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

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.

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.


2011 ◽  
Vol 4 (11) ◽  
pp. 2375-2388 ◽  
Author(s):  
P. Sellitto ◽  
B. R. Bojkov ◽  
X. Liu ◽  
K. Chance ◽  
F. Del Frate

Abstract. Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a neural network algorithm. An extended set of ozone sonde measurements at northern mid-latitudes for the years 2004–2008 has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.


2011 ◽  
Vol 4 (3) ◽  
pp. 2491-2524 ◽  
Author(s):  
P. Sellitto ◽  
B. R. Bojkov ◽  
X. Liu ◽  
K. Chance ◽  
F. Del Frate

Abstract. Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a Neural Network algorithms. An extended set of ozone sonde measurements at northern mid-latitudes has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.


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


2006 ◽  
Vol 44 (5) ◽  
pp. 1199-1208 ◽  
Author(s):  
P.F. Levelt ◽  
E. Hilsenrath ◽  
G.W. Leppelmeier ◽  
G.H.J. van den Oord ◽  
P.K. Bhartia ◽  
...  

2017 ◽  
Vol 10 (11) ◽  
pp. 4121-4134 ◽  
Author(s):  
Peter R. Colarco ◽  
Santiago Gassó ◽  
Changwoo Ahn ◽  
Virginie Buchard ◽  
Arlindo M. da Silva ◽  
...  

Abstract. We provide an analysis of the commonly used Ozone Monitoring Instrument (OMI) aerosol index (AI) product for qualitative detection of the presence and loading of absorbing aerosols. In our analysis, simulated top-of-atmosphere (TOA) radiances are produced at the OMI footprints from a model atmosphere and aerosol profile provided by the NASA Goddard Earth Observing System (GEOS-5) Modern-Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). Having established the credibility of the MERRAero simulation of the OMI AI in a previous paper we describe updates in the approach and aerosol optical property assumptions. The OMI TOA radiances are computed in cloud-free conditions from the MERRAero atmospheric state, and the AI is calculated. The simulated TOA radiances are fed to the OMI near-UV aerosol retrieval algorithms (known as OMAERUV) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining to the OMI algorithm assumptions of the surface pressure, which are generally different from what the actual surface pressure of an observation is, and the other related to simplifying assumptions in the molecular atmosphere radiative transfer used in the OMI algorithms. Surface pressure assumptions lead to systematic biases in the OMAERUV AI, particularly over the oceans. Simplifications in the molecular radiative transfer lead to biases particularly in regions of topography intermediate to surface pressures of 600 and 1013.25 hPa. Generally, the errors in the OMI AI due to these considerations are less than 0.2 in magnitude, though larger errors are possible, particularly over land. We recommend that future versions of the OMI algorithms use surface pressures from readily available atmospheric analyses combined with high-spatial-resolution topographic maps and include more surface pressure nodal points in their radiative transfer lookup tables.


2017 ◽  
Vol 10 (12) ◽  
pp. 4979-4994
Author(s):  
Germar Bernhard ◽  
Irina Petropavlovskikh ◽  
Bernhard Mayer

Abstract. A new method is presented to determine vertical ozone profiles from measurements of spectral global (direct Sun plus upper hemisphere) irradiance in the ultraviolet. The method is similar to the widely used Umkehr technique, which inverts measurements of zenith sky radiance. The procedure was applied to measurements of a high-resolution spectroradiometer installed near the centre of the Greenland ice sheet. Retrieved profiles were validated with balloon-sonde observations and ozone profiles from the space-borne Microwave Limb Sounder (MLS). Depending on altitude, the bias between retrieval results presented in this paper and MLS observations ranges between −5 and +3 %. The magnitude of this bias is comparable, if not smaller, to values reported in the literature for the standard Dobson Umkehr method. Total ozone columns (TOCs) calculated from the retrieved profiles agree to within 0.7±2.0 % (±1σ) with TOCs measured by the Ozone Monitoring Instrument on board the Aura satellite. The new method is called the Global-Umkehr method.


Author(s):  
Pieternel F. Levelt ◽  
Gijsbertus van den Oord ◽  
Marcel Dobber ◽  
Ruud Dirksen ◽  
Glen Jaross ◽  
...  

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