scholarly journals Validation of 10-year SAO OMI Ozone Profile (PROFOZ) Product Using Ozonesonde Observations

2017 ◽  
Author(s):  
Guanyu Huang ◽  
Xiong Liu ◽  
Kelly Chance ◽  
Kai Yang ◽  
Pawan K. Bhartia ◽  
...  

Abstract. We validate the Ozone Monitoring Instrument (OMI) ozone-profile (PROFOZ) product from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against ozonesonde observations. We also evaluate the effects of OMI Row anomaly (RA) on the retrieval by dividing the data set into before and after the occurrence of serious OMI RA, i.e., pre-RA (2004–2008) and post-RA (2009–2014). The retrieval shows good agreement with ozonesondes in the tropics and mid-latitudes and for pressure

2010 ◽  
Vol 10 (5) ◽  
pp. 2521-2537 ◽  
Author(s):  
X. Liu ◽  
P. K. Bhartia ◽  
K. Chance ◽  
R. J. D. Spurr ◽  
T. P. Kurosu

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°.


2009 ◽  
Vol 9 (5) ◽  
pp. 22693-22738 ◽  
Author(s):  
X. Liu ◽  
P. K. Bhartia ◽  
K. Chance ◽  
R. J. D. Spurr ◽  
T. P. Kurosu

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° 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°.


2015 ◽  
Vol 8 (5) ◽  
pp. 4817-4858
Author(s):  
J. Jia ◽  
A. Rozanov ◽  
A. Ladstätter-Weißenmayer ◽  
J. P. Burrows

Abstract. In this manuscript, the latest SCIAMACHY limb ozone scientific vertical profiles, namely the current V2.9 and the upcoming V3.0, are extensively compared with ozone sonde data from the WOUDC database. The comparisons are made on a global scale from 2003 to 2011, involving 61 sonde stations. The retrieval processors used to generate V2.9 and V3.0 data sets are briefly introduced. The comparisons are discussed in terms of vertical profiles and stratospheric partial columns. Our results indicate that the V2.9 ozone profile data between 20–30 km is in good agreement with ground based measurements with less than 5% relative differences in the latitude range of 90° S–40° N (with exception of the tropical Pacific region where an overestimation of more than 10% is observed), which corresponds to less than 5 DU partial column differences. In the tropics the differences are within 3%. However, this data set shows a significant underestimation northwards of 40° N (up to ~15%). The newly developed V3.0 data set reduces this bias to below 10% while maintaining a good agreement southwards of 40° N with slightly increased relative differences of up to 5% in the tropics.


2019 ◽  
Vol 12 (7) ◽  
pp. 3777-3788 ◽  
Author(s):  
Juseon Bak ◽  
Xiong Liu ◽  
Kang Sun ◽  
Kelly Chance ◽  
Jae-Hwan Kim

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.


2018 ◽  
Vol 11 (1) ◽  
pp. 17-32 ◽  
Author(s):  
Guanyu Huang ◽  
Xiong Liu ◽  
Kelly Chance ◽  
Kai Yang ◽  
Zhaonan Cai

Abstract. We validate the Ozone Monitoring Instrument (OMI) ozone profile (PROFOZ v0.9.3) product including ozone profiles between 0.22 and 261 hPa and stratospheric ozone columns (SOCs) down to 100, 215, and 261 hPa from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against the latest Microwave Limb Sound (MLS) v4.2x data. We also evaluate the effects of OMI row anomaly (RA) on the retrieval by dividing the data set into before and after the occurrence of serious RA, i.e., pre-RA (2004–2008) and post-RA (2009–2014). During the pre-RA period, OMI ozone profiles agree very well with MLS data. After applying OMI averaging kernels to MLS data, the global mean biases (MBs) are within 3 % between 0.22 and 100 hPa, negative biases are within 3–9 % for lower layers, and the standard deviations (SDs) are 3.5–5 % from 1 to 40 hPa, 6–10 % for upper layers, and 5–20 % for lower layers. OMI shows biases dependent on latitude and solar zenith angle (SZA), but MBs and SDs are mostly within 10 % except for low and high altitudes of high latitudes and SZAs. Compared to the retrievals during the pre-RA period, OMI retrievals during the post-RA period degrade slightly between 5 and 261 hPa with MBs and SDs typically larger by 2–5 %, and degrade much more for pressure less than ∼ 5 hPa, with larger MBs by up to 8 % and SDs by up to 15 %, where the MBs are larger by 10–15 % south of 40∘ N due to the blockage effect of RA and smaller by 15–20 % north of 40∘ N due to the solar contamination effect of RA. The much worse comparisons at high altitudes indicate the UV1 channel of pixels that are not flagged as RA is still affected by the RA. During the pre-RA period, OMI SOCs show very good agreement with MLS data with global mean MBs within 0.6 % and SDs of 1.9 % for SOCs down to 215 and 261 hPa and of 2.30 % for SOC down to 100 hPa. Despite clearly worse ozone profile comparisons during the post-RA period, OMI SOCs only slightly degrade, with SDs larger by 0.4–0.6 % mostly due to looser spatial coincidence criteria as a result of missing data from RA and MBs larger by 0.4–0.7 %. Our retrieval comparisons indicate significant bias trends, especially during the post-RA period. The spatiotemporal variation of our retrieval performance suggests the need to improve OMI's radiometric calibration to maintain the long-term stability and spatial consistency of the PROFOZ product.


2020 ◽  
Author(s):  
Nick Gorkavyi ◽  
Zachary Fasnacht ◽  
David Haffner ◽  
Sergey Marchenko ◽  
Joanna Joiner ◽  
...  

Abstract. Non-linear effects, such as from saturation, stray light, or obstruction of light, negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra and downstream retrievals of atmospheric and surface properties derived from these spectra. In addition, excessive noise such as from cosmic ray impacts, prevalent within the South Atlantic Anomaly, can also degrade satellite radiance measurements. Saturation specifically pertains to observations of very bright surfaces such as sun glint over water surfaces or thick clouds. Related residual electronic cross-talk or blooming effects may occur in spatial pixels adjacent to a saturated area. Obstruction of light can occur within the zones of solar eclipses as well as from material located outside of the satellite instrument. The latter may also produce unintended scattered light into a satellite instrument. When these effects cannot be corrected to an acceptable level for science quality retrievals, it is desirable to flag the affected pixels. Here, we introduce a new detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm-spectral range; our Decorrelation Index (DI for brevity) is simply defined as DI=1−r. DI increases with non-linear effects or excessive noise in either radiances (the most likely cause in OMI data) or irradiances. DI is relatively straight-forward to use and interpret and can be computed for different wavelength intervals. We developed a set of DIs for two spectral channels of the Ozone Monitoring Instrument (OMI), a hyperspectral pushbroom imaging spectrometer. For each OMI spatial measurement, we define 14 wavelength-dependent DIs within the OMI visible channel (350–498 nm) and 6 DIs in its ultraviolet 2 (UV2) channel (310–370 nm). As defined, DIs reflect a continuous range of deviations of observed spectra from the reference irradiance spectrum that are complementary to the binary Saturation Possibility Warning (SPW) flags currently provided for each individual spectral/spatial pixels in the OMI radiance data set. Smaller values of DI are also caused by a number of geophysical factors; this allows one to obtain interesting physical results on the global distribution of spectral variations.


2021 ◽  
Vol 14 (2) ◽  
pp. 961-974
Author(s):  
Nick Gorkavyi ◽  
Zachary Fasnacht ◽  
David Haffner ◽  
Sergey Marchenko ◽  
Joanna Joiner ◽  
...  

Abstract. Various instrumental or geophysical artifacts, such as saturation, stray light or obstruction of light (either coming from the instrument or related to solar eclipses), negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra and downstream retrievals of atmospheric and surface properties derived from these spectra. In addition, excessive noise such as from cosmic-ray impacts, prevalent within the South Atlantic Anomaly, can also degrade satellite radiance measurements. Saturation specifically pertains to observations of very bright surfaces such as sunglint over open water or thick clouds. When saturation occurs, additional photoelectric charge generated at the saturated pixel may overflow to pixels adjacent to a saturated area and be reflected as a distorted image in the final sensor output. When these effects cannot be corrected to an acceptable level for science-quality retrievals, flagging of the affected pixels is indicated. Here, we introduce a straightforward detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm spectral range; our decorrelation index (DI for brevity) is simply defined as a DI of 1−r. DI increases with anomalous additive effects or excessive noise in either radiances, the most likely cause in data from the Ozone Monitoring Instrument (OMI), or irradiances. DI is relatively straightforward to use and interpret and can be computed for different wavelength intervals. We developed a set of DIs for two spectral channels of the OMI, a hyperspectral pushbroom imaging spectrometer. For each OMI spatial measurement, we define 14 wavelength-dependent DIs within the OMI visible channel (350–498 nm) and six DIs in its ultraviolet 2 (UV2) channel (310–370 nm). As defined, DIs reflect a continuous range of deviations of observed spectra from the reference irradiance spectrum that are complementary to the binary saturation possibility warning (SPW) flags currently provided for each individual spectral or spatial pixel in the OMI radiance data set. Smaller values of DI are also caused by a number of geophysical factors; this allows one to obtain interesting physical results on the global distribution of spectral variations.


2017 ◽  
Author(s):  
Guanyu Huang ◽  
Xiong Liu ◽  
Kelly Chance ◽  
Kai Yang ◽  
Zhaonan Cai

Abstract. We validate the Ozone Monitoring Instrument (OMI) ozone profile (PROFOZ) product including ozone profiles between 0.22–261 hPa and Stratospheric Ozone Columns (SOCs) down to 100, 215, and 261 hPa from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against the latest Microwave Limb Sound (MLS) v4.2x data. We also evaluate the effects of OMI row anomaly (RA) on the retrieval by dividing the data set into before and after the occurrence of serious RA, i.e., pre-RA (2004–2008) and post-RA (2009–2014). During the pre-RA period, OMI ozone profiles agree very well with MLS data. Tthe global mean biases (MBs) are within 3 % between 0.22–100 hPa and negative 3–9 % for lower layers, and the standard deviations (SDs) are 3.5–5 % from 1–40 hPa, 6–10 % for upper layers and 5–20% for lower layers, after applying OMI averaging kernels to MLS data. OMI shows latitude and solar zenith angle (SZA) dependent biases, but MBs and SDs are mostly within 10 % except for low/high altitudes of high latitudes/SZAs. During the post-RA period, OMI retrievals degrade slightly between 5–261 hPa with MBs and SDs typically larger by 2–5%, and degrade much more, with larger MBs by up to 8 % and SDs by up to 15% for pressure less than ~ 5 hPa, where the MBs are larger by 10–15 % south of 40 °N due to the blockage effect of RA and smaller by 15–20 % north of 40 °N due to the solar contamination effect of RA. The much worse comparison at high altitudes indicates the UV-1 channel of pixels that are not flagged as RA is still affected by the RA. During the pre-RA period, OMI SOCs show very good agreement with MLS data with global mean MBs within 0.6 % and SDs of 1.9 % for SOCs down to 215 and 261 hPa and of 2.30 % for SOC down to 100 hPa. Despite clearly worse ozone profile comparison during the post-RA period, OMI SOCs only slightly degrade, with SDs larger by 0.4–0.6 % mostly due to looser spatial coincidence criterion as a result of missing data from RA and MBs larger by 0.4–0.7 %. The retrieval comparison indicates significant bias trends, especially during the post-RA period. The spatiotemporal variation of the retrieval performance suggests the need to improve OMI’s radiometric calibration to maintain the long-term stability and spatial consistency of the PROFOZ product. The good comparison with SOC down to 261 hPa supports that MLS ozone at 261 hPa, recommended for further evaluation by the MLS team, is suitable for scientific use.


2020 ◽  
Author(s):  
Colin Seftor ◽  
Glen Jaross ◽  
Leslie Moy ◽  
Natalya Kramarova ◽  
Eun-su Yang

<p>Measured sun-normalized radiances (S-NRs) from both the Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) and Nadir Profiler (NP) on the Suomi National Polar-orbiting Partnership (SNPP) satellite have been validated to the 2% level through, in part, comparisons with radiative transfer code calculations using co-located ozone profile retrievals inputs from the Microwave Limb Sounder (MLS) on the Aura satellite. To minimize the effects of clouds and aerosols, only low reflectivity and low aerosol scenes were used. We will describe the details of the comparison technique, including how low reflectivity / low aerosol scenes were determined.  We will also show results where we extend our study to compare measured S-NRs from the OMPS nadir sensors with those from both the Ozone Monitoring Instrument (OMI) on Aura sensor and, if available, the Version 2 dataset from the TROPOMI sensor on the Sentinel 5 Precursor (S5P) satellite.</p>


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