Implementation of a Modified Adaptive Covariance Inflation Scheme for the Big Data‐Driven NLS‐4DVar Algorithm-Reference-Cited by-同舟云学术

Implementation of a Modified Adaptive Covariance Inflation Scheme for the Big Data‐Driven NLS‐4DVar Algorithm

Published:2019-12 Issue:12 Volume:6 Page:2593-2604
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth and Space Science

Author:

Tian Xiangjun¹²³,Zhang Hongqin¹²

Affiliation:

1. International Center for Climate and Environment Sciences, Institute of Atmospheric PhysicsChinese Academy of Sciences Beijing China

2. University of Chinese Academy of Sciences Beijing China

3. Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and Technology Nanjing China

Funder

National Natural Science Foundation of China

National Basic Research Program of China

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019EA000963

Reference24 articles.

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

2. Operational implementation of a hybrid ensemble/4D-Var global data assimilation system at the Met Office

3. Dennis J. E. &R. B.SchnabelJr. (1996).Numerical methods for unconstrained optimization and nonlinear equations (classics in applied mathematics) SIAM 378pp.

4. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics

5. Data Assimilation

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