Ozone monitoring instrument calibration

Dobber, Marcel; Dirksen, Ruud; Levelt, P. F.; Oord, G. H. J. van den; Voors, Robert; Kleipool, Q.; Jaross, Glen; Kowalewski, M. G.; Hilsenrath, E.; Leppelmeier, G. W.; Vries, J. de; Dierssen, Werner; Rozemeijer, Nico

doi:10.1109/tgrs.2006.869987

Cited by 158 publications

(159 citation statements)

References 12 publications

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“…We assess the wavelength dependence of the shifts by splitting the entire fitting window into multiple overlapping micro-window segments and evaluating the RR spectrum amplitudes and wavelength adjustments for each segment. To account for the RR line-filling patterns, we use a linear combination of the atmospheric (Joiner et al, 1995) and the liquid-water (Vasilkov, 2002) RR spectra, convolved with the wavelength-and crosstrack-dependent OMI spectral transfer function (Dobber et al, 2006). Other steps in the algorithm include the estimation of, and correction for, spectral under-sampling patterns (Chance et al, 2005) and aggressive suppression of instrumental noise.…”

Section: New Scd Retrievalmentioning

confidence: 99%

The version 3 OMI NO<sub>2</sub> standard product

et al. 2017

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Abstract. We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO 2 ) products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc. gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO 2 slant column density (SCD) retrieval and (2) higherresolution (1 • latitude and 1.25 • longitude) a priori NO 2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry-transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by ∼ 10-40 %) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO 2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite-and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots.

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Section: New Scd Retrievalmentioning

confidence: 99%

The version 3 OMI NO<sub>2</sub> standard product

et al. 2017

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“…The TOMS algorithm uses ozone crosssection data based on Bass and Paur (1985). OMTO3 total ozone measurements largely rely on OMI's pre-launch radiometric calibration at nadir described by Dobber et al (2006) and validated by Jaross and Warner (2008). Small residual errors in the collection 3 radiances (Dobber et al, 2008) are further reduced using soft-calibration techniques where biases and irregularities that vary with viewing angle and wave- Table 2.…”

Section: Ozone Monitoring Instrument (Omi) and Omi Ozone Algorithmsmentioning

confidence: 99%

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

et al. 2015

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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 KOEBrewer 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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“…High-resolution (0.01 nm) ozone cross sections (Brion et al, 1993) were used in the simulation, which had been found to significantly reduce fitting residuals in the Huggins band compared to other cross sections . The simulated high spectral resolution radiances and Jacobians were convolved with the OMI instrument slit function, which was computed using the hyper-parameterization parameters obtained during the onground calibration measurements (Dobber et al, 2006). To account for the temperature dependence of ozone absorption, we used temperature profiles from TES Version 4 products.…”

Section: Radiative Transfer Calculation For the Uvmentioning

confidence: 99%

Characterization of ozone profiles derived from Aura TES and OMI radiances

Worden

Liu

et al. 2013

Atmos. Chem. Phys.

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We present satellite based ozone profile estimates derived by combining radiances measured at thermal infrared (TIR) wavelengths from the Aura Tropospheric Emission Spectrometer (TES) and ultraviolet (UV) wavelengths measured by the Aura Ozone Monitoring Instrument (OMI). The advantage of using these combined wavelengths and instruments for sounding ozone over either instrument alone is improved sensitivity near the surface as well as the capability to consistently resolve the lower troposphere, upper troposphere, and lower stratosphere for scenes with varying geophysical states. For example, the vertical resolution of ozone estimates from either TES or OMI varies strongly by surface albedo and temperature. Typically, TES provides 1.6 degrees of freedom for signal (DOFS) and OMI provides less than 1 DOFS in the troposphere. The combination provides 2 DOFS in the troposphere with approximately 0.4 DOFS for near surface ozone (surface to 700 hPa). We evaluated these new ozone profile estimates with ozonesonde measurements and found that calculated errors for the joint TES and OMI ozone profile estimates are in reasonable agreement with actual errors as derived by the root-mean-square (RMS) difference between the ozonesondes and the joint TES/OMI ozone estimates. We also used a common a priori profile in the retrievals in order to evaluate the capability of different retrieval approaches on capturing near-surface ozone variability. We found that the vertical resolution of the joint TES/OMI ozone profile estimates shows significant improvements on quantifying variations in near-surface ozone with RMS differences of 49.9% and correlation coefficient of R = 0.58 for the TES/OMI near-surface estimates as compared to 67.2% RMS difference and R = 0.33 for TES and 115.8% RMS difference and R = 0.09 for OMI. This comparison removes the impacts of using the climatological a priori in the retrievals. However, it results in artificially large sonde/retrieval differences. The TES/OMI ozone profiles from the production code of joint retrievals will use climatological a priori and therefore will have more realistic ozone estimates than those from using a common a priori volume mixing ratio profile

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Ozone monitoring instrument calibration

Cited by 158 publications

References 12 publications

The version 3 OMI NO<sub>2</sub> standard product

The version 3 OMI NO<sub>2</sub> standard product

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

Characterization of ozone profiles derived from Aura TES and OMI radiances

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Ozone monitoring instrument calibration

Cited by 158 publications

References 12 publications

The version 3 OMI NO&lt;sub&gt;2&lt;/sub&gt; standard product

The version 3 OMI NO&lt;sub&gt;2&lt;/sub&gt; standard product

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

Characterization of ozone profiles derived from Aura TES and OMI radiances

Contact Info

Product

Resources

About

The version 3 OMI NO<sub>2</sub> standard product

The version 3 OMI NO<sub>2</sub> standard product