Impact of Atmospheric and Aerosol Optical Depth Observations on Aerosol Initial Conditions in a strongly-coupled data assimilation system
- 1Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
- 2Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado USA
- 3Department of Chemical and Biochemical Engineering, The University of Iowa, Iowa City, IA USA
- 4Center of Global and Regional Environmental Research, The University of Iowa, Iowa City, IA USA
- 5Interdisciplinary Graduate Program in Informatics, The University of Iowa, Iowa City, IA USA
- 1Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
- 2Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado USA
- 3Department of Chemical and Biochemical Engineering, The University of Iowa, Iowa City, IA USA
- 4Center of Global and Regional Environmental Research, The University of Iowa, Iowa City, IA USA
- 5Interdisciplinary Graduate Program in Informatics, The University of Iowa, Iowa City, IA USA
Abstract. Strongly coupled data assimilation frameworks provide a mechanism for including additional information about aerosols through the coupling between aerosol and atmospheric variables, effectively utilizing atmospheric observations to change the aerosol analysis. Here, we investigate the impact of these observations on aerosol using the Maximum Likelihood Ensemble Filter (MLEF) algorithm with Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) which includes the Godard Chemistry Aerosol Radiation and Transport (GOCART) module. We apply this methodology to a dust storm event over the Arabian Peninsula and examine in detail the error covariance and in particular the impact of atmospheric observations on improving the aerosol initial conditions. The assimilated observations include conventional atmospheric observations and Aerosol Optical Depth (AOD) retrievals. Results indicate a positive impact of using strongly coupled data assimilation and atmospheric observations on the aerosol initial conditions, quantified using Degrees of Freedom for Signal.
Milija Zupanski et al.


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RC1: 'Strongly coupled aerosol/atmospheric assimilation', Anonymous Referee #1, 25 Apr 2019
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RC2: 'Review', Anonymous Referee #2, 29 Apr 2019
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AC1: 'Impact of Atmospheric and Aerosol Optical Depth Observations on Aerosol Initial Conditions in a strongly-coupled data assimilation system', Milija Zupanski, 11 Jul 2019


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RC1: 'Strongly coupled aerosol/atmospheric assimilation', Anonymous Referee #1, 25 Apr 2019
-
RC2: 'Review', Anonymous Referee #2, 29 Apr 2019
-
AC1: 'Impact of Atmospheric and Aerosol Optical Depth Observations on Aerosol Initial Conditions in a strongly-coupled data assimilation system', Milija Zupanski, 11 Jul 2019
Milija Zupanski et al.
Milija Zupanski et al.
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