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© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 17 Dec 2018

Research article | 17 Dec 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

RAMS-MLEF Atmosphere-Aerosol Coupled Data Assimilation: A Case Study of A Dust Event over the Arabian Peninsula on 4 August 2016

Ting-Chi Wu1, Milija Zupanski1, Stephen Saleeby2, Anton Kliewer1, Lewis Grasso1, Qijing Bian2, Samuel A. Atwood2, Yi Wang3, and Jun Wang3 Ting-Chi Wu et al.
  • 1Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, U.S.A.
  • 2Department of Atmospheric Science, Colorado State University, Fort Collins, CO, U.S.A.
  • 3Department of Chemical and Biochemical Engineering, Interdisciplinary Graduate Program in Informatics, and Center for Global and Regional Environmental Research, The University of Iowa, Iowa City, IA, U.S.A

Abstract. The Regional Atmospheric Modeling System (RAMS) has been interfaced with the Maximum Likelihood Ensemble Filter (MLEF) with the goal of improving initial conditions for aerosol weather forecasting via atmosphere-aerosol coupled data assimilation (RAMS-MLEF). In order to assimilate satellite retrieved aerosol optical depth (AOD), an AOD observation operator customized for the RAMS aerosol module is implemented. Two MLEF-RAMS experiments are carried out for a dust storm event over the Arabian Peninsula that occurred on 4 August 2016. In the first experiment, conventional atmospheric observations from the National Centre for Environmental Prediction (NCEP) Prepared Binary Universal Form for the Representation of meteorological data (PrepBUFR) dataset are assimilated (ATMONLY), while both the atmospheric observations and AOD retrievals from Moderate Resolution Imaging Spectroradiometer (MODIS) are assimilated in the second experiment (ATMAOD). In the two experiments, a list of control variables is used and it includes the three-dimensional wind components, perturbation Exner function, ice-liquid water potential temperature, total water mass mixing ratio, and the two dust modes from the aerosol module. Results indicate that the assimilation of MODIS AOD retrievals improves the representation of the dust plume over Persian Gulf, however, has no obvious impact on the dust plume interior of Saudi Arabia. Such finding is further supported by the examination of analysis increments of some control variables and the information measure in terms of degrees of freedom for signal. This is likely due to the lack of AOD retrievals interior of the Arabian Peninsula. Finally, a 12-h forecast initialized from both experiments is conducted. In general, ATMAOD forecast better represents the Persian Plume but performs poorly for the Saudi Plume, when verified against the aerosol reanalysis product from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) dataset.

Ting-Chi Wu et al.
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Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Ting-Chi Wu et al.
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