is to assess where the algorithms produce comparable results and where the differences are significant. Starting with the same set of Earth reflectance data, the Total Ozone data used in this study have been derived using OMI-TOMS and OMI–Differential Optical Absorption Spectroscopy (DOAS) algorithms. OMI-TOMS is based on the TOMS version 8 algorithm that has been used to process TOMS data taken since November 1978. The OMI-DOAS retrieval algorithm was developed specifically for OMI. It takes advantage of the hyperspectral feature of the OMI instrument to reduce errors due to aerosols, clouds, surface, and sulfur dioxide from volcanic eruptions. The OMI-DOAS algorithm also has improved correction for cloud height. The mean differences in the Ozone column derived from the two algorithms vary from 0 to 9 DU (0–3%), and their correlation coefficients vary between 0.89 and 0.99 with latitude and season. The largest differences occur in the polar regions and over clouds. Some of the differences are due to stray light, dark current, and other instrumental errors that have been corrected in the new version of the OMI radiance/irradiance data set (collection 3). Other differences are algorithmic. OMI-DOAS algorithmic errors identified through this analysis are also being corrected in collection 3 reprocessing. However, for consistency with the long-term TOMS record, OMI-TOMS collection 3 data will still be based on the TOMS V8 algorithm. Preliminary analysis shows much better agreement in the two Total Ozone data sets after reprocessing. Reprocessed collection 3 data from both algorithms will be available before the end of 2007. Continuing the TOMS Total Ozone column data record that dates back to November 1978 is the primary OMI mission goal that is achievable with either OMI Total Ozone column data product.

  • global and zonal Total Ozone variations estimated from ground based and satellite measurements 1964 2000
    Journal of Geophysical Research, 2002
    Co-Authors: Vitali Fioletov, R D Mcpeters, Alvin J Miller, G E Bodeker, R. S. Stolarski
    Abstract:

    [1] Six data sets of monthly average zonal Total Ozone were intercompared and then used to estimate latitudinal and global Total Ozone temporal variations and trends. The data sets were prepared by different groups and are based on TOMS, SBUV-SBUV/2, GOME, and ground-based measurements. Different approaches have been used to homogenize the records over the period 1979–2000. Systematic differences of up to 3% were found between different data sets for zonal and global Total Ozone area weighted average values. However, when these systematic differences were removed by deseasonalizing the data, the residuals agreed to within ±0.5% of the long-term mean Ozone values. All data sets show changes in the rate of the Total Ozone decline in recent years. While global Ozone was fairly constant during the 1990s, the average values of the 1990s are about 2–3% lower than those of the late 1970s. About 38% of the global Ozone is located between 25°S and 25°N where the data show no decline. The strongest decline and the largest variability occur over the 35°N–60°N zone during the winter-spring season with the largest negative deviations occurring in 1993 and 1995. The decline in autumn is much smaller at these latitudes. Over the 35°S–60°S zone the Ozone decline shows less seasonal dependence, and the largest deviations there were observed in 1985 and 1997. Sliding 11-year trends were calculated to estimate Ozone changes over different time intervals. The first interval was from 1964 to 1974, and the last interval was from 1990 to 2000. The steepest year-round trends, of up to −5% per decade, occurred in the 11-year periods ending between 1992 and 1997 over the 35°–60°N zone and between 1985 and 1993 over the 35°–55°S zone. More recent 11-year trends have smaller declines.

M E Koukouli - One of the best experts on this subject based on the ideXlab platform.

  • the use of qbo enso and nao perturbations in the evaluation of gome 2 metop a Total Ozone measurements
    Atmospheric Measurement Techniques, 2019
    Co-Authors: K Eleftheratos, M E Koukouli, Pieter Valks, Dimitris Balis, Christophe Lerot, Diego Loyola, C S Zerefos, Melanie Coldeweyegbers, J Kapsomenakis, S M Frith
    Abstract:

    In this work we present evidence that quasi-cyclical perturbations in Total Ozone (quasi-biennial oscillation – QBO, El Nino–Southern Oscillation – ENSO, and North Atlantic Oscillation – NAO) can be used as independent proxies in evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A (GOME-2A) satellite Total Ozone data, using ground-based (GB) measurements, other satellite data, and chemical transport model calculations. The analysis is performed in the frame of the validation strategy on longer time scales within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF) project, covering the period 2007–2016. Comparison of GOME-2A Total Ozone with ground observations shows mean differences of about −0.7±1.4 % in the tropics (0–30∘), about +0.1±2.1 % in the mid-latitudes (30–60∘), and about +2.5±3.2 % and 0.0±4.3 % over the northern and southern high latitudes (60–80∘), respectively. In general, we find that GOME-2A Total Ozone data depict the QBO–ENSO–NAO natural fluctuations in concurrence with the co-located solar backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential Climate Variable (GTO-ECV; composed of Total Ozone observations from GOME, SCIAMACHY – SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI – Ozone monitoring instrument, combined into one homogeneous time series), and ground-based observations. Total Ozone from GOME-2A is well correlated with the QBO (highest correlation in the tropics of +0.8) in agreement with SBUV, GTO-ECV, and GB data which also give the highest correlation in the tropics. The differences between deseazonalized GOME-2A and GB Total Ozone in the tropics are within ±1 %. These differences were tested further as to their correlations with the QBO. The differences had practically no QBO signal, providing an independent test of the stability of the long-term variability of the satellite data. Correlations between GOME-2A Total Ozone and the Southern Oscillation Index (SOI) were studied over the tropical Pacific Ocean after removing seasonal, QBO, and solar-cycle-related variability. Correlations between Ozone and the SOI are on the order of +0.5, consistent with SBUV and GB observations. Differences between GOME-2A and GB measurements at the station of Samoa (American Samoa; 14.25∘ S, 170.6∘ W) are within ±1.9 %. We also studied the impact of the NAO on Total Ozone in the northern mid-latitudes in winter. We find very good agreement between GOME-2A and GB observations over Canada and Europe as to their NAO-related variability, with mean differences reaching the ±1 % levels. The agreement and small differences which were found between the independently produced Total Ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as additional tool for monitoring the long-term stability of satellite–ground-truth biases.

  • evaluating a new homogeneous Total Ozone climate data record from gome ers 2 sciamachy envisat and gome 2 metop a
    Journal of Geophysical Research, 2015
    Co-Authors: M E Koukouli, Dimitris Balis, I Zyrichidou, Michel Van Roozendael, Christophe Lerot, Florence Goutail, Jean Pierre Pommereau, J C Lambert, J Granville, Melanie Coldeweyegbers
    Abstract:

    The European Space Agency's Ozone Climate Change Initiative (O3-CCI) project aims at producing and validating a number of high-quality Ozone data products generated from different satellite sensors. For Total Ozone, the O3-CCI approach consists of minimizing sources of bias and systematic uncertainties by applying a common retrieval algorithm to all level 1 data sets, in order to enhance the consistency between the level 2 data sets from individual sensors. Here we present the evaluation of the Total Ozone products from the European sensors Global Ozone Monitoring Experiment (GOME)/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A produced with the GOME-type Direct FITting (GODFIT) algorithm v3. Measurements from the three sensors span more than 16 years, from 1996 to 2012. In this work, we present the latest O3-CCI Total Ozone validation results using as reference ground-based measurements from Brewer and Dobson spectrophotometers archived at the World Ozone and UV Data Centre of the World Meteorological Organization as well as from UV-visible differential optical absorption spectroscopy (DOAS)/Systeme D′Analyse par Observations Zenithales (SAOZ) instruments from the Network for the Detection of Atmospheric Composition Change. In particular, we investigate possible dependencies in these new GODFIT v3 Total Ozone data sets with respect to latitude, season, solar zenith angle, and different cloud parameters, using the most adequate type of ground-based instrument. We show that these three O3-CCI Total Ozone data products behave very similarly and are less sensitive to instrumental degradation, mainly as a result of the new reflectance soft-calibration scheme. The mean bias to the ground-based observations is found to be within the 1 ± 1% level for all three sensors while the near-zero decadal stability of the Total Ozone columns (TOCs) provided by the three European instruments falls well within the 1–3% requirement of the European Space Agency's Ozone Climate Change Initiative project.

  • the gome type Total Ozone essential climate variable gto ecv data record from the esa climate change initiative
    Atmospheric Measurement Techniques, 2015
    Co-Authors: Melanie Coldeweyegbers, M E Koukouli, Diego Loyola, M. Van Roozendael, J Granville, Dimitris Alis, Jeanchristophe Lambe, T Verhoels, Christophe Lero, R Spu
    Abstract:

    Abstract. We present the new GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record which has been created within the framework of the European Space Agency's Climate Change Initiative (ESA-CCI). Total Ozone column observations – based on the GOME-type Direct Fitting version 3 algorithm – from GOME (Global Ozone Monitoring Experiment), SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY), and GOME-2 have been combined into one homogeneous time series, thereby taking advantage of the high inter-sensor consistency. The data record spans the 15-year period from March 1996 to June 2011 and it contains global monthly mean Total Ozone columns on a 1°× 1° grid. Geophysical ground-based validation using Brewer, Dobson, and UV–visible instruments has shown that the GTO-ECV level 3 data record is of the same high quality as the equivalent individual level 2 data products that constitute it. Both absolute agreement and long-term stability are excellent with respect to the ground-based data, for almost all latitudes apart from a few outliers which are mostly due to sampling differences between the level 2 and level 3 data. We conclude that the GTO-ECV data record is valuable for a variety of climate applications such as the long-term monitoring of the past evolution of the Ozone layer, trend analysis and the evaluation of chemistry–climate model simulations.

  • gome 2 Total Ozone columns from metop a metop b and assimilation in the macc system
    Atmospheric Measurement Techniques, 2014
    Co-Authors: M E Koukouli, Antje Inness, Pieter Valks, Dimitris Balis, I Zyrichidou, Michel Van Roozendael, Christophe Lerot, Walter Zimmer, Diego Loyola, Ray Spurr
    Abstract:

    Abstract. The two Global Ozone Monitoring Instrument (GOME-2) sensors operated in tandem are flying onboard EUMETSAT's (European Organisation for the Exploitation of Meteorological Satellites) MetOp-A and MetOp-B satellites, launched in October 2006 and September 2012 respectively. This paper presents the operational GOME-2/MetOp-A (GOME-2A) and GOME-2/MetOp-B (GOME-2B) Total Ozone products provided by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). These products are generated using the latest version of the GOME Data Processor (GDP version 4.7). The enhancements in GDP 4.7, including the application of Brion–Daumont–Malicet Ozone absorption cross sections, are presented here. On a global scale, GOME-2B has the same high accuracy as the corresponding GOME-2A products. There is an excellent agreement between the Ozone Total columns from the two sensors, with GOME-2B values slightly lower with a mean difference of only 0.55±0.29%. First global validation results for 6 months of GOME-2B Total Ozone using ground-based measurements show that on average the GOME-2B Total Ozone data obtained with GDP 4.7 are slightly higher than, both, Dobson observations by about 2.0±1.0% and Brewer observations by about 1.0±0.8%. It is concluded that the Total Ozone columns (TOCs) provided by GOME-2A and GOME-2B are consistent and may be used simultaneously without introducing systematic effects, which has been illustrated for the Antarctic Ozone hole on 18 October 2013. GOME-2A Total Ozone data have been used operationally in the Copernicus atmospheric service project MACC-II (Monitoring Atmospheric Composition and Climate – Interim Implementation) near-real-time (NRT) system since October 2013. The magnitude of the bias correction needed for assimilating GOME-2A Ozone is reduced (to about −6 DU in the global mean) when the GOME-2 Ozone retrieval algorithm changed to GDP 4.7.

  • geophysical validation and long term consistency between gome 2 metop a Total Ozone column and measurements from the sensors gome ers 2 sciamachy envisat and omi aura
    Atmospheric Measurement Techniques, 2012
    Co-Authors: M E Koukouli, Pieter Valks, Dimitris Balis, Michel Van Roozendael, Christophe Lerot, Walter Zimmer, Diego Loyola, J C Lambert, Ray Spurr
    Abstract:

    The main aim of the paper is to assess the consistency of five years of Global Ozone Monitoring Experiment-2/Metop-A [GOME-2] Total Ozone columns and the long-term Total Ozone satellite monitoring database already in existence through an extensive inter-comparison and validation exercise using as reference Brewer and Dobson ground-based measurements. The behaviour of the GOME-2 measurements is being weighed against that of GOME (1995–2011), Ozone Monitoring Experiment [OMI] (since 2004) and the Scanning Imaging Absorption spectroMeter for Atmospheric CartograpHY [SCIAMACHY] (since 2002) Total Ozone column products. Over the background truth of the ground-based measurements, the Total Ozone columns are inter-evaluated using a suite of established validation techniques; the GOME-2 time series follow the same patterns as those observed by the other satellite sensors. In particular, on average, GOME-2 data underestimate GOME data by about 0.80%, and underestimate SCIAMACHY data by 0.37% with no seasonal dependence of the differences between GOME-2, GOME and SCIAMACHY. The latter is expected since the three datasets are based on similar DOAS algorithms. This underestimation of GOME-2 is within the uncertainty of the reference data used in the comparisons. Compared to the OMI sensor, on average GOME-2 data underestimate OMI_DOAS (collection 3) data by 1.28%, without any significant seasonal dependence of the differences between them. The lack of seasonality might be expected since both the GOME data processor [GDP] 4.4 and OMI_DOAS are DOAS-type algorithms and both consider the variability of the stratospheric temperatures in their retrievals. Compared to the OMI_TOMS (collection 3) data, no bias was found. We hence conclude that the GOME-2 Total Ozone columns are well suitable to continue the long-term global Total Ozone record with the accuracy needed for climate monitoring studies.

M. Van Roozendael - One of the best experts on this subject based on the ideXlab platform.

  • the gome type Total Ozone essential climate variable gto ecv data record from the esa climate change initiative
    Atmospheric Measurement Techniques, 2015
    Co-Authors: Melanie Coldeweyegbers, M E Koukouli, Diego Loyola, M. Van Roozendael, J Granville, Dimitris Alis, Jeanchristophe Lambe, T Verhoels, Christophe Lero, R Spu
    Abstract:

    Abstract. We present the new GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record which has been created within the framework of the European Space Agency's Climate Change Initiative (ESA-CCI). Total Ozone column observations – based on the GOME-type Direct Fitting version 3 algorithm – from GOME (Global Ozone Monitoring Experiment), SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY), and GOME-2 have been combined into one homogeneous time series, thereby taking advantage of the high inter-sensor consistency. The data record spans the 15-year period from March 1996 to June 2011 and it contains global monthly mean Total Ozone columns on a 1°× 1° grid. Geophysical ground-based validation using Brewer, Dobson, and UV–visible instruments has shown that the GTO-ECV level 3 data record is of the same high quality as the equivalent individual level 2 data products that constitute it. Both absolute agreement and long-term stability are excellent with respect to the ground-based data, for almost all latitudes apart from a few outliers which are mostly due to sampling differences between the level 2 and level 3 data. We conclude that the GTO-ECV data record is valuable for a variety of climate applications such as the long-term monitoring of the past evolution of the Ozone layer, trend analysis and the evaluation of chemistry–climate model simulations.

  • comparison of profile Total Ozone from sbuv v8 6 with gome type and ground based Total Ozone for a 16 year period 1996 to 2011
    Atmospheric Measurement Techniques, 2013
    Co-Authors: E W Chiou, Christophe Lerot, Pawan K. Bhartia, Diego Loyola, M. Van Roozendael, R Spurr, R D Mcpeters, Melanie Coldeweyegbers, Vitali Fioletov, S M Frith
    Abstract:

    Abstract. This paper describes the comparison of the variability of Total column Ozone inferred from the three independent multi-year data records, namely, (i) Solar Backscatter Ultraviolet Instrument (SBUV) v8.6 profile Total Ozone, (ii) GTO (GOME-type Total Ozone), and (iii) ground-based Total Ozone data records covering the 16-year overlap period (March 1996 through June 2011). Analyses are conducted based on area-weighted zonal means for 0–30° S, 0–30° N, 50–30° S, and 30–60° N. It has been found that, on average, the differences in monthly zonal mean Total Ozone vary between −0.3 and 0.8 % and are well within 1%. For GTO minus SBUV, the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean Total Ozone vary between 0.6–0.7% and 2.8–3.8% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.4–0.6% and 2.2–3.5%. The standard deviations and ranges of the differences ground-based minus SBUV regarding both monthly zonal means and anomalies are larger by a factor of 1.4–2.9 in comparison to GTO minus SBUV. The ground-based zonal means demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences GTO minus SBUV and ground-based minus SBUV are found to vary between −0.04 and 0.1% yr−1 (−0.1 and 0.3 DU yr−1). These negligibly small trends have provided strong evidence that there are no significant time-dependent differences among these multi-year Total Ozone data records. Analyses of the annual deviations from pre-1980 level indicate that, for the 15-year period of 1996 to 2010, all three data records show a gradual increase at 30–60° N from −5% in 1996 to −2% in 2010. In contrast, at 50–30° S and 30° S–30° N there has been a levelling off in the 15 years after 1996. The deviations inferred from GTO and SBUV show agreement within 1%, but a slight increase has been found in the differences during the period 1996–2010.

  • 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, 2012
    Co-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 Koukouli
    Abstract:

    [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.

  • 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, 2007
    Co-Authors: Dimitris Balis, Pieter Valks, Diego Loyola, M. Van Roozendael, Jean-christopher Lambert, R Spurr, Y Livschitz, V Amiridis, P Gerard, J Granville
    Abstract:

    [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.

  • ten years of gome ers 2 Total Ozone data the new gome data processor gdp version 4 1 algorithm description
    Journal of Geophysical Research, 2006
    Co-Authors: M. Van Roozendael, Pieter Valks, Dimitris Balis, Diego Loyola, Jean-christopher Lambert, Thomas Ruppert, R Spurr, Y Livschitz, P Kenter, C Fayt
    Abstract:

    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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