scholarly journals Simulation of the Ozone Monitoring Instrument aerosol index using the NASA Goddard Earth Observing System aerosol reanalysis products

2017 ◽  
Vol 10 (11) ◽  
pp. 4121-4134 ◽  
Author(s):  
Peter R. Colarco ◽  
Santiago Gassó ◽  
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 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.

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

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.

scholarly journals 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

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.

The use of radiative transfer modeling to compare normalized radiances from different instruments

2020 ◽  
Author(s):  
Colin Seftor ◽  
Glen Jaross ◽  
Leslie Moy ◽  
Natalya Kramarova ◽  
Eun-su Yang
Keyword(s):  
Radiative Transfer ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Profile ◽  
Ozone Monitoring ◽  
Radiative Transfer Modeling ◽  
Comparison Technique

<p>Measured sun-normalized radiances (S-NRs) from both the Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) and Nadir Profiler (NP) on the Suomi National Polar-orbiting Partnership (SNPP) satellite have been validated to the 2% level through, in part, comparisons with radiative transfer code calculations using co-located ozone profile retrievals inputs from the Microwave Limb Sounder (MLS) on the Aura satellite. To minimize the effects of clouds and aerosols, only low reflectivity and low aerosol scenes were used. We will describe the details of the comparison technique, including how low reflectivity / low aerosol scenes were determined.  We will also show results where we extend our study to compare measured S-NRs from the OMPS nadir sensors with those from both the Ozone Monitoring Instrument (OMI) on Aura sensor and, if available, the Version 2 dataset from the TROPOMI sensor on the Sentinel 5 Precursor (S5P) satellite.</p>

Science objectives of the ozone monitoring instrument

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 ◽  
...  
Keyword(s):  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Monitoring

scholarly journals Retrieving vertical ozone profiles from measurements of global spectral irradiance

2017 ◽  
Vol 10 (12) ◽  
pp. 4979-4994
Author(s):  
Germar Bernhard ◽  
Irina Petropavlovskikh ◽  
Bernhard Mayer
Keyword(s):  
High Resolution ◽  
Total Ozone ◽  
Greenland Ice Sheet ◽  
Spectral Irradiance ◽  
New Method ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Monitoring ◽  
Vertical Ozone ◽  
Vertical Ozone Profiles

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.

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