Applying the Local Ensemble Transform Kalman Filter to the Nonhydrostatic Icosahedral Atmospheric Model (NICAM)
Author:
Affiliation:
1. Graduate School of Life and Environmental Sciences, University of Tsukuba
2. Center for Computational Sciences, University of Tsukuba
Publisher
Meteorological Society of Japan
Subject
Atmospheric Science
Link
http://www.jstage.jst.go.jp/article/sola/5/0/5_0_121/_pdf
Reference14 articles.
1. Desroziers, G., L. Berre, B. Chapnik, and P. Poli, 2005: Diagnosis of observation, backgraound and analysis error statistics in observation space. Quart. J. Roy. Meteor. Soc., 131, 3385-3396.
2. Evensen, G., 1994: Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 99C5, 10143-10162.
3. Gaspari, G., and S. E. Cohn, 1999: Construction of correlation functions in two and three dimensions. Quart. J. Roy. Meteor. Soc., 125, 723-757.
4. Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter
5. Kalman, R., 1960: A new approach to linear filtering and predicted problems. J. Basic Eng., 82, 35-45.
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