Journal article

Improving Assimilation of Radiance Observations by Implementing Model Space Localization in an Ensemble Kalman Filter

Lili Lei, Jeffrey S Whitaker, Craig Bishop

Journal of Advances in Modeling Earth Systems | American Geophysical Union (AGU) | Published : 2018

Abstract

Experiments using the National Oceanic and Atmospheric Administration Finite‐Volume Cubed‐Sphere Dynamical Core Global Forecasting System (FV3GFS) reveal that the four‐dimensional ensemble‐variational method (4DEnVAR) performs similarly to an ensemble Kalman filter (EnKF) when no radiance observations are assimilated, but 4DEnVAR is superior to an EnKF when radiance observations are assimilated. The hypothesis for the cause of the differences between 4DEnVAR and EnKF is the difference in vertical localization, since radiance observations are integral observations in the vertical and 4DEnVAR uses model space localization while the EnKF uses observation space localization. A modulation approac..

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University of Melbourne Researchers

Grants

Awarded by National Key R&D Program of China


Awarded by National Natural Science Foundation of China


Awarded by NOAA High-Impact Weather Prediction Project (HIWPP)


Awarded by Australian Research Council's Centres of Excellence Scheme


Funding Acknowledgements

Thanks to two anonymous reviewers for their constructive suggestions. This work is jointly sponsored by the National Key R&D Program of China through grant 2017YFC1501603, the National Natural Science Foundation of China through grant 41675052, the NOAA High-Impact Weather Prediction Project (HIWPP) under award NA14OAR4830123, and the NOAA/NWS Next-Generation Global Prediction System (NGGPS) project. Craig H. Bishop acknowledges support from the Australian Research Council's Centres of Excellence Scheme (CE170100023). The data used to generate the simulation experiments were obtained from the National Centers for Environmental Prediction (NCEP; https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/global-forcast-system-gfs).