scholarly journals Simultaneous Retrievals of Polar Mesospheric Clouds (PMCs) with Ozone from OMI UV measurements

2015 ◽  
Vol 15 (18) ◽  
pp. 25907-25932
Author(s):  
J. Bak ◽  
X. Liu ◽  
J. H. Kim ◽  
M. T. Deland ◽  
K. Chance
Keyword(s):  
Optimal Estimation ◽  
High Latitudes ◽  
Ozone Monitoring Instrument ◽  
Polar Mesospheric Clouds ◽  
Ozone Profile ◽  
Back Scattering ◽  
Sensitivity Studies ◽  
Systematic Biases ◽  
Retrieval Errors ◽  
Mesospheric Clouds

Abstract. The presence of polar mesospheric clouds (PMCs) at high latitudes could affect the retrieval of ozone profiles using backscattered ultraviolet (BUV) measurements. PMC-induced errors in ozone profile retrievals from Ozone Monitoring Instrument (OMI) BUV measurements are investigated through comparisons with Microwave Limb Sounder (MLS) ozone measurements. This comparison demonstrates that the presence of PMCs leads to systematic biases at altitudes above 6 hPa in summer high latitudes; the biases increase from ~ −2 % at 2 hPa to ~ −20 % at 0.5 hPa on average, and are significantly correlated with brightness of PMCs. Sensitivity studies show that the radiance sensitivity to PMCs strongly depends on wavelengths, increasing by a factor of ~ 4 from 300 to 265 nm. It also strongly depends on the PMC scattering, thus depending on viewing geometry. The optimal estimation-based retrieval sensitivity analysis shows that PMCs located at 80–85 km have the greatest effect on ozone retrievals at ~ 0.2 hPa (~ 60 km), where the retrieval errors range from −2.5 % with PMC optical depth (POD) of 10−4 to −20 % with 10−3 at back scattering angles, and the impacts increase by a factor of ~ 5 at forward scattering angles due to stronger PMC sensitivities. To reduce the interference of PMCs on ozone retrievals, we perform simultaneous retrievals of POD and ozone with a loose constraint of 10−3 for POD, which results in retrieval errors of 1–4 × 10−4. It is demonstrated that the negative bias of OMI ozone retrievals relative to MLS could be improved by including the PMC in the forward model calculation and retrieval.

scholarly journals Improvement of OMI ozone profile retrievals by simultaneously fitting polar mesospheric clouds

2016 ◽  
Vol 9 (9) ◽  
pp. 4521-4531 ◽  
Author(s):  
Juseon Bak ◽  
Xiong Liu ◽  
Jae H. Kim ◽  
Matthew T. Deland ◽  
Kelly Chance
Keyword(s):  
Optimal Estimation ◽  
High Latitudes ◽  
Ozone Monitoring Instrument ◽  
Polar Mesospheric Clouds ◽  
Ozone Profile ◽  
Sensitivity Studies ◽  
Systematic Biases ◽  
Ozone Monitoring ◽  
Retrieval Errors ◽  
Mesospheric Clouds

Abstract. The presence of polar mesospheric clouds (PMCs) at summer high latitudes could affect the retrieval of ozone profiles using backscattered ultraviolet (UV) measurements. PMC-induced errors in ozone profile retrievals from Ozone Monitoring Instrument (OMI) backscattered UV measurements are investigated through comparisons with Microwave Limb Sounder (MLS) ozone measurements. This comparison demonstrates that the presence of PMCs leads to systematic biases for pressures smaller than 6 hPa; the biases increase from  ∼ −2 % at 2 hPa to  ∼ −20 % at 0.5 hPa on average and are significantly correlated with brightness of PMCs. Sensitivity studies show that the radiance sensitivity to PMCs strongly depends on wavelength, increasing by a factor of  ∼  4 from 300 to 265 nm. It also strongly depends on the PMC scattering, thus depending on viewing geometry. The optimal estimation-based retrieval sensitivity analysis shows that PMCs located at 80–85 km have the greatest effect on ozone retrievals at  ∼  0.2 hPa ( ∼  60 km), where the retrieval errors range from −2.5 % with PMC vertical optical depth (POD) of 10−4 to −20 % with 10−3 POD at backscattering angles. The impacts increase by a factor of  ∼  5 at forward-scattering angles due to stronger PMC sensitivities. To reduce the interference of PMCs on ozone retrievals, we perform simultaneous retrievals of POD and ozone with a loose constraint of 10−3 for POD, which results in retrieval errors of 1–4 × 10−4. It is demonstrated that the negative bias of OMI ozone retrievals relative to MLS can be improved by including the PMC in the forward-model calculation and retrieval.

scholarly journals Improvement of OMI ozone profile retrievals by simultaneously fitting Polar Mesospheric Clouds

2016 ◽  
Author(s):  
Juseon Bak ◽  
Xiong Liu ◽  
Jae H. Kim ◽  
Matthew T. Deland ◽  
Kelly Chance
Keyword(s):  
Optimal Estimation ◽  
Ozone Monitoring Instrument ◽  
Polar Mesospheric Clouds ◽  
Ozone Profile ◽  
Back Scattering ◽  
Sensitivity Studies ◽  
Systematic Biases ◽  
Ozone Monitoring ◽  
Retrieval Errors ◽  
Mesospheric Clouds

Abstract. The presence of polar mesospheric clouds (PMCs) in summer high latitudes could affect the retrieval of ozone profiles using backscattered ultraviolet (UV) measurements. PMC-induced errors in ozone profile retrievals from Ozone Monitoring Instrument (OMI) backscattered UV measurements are investigated through comparisons with Microwave Limb Sounder (MLS) ozone measurements. This comparison demonstrates that the presence of PMCs leads to systematic biases at pressures less than 6 hPa (~35 km); the biases increase from ~−2 % at 2 hPa to ~−20 % at 0.5 hPa on average, and are significantly correlated with brightness of PMCs. Sensitivity studies show that the radiance sensitivity to PMCs strongly depends on wavelength, increasing by a factor of ~4 from 300 nm to 265 nm. It also strongly depends on the PMC scattering, thus depending on viewing geometry. The optimal estimation-based retrieval sensitivity analysis shows that PMCs located at 80–85 km have the greatest effect on ozone retrievals at ~0.2 hPa (~60 km), where the retrieval errors range from −2.5 % with PMC optical depth (POD) of 10−4 to −20 % with 10−3 at back scattering angles, and the impacts increase by a factor of ~5 at forward scattering angles due to stronger PMC sensitivities. To reduce the interference of PMCs on ozone retrievals, we perform simultaneous retrievals of POD and ozone with a loose constraint of 10−3 for POD, which results in retrieval errors of 1–4×10−4. It is demonstrated that the negative bias of OMI ozone retrievals relative to MLS can be improved by including the PMC in the forward model calculation and retrieval.

scholarly journals Linearization of the effect of slit function changes for improving OMI ozone profile retrievals

2019 ◽  
Author(s):  
Juseon Bak ◽  
Xiong Liu ◽  
Kang Sun ◽  
Kelly Chance ◽  
Jae-Hwan Kim
Keyword(s):  
Cross Sections ◽  
Shape Factor ◽  
Optimal Estimation ◽  
Ozone Monitoring Instrument ◽  
Thermally Induced ◽  
Spectral Fitting ◽  
Ozone Profile ◽  
Systematic Biases ◽  
Hartley Band ◽  
The Tropics

Abstract. We introduce a method that reduces the spectral fit residuals caused by the slit function errors in an optimal estimation based spectral fitting process to improve ozone profile retrievals from the Ozone Monitoring Instrument (OMI) ultraviolet measurements (270–330 nm). Previously, a slit function was parameterized as a standard Gaussian by fitting the Full Width at Half Maximum (FWHM) of the slit function from climatological OMI solar irradiances. This cannot account for the temporal variation of slit function in irradiance, the intra-orbit slit function changes due to thermally-induced change and scene inhomogeneity, and potential differences in the slit functions of irradiance and radiance measurements. As a result, radiance simulation errors may be induced due to using the convolved reference spectra with incorrect slit functions. To better represent the shape of the slit functions, we implement a more generic super Gaussian slit function with two free parameters (slit width and shape factor); it becomes standard Gaussian when the shape factor is fixed to be 2. The effects of errors in slit function parameters on radiance spectra, referred as Pseudo Absorbers (PAs), are linearized by convolving high-resolution cross sections or simulated radiances with the partial derivatives of the slit function with respect to the slit parameters. The PAs are included in the spectral fitting scaled by fitting coefficients that are iteratively adjusted as elements of the state vector along with ozone and other fitting parameters. The fit coefficients vary with cross-track and along-track pixels and show sensitivity to heterogeneous scenes. The total PA spectrum is quite similar in the Hartley band below 310 nm for both standard and super Gaussians, but is more distinctly structured in the Huggins band above 310 nm with the use of super Gaussian slit functions. Finally, we demonstrate that some spikes of fitting residuals are slightly smoothed by accounting for the slit function errors. Comparisons with ozonesondes demonstrate substantial improvements with the use of PAs for both standard and super Gaussians, especially for reducing the systematic biases in the tropics and mid-latitudes and reducing the standard deviations at high-latitudes. Including PAs also makes the retrievals consistent between standard and super Gaussians. This study corroborates the slit function differences between radiance and irradiance demonstrating that it is important to account for such differences in the ozone profile retrievals.

scholarly journals Evaluation of ozone profile and tropospheric ozone retrievals from GEMS and OMI spectra

2013 ◽  
Vol 6 (2) ◽  
pp. 239-249 ◽  
Author(s):  
J. Bak ◽  
J. H. Kim ◽  
X. Liu ◽  
K. Chance ◽  
J. Kim
Keyword(s):  
Spectral Resolution ◽  
Tropospheric Ozone ◽  
Stratospheric Ozone ◽  
A Priori ◽  
Ozone Monitoring Instrument ◽  
Satellite Platform ◽  
Ozone Profile ◽  
Retrieval Errors ◽  
Standard Deviations ◽  
Column Ozone

Abstract. South Korea is planning to launch the GEMS (Geostationary Environment Monitoring Spectrometer) instrument into the GeoKOMPSAT (Geostationary Korea Multi-Purpose SATellite) platform in 2018 to monitor tropospheric air pollutants on an hourly basis over East Asia. GEMS will measure backscattered UV radiances covering the 300–500 nm wavelength range with a spectral resolution of 0.6 nm. The main objective of this study is to evaluate ozone profiles and stratospheric column ozone amounts retrieved from simulated GEMS measurements. Ozone Monitoring Instrument (OMI) Level 1B radiances, which have the spectral range 270–500 nm at spectral resolution of 0.42–0.63 nm, are used to simulate the GEMS radiances. An optimal estimation-based ozone profile algorithm is used to retrieve ozone profiles from simulated GEMS radiances. Firstly, we compare the retrieval characteristics (including averaging kernels, degrees of freedom for signal, and retrieval error) derived from the 270–330 nm (OMI) and 300–330 nm (GEMS) wavelength ranges. This comparison shows that the effect of not using measurements below 300 nm on retrieval characteristics in the troposphere is insignificant. However, the stratospheric ozone information in terms of DFS decreases greatly from OMI to GEMS, by a factor of ∼2. The number of the independent pieces of information available from GEMS measurements is estimated to 3 on average in the stratosphere, with associated retrieval errors of ~1% in stratospheric column ozone. The difference between OMI and GEMS retrieval characteristics is apparent for retrieving ozone layers above ~20 km, with a reduction in the sensitivity and an increase in the retrieval errors for GEMS. We further investigate whether GEMS can resolve the stratospheric ozone variation observed from high vertical resolution Earth Observing System (EOS) Microwave Limb Sounder (MLS). The differences in stratospheric ozone profiles between GEMS and MLS are comparable to those between OMI and MLS below ~3 hPa (~40 km), except with slightly larger biases and larger standard deviations by up to 5%. At pressure altitudes above ~3 hPa, GEMS retrievals show strong influence of a priori and large differences with MLS, which, however, can be sufficiently improved by using better a priori information. The GEMS-MLS differences show negative biases of less than 4% for stratospheric column ozone, with standard deviations of 1–3%, while OMI retrievals show similar agreements with MLS except for 1% smaller biases at middle and high latitudes. Based on the comparisons, we conclude that GEMS will measure tropospheric ozone and stratospheric ozone columns with accuracy comparable to that of OMI and ozone profiles with slightly worse performance than that of OMI below ~3 hPa.

scholarly journals Characterization and Correction of OMPS Nadir Mapper Measurements for Ozone Profile Retrievals

2017 ◽  
Author(s):  
Juseon Bak ◽  
Xiong Liu ◽  
Jae-Hwan Kim ◽  
David P. Haffner ◽  
Kelly Chance ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Degrees Of Freedom ◽  
Optimal Estimation ◽  
Inversion Method ◽  
Radiometric Calibration ◽  
Ozone Monitoring Instrument ◽  
Ozone Profile ◽  
Noise Error ◽  
Significant Wavelength ◽  
Cross Track

Abstract. This paper verifies and corrects the Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) Level 1B v2.0 measurements with the aim of producing accurate ozone profile retrievals using an optimal estimation based inversion method to fit measurements in the spectral range 302.5–340 nm. The evaluation of available slit functions demonstrates that preflight-measured slit functions well represent OMPS measurements compared to derived Gaussian slit functions. Our initial OMPS fitting residuals contain significant wavelength and cross-track dependent biases, resulting into serious cross-track striping errors in the tropospheric ozone retrievals. To eliminate the systematic component of the fitting residuals, we apply “soft calibration” to OMPS radiances. With the soft calibration the amplitude of fitting residuals decreases from ~ 1 % to 0.2 % over low/mid latitudes, and thereby the consistency of tropospheric ozone retrievals between OMPS and the Ozone Monitoring Instrument (OMI) is substantially improved. A common mode correction is also implemented for additional radiometric calibration; it improves retrievals especially at high latitudes where the amplitude of fitting residuals decreases by a factor of ~ 2. We estimate the floor noise error of OMPS measurements from standard deviations of the fitting residuals. The derived error in the Huggins band (~ 0.1 %) is twice the OMPS L1B measurement error. OMPS floor noise errors better constrains our retrievals, leading to improving information content of ozone and reducing fitting residuals. The final precision of the fitting residuals is less than 0.1 % in the low/mid latitude, with ~ 1 degrees of freedom for signal for the tropospheric ozone, meeting the general requirements for successful tropospheric ozone retrievals.

scholarly journals Linearization of the effect of slit function changes for improving Ozone Monitoring Instrument ozone profile retrievals

2019 ◽  
Vol 12 (7) ◽  
pp. 3777-3788 ◽  
Author(s):  
Juseon Bak ◽  
Xiong Liu ◽  
Kang Sun ◽  
Kelly Chance ◽  
Jae-Hwan Kim
Keyword(s):  
Cross Sections ◽  
Shape Factor ◽  
Optimal Estimation ◽  
Ozone Monitoring Instrument ◽  
Thermally Induced ◽  
Monitoring Instrument ◽  
Spectral Fitting ◽  
Ozone Profile ◽  
Ozone Monitoring ◽  
Hartley Band

Abstract. We introduce a method that accounts for errors caused by the slit function in an optimal-estimation-based spectral fitting process to improve ozone profile retrievals from the Ozone Monitoring Instrument (OMI) ultraviolet measurements (270–330 nm). Previously, a slit function was parameterized as a standard Gaussian by fitting the full width at half maximum (FWHM) of the slit function from climatological OMI solar irradiances. This cannot account for the temporal variation in slit function in irradiance, the intra-orbit changes due to thermally induced change and scene inhomogeneity, and potential differences in the slit functions of irradiance and radiance measurements. As a result, radiance simulation errors may be induced due to convolving reference spectra with incorrect slit functions. To better represent the shape of the slit functions, we implement a more generic super Gaussian slit function with two free parameters (slit width and shape factor); it becomes standard Gaussian when the shape factor is fixed to be 2. The effects of errors in slit function parameters on radiance spectra, referred to as pseudo absorbers (PAs), are linearized by convolving high-resolution cross sections or simulated radiances with the partial derivatives of the slit function with respect to the slit parameters. The PAs are included in the spectral fitting scaled by fitting coefficients that are iteratively adjusted as elements of the state vector along with ozone and other fitting parameters. The fitting coefficients vary with cross-track and along-track pixels and show sensitivity to heterogeneous scenes. The PA spectrum is quite similar in the Hartley band below 310 nm for both standard and super Gaussians, but is more distinctly structured in the Huggins band above 310 nm with the use of super Gaussian slit functions. Finally, we demonstrate that some spikes of fitting residuals are slightly smoothed by accounting for the slit function errors. Comparisons with ozonesondes demonstrate noticeable improvements when using PAs for both standard and super Gaussians, especially for reducing the systematic biases in the tropics and midlatitudes (mean biases of tropospheric column ozone reduced from -1.4∼0.7 to 0.0∼0.4 DU) and reducing the standard deviations of tropospheric ozone column differences at high latitudes (by 1 DU for the super Gaussian). Including PAs also makes the retrievals consistent between standard and super Gaussians. This study corroborates the slit function differences between radiance and irradiance, demonstrating that it is important to account for such differences in the ozone profile retrievals.

scholarly journals Ozone profile retrievals from the Ozone Monitoring Instrument

2010 ◽  
Vol 10 (5) ◽  
pp. 2521-2537 ◽  
Author(s):  
X. Liu ◽  
P. K. Bhartia ◽  
K. Chance ◽  
R. J. D. Spurr ◽  
T. P. Kurosu
Keyword(s):  
Degrees Of Freedom ◽  
Optimal Estimation ◽  
Anthropogenic Pollution ◽  
Horizontal Resolution ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Profile ◽  
Ozone Monitoring ◽  
The Tropics ◽  
Middle Stratosphere

Abstract. Ozone profiles from the surface to about 60 km are retrieved from Ozone Monitoring Instrument (OMI) ultraviolet radiances using the optimal estimation technique. OMI provides daily ozone profiles for the entire sunlit portion of the earth at a horizontal resolution of 13 km×48 km for the nadir position. The retrieved profiles have sufficient accuracy in the troposphere to see ozone perturbations caused by convection, biomass burning and anthropogenic pollution, and to track their spatiotemporal transport. However, to achieve such accuracy it has been necessary to calibrate OMI radiances carefully (using two days of Aura/Microwave Limb Sounder data taken in the tropics). The retrieved profiles contain ~6–7 degrees of freedom for signal, with 5–7 in the stratosphere and 0–1.5 in the troposphere. Vertical resolution varies from 7–11 km in the stratosphere to 10–14 km in the troposphere. Retrieval precisions range from 1% in the middle stratosphere to 10% in the lower stratosphere and troposphere. Solution errors (i.e., root sum square of precisions and smoothing errors) vary from 1–6% in the middle stratosphere to 6–35% in the troposphere, and are dominated by smoothing errors. Total, stratospheric, and tropospheric ozone columns can be retrieved with solution errors typically in the few Dobson unit range at solar zenith angles less than 80°.

scholarly journals Characterization and correction of OMPS nadir mapper measurements for ozone profile retrievals

2017 ◽  
Vol 10 (11) ◽  
pp. 4373-4388 ◽  
Author(s):  
Juseon Bak ◽  
Xiong Liu ◽  
Jae-Hwan Kim ◽  
David P. Haffner ◽  
Kelly Chance ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Degrees Of Freedom ◽  
Optimal Estimation ◽  
Inversion Method ◽  
Radiometric Calibration ◽  
Ozone Monitoring Instrument ◽  
Noise Floor ◽  
Middle Latitudes ◽  
Ozone Profile ◽  
Cross Track

Abstract. This paper verifies and corrects the Ozone Mapping and Profiler Suite (OMPS) nadir mapper (NM) level 1B v2.0 measurements with the aim of producing accurate ozone profile retrievals using an optimal-estimation-based inversion method to fit measurements in the spectral range 302.5–340 nm. The evaluation of available slit functions demonstrates that preflight-measured slit functions represent OMPS measurements well compared to derived Gaussian slit functions. Our initial OMPS fitting residuals contain significant wavelength and cross-track-dependent biases, resulting in serious cross-track striping errors in the tropospheric ozone retrievals. To eliminate the systematic component of the fitting residuals, we apply soft calibration to OMPS radiances. With the soft calibration the amplitude of fitting residuals decreases from  ∼  1 to 0.2 % over low and middle latitudes, and thereby the consistency of tropospheric ozone retrievals between OMPS and the Ozone Monitoring Instrument (OMI) is substantially improved. A common mode correction is also implemented for additional radiometric calibration; it improves retrievals especially at high latitudes where the amplitude of fitting residuals decreases by a factor of  ∼  2. We estimate the noise floor error of OMPS measurements from standard deviations of the fitting residuals. The derived error in the Huggins band ( ∼  0.1 %) is twice the OMPS L1B measurement error. OMPS noise floor errors constrain our retrievals better, leading to improving information content of ozone and reducing fitting residuals. The final precision of the fitting residuals is less than 0.1 % in the low and middle latitudes, with  ∼  1 degrees of freedom for signal for the tropospheric ozone, meeting the general requirements for successful tropospheric ozone retrievals.

scholarly journals Evaluation of ozone profile and tropospheric ozone retrievals from GEMS and OMI spectra

2012 ◽  
Vol 5 (5) ◽  
pp. 6733-6762 ◽  
Author(s):  
J. Bak ◽  
J. H. Kim ◽  
X. Liu ◽  
K. Chance ◽  
J. Kim
Keyword(s):  
Spectral Resolution ◽  
Tropospheric Ozone ◽  
Degrees Of Freedom ◽  
Stratospheric Ozone ◽  
A Priori ◽  
Ozone Monitoring Instrument ◽  
Ozone Profile ◽  
Retrieval Errors ◽  
Standard Deviations ◽  
Column Ozone

Abstract. Korea is planning to launch the GEMS (Geostationary Environment Monitoring Spectrometer) instrument into a Geostationary (GEO) platform in 2018 to monitor tropospheric air pollutants on an hourly basis over East Asia. GEMS will measure backscattered UV radiances covering the 300–500 nm wavelength range with a spectral resolution of 0.6 nm. The main objective of this study is to evaluate ozone profiles and stratospheric column ozone amounts retrieved from simulated GEMS measurements. Ozone Monitoring Instrument (OMI) Level 1B radiances, which have the spectral range 270–500 nm at spectral resolution of 0.42–0.63 nm, are used to simulate the GEMS radiances. An optimal estimation-based ozone profile algorithm is used to retrieve ozone profiles from simulated GEMS radiances. Firstly, we compare the retrieval characteristics (including averaging kernels, degrees of freedom for signal, and retrieval error) derived from the 270–330 nm (OMI) and 300–330 nm (GEMS) wavelength ranges. This comparison shows that the effect of not using measurements below 300 nm on tropospheric ozone retrievals is insignificant. However, the stratospheric ozone information decreases greatly from OMI to GEMS, by a factor of ∼2. The number of the independent pieces of information available from GEMS measurements is estimated to 3 on average in the stratosphere, with associated retrieval errors of ∼1% in stratospheric column ozone. The difference between OMI and GEMS retrieval characteristics is apparent for retrieving ozone layers above ∼20 km, with a reduction in the sensitivity and an increase in the retrieval errors for GEMS. We further investigate whether GEMS can resolve the stratospheric ozone variation observed from high vertical resolution EOS Microwave Limb Sounder (MLS). The differences in stratospheric ozone profiles between GEMS and MLS are comparable to those between OMI and MLS above ∼3 hPa (∼40 km) except with slightly larger biases and larger standard deviations by up to 5%. At pressure altitudes above ∼3 hPa, GEMS retrievals show strong influence of a priori and large differences with MLS, which, however, can be sufficiently improved by using better a priori information. The GEMS-MLS differences show negative biases of less than 4% for stratospheric column ozone, with standard deviations of 1–3%, while OMI retrievals show similar agreements with MLS except for 1% smaller biases at mid and high latitudes. Based on the comparisons, we conclude that GEMS will measure tropospheric ozone and stratospheric ozone columns with accuracy comparable to that of OMI and ozone profiles with slightly worse performance than that of OMI below ∼3 hPa.

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

2015 ◽  
Vol 15 (2) ◽  
pp. 667-683 ◽  
Author(s):  
J. Bak ◽  
X. Liu ◽  
J. H. Kim ◽  
K. Chance ◽  
D. P. Haffner
Keyword(s):  
Total Ozone ◽  
A Priori ◽  
Optimal Estimation ◽  
Optical Absorption Spectroscopy ◽  
Ozone Monitoring Instrument ◽  
Total Column Ozone ◽  
Cloud Parameters ◽  
Ozone Profile ◽  
The Stability ◽  
Cloud Parameter

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.

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