Assimilation of AERONET and MODIS AOT observations using variational and ensemble data assimilation methods and its impact on aerosol forecasting skill-Reference-Cited by-同舟云学术

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Assimilation of AERONET and MODIS AOT observations using variational and ensemble data assimilation methods and its impact on aerosol forecasting skill

Published:2017-05-11 Issue:9 Volume:122 Page:4967-4992
ISSN:2169-897X
Container-title:Journal of Geophysical Research: Atmospheres
language:en
Short-container-title:J. Geophys. Res. Atmos.

Author:

Rubin Juli I.¹²³,Reid Jeffrey S.⁴^ORCID,Hansen James A.⁴,Anderson Jeffrey L.⁵,Holben Brent N.⁶,Xian Peng⁴^ORCID,Westphal Douglas L.⁴,Zhang Jianglong⁷^ORCID

Affiliation:

1. National Research Council Washington District of Columbia USA

2. Naval Research Laboratory Monterey California USA

3. Now at Remote Sensing Division Naval Research Laboratory Washington District of Columbia USA

4. Marine Meteorology Division Naval Research Laboratory Monterey California USA

5. National Center for Atmospheric Research Boulder Colorado USA

6. NASA Goddard Space Flight Center Greenbelt Maryland USA

7. Department of Atmospheric Sciences University of North Dakota Grand Forks North Dakota USA

Funder

Office of Naval Research

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2016JD026067

Reference65 articles.

1. An Ensemble Adjustment Kalman Filter for Data Assimilation

2. An adaptive covariance inflation error correction algorithm for ensemble filters

3. The Data Assimilation Research Testbed: A Community Facility

4. Spatially and temporally varying adaptive covariance inflation for ensemble filters

5. Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation

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