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.
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.
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
CORRESPONDING AUTHOR
National Research Council, Washington D.C.; Naval Research
Laboratory, Monterey, CA, USA
Jeffrey S. Reid
CORRESPONDING AUTHOR
Marine Meteorology Division, Naval Research Laboratory,
Monterey, CA, USA
James A. Hansen
Marine Meteorology Division, Naval Research Laboratory,
Monterey, CA, USA
Jeffrey L. Anderson
National Center for Atmospheric Research, Boulder,
CO, USA
Nancy Collins
National Center for Atmospheric Research, Boulder,
CO, USA
Timothy J. Hoar
National Center for Atmospheric Research, Boulder,
CO, USA
Timothy Hogan
Marine Meteorology Division, Naval Research Laboratory,
Monterey, CA, USA
Peng Lynch
CSC, Inc., Monterey, CA, USA
Justin McLay
Marine Meteorology Division, Naval Research Laboratory,
Monterey, CA, USA
Carolyn A. Reynolds
Marine Meteorology Division, Naval Research Laboratory,
Monterey, CA, USA
Walter R. Sessions
CSC, Inc., Monterey, CA, USA
Douglas L. Westphal
Marine Meteorology Division, Naval Research Laboratory,
Monterey, CA, USA
Jianglong Zhang
Department of Atmospheric Sciences, University of North Dakota, Grand Forks, ND, USA
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Latest update: 21 Nov 2024
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.
This work tests the use of an ensemble prediction system for aerosol forecasting, including an...
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