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Volume 16, issue 6
Atmos. Chem. Phys., 16, 3927–3951, 2016
https://doi.org/10.5194/acp-16-3927-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 16, 3927–3951, 2016
https://doi.org/10.5194/acp-16-3927-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 23 Mar 2016

Research article | 23 Mar 2016

Development of the Ensemble Navy Aerosol Analysis Prediction System (ENAAPS) and its application of the Data Assimilation Research Testbed (DART) in support of aerosol forecasting

Juli I. Rubin et al.
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Adhikary, B., Kulkarni, S., Dallura, A., Tang, Y., Chai, T., Leung, L.R., Qian, Y., Chung, C. E., Ramanathan, V., and Carmichael, G. R.: A regional scale chemical transport modeling of Asian aerosols with data assimilation of AOD observations using optimal interpolation technique, Atmos. Environ., 42, 8600–8615, https://doi.org/10.1016/j.atmosenv.2008.08.031, 2008.
Anderson, J. L.: A method for producing and evaluating probabilistic forecasts from ensemble model integrations, J. Climate, 9, 1518–1530, 1996.
Anderson, J. L.: An ensemble adjustment Kalman filter for data assimilation, Mon. Weather Rev., 129, 2894–2903, 2001.
Anderson, J. L.: An adaptive covariance inflation error correction algorithm for ensemble filters, Tellus, 59A, 210–224, 2007.
Anderson, J. L.: Spatially and temporally varying adaptive covariance inflation for ensemble filters, Tellus, 61A, 72–83, 2009.
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This work tests the use of an ensemble prediction system for aerosol forecasting, including an ensemble adjustment Kalman filter for MODIS AOT assimilation. Key findings include (1) meteorology and source-perturbed ensembles are needed to capture long-range transport and near-source aerosol events, (2) adaptive covariance inflation is recommended for assimilating spatially heterogeneous observations and (3) the ensemble system captures sharp gradients relative to a deterministic/variational system.
This work tests the use of an ensemble prediction system for aerosol forecasting, including an...
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