scholarly journals GOMOS bright limb ozone data set

2015 ◽  
Vol 8 (8) ◽  
pp. 3107-3115 ◽  
Author(s):  
S. Tukiainen ◽  
E. Kyrölä ◽  
J. Tamminen ◽  
J. Kujanpää ◽  
L. Blanot
Keyword(s):  
Stray Light ◽  
Atmospheric Composition ◽  
Profile Data ◽  
Satellite Measurements ◽  
Data Set ◽  
Infrared Imager ◽  
Ozone Profile ◽  
Stellar Occultation ◽  
Ozone Monitoring ◽  
Better Than

Abstract. We have created a daytime ozone profile data set from the measurements of the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the Envisat satellite. This so-called GOMOS bright limb (GBL) data set contains ∼ 358 000 stratospheric daytime ozone profiles measured by GOMOS in 2002–2012. The GBL data set complements the widely used GOMOS nighttime data based on stellar occultation measurements. The GBL data set is based on the GOMOS daytime occultations but instead of the transmitted star light we use limb-scattered solar light. The ozone profiles retrieved from these radiance spectra cover the 18–60 km altitude range and have approximately 2–3 km vertical resolution. We show that these profiles are generally in better than 10 % agreement with the NDACC (Network for the Detection of Atmospheric Composition Change) ozonesonde profiles and with the GOMOS nighttime, MLS (Microwave Limb Sounder), and OSIRIS (Optical Spectrograph and InfraRed Imager System) satellite measurements. However, there is a 10–13 % negative bias at 40 km altitude and a 10–50 % positive bias at 50 km for solar zenith angles > 75°. These biases are most likely caused by stray light which is difficult to characterize and to remove entirely from the measured spectra. Nevertheless, the GBL data set approximately doubles the amount of useful GOMOS ozone profiles and improves coverage of the summer pole.

scholarly journals Round-robin evaluation of nadir ozone profile retrievals: methodology and application to MetOp-A GOME-2

2015 ◽  
Vol 8 (5) ◽  
pp. 2093-2120 ◽  
Author(s):  
A. Keppens ◽  
J.-C. Lambert ◽  
J. Granville ◽  
G. Miles ◽  
R. Siddans ◽  
...  
Keyword(s):  
Information Content ◽  
Global Climate ◽  
Optimal Estimation ◽  
Round Robin ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Profile Data ◽  
Satellite Measurements ◽  
Data Set ◽  
Ozone Profile

Abstract. A methodology for the round-robin evaluation and the geophysical validation of ozone profile data retrieved from nadir UV backscatter satellite measurements is detailed and discussed, consisting of data set content studies, information content studies, co-location studies, and comparisons with reference measurements. Within the European Space Agency's Climate Change Initiative on ozone (Ozone_cci project), the proposed round-robin procedure is applied to two nadir ozone profile data sets retrieved at the Royal Netherlands Meteorological Institute (KNMI) and the Rutherford Appleton Laboratory (RAL, United Kingdom), using their respective OPERA v1.26 and RAL v2.1 optimal estimation algorithms, from MetOp-A GOME-2 (i.e. the second generation Global Ozone Monitoring Experiment on the first Meteorological Operational Satellite) measurements taken in 2008. The ground-based comparisons use ozonesonde and lidar profiles as reference data, acquired by the Network for the Detection of Atmospheric Composition Change (NDACC), Southern Hemisphere Additional Ozonesonde programme (SHADOZ), and other stations of the World Meteorological Organisation's Global Atmosphere Watch (WMO GAW). This direct illustration highlights practical issues that inevitably emerge from discrepancies in e.g. profile representation and vertical smoothing, for which different recipes are investigated and discussed. Several approaches for information content quantification, vertical resolution estimation, and reference profile resampling are compared and applied as well. The paper concludes with compliance estimates of the two GOME-2 ozone profile data sets with user requirements from the Global Climate Observing System (GCOS) and from climate modellers.

scholarly journals GOMOS bright limb ozone data set

2015 ◽  
Vol 8 (1) ◽  
pp. 987-1011
Author(s):  
S. Tukiainen ◽  
E. Kyrölä ◽  
J. Tamminen ◽  
L. Blanot
Keyword(s):  
Infrared Imaging ◽  
Imaging System ◽  
Stray Light ◽  
Atmospheric Composition ◽  
Time Data ◽  
Satellite Measurements ◽  
Night Time ◽  
Data Set ◽  
Height Range ◽  
Ozone Profile

Abstract. We have created a daytime ozone profile data set from the measurements of the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the Envisat satellite. This so-called GOMOS bright limb (GBL) data set contains ~ 358 000 stratospheric daytime ozone profiles measured by GOMOS in 2002–2012. The GBL data set complements the widely used GOMOS night-time data based on stellar occultation measurements. The GBL data set is based on the GOMOS daytime occultations but instead of the transmitted star light, we use limb scattered solar light. The ozone profiles retrieved from these radiance spectra cover 18–60 km tangent height range and have approximately 2–3 km vertical resolution. We show that these profiles are generally in better than 10% agreement with the NDACC (Network for the Detection of Atmospheric Composition Change) ozone sounding profiles and with the GOMOS night-time, MLS (Microwave Limb Sounder), and OSIRIS (Optical Spectrograph, and InfraRed Imaging System) satellite measurements. However, there is a 10–13% negative bias at 40 km tangent height and a 10–50% positive bias at 50 km when the solar zenith angle > 75°. These biases are most likely caused by stray light which is difficult to characterize and remove entirely from the measured spectra. Nevertheless, the GBL data set approximately doubles the amount of useful GOMOS ozone profiles and improves coverage of the summer pole.

scholarly journals Round-robin evaluation of nadir ozone profile retrievals: methodology and application to MetOp-A GOME-2

2014 ◽  
Vol 7 (11) ◽  
pp. 11481-11546 ◽  
Author(s):  
A. Keppens ◽  
J.-C. Lambert ◽  
J. Granville ◽  
G. Miles ◽  
R. Siddans ◽  
...  
Keyword(s):  
Information Content ◽  
Optimal Estimation ◽  
Round Robin ◽  
Atmospheric Composition ◽  
User Requirements ◽  
Satellite Measurements ◽  
Estimation Algorithms ◽  
Ozone Profile ◽  
Reference Measurements ◽  
Resolution Estimation

Abstract. A methodology for the round-robin evaluation and geophysical validation of ozone profile data retrieved from nadir UV backscatter satellite measurements is detailed and discussed, consisting of dataset content studies, information content studies, co-location studies, and comparisons with reference measurements. Within ESA's Climate Change Initiative on ozone (Ozone_cci project), the proposed round-robin procedure is applied to two nadir ozone profile datasets retrieved at KNMI and RAL, using their respective OPERA v1.26 and RAL v2.1 optimal estimation algorithms, from MetOp-A GOME-2 measurements taken in 2008. The ground-based comparisons use ozonesonde and lidar profiles as reference data, acquired by the Network for the Detection of Atmospheric Composition Change (NDACC), Southern Hemisphere Additional Ozonesonde programme (SHADOZ), and other stations of WMO's Global Atmosphere Watch. This direct illustration highlights practical issues that inevitably emerge from discrepancies in e.g. profile representation and vertical smoothing, for which different recipes are investigated and discussed. Several approaches for information content quantification, vertical resolution estimation, and reference profile resampling are compared and applied as well. The paper concludes with compliance estimates of the two GOME-2 ozone profile datasets with user requirements from GCOS and from climate modellers.

scholarly journals Deriving the slit functions from OMI solar observations and its implications for ozone-profile retrieval

2017 ◽  
Vol 10 (10) ◽  
pp. 3677-3695 ◽  
Author(s):  
Kang Sun ◽  
Xiong Liu ◽  
Guanyu Huang ◽  
Gonzalo González Abad ◽  
Zhaonan Cai ◽  
...  
Keyword(s):  
Atmospheric Composition ◽  
Half Maximum ◽  
Ozone Monitoring Instrument ◽  
Gaussian Functions ◽  
Solar Observations ◽  
Ozone Profile ◽  
Retrieval Algorithms ◽  
Ozone Monitoring ◽  
Cross Track ◽  
Over Time

Abstract. The Ozone Monitoring Instrument (OMI) has been successfully measuring the Earth's atmospheric composition since 2004, but the on-orbit behavior of its slit functions has not been thoroughly characterized. Preflight measurements of slit functions have been used as a static input in many OMI retrieval algorithms. This study derives on-orbit slit functions from the OMI irradiance spectra assuming various function forms, including standard and super-Gaussian functions and a stretch to the preflight slit functions. The on-orbit slit functions in the UV bands show U-shaped cross-track dependences that cannot be fully represented by the preflight ones. The full widths at half maximum (FWHM) of the stretched preflight slit functions for detector pixels at large viewing angles are up to 30 % larger than the nadir pixels for the UV1 band, 5 % larger for the UV2 band, and practically flat in the VIS band. Nonetheless, the on-orbit changes of OMI slit functions are found to be insignificant over time after accounting for the solar activity, despite of the decaying of detectors and the occurrence of OMI row anomaly. Applying the derived on-orbit slit functions to ozone-profile retrieval shows substantial improvements over the preflight slit functions based on comparisons with ozonesonde validations.

scholarly journals Retrievals from GOMOS stellar occultation measurements using characterization of modeling errors

2010 ◽  
Vol 3 (1) ◽  
pp. 579-597 ◽  
Author(s):  
V. F. Sofieva ◽  
J. Vira ◽  
E. Kyrölä ◽  
J. Tamminen ◽  
V. Kan ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Large Data ◽  
Inversion Algorithm ◽  
Data Set ◽  
High Importance ◽  
Numerical Efficiency ◽  
Modeling Errors ◽  
Stellar Occultation ◽  
Ozone Monitoring

Abstract. In this paper, we discuss the development of the inversion algorithm for the GOMOS (Global Ozone Monitoring by Occultation of Star) instrument on board the Envisat satellite. The proposed algorithm takes accurately into account the wavelength-dependent modeling errors, which are mainly due to the incomplete scintillation correction in the stratosphere. The special attention is paid to numerical efficiency of the algorithm. The developed method is tested on a large data set and its advantages are demonstrated. Its main advantage is a proper characterization of the uncertainties of the retrieved profiles of atmospheric constituents, which is of high importance for data assimilation, trend analyses and validation.

scholarly journals Technical Note: Validation of Odin/SMR limb observations of ozone, comparisons with OSIRIS, POAM III, ground-based and balloon-borne instruments

2008 ◽  
Vol 8 (1) ◽  
pp. 727-779
Author(s):  
F. Jégou ◽  
J. Urban ◽  
J. de La Noë ◽  
P. Ricaud ◽  
E. Le Flochmoën ◽  
...  
Keyword(s):  
Stratospheric Ozone ◽  
Technical Note ◽  
Atmospheric Composition ◽  
Satellite Measurements ◽  
Space Agency ◽  
Infrared Imager ◽  
Ozone Maximum ◽  
Polar Ozone ◽  
Good Agreement

Abstract. The Odin satellite carries two instruments capable of determining stratospheric ozone profiles by limb sounding: the Sub-Millimetre Radiometer (SMR) and the UV-visible spectrograph of the OSIRIS (Optical Spectrograph and InfraRed Imager System) instrument. A large number of ozone profiles measurements were performed during six years from November 2001 to present. This ozone dataset is here used to make quantitative comparisons with satellite measurements in order to assess the quality of the Odin/SMR ozone measurements. In a first step, we compare Swedish SMR retrievals version 2.1, French SMR ozone retrievals version 222 (both from the 501.8 GHz band), and the OSIRIS retrievals version 3.0, with the operational version 4.0 ozone product from POAM III (Polar Ozone Atmospheric Measurement). In a second step, we refine the Odin/SMR validation by comparisons with ground-based instruments and balloon-borne observations. We use observations carried out within the framework of the Network for Detection of Atmospheric Composition Change (NDACC) and balloon flight missions conducted by the Canadian Space Agency (CSA), the Laboratoire de Physique et de Chimie de l'Environnement (LPCE, Orléans, France), and the Service d'Aéronomie (SA, Paris, France). Coincidence criteria were 5° in latitude x in 10° longitude, and 5 h in time in Odin/POAM III comparisons, 12 h in Odin/NDACC comparisons, and 72 h in Odin/balloons comparisons. An agreement is found with the POAM III experiment (10–60 km) within −0.3±0.2 ppmv (bias±standard deviation) for SMR (v222, v2.1) and within −0.5±0.2 ppmv for OSIRIS (v3.0). Odin ozone mixing ratio products are systematically slightly lower than the POAM III data and show an ozone maximum lower by 1–5 km in altitude. The comparisons with the NDACC data (10–34 km for ozonesonde, 10–50 km for lidar, 10–60 for microwave instruments) yield a good agreement within −0.15±0.3 ppmv for the SMR data and −0.3±0.3 ppmv for the OSIRIS data. Finally the comparisons with instruments on large balloons (10–31 km) show a good agreement, within −0.7±1 ppmv.

scholarly journals ML-TOMCAT: machine-learning-based satellite-corrected global stratospheric ozone profile data set from a chemical transport model

2021 ◽  
Vol 13 (12) ◽  
pp. 5711-5729
Author(s):  
Sandip S. Dhomse ◽  
Carlo Arosio ◽  
Wuhu Feng ◽  
Alexei Rozanov ◽  
Mark Weber ◽  
...  
Keyword(s):  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Profile Data ◽  
Data Set ◽  
Ozone Profile ◽  
Satellite Instruments

Abstract. High-quality stratospheric ozone profile data sets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments provide stratospheric ozone profile measurements over typical mission durations of 5–15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create long-term observation-based ozone profile data sets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different data sets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a random-forest (RF) ensemble learning method to create a merged 42-year (1979–2020) stratospheric ozone profile data set (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gases, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991–1998) and Aura (2005–2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based data sets which use pressure as a vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the data sets which are altitude-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties of the observational data sets. The ML-TOMCAT (V1.0) data set is ideally suited for the evaluation of chemical model ozone profiles from the tropopause to 0.1 hPa and is freely available via https://doi.org/10.5281/zenodo.5651194 (Dhomse et al., 2021).

scholarly journals Sensitivity of Dobson and Brewer Umkehr ozone profile retrievals to ozone cross-sections and stray light effects

2011 ◽  
Vol 4 (9) ◽  
pp. 1841-1853 ◽  
Author(s):  
I. Petropavlovskikh ◽  
R. Evans ◽  
G. McConville ◽  
S. Oltmans ◽  
D. Quincy ◽  
...  
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
European Space Agency ◽  
Stray Light ◽  
Ozone Monitoring Instrument ◽  
Section Data ◽  
Space Agency ◽  
Ozone Profile ◽  
The World ◽  
Ozone Monitoring

Abstract. Remote sounding methods are used to derive ozone profile and column information from various ground-based and satellite measurements. Vertical ozone profiles measured in Dobson units (DU) are currently retrieved based on laboratory measurements of the ozone absorption cross-section spectrum between 270 and 400 nm published in 1985 by Bass and Paur (BP). Recently, the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) proposed using the set of ozone cross-section measurements made at the Daumont laboratory in 1992 (BDM) for revising the Aura Ozone Monitoring Instrument (OMI) and Global Ozone Monitoring Experiment (GOME) satellite ozone profiles and total ozone column retrievals. Dobson Umkehr zenith sky data have been collected by NOAA ground-based stations at Boulder, CO (BDR) and Mauna Loa Observatory, HI (MLO) since the 1980s. The UMK04 algorithm is based on the BP ozone cross-section data. It is currently used for all Dobson Umkehr data processing submitted to the World Ozone and Ultraviolet radiation Data Centre (WOUDC) under the Global Atmosphere Watch (GAW) program of the World Meteorological Organization (WMO). Ozone profiles are also retrieved from measurements by the Mark IV Brewers operated by the NOAA-EPA Brewer Spectrophotometer UV and Ozone Network (NEUBrew) using a modified UMK04 algorithm (O3BUmkehr v.2.6, Martin Stanek). This paper describes the sensitivity of the Umkehr retrievals with respect to the proposed ozone cross-section changes. It is found that the ozone cross-section choice only minimally (within the retrieval accuracy) affects the Dobson and the Brewer Umkehr retrievals. On the other hand, significantly larger errors were found in the MLO and Boulder Umkehr ozone data (−8 and +5% bias in stratosphere and troposphere respectively) when the out-of-band (OOB) stray light contribution to the Umkehr measurement is not taken into account (correction is currently not included in the UMK04). The vertical distribution of OOB effect in the retrieved profile can be related to the local ozone climatology, instrument degradation, and optical characteristics of the instrument. Nonetheless, recurring OOB errors do not contribute to the long-term ozone trends.

scholarly journals Retrieval of ozone profiles from GOMOS limb scattered measurements

2011 ◽  
Vol 4 (4) ◽  
pp. 659-667 ◽  
Author(s):  
S. Tukiainen ◽  
E. Kyrölä ◽  
P. T. Verronen ◽  
D. Fussen ◽  
L. Blanot ◽  
...  
Keyword(s):  
Imaging System ◽  
Signal To Noise Ratio ◽  
Stray Light ◽  
Data Sets ◽  
Night Time ◽  
Retrieval Method ◽  
Stellar Radiation ◽  
Stellar Occultation ◽  
Infra Red ◽  
Ozone Monitoring

Abstract. The GOMOS (Global Ozone Monitoring by Occultation of Stars) instrument on board the Envisat satellite measures the vertical composition of the atmosphere using the stellar occultation technique. While the night-time occultations of GOMOS have been proven to be of good quality, the daytime occultations are more challenging due to weaker signal-to-noise ratio. During daytime GOMOS measures limb scattered solar radiation in addition to stellar radiation. In this paper we introduce a retrieval method that determines ozone profiles between 20–60 km from GOMOS limb scattered solar radiances. GOMOS observations contain a considerable amount of stray light at high altitudes. We introduce a method for removing stray light and demonstrate its feasibility by comparing the corrected radiances against those measured by the OSIRIS (Optical Spectrograph & Infra Red Imaging System) instrument. For the retrieval of ozone profiles, a standard onion peeling method is used. The first comparisons with other data sets suggest that the retrieved ozone profiles in 22–50 km are within 10% compared with the GOMOS night-time occultations and within 15% compared with OSIRIS. GOMOS has measured about 350 000 daytime profiles since 2002. The retrieval method presented here makes this large amount of data available for scientific use.

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