261 research outputs found
How big is an OMI pixel?
No full textThe Ozone Monitoring Instrument
(OMI) is a push-broom imaging spectrometer, observing solar radiation
backscattered by the Earth's atmosphere and surface. The incoming radiation
is detected using a static imaging CCD (charge-coupled device) detector array with no moving parts,
as opposed to most of the previous satellite spectrometers, which used a
moving mirror to scan the Earth in the across-track direction. The field of
view (FoV) of detector pixels is the solid angle from which radiation is
observed, averaged over the integration time of a measurement. The OMI FoV is
not quadrangular, which is common for scanning instruments, but rather
super-Gaussian shaped and overlapping with the FoV of neighbouring pixels.
This has consequences for pixel-area-dependent applications, like cloud
fraction products, and visualisation.The shapes and sizes of OMI FoVs were determined pre-flight by
theoretical and experimental tests but never verified after launch.
In this paper the OMI FoV is characterised using collocated MODerate
resolution Imaging Spectroradiometer (MODIS) reflectance measurements.
MODIS measurements have a much higher spatial resolution than OMI
measurements and spectrally overlap at 469 nm. The OMI FoV was
verified by finding the highest correlation between MODIS and OMI
reflectances in cloud-free scenes, assuming a 2-D super-Gaussian
function with varying size and shape to represent the OMI FoV. Our
results show that the OMPIXCOR product 75FoV corner coordinates
are accurate as the full width at half maximum (FWHM) of a
super-Gaussian FoV model when this function is assumed. The softness
of the function edges, modelled by the super-Gaussian exponents, is
different in both directions and is view angle dependent.The optimal overlap function between OMI and MODIS reflectances is
scene dependent and highly dependent on time differences between
overpasses, especially with clouds in the scene. For partially clouded
scenes, the optimal overlap function was represented by super-Gaussian
exponents around 1 or smaller, which indicates that this function is
unsuitable to represent the overlap sensitivity function in these
cases. This was especially true for scenes before 2008, when the time
differences between Aqua and Aura overpasses was about 15 min,
instead of 8 min after 2008. During the time between overpasses,
clouds change the scene reflectance, reducing the correlation and
influencing the shape of the optimal overlap function
Retrievals of tropospheric ozone profiles from the synergism of AIRS and OMI: Methodology and validation
No full textThe Tropospheric Emission Spectrometer (TES) on the A-Train Aura satellite was designed to profile tropospheric ozone and its precursors, taking measurements from 2004 to 2018. Starting in 2008, TES global sampling of tropospheric ozone was gradually reduced in latitude, with global coverage stopping in 2011. To extend the record of TES, this work presents a multispectral approach that will provide O3 data products with vertical resolution and measurement error similar to TES by combining the single-footprint thermal infrared (TIR) hyperspectral radiances from the Aqua Atmospheric Infrared Sounder (AIRS) instrument and the ultraviolet (UV) channels from the Aura Ozone Monitoring Instrument (OMI). The joint AIRS+OMI O3 retrievals are processed through the MUlti-SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) retrieval algorithm. Comparisons of collocated joint AIRS+OMI and TES to ozonesonde measurements show that both systems have similar errors, with mean and standard deviation of the differences well within the estimated measurement error. AIRS+OMI and TES have slightly different biases (within 5 parts per billion) vs. the sondes. Both AIRS and OMI have wide swath widths ( ĝ1/4 1650 km for AIRS; ĝ1/4 2600 km for OMI) across satellite ground tracks. Consequently, the joint AIRS+OMI measurements have the potential to maintain TES vertical sensitivity while increasing coverage by 2 orders of magnitude, thus providing an unprecedented new data set with which to quantify the evolution of tropospheric ozone.Atmospheric Remote Sensin
Validation of 10-year SAO OMI ozone profile (PROFOZ) product using Aura MLS measurements
No full textWe 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 profile 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 presure 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 produc
An Evaluation of the Ability of the Ozone Monitoring Instrument (OMI) to Observe Boundary Layer Ozone Pollution across China: Application to 2005- 2017 Ozone Trends
No full textNadir-viewing satellite observations of tropospheric ozone in the UV have been shown to have some sensitivity to boundary layer ozone pollution episodes, but so far they have not yet been compared to surface ozone observations collected by large-scale monitoring networks. Here we use 2013�2017 surface ozone data from China�s new Ministry of Ecology and Environment (MEE) network of ? 1000 sites, together with vertical profiles from ozonesondes and aircraft, to quantify the ability of tropospheric ozone retrievals from the Ozone Monitoring Instrument (OMI) and to detect boundary layer ozone pollution in China. We focus on summer when ozone pollution in China is most severe and when OMI has the strongest sensitivity. After subtracting the Pacific background, we find that the 2013�2017 mean OMI ozone enhancements over eastern China have strong spatial correlation with the corresponding multiyear means in the surface afternoon observations (R = 0.73), and that OMI can estimate these multiyear means in summer afternoon surface ozone with a precision of 8 ppb. The OMI data show significantly higher values on observed surface ozone episode days (> 82 ppb) than on non-episode days. Day-to-day correlations with surface ozone are much weaker due to OMI noise and are stronger for sites in southern China (<34? N;R = 0.3�0.6) than in northern China (R = 0.1�0.3) becauseof weaker retrieval sensitivity and larger upper tropospheric variability in the north. Ozonesonde data show that much of the variability of OMI ozone over southern China in summer is driven by the boundary layer. Comparison of 2005�2009 and 2013�2017 OMI data indicates that mean summer afternoon surface ozone in southern China (including urban and rural regions) has increased by 3.5 � 3.0 ppb over the 8-year period and that the number of episode days per summer has increased by 2.2�0.4 (as diagnosed by an extreme value model), generally consistent with the few long-term surface records. Ozone increases have been particularly large in the Yangtze River Delta and in the Hubei, Guangxi and Hainan provinces
Observation of slant column NO2 using the super-zoom mode of AURA-OMI
No full textWe retrieve slant column NO2 from the superzoom mode of the Ozone Monitoring Instrument (OMI) to explore its utility for understanding NOx emissions and variability. Slant column NO2 is operationally retrieved from OMI (Boersma et al., 2007; Bucsela et al., 2006) with a nadir footprint of 13×24 km2, the result of averaging eight detector elements on board the instrument. For 85 orbits in late 2004, OMI reported observations from individual “superzoom” detector elements (spaced at 13×3 km2 at nadir). We assess the spatial response of these individual detector elements in-flight and determine an upper-bound on spatial resolution of 9 km, in good agreement with on-ground calibration (7 km FWHM). We determine the precision of the super-zoom mode to be 2.1×10^15 molecules cm?2, approximately a factor of ?8 lower than an identical retrieval at operational scale as expected if random noise dominates the uncertainty. We retrieve slant column NO2 over the Satpura power plant in India; Seoul, South Korea; Dubai, United Arab Emirates; and a set of large point sources on the Rihand Reservoir in India using differential optical absorption spectroscopy (DOAS). Over these sources, the super-zoom mode of OMI observes variation in slant column NO2 of up to 30 × the instrumental precision within one operational footprint.Delft University of Technolog
S5P TROPOMI NO2 slant column retrieval: Method, stability, uncertainties and comparisons with OMI
No full textThe Tropospheric Monitoring Instrument (TROPOMI), aboard the Sentinel-5 Precursor (S5P) satellite, launched on 13 October 2017, provides measurements of atmospheric trace gases and of cloud and aerosol properties at an unprecedented spatial resolution of approximately 7 × 3:5 km2 (approx. 5:5 × 3:5 km2 as of 6 August 2019), achieving near-global coverage in 1 d. The retrieval of nitrogen dioxide (NO2) concentrations is a three-step procedure: slant column density (SCD) retrieval, separation of the SCD in its stratospheric and tropospheric components, and conversion of these into vertical column densities. This study focusses on the TROPOMI NO2 SCD retrieval: the retrieval method used, the stability of the SCDs and the SCD uncertainties, and a comparison with the Ozone Monitoring Instrument (OMI) NO2 SCDs. The statistical uncertainty, based on the spatial variability of the SCDs over a remote Pacific Ocean sector, is 8.63 μmol m-2 for all pixels (9.45 μmol m-2 for clear-sky pixels), which is very stable over time and some 30 % less than the long-term average over OMI-QA4ECV data (since the pixel size reduction TROPOMI uncertainties are ~ 8 % larger). The SCD uncertainty reported by the differential optical absorption spectroscopy (DOAS) fit is about 10 % larger than the statistical uncertainty, while for OMI-QA4ECV the DOAS uncertainty is some 20 % larger than its statistical uncertainty. Comparison of the SCDs themselves over the Pacific Ocean, averaged over 1 month, shows that TROPOMI is about 5 % higher than OMI-QA4ECV, which seems to be due mainly to the use of the so-called intensity offset correction in OMI-QA4ECV but not in TROPOMI: turning that correction off means about 5 % higher SCDs. The row-torow variation in the SCDs of TROPOMI, the "stripe amplitude", is 2.15 μmol m, while for OMI-QA4ECV it is a factor of ~ 2 (~ 5) larger in 2005 (2018); still, a so-called stripe correction of this non-physical across-track variation is useful for TROPOMI data. In short, TROPOMI shows a superior performance compared with OMI-QA4ECV and operates as anticipated from instrument specifications. The TROPOMI data used in this study cover 30 April 2018 up to 31 January 2020.Atmospheric Remote Sensin
Impact of aerosols on the OMI tropospheric NO2 retrievals over industrialized regions: how accurate is the aerosol correction of cloud-free scenes via a simple cloud model?
No full textThe Ozone Monitoring Instrument (OMI) has provided daily global measurements of tropospheric NO2 for more than a decade. Numerous studies have drawn attention to the complexities related to measurements of tropospheric NO2 in the presence of aerosols. Fine particles affect the OMI spectral measurements and the length of the average light path followed by the photons. However, they are not explicitly taken into account in the current operational OMI tropospheric NO2 retrieval chain (DOMINO – Derivation of OMI tropospheric NO2) product. Instead, the operational OMI O2 − O2 cloud retrieval algorithm is applied both to cloudy and to cloud-free scenes (i.e. clear sky) dominated by the presence of aerosols. This paper describes in detail the complex interplay between the spectral effects of aerosols in the satellite observation and the associated response of the OMI O2 − O2 cloud retrieval algorithm. Then, it evaluates the impact on the accuracy of the tropospheric NO2 retrievals through the computed Air Mass Factor (AMF) with a focus on cloud-free scenes. For that purpose, collocated OMI NO2 and MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua aerosol products are analysed over the strongly industrialized East China area. In addition, aerosol effects on the tropospheric NO2 AMF and the retrieval of OMI cloud parameters are simulated. Both the observation-based and the simulation-based approach demonstrate that the retrieved cloud fraction increases with increasing Aerosol Optical Thickness (AOT), but the magnitude of this increase depends on the aerosol properties and surface albedo. This increase is induced by the additional scattering effects of aerosols which enhance the scene brightness. The decreasing effective cloud pressure with increasing AOT primarily represents the shielding effects of the O2 − O2 column located below the aerosol layers. The study cases show that the aerosol correction based on the implemented OMI cloud model results in biases between −20 and −40 % for the DOMINO tropospheric NO2 product in cases of high aerosol pollution (AOT ≥ 0.6) at elevated altitude. These biases result from a combination of the cloud model error, used in the presence of aerosols, and the limitations of the current OMI cloud Look-Up-Table (LUT). A new LUT with a higher sampling must be designed to remove the complex behaviour between these biases and AOT. In contrast, when aerosols are relatively close to the surface or mixed with NO2, aerosol correction based on the cloud model results in an overestimation of the DOMINO tropospheric NO2 column, between 10 and 20 %. These numbers are in line with comparison studies between ground-based and OMI tropospheric NO2 measurements in the presence of high aerosol pollution and particles located at higher altitudes. This highlights the need to implement an improved aerosol correction in the computation of tropospheric NO2 AMFs
Impact of aerosols on the OMI tropospheric NO2 retrievals over industrialized regions: How accurate is the aerosol correction of cloud-free scenes via a simple cloud model? (discussion paper)
No full textThe Ozone Monitoring Instrument (OMI) instrument has provided daily global measurements of tropospheric NO2 for more than a decade. Numerous studies have drawn attention to the complexities related to measurements of tropospheric NO2 in the presence of aerosols. Fine particles affect the OMI spectral measurements and the length of the average light path followed by the photons. However, they are not explicitly taken into account in the current OMI tropospheric NO2 retrieval chain. Instead, the operational OMI O2-O2 cloud retrieval algorithm is applied both to cloudy scenes and to cloud free scenes with aerosols present. This paper describes in detail the complex interplay between the spectral effects of aerosols, the OMI O2-O2 cloud retrieval algorithm and the impact on the accuracy of the tropospheric NO2 retrievals through the computed Air Mass Factor (AMF) over cloud-free scenes. Collocated OMI NO2 and MODIS Aqua aerosol products are analysed over East China, in industrialized area. In addition, aerosol effects on the tropospheric NO2 AMF and the retrieval of OMI cloud parameters are simulated. Both the observation-based and the simulation-based approach demonstrate that the retrieved cloud fraction linearly increases with increasing Aerosol Optical Thickness (AOT), but the magnitude of this increase depends on the aerosol properties and surface albedo. This increase is induced by the additional scattering effects of aerosols which enhance the scene brightness. The decreasing effective cloud pressure with increasing AOT represents primarily the absorbing effects of aerosols. The study cases show that the actual aerosol correction based on the implemented OMI cloud model results in biases between ?20 and ?40 % for the DOMINO tropospheric NO2 product in cases of high aerosol pollution (AOT ? 0.6) and elevated particles. On the contrary, when aerosols are relatively close to the surface or mixed with NO2, aerosol correction based on the cloud model results in overestimation of the DOMINO tropospheric NO2 product, between 10 and 20 %. These numbers are in line with comparison studies between ground-based and OMI tropospheric NO2 measurements under conditions with high aerosol pollution and elevated particles. This highlights the need to implement an improved aerosol correction in the computation of tropospheric NO2 AMFs.Geoscience & Remote SensingCivil Engineering and Geoscience
Aura OMI Observations of Regional SO2 and NO2 Pollution Changes from 2005 to 2015
No full textThe Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite has been providing global observations of the ozone layer and key atmospheric pollutant gases, such as nitrogen dioxide (NO2) and sulfur dioxide (SO2), since October 2004. The data products from the same instrument provide consistent spatial and temporal coverage and permit the study of anthropogenic and natural emissions on local-to-global scales. In this paper, we examine changes in SO2 and NO2 over some of the world's most polluted industrialized regions during the first decade of OMI observations. In terms of regional pollution changes, we see both upward and downward trends, sometimes in opposite directions for NO2 and SO2, for different study areas. The trends are, for the most part, associated with economic and/or technological changes in energy use, as well as regional regulatory policies. Over the eastern US, both NO2 and SO2 levels decreased dramatically from 2005 to 2015, by more than 40 and 80 percent, respectively, as a result of both technological improvements and stricter regulations of emissions. OMI confirmed large reductions in SO2 over eastern Europe's largest coal-fired power plants after installation of flue gas desulfurization devices. The North China Plain has the world's most severe SO2 pollution, but a decreasing trend has been observed since 2011, with about a 50 percent reduction in 2012-2015, due to an economic slowdown and government efforts to restrain emissions from the power and industrial sectors. In contrast, India's SO2 and NO2 levels from coal power plants and smelters are growing at a fast pace, increasing by more than 100 and 50 percent, respectively, from 2005 to 2015. Several SO2 hot spots observed over the Persian Gulf are probably related to oil and gas operations and indicate a possible underestimation of emissions from these sources in bottom-up emission inventories. Overall, OMI observations have proved valuable in documenting rapid changes in air quality over different parts of the world during last decade. The baseline established during the first 11 years of OMI is indispensable for the interpretation of air quality measurements from current and future satellite atmospheric composition missions
OMI tropospheric NO2 profiles from cloud slicing: Constraints on surface emissions, convective transport and lightning NOx
No full textWe derive annual and seasonal global climatologies of tropospheric NO2 profiles from OMI cloudy observations for the year 2006 using the cloud-slicing method on six pressure levels centered at about 280, 380, 500, 620, 720 and 820 hPa. A comparison between OMI and the TM4 model tropospheric NO2 profiles reveals striking overall similarities, which confer great confidence to the cloud-slicing approach to provide details that pertain to annual as well as seasonal means, along with localized discrepancies that seem to probe into particular model processes. Anomalies detected at the lowest levels can be traced to deficiencies in the model surface emission inventory, at mid-tropospheric levels to convective transport and horizontal advective diffusion, and at the upper tropospheric levels to model lightning NOx production and the placement of deeply transported NO2 plumes such as from the Asian summer monsoon. The vertical information contained in the OMI cloud-sliced NO2 profiles provides a global observational constraint that can be used to evaluate chemistry transport models (CTMs) and guide the development of key parameterization schemes.Geoscience & Remote SensingCivil Engineering and Geoscience
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