Hotspot analysis and long-term trends of absorbing aerosol index from dust emissions measured by the Ozone Monitoring Instrument at different urban locations in India during 2005–2018

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.

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Review of: ''Impact of the Ozone Monitoring Instrument Row Anomaly on the Long-term Record of Aerosol Products''

10.5194/amt-2017-429-rc1 ◽

2018 ◽

Author(s):

Anonymous

Keyword(s):

Ozone Monitoring Instrument ◽

Monitoring Instrument ◽

Ozone Monitoring

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Review of “Simulation of the Ozone Monitoring Instrument Aerosol Index using the NASA Goddard Earth Observing System Aerosol Reanalysis Products”

10.5194/amt-2017-87-rc1 ◽

2017 ◽

Author(s):

Anonymous

Keyword(s):

Ozone Monitoring Instrument ◽

Monitoring Instrument ◽

Earth Observing System ◽

Ozone Monitoring ◽

Aerosol Index

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In-flight performance of the Ozone Monitoring Instrument

Atmospheric Measurement Techniques ◽

10.5194/amt-10-1957-2017 ◽

2017 ◽

Vol 10 (5) ◽

pp. 1957-1986 ◽

Cited By ~ 54

Author(s):

V. M. Erik Schenkeveld ◽

Glen Jaross ◽

Sergey Marchenko ◽

David Haffner ◽

Quintus L. Kleipool ◽

...

Keyword(s):

Trace Gas ◽

Flight Performance ◽

Line Profiles ◽

Ozone Monitoring Instrument ◽

Wavelength Calibration ◽

Monitoring Instrument ◽

Ozone Monitoring ◽

Imaging Spectrograph ◽

High Wavelength

Abstract. The Dutch–Finnish Ozone Monitoring Instrument (OMI) is an imaging spectrograph flying on NASA's EOS Aura satellite since 15 July 2004. OMI is primarily used to map trace-gas concentrations in the Earth's atmosphere, obtaining mid-resolution (0.4–0.6 nm) ultraviolet–visible (UV–VIS; 264–504 nm) spectra at multiple (30–60) simultaneous fields of view. Assessed via various approaches that include monitoring of radiances from selected ocean, land ice and cloud areas, as well as measurements of line profiles in the solar spectra, the instrument shows low optical degradation and high wavelength stability over the mission lifetime. In the regions relatively free from the slowly unraveling row anomaly (RA) the OMI irradiances have degraded by 3–8 %, while radiances have changed by 1–2 %. The long-term wavelength calibration of the instrument remains stable to 0.005–0.020 nm.

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Simulation of the Ozone Monitoring Instrument Aerosol Index using the NASA Goddard Earth Observing System Aerosol Reanalysis Products

10.5194/amt-2017-87 ◽

2017 ◽

Author(s):

Peter R. Colarco ◽

Santiago Gasso' ◽

Changwoo Ahn ◽

Virginie Buchard ◽

Arlindo M. da Silva ◽

...

Keyword(s):

Radiative Transfer ◽

Surface Pressure ◽

Model Atmosphere ◽

Ozone Monitoring Instrument ◽

Aerosol Optical Property ◽

Actual Surface ◽

Monitoring Instrument ◽

Earth Observing System ◽

Ozone Monitoring ◽

Aerosol Index

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 aerosol retrieval algorithms, and its retrieved AI (OMAERUV AI) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining 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 hPa 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.

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In-flight performance of the Ozone Monitoring Instrument

10.5194/amt-2016-420 ◽

2017 ◽

Cited By ~ 1

Author(s):

V. M. Erik Schenkeveld ◽

Glen Jaross ◽

Sergey Marchenko ◽

David Haffner ◽

Quintus L. Kleipool ◽

...

Keyword(s):

Trace Gas ◽

Flight Performance ◽

Line Profiles ◽

Ozone Monitoring Instrument ◽

Wavelength Calibration ◽

Monitoring Instrument ◽

Ozone Monitoring ◽

Imaging Spectrograph ◽

High Wavelength

Abstract. The Dutch-Finnish Ozone Monitoring Instrument (OMI) is an imaging spectrograph flying on NASA's EOS Aura satellite since July 15, 2004. OMI is primarily used to map trace gas concentrations in the Earth’s atmosphere, obtaining mid-resolution (0.4–0.6 nm) UV-VIS (264–504 nm) spectra at multiple (30–60) simultaneous fields of view. Assessed via various approaches that include monitoring of radiances from selected ocean, land, ice and cloud areas, as well as measurements of line profiles in the Solar spectra, the instrument shows low optical degradation and high wavelength stability over the mission lifetime. In the regions relatively free from the slowly unraveling ‘row anomaly’ the OMI irradiances have degraded by 3–8 %, while radiances have changed by 1–2 %. The long-term wavelength calibration of the instrument remains stable to 0.005–0.020 nm.

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Development of an Ozone Monitoring Instrument (OMI) aerosol index (AI) data assimilation scheme for aerosol modeling over bright surfaces – a step toward direct radiance assimilation in the UV spectrum

Geoscientific Model Development ◽

10.5194/gmd-14-27-2021 ◽

2021 ◽

Vol 14 (1) ◽

pp. 27-42

Author(s):

Jianglong Zhang ◽

Robert J. D. Spurr ◽

Jeffrey S. Reid ◽

Peng Xian ◽

Peter R. Colarco ◽

...

Keyword(s):

Radiative Transfer ◽

Data Assimilation ◽

Ozone Monitoring Instrument ◽

Uv Spectrum ◽

Model Simulations ◽

Monitoring Instrument ◽

Radiance Assimilation ◽

Ozone Monitoring ◽

Aerosol Index ◽

Assimilation Scheme

Abstract. Using the Vector LInearized Discrete Ordinate Radiative Transfer (VLIDORT) code as the main driver for forward model simulations, a first-of-its-kind data assimilation scheme has been developed for assimilating Ozone Monitoring Instrument (OMI) aerosol index (AI) measurements into the Naval Aerosol Analysis and Predictive System (NAAPS). This study suggests that both root mean square error (RMSE) and absolute errors can be significantly reduced in NAAPS analyses with the use of OMI AI data assimilation when compared to values from NAAPS natural runs. Improvements in model simulations demonstrate the utility of OMI AI data assimilation for aerosol model analysis over cloudy regions and bright surfaces. However, the OMI AI data assimilation alone does not outperform aerosol data assimilation that uses passive-based aerosol optical depth (AOD) products over cloud-free skies and dark surfaces. Further, as AI assimilation requires the deployment of a fully multiple-scatter-aware radiative transfer model in the forward simulations, computational burden is an issue. Nevertheless, the newly developed modeling system contains the necessary ingredients for assimilation of radiances in the ultraviolet (UV) spectrum, and our study shows the potential of direct radiance assimilation at both UV and visible spectrums, possibly coupled with AOD assimilation, for aerosol applications in the future. Additional data streams can be added, including data from the TROPOspheric Monitoring Instrument (TROPOMI), the Ozone Mapping and Profiler Suite (OMPS), and eventually the Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission.

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