Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 16, issue 6
Articles | Volume 16, issue 6
https://doi.org/10.5194/acp-16-3927-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-3927-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 16, issue 6
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, Jeffrey S. Reid, James A. Hansen, Jeffrey L. Anderson, Nancy Collins, Timothy J. Hoar, Timothy Hogan, Peng Lynch, Justin McLay, Carolyn A. Reynolds, Walter R. Sessions, Douglas L. Westphal, and Jianglong Zhang

Viewed

Total article views: 4,553 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,513 1,852 188 4,553 163 199
  • HTML: 2,513
  • PDF: 1,852
  • XML: 188
  • Total: 4,553
  • BibTeX: 163
  • EndNote: 199
Views and downloads (calculated since 20 Oct 2015)
Cumulative views and downloads (calculated since 20 Oct 2015)
Latest update: 06 Dec 2025
Download
Short summary
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint