Model Error Correction in Data Assimilation by Integrating Neural Networks
In this paper, we suggest a new methodology which combines Neural Networks (NN) into Data Assimilation (DA). Focusing on the structural model uncertainty, we propose a framework for integration NN with the physical models by DA algorithms, to improve both the assimilation process and the forecasting...
Saved in:
Main Authors: | Jiangcheng Zhu, Shuang Hu, Rossella Arcucci, Chao Xu, Jihong Zhu, Yi-ke Guo |
---|---|
Format: | Article |
Language: | English |
Published: |
Tsinghua University Press
2019-06-01
|
Series: | Big Data Mining and Analytics |
Subjects: | |
Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2018.9020033 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Effective Variational Data Assimilation in Air-Pollution Prediction
by: Rossella Arcucci, et al.
Published: (2018-12-01) -
A comparison of nonlinear filtering approaches in the context of anHIV model
by: H. Thomas Banks, et al.
Published: (2010-03-01) -
Adaptive Kalman Filtering: Measurement and Process Noise Covariance Estimation Using Kalman Smoothing
by: Theresa Kruse, et al.
Published: (2025-01-01) -
Optimized Gross Primary Productivity Over the Croplands Within the BEPS Particle Filtering Data Assimilation System (BEPS_PF v1.0)
by: Xiuli Xing, et al.
Published: (2025-01-01) -
The Impact of Spatial Dynamic Error on the Assimilation of Soil Moisture Retrieval Products
by: Xuesong Bai, et al.
Published: (2025-01-01)