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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/gmd-2020-216
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-216
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  08 Jul 2020

08 Jul 2020

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This preprint is currently under review for the journal GMD.

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

Jianglong Zhang1, Robert J. D. Spurr2, Jeffrey S. Reid3, Peng Xian3, Peter R. Colarco4, James R. Campbell3, Edward J. Hyer3, and Nancy Baker3 Jianglong Zhang et al.
  • 1Department of Atmospheric Sciences, University of North Dakota, Grand Forks, ND, USA
  • 2RT SOLUTIONS Inc., Cambridge MA, USA
  • 3Marine Meteorology Division, Naval Research Laboratory, Monterey, CA, USA
  • 4NASA Goddard Space FlightCenter, Greenbelt, MD, USA

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 both 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 improving the accuracy of aerosol model analysis over cloudy regions and bright surfaces. However, the OMI AI data assimilation alone does not out-perform 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 ultra-violet (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 TROPOspheric Monitoring Instrument (TROPOMI), Ozone Mapping and Profiler Suite (OMPS) and eventually with the Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission.

Jianglong Zhang et al.

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Jianglong Zhang et al.

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Short summary
A first-of-its-kind scheme has been developed for assimilating Ozone Monitoring Instrument (OMI) aerosol index (AI) measurements into the Naval Aerosol Analysis and Predictive System. Improvements in model simulations demonstrate the utility of OMI AI data assimilation for improving the accuracy of aerosol model analysis over cloudy regions and bright surfaces. This study can be considered as one of the first attempts for direct radiance assimilation at the UV spectrum for aerosol analyses.
A first-of-its-kind scheme has been developed for assimilating Ozone Monitoring Instrument (OMI)...
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