| Autor: |
Jianglong Zhang, Spurr, Robert J. D., Reid, Jeffrey S., Peng Xian, Colarco, Peter R., Campbell, James R., Hyer, Edward J., Baker, Nancy |
| Předmět: |
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| Zdroj: |
Geoscientific Model Development Discussions; 7/8/2020, p1-47, 47p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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