Metrology of ground-based satellite validation: co-location mismatch and smoothing issues of total ozone comparisons

Abstract. Comparisons with ground-based correlative measurements constitute a key component in the validation of satellite data on atmospheric composition. The error budget of these comparisons contains not only the measurement errors but also several terms related to differences in sampling and smoothing of the inhomogeneous and variable atmospheric field. A versatile system for Observing System Simulation Experiments (OSSEs), named OSSSMOSE, is used here to quantify these terms. Based on the application of pragmatic observation operators onto high-resolution atmospheric fields, it allows a simulation of each individual measurement, and consequently, also of the differences to be expected from spatial and temporal field variations between both measurements making up a comparison pair. As a topical case study, the system is used to evaluate the error budget of total ozone column (TOC) comparisons between GOME-type direct fitting (GODFITv3) satellite retrievals from GOME/ERS2, SCIAMACHY/Envisat, and GOME-2/MetOp-A, and ground-based direct-sun and zenith–sky reference measurements such as those from Dobsons, Brewers, and zenith-scattered light (ZSL-)DOAS instruments, respectively. In particular, the focus is placed on the GODFITv3 reprocessed GOME-2A data record vs. the ground-based instruments contributing to the Network for the Detection of Atmospheric Composition Change (NDACC). The simulations are found to reproduce the actual measurements almost to within the measurement uncertainties, confirming that the OSSE approach and its technical implementation are appropriate. This work reveals that many features of the comparison spread and median difference can be understood as due to metrological differences, even when using strict co-location criteria. In particular, sampling difference errors exceed measurement uncertainties regularly at most mid- and high-latitude stations, with values up to 10 % and more in extreme cases. Smoothing difference errors only play a role in the comparisons with ZSL-DOAS instruments at high latitudes, especially in the presence of a polar vortex due to the strong TOC gradient it induces. At tropical latitudes, where TOC variability is lower, both types of errors remain below about 1 % and consequently do not contribute significantly to the comparison error budget. The detailed analysis of the comparison results, including the metrological errors, suggests that the published random measurement uncertainties for GODFITv3 reprocessed satellite data are potentially overestimated, and adjustments are proposed here. This successful application of the OSSSMOSE system to close for the first time the error budget of TOC comparisons, bodes well for potential future applications, which are briefly touched upon.

[1]  Bernhard Mayer,et al.  Atmospheric Chemistry and Physics Technical Note: the Libradtran Software Package for Radiative Transfer Calculations – Description and Examples of Use , 2022 .

[2]  J. Staehelin,et al.  Long‐term total ozone observations at Arosa (Switzerland) with Dobson and Brewer instruments (1988–2007) , 2010 .

[3]  W. Komhyr,et al.  Effective Bass‐Paur 1985 ozone absorption coefficients for use with Dobson ozone spectrophotometers , 1993 .

[4]  L. Froidevaux,et al.  On sampling uncertainty of satellite ozone profile measurements , 2014 .

[5]  Fuzhong Weng,et al.  JCSDA Community Radiative Transfer Model (CRTM) : version 1 , 2006 .

[6]  J. Staehelin,et al.  Performance of the ground-based total ozone network assessed using satellite data , 2008 .

[7]  S. Schubert,et al.  MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .

[8]  Walter Zimmer,et al.  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 , 2012 .

[9]  James F. Gleason,et al.  Comparison of total ozone from the satellite instruments GOME and TOMS with measurements from the Dobson network 1996-2000 , 2002 .

[10]  Ulrich Platt,et al.  Differential optical absorption spectroscopy , 2008 .

[11]  Fabio Madonna,et al.  Statistical modelling of collocation uncertainty in atmospheric thermodynamic profiles , 2013 .

[12]  F. Goutail,et al.  Validation of Ground-Based Visible Measurements of Total Ozone by Comparison with Dobson and Brewer Spectrophotometers , 1998 .

[13]  Walter Zimmer,et al.  The GOME-2 total column ozone product: Retrieval algorithm and ground-based validation , 2011 .

[14]  J. Lambert,et al.  Combining and Merging Water Vapour Observations: A Multi-dimensional Perspective on Smoothing and Sampling Issues , 2013 .

[15]  B. Connor,et al.  Intercomparison of remote sounding instruments , 1999 .

[16]  P. Bhartia,et al.  A comparison of 40 years of SBUV measurements of column ozone with data from the Dobson/Brewer network , 2013 .

[17]  James B. Kerr,et al.  Altitude distributions of stratospheric constituents from ground‐based measurements at twilight , 1991 .

[18]  Dimitris Balis,et al.  Validation of Ozone Monitoring Instrument total ozone column measurements using Brewer and Dobson spectrophotometer ground‐based observations , 2007 .

[19]  G. Labow,et al.  Bias in Dobson total ozone measurements at high latitudes due to approximations in calculations of ozone absorption coefficients and air mass , 2005 .

[20]  Jing Guo,et al.  Development and validation of observing‐system simulation experiments at NASA's Global Modeling and Assimilation Office , 2013 .

[21]  Dimitris Balis,et al.  Validation of the Aura Ozone Monitoring Instrument total column ozone product , 2008 .

[22]  Gerald Wetzel,et al.  Geophysical validation of temperature retrieved by the ESA processor from MIPAS / ENVISAT atmospheric limb-emission measurements , 2007 .

[23]  M. Dameris,et al.  Tropical tropospheric ozone column retrieval for GOME-2 , 2014 .

[24]  Karen L. Smith,et al.  The surface impacts of Arctic stratospheric ozone anomalies , 2014 .

[25]  Jean-Noël Thépaut,et al.  The MACC reanalysis: an 8 yr data set of atmospheric composition , 2012 .

[26]  C. Rodgers.  Characterization and Error Analysis of Profiles Retrieved From Remote Sounding Measurements , 1990 .

[27]  Richard Siddans,et al.  Round-robin evaluation of nadir ozone profile retrievals: methodology and application to MetOp-A GOME-2 , 2014, Atmospheric Measurement Techniques.

[28]  R. Katz,et al.  Extreme events in a changing climate: Variability is more important than averages , 1992 .

[29]  Dimitris Balis,et al.  Homogenized total ozone data records from the European sensors GOME/ERS‐2, SCIAMACHY/Envisat, and GOME‐2/MetOp‐A , 2014 .

[30]  Costas A. Varotsos,et al.  Geophysical validation of MIPAS-ENVISAT operational ozone data , 2007 .

[31]  R. Ignaccolo,et al.  Modelling collocation uncertainty of 3D atmospheric profiles , 2015, Stochastic Environmental Research and Risk Assessment.

[32]  Stanley C. Solomon,et al.  On the interpretation of zenith sky absorption measurements , 1987 .

[33]  James F. Gleason,et al.  Combined characterisation of GOME and TOMS total ozone measurements from space using ground-based observations from the NDSC , 2000 .

[34]  J. Burrows,et al.  The Brewer-Dobson circulation and total ozone from seasonal to decadal time scales , 2011 .

[35]  W. Josefsson.  Focused sun observations using a Brewer ozone spectrophotometer , 1992 .

[36]  H. Kelder,et al.  An ozone climatology based on ozonesonde and satellite measurements , 1998 .

[37]  F. Hendrick,et al.  NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations , 2011 .

[38]  J. Lambert,et al.  Copernicus stratospheric ozone service, 2009–2012: validation, system intercomparison and roles of input data sets , 2015 .

[39]  Clifford H. Dey,et al.  Observing-Systems Simulation Experiments: Past, Present, and Future , 1986 .

[40]  J. Staehelin,et al.  Comparison of the GOME ozone and NO2 total amounts at mid-latitude with ground-based zenith-sky measurements , 2017 .

[41]  Johannes W. Kaiser,et al.  Global reactive gases forecasts and reanalysis in the MACC project , 2012 .

[42]  Florence Goutail,et al.  O3 and NO2 ground‐based measurements by visible spectrometry during Arctic winter and spring 1988 , 1988 .

[43]  Dimitris Balis,et al.  Evaluating a new homogeneous total ozone climate data record from GOME/ERS‐2, SCIAMACHY/Envisat, and GOME‐2/MetOp‐A , 2015 .

[44]  Clive D Rodgers,et al.  Inverse Methods for Atmospheric Sounding: Theory and Practice , 2000 .

[45]  J. Lambert,et al.  Investigation of Pole-to-Pole Performances of Spaceborne Atmospheric Chemistry Sensors with the NDSC , 1999 .

[46]  Linnea M. Avallone,et al.  Estimating the impact of small‐scale variability in satellite measurement validation , 2006 .

[47]  Pieter Valks,et al.  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 , 2007 .