Total Ozone Retrieval Research Articles

The transition to new ozone absorption cross sections for Dobson and Brewer total ozone measurements

Abstract. Comparisons between total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers and from various satellite instruments generally reveal seasonally varying differences of a few percent. A large part of these differences has been attributed to the operationally used Bass and Paur ozone cross sections and the lack of accounting for varying stratospheric temperatures in the standard total ozone retrieval for Dobson. This paper demonstrates how the use of new ozone absorption cross sections from the University of Bremen (Weber et al., 2016), as recommended by the Absorption Cross Sections of Ozone (ACSO) committee; the application of appropriate slit functions, especially for the Dobson instrument (Bernhard et al., 2005); and the use of climatological values for the effective ozone layer temperature (Teff), e.g., from TEMIS (Tropospheric Emission Monitoring Internet Service), essentially eliminate these seasonally varying differences between Brewer and Dobson total ozone data (to generally less than ±0.5 %). For Hohenpeissenberg, the previous seasonal difference (close to 0 % in summer and up to 2.5 % in winter) is reduced to less than ±0.5 % year-round. Implementing this approach to the existing global network of Dobson spectrometers will reduce the overall uncertainty in their total ozone data from 3 % to 4 % previously to under 2 % at most locations.

Evaluation of total ozone measurements from Geostationary Environmental Monitoring Spectrometer (GEMS)

Abstract. The continued interest in air pollution and stratospheric ozone variability has motivated the development of a Geostationary Environmental Monitoring Spectrometer (GEMS) for hourly ozone monitoring. This paper provides the atmospheric science community with the world's first assessment of GEMS total column ozone (TCO) retrieval performance and diurnal ozone variation. The algorithm used for GEMS is a more advanced version of its predecessor, the Total Ozone Mapping Spectrometer (TOMS) V8, that incorporates several improvements, including a new lookup table, a simple Lambertian-equivalent reflectivity model, and a spectral dependence correction. The GEMS algorithm also uses the optimal estimation method (OEM) to make error analysis more accessible and robust. The estimated retrieval errors range from 1.5 to 2 DU in September and 2 DU in December, with a constant degree of freedom of the signal (DFS) of 1 in September and a variable DFS of 1.25 to 1.4 in December throughout the day, depending on solar zenith angle (SZA). To assess the performance of the GEMS algorithm, the hourly GEMS total ozone was compared with ground-based measurements from Pandora instruments and other satellite platforms from TROPOMI (TROPOspheric Monitoring Instrument) and OMPS (Ozone Mapping and Profiler Suite Nadir Mapper). GEMS has a high correlation of 0.97 and small RMSE values compared to Pandora TCO at Busan and Seoul in South Korea. It is notable that despite exhibiting seasonal dependence in the mean bias of GEMS with Pandora, GEMS is capable of observing daily variations in ozone that are highly consistent with Pandora measurements, with a bias of approximately 1 %. The comparison of GEMS TCO data with TROPOMI and OMPS TCO data shows a high correlation of 0.99 and low RMSE compared to TROPOMI and OMPS TCO data, but the data have a negative bias of −2.38 % and −2.17 %, with standard deviations of 1.33 % and 1.57 %, respectively. Similar to OMPS, the influence of SO2 from volcanic eruptions is not properly removed in some regions, leading to GEMS overestimating TCO in those areas. The mean biases of GEMS TCO data with TROPOMI and OMPS TCO are within ±1 % at low latitudes but become negative at midlatitudes, with an increasingly negative dependence on latitude. Furthermore, this dependence becomes more prominent from summer to winter. The empirical correction applied to the GEMS irradiance data improves the dependence of the mean bias on season and latitude, but a consistent bias still remains, and a marginal positive trend was observed in December. Therefore, further investigation into correction methods is needed. The results are a meaningful scientific advance by providing the first validated, hourly UV ozone retrievals from a satellite in geostationary orbit. This experience can be used to advance research with future geostationary environmental satellite missions, including the incoming TEMPO (Tropospheric Emissions: Monitoring of Pollution) and Sentinel-4.

Total column ozone retrieval from a novel array spectroradiometer

Abstract. This study presents a new total column ozone (TCO) retrieval from the Koherent system, developed at the Physikalisch-Meteorologisches Observatorium Davos, World Radiation Center (PMOD/WRC). The instrument is based on a small, cost-effective, robust, low-maintenance and state-of-the-art-technology array spectroradiometer. It consists of a BTS-2048-UV-S-F array spectroradiometer from Gigahertz-Optik GmbH, coupled with an optical fibre to a lens-based telescope mounted on a sun tracker for measuring direct UV irradiance in the ultraviolet wavelength band between 305 to 345 nm. Two different algorithms are developed for retrieving TCO from these spectral measurements: (1) TCO retrieved by a least-squares-fit algorithm (LSF) and (2) a custom-double-ratio (CDR) technique using four specifically selected wavelengths from the spectral measurements. The double-ratio technique is analogous to the retrieval algorithm applied for the Dobson instruments and the Brewer instruments but is adopted here for TCO retrieval with Koherent. The instrument was calibrated in two different ways: (a) absolute calibration of the spectra using the portable reference for ultraviolet radiation QASUME for the LSF retrieval and (b) relative calibration of the extraterrestrial constant (ETC) of the CDR retrieval by minimising the slope between air mass and the relative differences of TCO from QASUME and Koherent. This adjustment of the ETC allows the instrument to be calibrated with standard TCO reference instruments during calibration campaigns, such as a double-monochromator Brewer. A 2-year comparison in Davos, Switzerland, between Koherent and the Brewer 156 (double monochromator) shows that TCO derived from Koherent and the Brewer 156 agree, on average, over the entire period within 0.7 % for all retrievals in terms of offset. The performance in terms of slant path depends on the selected retrieval and the applied corrections. The stray-light-corrected LSF retrieval exhibits a smaller slant path dependency than the CDR retrieval and performs almost as well as a double-monochromator system. The slant path dependency of the CDR is comparable to the slant path dependency of a single Brewer monochromator. The combination of both retrievals leads to performance with an offset close to zero compared to Brewer 156, a seasonal amplitude of the relative difference of 0.08 % and a slant path dependency of maximum 1.64 %, which is similar to other standard TCO instruments such as single Brewer or Dobson. Applying the double-ratio technique by selecting the wavelengths and slit functions from Brewer and Dobson, respectively, allows for the determination of the effective ozone temperature with an uncertainty of 3 K in terms of daily averages. With the improved TCO retrieval, Koherent serves as a new low-maintenance instrument which could also be used to monitor TCO at remote sites. The TCO retrieval presented here may be applied to other array-based spectroradiometers, providing direct spectral measurements in the ultraviolet wavelength band.

Algorithm theoretical basis for ozone and sulfur dioxide retrievals from DSCOVR EPIC

Abstract. On board the Deep Space Climate Observatory (DSCOVR), the first Earth-observing satellite at the L1 point (the first Lagrangian point in the Earth–Sun system), the Earth Polychromatic Imaging Camera (EPIC) continuously observes the entire sunlit face of the Earth. EPIC measures the solar backscattered and reflected radiances in 10 discrete spectral channels, four of which are in the ultraviolet (UV) range. These UV bands are selected primarily for total ozone (O3) and aerosol retrievals based on heritage algorithms developed for the series of Total Ozone Mapping Spectrometers (TOMS). These UV measurements also provide sensitive detection of sulfur dioxide (SO2) and volcanic ash, both of which may be episodically injected into the atmosphere during explosive volcanic eruptions. This paper presents the theoretical basis and mathematical procedures for the direct vertical column fitting (DVCF) algorithm used for retrieving total vertical columns of O3 and SO2 from DSCOVR EPIC. This paper describes algorithm advances, including an improved O3 profile representation that enables profile adjustments from multiple spectral measurements and the spatial optimal estimation (SOE) scheme that reduces O3 artifacts resulting from EPIC's band-to-band misregistrations. Furthermore, this paper discusses detailed error analyses and presents intercomparisons with correlative data to validate O3 and SO2 retrievals from EPIC.

Evaluation of Version 3 Total and Tropospheric Ozone Columns From Earth Polychromatic Imaging Camera on Deep Space Climate Observatory for Studying Regional Scale Ozone Variations

Discrete wavelength radiance measurements from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) allows derivation of global synoptic maps of total and tropospheric ozone columns every hour during Northern Hemisphere (NH) Summer or 2 hours during Northern Hemisphere winter. In this study, we present version 3 retrieval of Earth Polychromatic Imaging Camera ozone that covers the period from June 2015 to the present with improved geolocation, calibration, and algorithmic updates. The accuracy of total and tropospheric ozone measurements from EPIC have been evaluated using correlative satellite and ground-based total and tropospheric ozone measurements at time scales from daily averages to monthly means. The comparisons show good agreement with increased differences at high latitudes. The agreement improves if we only accept retrievals derived from the EPIC 317 nm triplet and limit solar zenith and satellite looking angles to 70°. With such filtering in place, the comparisons of EPIC total column ozone retrievals with correlative satellite and ground-based data show mean differences within ±5-7 Dobson Units (or 1.5–2.5%). The biases with other satellite instruments tend to be mostly negative in the Southern Hemisphere while there are no clear latitudinal patterns in ground-based comparisons. Evaluation of the EPIC ozone time series at different ground-based stations with the correlative ground-based and satellite instruments and ozonesondes demonstrated good consistency in capturing ozone variations at daily, weekly and monthly scales with a persistently high correlation (r2 > 0.9) for total and tropospheric columns. We examined EPIC tropospheric ozone columns by comparing with ozonesondes at 12 stations and found that differences in tropospheric column ozone are within ±2.5 DU (or ∼±10%) after removing a constant 3 DU offset at all stations between EPIC and sondes. The analysis of the time series of zonally averaged EPIC tropospheric ozone revealed a statistically significant drop of ∼2–4 DU (∼5–10%) over the entire NH in spring and summer of 2020. This drop in tropospheric ozone is partially related to the unprecedented Arctic stratospheric ozone losses in winter-spring 2019/2020 and reductions in ozone precursor pollutants due to the COVID-19 pandemic.

Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements

Abstract. The retrieval of trace gas, cloud, and aerosol measurements from ultraviolet, visible, and near-infrared (UVN) sensors requires precise information on surface properties that are traditionally obtained from Lambertian equivalent reflectivity (LER) climatologies. The main drawbacks of using LER climatologies for new satellite missions are that (a) climatologies are typically based on previous missions with significantly lower spatial resolutions, (b) they usually do not account fully for satellite-viewing geometry dependencies characterized by bidirectional reflectance distribution function (BRDF) effects, and (c) climatologies may differ considerably from the actual surface conditions especially with snow/ice scenarios. In this paper we present a novel algorithm for the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) from UVN sensors; the algorithm is based on the full-physics inverse learning machine (FP_ILM) retrieval. Radiances are simulated using a radiative transfer model that takes into account the satellite-viewing geometry, and the inverse problem is solved using machine learning techniques to obtain the GE_LER from satellite measurements. The GE_LER retrieval is optimized not only for trace gas retrievals employing the DOAS algorithm, but also for the large amount of data from existing and future atmospheric Sentinel satellite missions. The GE_LER can either be deployed directly for the computation of air mass factors (AMFs) using the effective scene approximation or it can be used to create a global gapless geometry-dependent LER (G3_LER) daily map from the GE_LER under clear-sky conditions for the computation of AMFs using the independent pixel approximation. The GE_LER algorithm is applied to measurements of TROPOMI launched in October 2017 on board the EU/ESA Sentinel-5 Precursor (S5P) mission. The TROPOMI GE_LER/G3_LER results are compared with climatological OMI and GOME-2 LER datasets and the advantages of using GE_LER/G3_LER are demonstrated for the retrieval of total ozone from TROPOMI.

Application of temperature dependent ozone absorption cross-sections in total ozone retrieval at Kunming and Hohenpeissenberg stations

We analyzed the temperature dependence of ozone absorption cross-sections in four data sets: the quadratic temperature data based on measurements of Bass and Paur (BPQ); data measured with the SCIAMACHY satellite spectrometer (SAC); data derived by Daumont, Brion, and Malicet (DBM); and data determined by Serdyuchenko et al. from the University of Bremen (SER). The ozone effective absorption coefficients of the Dobson and Brewer instruments at Kunming in the low-latitude stations and Hohenpeissenberg in the middle-latitude stations were calculated. The test of the total ozone column (TOC) from different ozone absorption cross-section data sets shows that in the Dobson and Brewer retrieval algorithms, the effect of temperature on the Brewer instrument is smaller than that for the Dobson instrument. The temperature sensitivity of the two instruments to the SAC is −0.005%°C−1 and 0.102%°C−1, respectively, indicating that the differences in the temperature sensitivity result in differences in the TOC measurements between the two instruments, as well as in systematic seasonal differences. Using BPQ, DBM and SER to retrieve TOC will increase the overall deviation of the two instruments by 2.5%, −2.77% and −1.89%, respectively. The consistency of the TOC retrieval in the two instruments is the best when using the SAC, which shows a deviation of only 0.03%. The systematic seasonal deviation can also be effectively improved. In addition, this work makes up for the lack of relevant research in low-latitude areas. The rangeability of the monthly mean value of the instrument system deviation at a low-latitude station is about one-half of that at the mid-latitude station (Kunming: 0.2%–1.1%, Hohenpeissenberg: 0.2%–2.0%). This is because the vertical distribution of the ozone and temperature varies in different latitudes, the seasonal variation in the middle and high latitudes is significant, and the effective temperature of ozone (Teff) in low latitudes changes little.

Total Column Ozone Retrieval From the Infrared Measurements of a Geostationary Imager

A new algorithm has been developed to retrieve total column ozone (TOZ) from the infrared measurements of a geostationary satellite imager such as the Advanced Himawari Imager (AHI) aboard Himawari-8 and the advanced meteorological imager flying with the second generation geostationary satellite of South Korea. Based on a nonlinear optimal estimation method, this operational algorithm iteratively retrieves TOZ from AHI thermal measurements under clear-sky conditions as well as over low clouds at 10-min intervals with 6-km spatial resolutions. The first guess for ozone is prepared by combining a monthly climatology with the daily updated TOZ from polar orbiting satellites, while the first guess for the temperature and humidity profiles are from a numerical weather prediction model. AHI contains only one ozone absorption channel ( $9.6~\mu \text{m}$ ), providing information contents (degrees of freedom for signal) of about 0.98 for the ozone retrieval. However, the study shows that the retrieved TOZ successfully captures the temporal and latitudinal variations of ozone flow particularly at mid- and high-latitudes. A validation using the Ozone Monitoring Instrument, Infrared Atmospheric Sounding Interferometer (IASI), and ozonesondes shows that the AHI TOZ are in a good agreement with the three references with mean difference of 2.5%, −0.5%, and 2.6%, respectively. This impressive performance is attributed to the improvements in both first-guess information and the accuracy of the retrieved temperature and humidity profiles. In particular, the good agreement shown in the comparison with the night-time IASI TOZ suggests potential benefits of using the retrieved TOZ for a continuous monitoring of global ozone evolution with high spatial resolution.

Verification of satellite ozone/temperature profile products and ozone effective height/temperature over Kunming, China

Ozonesonde data from November 2013 to April 2015 over Kunming, China are used to verify ozone and temperature profile retrievals from two spaceborne instruments, the version 4.2 product from the Microwave Limb Sounder (MLS) on the NASA Aura satellite and the version 6.0 product from the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite. We calculated and compared the ozone effective height Heff and effective temperature Teff, which are two important parameters in ground-based total ozone retrieval through the use of various profile datasets. This is used to verify the accuracy of the operative values (Heff(0) = 23 km, Teff(0) = −46.3 °C (or −45 °C)) from the World Meteorological Organization. The results show that the deviation of MLS and AIRS ozone profiles from ozone sounding data has significant oscillation and scatter in the upper troposphere and lower stratosphere. The average difference of MLS at 82.5 hPa is (80.5 ± 65.1) %, and that of AIRS at 70 and 100 hPa are (105.6 ± 74.9) % and (107.0 ± 67.8) %, respectively. The two satellite temperature profiles have differences within ±3 °C and can effectively describe the vertical distribution and variation of temperature. When calculating the Heff and Teff, upper stratospheric data missing from the sounding data must be filled in by the satellite profile data; otherwise the calculated results will show large errors of 3.2 km and 3.3 °C. The Heff and Teff at Kunming are respectively 24.36 to 25.51 km and −48.3 to −43.6 °C. The operational Heff and Teff used at Kunming ozone observation station clearly do not conform to the actual situation and must be corrected.

Examination on total ozone column retrievals by Brewer spectrophotometry using different processing software

Abstract. The availability of long-term records of the total ozone content (TOC) represents a valuable source of information for studies on the assessment of short- and long-term atmospheric changes and their impact on the terrestrial ecosystem. In particular, ground-based observations represent a valuable tool for validating satellite-derived products. To our knowledge, details about software packages for processing Brewer spectrophotometer measurements and for retrieving the TOC are seldom specified in studies using such datasets. The sources of the differences among retrieved TOCs from the Brewer instruments located at the Italian stations of Rome and Aosta, using three freely available codes (Brewer Processing Software, BPS; O3Brewer software; and European Brewer Network (EUBREWNET) level 1.5 products) are investigated here. Ground-based TOCs are also compared with Ozone Monitoring Instrument (OMI) TOC retrievals used as an independent dataset since no other instruments near the Brewer sites are available. The overall agreement of the BPS and O3Brewer TOC data with EUBREWNET data is within the estimated total uncertainty in the retrieval of total ozone from a Brewer spectrophotometer (1 %). However, differences can be found depending on the software in use. Such differences become larger when the instrumental sensitivity exhibits a fast and dramatic drift which can affect the ozone retrievals significantly. Moreover, if daily mean values are directly generated by the software, differences can be observed due to the configuration set by the users to process single ozone measurement and the rejection rules applied to data to calculate the daily value. This work aims to provide useful information both for scientists engaged in ozone measurements with Brewer spectrophotometers and for stakeholders of the Brewer data products available on Web-based platforms.

DOAS-based total column ozone retrieval from Phaethon system

This study introduces the measurement of the total ozone column using Differential Optical Absorption Spectroscopy (DOAS) analysis of direct-sun spectra recorded by the Phaethon system. This methodology is based on the analysis of spectra relative to a reference spectrum that has been recorded by the same instrument. The slant column density of ozone associated with the reference spectrum is derived by Langley extrapolation. Total ozone data derived by Phaethon over two years in Thessaloniki are compared with those of a collocated, well-maintained and calibrated, Brewer spectrophotometer. When the retrieval of total ozone is based on the absorption cross sections of (Paur and Bass, 1984) at 228 K, Phaethon shows an average overestimation of 1.85 ± 1.86%. Taking into account the effect of the day-to-day variability of stratospheric temperature on total ozone derived by both systems, the bias is reduced to 0.94 ± 1.26%. The sensitivity of the total ozone retrieval to changes in temperature is larger for Phaethon than for Brewer.

A reanalysis of ozone on Mars from assimilation of SPICAM observations

We have assimilated for the first time SPICAM retrievals of total ozone into a Martian global circulation model to provide a global reanalysis of the ozone cycle. Disagreement in total ozone between model prediction and assimilation is observed between 45°S–10°S from LS=135–180° and at northern polar (60°N–90°N) latitudes during northern fall (LS=150–195°). Large percentage differences in total ozone at northern fall polar latitudes identified through the assimilation process are linked with excessive northward transport of water vapour west of Tharsis and over Arabia Terra. Modelling biases in water vapour can also explain the underestimation of total ozone between 45°S–10°S from LS=135–180°. Heterogeneous uptake of odd hydrogen radicals are unable to explain the outstanding underestimation of northern polar total ozone in late northern fall.Assimilation of total ozone retrievals results in alterations of the modelled spatial distribution of ozone in the southern polar winter high altitude ozone layer. This illustrates the potential use of assimilation methods in constraining total ozone where SPICAM cannot observe, in a region where total ozone is especially important for potential investigations of the polar dynamics.

Statistical Retrieval of Ozone and Meteorological Parameters Using SHADOZ Observations and Radiative Transfer Model

A statistical retrieval algorithm has been developed using SHADOZ ozonesonde observations and radiative transfer model simulations for the retrieval of vertical profiles of temperature, water vapor and ozone. Retrieved profiles of ozone and meteorological parameters are compared with corresponding in-situ ozonesonde observations and IASI observations to test accuracy of the retrieval algorithm. The standard deviation error in the temperature profile, estimated using retrieved and ozonesonde observed profiles, is found to be in the range of 0.7–2.7° K. The percentage root mean square error (RMSE) estimated using retrieved and actual profiles of ozone and water vapor are found to be in the range of 5–30 % and 10–30 %, respectively. The standard deviation error in temperature (2 to 3.5° K) and RMSE in water vapor (~35–55 %) estimated using actual IASI observations (retrieved and observed) is relatively higher than the retrieval errors from the simulated radiances. The RMSE in the retrieval of total column ozone is also estimated using simulated and actual IASI radiances. The RMSE for simulated data is found to be 1.9 ± 1.4 %. The RMSE in the total column ozone estimated for actual IASI observations is found to be 3.8 ± 3.2 %. Inclusion of the zenith angle as a predictor in the regression coefficients has improved retrieval error of atmospheric parameters. The standard deviation error for temperature is improved by 0.2–0.3° K and RMSE for ozone and water vapor is improved by 2–4 % and 4–7 % respectively in different atmospheric regions.

Extended and refined multi sensor reanalysis of total ozone for the period 1970–2012

Abstract. The ozone multi-sensor reanalysis (MSR) is a multi-decadal ozone column data record constructed using all available ozone column satellite data sets, surface Brewer and Dobson observations and a data assimilation technique with detailed error modelling. The result is a high-resolution time series of 6-hourly global ozone column fields and forecast error fields that may be used for ozone trend analyses as well as detailed case studies. The ozone MSR is produced in two steps. First, the latest reprocessed versions of all available ozone column satellite data sets are collected and then are corrected for biases as a function of solar zenith angle (SZA), viewing zenith angle (VZA), time (trend), and stratospheric temperature using surface observations of the ozone column from Brewer and Dobson spectrophotometers from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Subsequently the de-biased satellite observations are assimilated within the ozone chemistry and data assimilation model TMDAM. The MSR2 (MSR version 2) reanalysis upgrade described in this paper consists of an ozone record for the 43-year period 1970–2012. The chemistry transport model and data assimilation system have been adapted to improve the resolution, error modelling and processing speed. Backscatter ultraviolet (BUV) satellite observations have been included for the period 1970–1977. The total record is extended by 13 years compared to the first version of the ozone multi sensor reanalysis, the MSR1. The latest total ozone retrievals of 15 satellite instruments are used: BUV-Nimbus4, TOMS-Nimbus7, TOMS-EP, SBUV-7, -9, -11, -14, -16, -17, -18, -19, GOME, SCIAMACHY, OMI and GOME-2. The resolution of the model runs, assimilation and output is increased from 2° × 3° to 1° × 1°. The analysis is driven by 3-hourly meteorology from the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) starting from 1979, and ERA-40 before that date. The chemistry parameterization has been updated. The performance of the MSR2 analysis is studied with the help of observation-minus-forecast (OmF) departures from the data assimilation, by comparisons with the individual station observations and with ozone sondes. The OmF statistics show that the mean bias of the MSR2 analyses is less than 1 % with respect to de-biased satellite observations after 1979.

Validation of OMI total ozone retrievals from the SAO ozone profile algorithm and three operational algorithms with Brewer measurements

Abstract. The accuracy of total ozone computed from the Smithsonian Astrophysical Observatory (SAO) optimal estimation (OE) ozone profile algorithm (SOE) applied to the Ozone Monitoring Instrument (OMI) is assessed through comparisons with ground-based Brewer spectrometer measurements from 2005 to 2008. We also compare the three OMI operational ozone products, derived from the NASA Total Ozone Mapping Spectrometer (TOMS) algorithm, the KNMI (Royal Netherlands Meteorological Institute) differential optical absorption spectroscopy (DOAS) algorithm, and KNMI's Optimal Estimation (KOE) algorithm. The best agreement is observed between SAO and Brewer, with a mean difference of within 1% at most individual stations. The KNMI OE algorithm systematically overestimates Brewer total ozone by 2% at low and mid-latitudes and 5% at high latitudes while the TOMS and DOAS algorithms underestimate it by ~1.65% on average. Standard deviations of ~1.8% are calculated for both SOE and TOMS, but DOAS and KOE have higher values of 2.2% and 2.6%, respectively. The stability of the SOE algorithm is found to have insignificant dependence on viewing geometry, cloud parameters, or total ozone column. In comparison, the KOE–Brewer differences are significantly correlated with solar and viewing zenith angles and show significant deviations depending on cloud parameters and total ozone amount. The TOMS algorithm exhibits similar stability to SOE with respect to viewing geometry and total column ozone, but has stronger cloud parameter dependence. The dependence of DOAS on observational geometry and geophysical conditions is marginal compared to KOE, but is distinct compared to the SOE and TOMS algorithms. Comparisons of all four OMI products with Brewer show no apparent long-term drift, but seasonal features are evident, especially for KOE and TOMS. The substantial differences in the KOE vs. SOE algorithm performance cannot be sufficiently explained by the use of soft calibration (in SOE) and the use of different a priori error covariance matrices; however, other algorithm details cause fitting residuals larger by a factor of 2–3 for KOE.

First results from a rotational Raman scattering cloud algorithm applied to the Suomi National Polar-orbiting Partnership (NPP) Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper

Abstract. This paper reports initial results from an Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper cloud pressure and cloud fraction algorithm. The OMPS cloud products are intended for use in OMPS ozone or other trace-gas algorithms. We developed the OMPS cloud products using a heritage algorithm developed for the Ozone Monitoring Instrument (OMI) on NASA's Aura satellite. The cloud pressure algorithm utilizes the filling-in of ultraviolet solar Fraunhofer lines by rotational Raman scattering. The OMPS cloud products are evaluated by comparison with OMI cloud products that have been compared in turn with other collocated satellite data including cloud optical thickness profiles derived from a combination of measurements from the CloudSat radar and MODerate-resolution Imaging Spectroradiometer (MODIS). We find that the probability density functions (PDFs) of effective cloud fraction retrieved from OMPS and OMI measurements are very similar. The PDFs of the OMPS and OMI cloud pressures are comparable. However, OMPS retrieves somewhat higher pressures on average. The current NASA total ozone retrieval algorithm makes use of a monthly gridded cloud pressure climatology developed from OMI. This climatology captures much of the variability associated with the relevant cloud pressures. However, the use of actual cloud pressures retrieved with OMPS in place of the OMI climatology changes OMPS total column ozone estimates locally (presumably in the correct direction) only in areas with large differences between climatological and actual cloud pressures. The ozone differences can be up to 5% in such areas.

The Effect of Three Different Absorption Cross-Sections and their Temperature Dependence on Total Ozone Measured by a Mid-Latitude Brewer Spectrophotometer

The influence of variations in atmospheric temperature and ozone profiles on the total ozone column (TOC) derived from a Brewer MKII spectrophotometer operating in Thessaloniki, Greece, is investigated using three different sets of ozone absorption cross-sections. The standard Brewer total ozone retrieval algorithm uses the Bass and Paur (1985) cross-sections without accounting for the temperature dependence of the ozone cross-sections which produces a seasonally dependent bias in the measured TOC. The magnitude of this temperature effect depends on the altitude where the bulk of the ozone absorption occurs. Radiosonde measurements for the period 2000 to 2010 combined with climatological ozone profiles were used to calculate the effective temperature of ozone absorption and investigate its effect on the retrieved ozone column. Three different ozone absorption cross-section spectra convolved with the instrument's slit function were used: those of Bass and Paur (hereafter BP), currently used in the standard Brewer retrieval algorithm; those of Brion, Daumont, and Malicet (Malicet et al., 1985; hereafter BDM); and the recently published set by Serdyuchenko et al. (2013 hereafter S13). The temperature dependence of the differential ozone absorption coefficient ranges between 0.09 and 0.13% per degree Celsius for BP, between −0.11 and −0.06% per degree Celsius for BDM, and between 0.018 to 0.022% per degree Celsius for S13, resulting in a seasonal bias in the derived TOC of up to 2%, 1.8%, and 0.4%, respectively. The temperature sensitivity of the differential ozone absorption coefficient for the Brewer spectrophotometer at Thessaloniki for the BP and BDM cross-sections is found to be within the range reported for other Brewer instruments in earlier studies, whereas the seasonal bias in TOC is minimized when using the new S13 cross-sections because of their small temperature dependence.

Solar Backscatter UV (SBUV) total ozone and profile algorithm

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.

Optical property dimensionality reduction techniques for accelerated radiative transfer performance: Application to remote sensing total ozone retrievals

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.

Global validation of FY-3A total ozone unit (TOU) total ozone columns using ground-based Brewer and Dobson measurements

Analysis of the accuracy and variability of total ozone columns (TOC) has been conducted by many studies, while the TOC observations derived from the total ozone unit (TOU) on board the Chinese FengYun-3A (FY-3A) satellite platform are notably less well documented. Therefore, in this present study, we mainly focus on the global-scale validation of TOU-derived total ozone column data by comparing them with spatially and temporally co-located ground-based measurements from the well-established Brewer and Dobson spectrophotometer for the period July 2009 through December 2011. The results show that TOU-derived total ozone column data yields high accuracy, with the root mean square error less than 5% in comparison with ground-based measurements. Meanwhile, TOU underestimates Brewer measurements by 1.1% in the Northern Hemisphere and overestimates Dobson total ozone 0.3% globally. In addition, TOU-derived total ozone shows no significant dependence on latitude in comparison with either Brewer or Dobson total ozone measurements. Nevertheless, a significant dependence of TOU-derived total ozone is observed on the solar zenith angle (SZA) in comparison with both Brewer and Dobson, demonstrating that TOU underestimates at large SZA and overestimates at small SZA. Finally, the dependence of satellite – ground-based relative difference for total ozone values shows fair agreement when total ozone values are in the range 250–450 Dobson units (DU). Overall, the Chinese FY-3A/TOU performs well on total ozone retrieval with high accuracy, and the total ozone data derived from the TOU can be used as a reliable data source for ozone monitoring and other atmospheric applications.