A cloud-ozone data product from Aura OMI and MLS satellite measurements

Ziemke, J. R.; Strode, Sarah A.; Douglass, Anne R.; Joiner, Joanna; Vasilkov, A. P.; Oman, Luke D.; Liu, Junhua; Strahan, S. E.; Bhartia, P. K.; Haffner, D. P.

doi:10.5194/amt-10-4067-2017

Cited by 6 publications

(3 citation statements)

References 31 publications

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“…The DI can be a useful tool for analyzing spectra obtained from other current and future space-borne sensors that may suffer from saturation and blooming such as TROPOMI (launched in 2017) or the similar Environmental trace gases Monitoring Instrument (EMI) on the GaoFen-5 satellite (Cheng et al, 2019;Ren et al, 2020) (launched in 2018). Similar sensors include the OCO-2 (launched in 2014) and OCO-3 (launched in 2019) (Eldering et al, 2019), South Korea's geostationary Environment Monitoring Spectrometer (GEMS) (launched 18 February 2020), NASA's geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) (Zoogman et al, 2017) (planned for launch in 2022), the Copernicus geostationary Sentinel-4 (planned for launch in 2023) and low-Earth-orbit Sentinel-5 (planned for launch in 2023). Many of these sensors have a smaller pixel size and/or smaller FOV than OMI.…”

Section: Discussionmentioning

confidence: 99%

Detection of anomalies in the UV–vis reflectances from the Ozone Monitoring Instrument

et al. 2021

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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.

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Section: Discussionmentioning

confidence: 99%

Detection of anomalies in the UV–vis reflectances from the Ozone Monitoring Instrument

et al. 2021

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“…The Convective Cloud Differential (CCD) method (Ziemke et al, 1998) or the Cloud-Clear Pair (CCP) method (Newchurch et al, 2003) use this approach with TOMS. This method has been applied to OMI, GOME, GOME-2, and SCIAMACHY data (Ziemke et al, 2017;Valks et al, 2014;Leventidou et al, 2016). A second method, called "cloud slicing" (Ziemke et al, 2001(Ziemke et al, , 2009(Ziemke et al, , 2017, uses measurements of above-cloud column ozone together with cloud-top pressure data to derive ozone column amounts in the upper troposphere.…”

Section: Tropospheric Ozone Satellite and Residual Measurementsmentioning

confidence: 99%

“…This method has been applied to OMI, GOME, GOME-2, and SCIAMACHY data (Ziemke et al, 2017;Valks et al, 2014;Leventidou et al, 2016). A second method, called "cloud slicing" (Ziemke et al, 2001(Ziemke et al, , 2009(Ziemke et al, , 2017, uses measurements of above-cloud column ozone together with cloud-top pressure data to derive ozone column amounts in the upper troposphere. Used in combination, these methods can estimate 400 to 1000 hPa lower tropospheric column ozone.…”

Section: Tropospheric Ozone Satellite and Residual Measurementsmentioning

confidence: 99%

Tropospheric Ozone Assessment Report: Tropospheric ozone from 1877 to 2016, observed levels, trends and uncertainties

Tarasick

Galbally

Cooper

et al. 2019

Elementa: Science of the Anthropocene

157

168

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From the earliest observations of ozone in the lower atmosphere in the 19th century, both measurement methods and the portion of the globe observed have evolved and changed. These methods have different uncertainties and biases, and the data records differ with respect to coverage (space and time), information content, and representativeness. In this study, various ozone measurement methods and ozone datasets are reviewed and selected for inclusion in the historical record of background ozone levels, based on relationship of the measurement technique to the modern UV absorption standard, absence of interfering pollutants, representativeness of the well-mixed boundary layer and expert judgement of their credibility. There are significant uncertainties with the 19th and early 20th-century measurements related to interference of other gases. Spectroscopic methods applied before 1960 have likely underestimated ozone by as much as 11% at the surface and by about 24% in the free troposphere, due to the use of differing ozone absorption coefficients.There is no unambiguous evidence in the measurement record back to 1896 that typical mid-latitude background surface ozone values were below about 20 nmol mol -1 , but there is robust evidence for increases in the temperate and polar regions of the northern hemisphere of 30-70%, with large uncertainty, between the period of historic observations, 1896-1975, and the modern period (1990-2014). Independent historical observations from balloons and aircraft indicate similar changes in the free troposphere. Changes in the southern hemisphere are much less. Regional representativeness of the available observations remains a potential source of large errors, which are difficult to quantify.The great majority of validation and intercomparison studies of free tropospheric ozone measurement methods use ECC ozonesondes as reference. Compared to UV-absorption measurements they show a modest (~1-5% ±5%) high bias in the troposphere, but no evidence of a change with time. Umkehr, lidar, and FTIR methods all show modest low biases relative to ECCs, and so, using ECC sondes as a transfer standard, all appear to agree to within one standard deviation with the modern UV-absorption standard. Other sonde types show an increase of 5-20% in sensitivity to tropospheric ozone from 1970-1995. Biases and standard deviations of satellite retrieval comparisons are often 2-3 times larger than those of other free tropospheric measurements. The lack of information on temporal changes of bias for satellite measurements of tropospheric ozone is an area of concern for long-term trend studies.

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Global-Scale Patterns and Trends in Tropospheric NO2 Concentrations, 2005–2018

Jamali

Klingmyr²,

Tagesson

2020

Remote Sensing

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Nitrogen dioxide (NO2) is an important air pollutant with both environmental and epidemiological effects. The main aim of this study is to analyze spatial patterns and temporal trends in tropospheric NO2 concentrations globally using data from the satellite-based Ozone Monitoring Instrument (OMI). Additional aims are to compare the satellite data with ground-based observations, and to find the timing and magnitude of greatest breakpoints in tropospheric NO2 concentrations for the time period 2005–2018. The OMI NO2 concentrations showed strong relationships with the ground-based observations, and inter-annual patterns were especially well reproduced. Eastern USA, Western Europe, India, China and Japan were identified as hotspot areas with high concentrations of NO2. The global average trend indicated slightly increasing NO2 concentrations (0.004 × 1015 molecules cm−2 y−1) in 2005–2018. The contribution of different regions to this global trend showed substantial regional differences. Negative trends were observed for most of Eastern USA, Western Europe, Japan and for parts of China, whereas strong, positive trends were seen in India, parts of China and in the Middle East. The years 2005 and 2007 had the highest occurrence of negative breakpoints, but the trends thereafter in general reversed, and the highest tropospheric NO2 concentrations were observed for the years 2017–2018. This indicates that the anthropogenic contribution to air pollution is still a major issue and that further actions are necessary to reduce this contribution, having a substantial impact on human and environmental health.

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A cloud-ozone data product from Aura OMI and MLS satellite measurements

Cited by 6 publications

References 31 publications

Detection of anomalies in the UV–vis reflectances from the Ozone Monitoring Instrument

Detection of anomalies in the UV–vis reflectances from the Ozone Monitoring Instrument

Tropospheric Ozone Assessment Report: Tropospheric ozone from 1877 to 2016, observed levels, trends and uncertainties

Global-Scale Patterns and Trends in Tropospheric NO2 Concentrations, 2005–2018

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