Adaptive Localization for Tropical Cyclones With Satellite Radiances in an Ensemble Kalman Filter
One important aspect of successfully implementing an ensemble Kalman filter (EnKF) in a high dimensional geophysical application is covariance localization. But for satellite radiances whose vertical locations are not well defined, covariance localization is not straightforward. The global group fil...
Main Authors: | Chen Wang, Lili Lei, Zhe-Min Tan, Kekuan Chu |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2020-02-01
|
Series: | Frontiers in Earth Science |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/feart.2020.00039/full |
Similar Items
-
The Effect of Assimilating AMSU-A Radiance Data from Satellites and Large-Scale Flows from GFS on Improving Tropical Cyclone Track Forecast
by: Zhijuan Lai, et al.
Published: (2022-11-01) -
Data Assimilation in Spatio-Temporal Models with Non-Gaussian Initial States—The Selection Ensemble Kalman Model
by: Maxime Conjard, et al.
Published: (2020-08-01) -
Online Nonlinear Bias Correction in Ensemble Kalman Filter to Assimilate GOES‐R All‐Sky Radiances for the Analysis and Prediction of Rapidly Developing Supercells
by: Krishnamoorthy Chandramouli, et al.
Published: (2022-03-01) -
Adaptive Localization for Satellite Radiance Observations in an Ensemble Kalman Filter
by: Lili Lei, et al.
Published: (2020-08-01) -
A hybrid nudging-ensemble Kalman filter approach to data assimilation. Part I: application in the Lorenz system
by: Lili Lei, et al.
Published: (2012-05-01)