Data assimilation (DA) can provide the more accurate initial state for numerical forecasting models. But traditional DA algorithms has the problem of long calculation time. This paper proposes fast data assimilation (FDA) based on machine learning. For training model, FDA uses 4DVAR, iForest, ...
Analog ensemble data assimilation and a method for constructing analogs with variational autoencoders Ian Grooms,QJR Meteorol. Soc, 2021, Q2Citations 7) Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 ...
15 Combining data assimilation and machine learning to emulate hidden dynamics a 8 -- 31:24 App 11 Neural network products in land surface data assimilation- Peter Weston (ECMW 10 -- 50:02 App 03 Learning from earth system observations- machine learning or data assimilatio 33 -- 19:03 App...
Data assimilation (DA) and uncertainty quantification (UQ) are extensively used in analysing and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical applications span from computational fluid dynamics (CFD) to geoscience and
With the continuous improvement of observational techniques, data assimilation has gradually become an effective method to improve the numerical simulation prediction. In addition, with the advent of big data and the enhancement of computing resources, machine learning has achieved great success. Studies ...
In this paper, we propose a robust data﹚orth analysis framework based on a hybrid data assimilation method. By constructing Gaussian process (GP) error model, this study attempts to alleviate biased data﹚orth assessments caused by unknown model structural errors, and to excavate complementary ...
A data assimilation technique was used to build a learning machine model that generated soil moisture estimates commensurate with the scale of the data. The research was taken further by developing a multivariate machine learning algorithm to predict root zone soil moisture both in space and time. ...
A hybrid data assimilation method based on real-time Ensemble Kalman filtering and KNN for COVID-19 prediction SongTao Zhang & LiHong Yang Article 16 January 2025 | Open Access Multimodal sentiment analysis based on multi-layer feature fusion and multi-task learning Yujian Cai , Xingguang...
Ingestion: The Art of Data Assimilation 2. 摄取:数据同化的艺术 In the Data Engineering process, the ingestion stage is essential, gathering data from diverse sources for downstream processing. This phase can pose significant challenges due to variable data sources and streams. Carefully selecting betw...
This often involves a data assimilation process to produce an integrated and consistent estimate of the atmospheric state over extended periods. By offering a comprehensive view of various climate variables, reanalysis data enable the identification and tracking of atmospheric hazards. For example, storms...