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In variational assimilation, the most probable state of a dynamical system under Gaussian assumptions for the prior and likelihood can be found by solving a least-squares minimization problem . In recent years, we have seen the popularity of hybrid v
Externí odkaz:
http://arxiv.org/abs/2306.11869
Data assimilation combines prior (or background) information with observations to estimate the initial state of a dynamical system over a given time-window. A common application is in numerical weather prediction where a previous forecast and atmosph
Externí odkaz:
http://arxiv.org/abs/2107.12361
Autor:
LAZERUS, RACHEL
Publikováno v:
Publishers Weekly. 1/29/2024, Vol. 271 Issue 4, p47-47. 2/3p. 1 Color Photograph.
Publikováno v:
Publishers Weekly. 1/29/2024, Vol. 271 Issue 4, p46-47. 2p.
Data assimilation algorithms combine prior and observational information, weighted by their respective uncertainties, to obtain the most likely posterior of a dynamical system. In variational data assimilation the posterior is computed by solving a n
Externí odkaz:
http://arxiv.org/abs/2010.08416
Autor:
Xian, Xiaoling, Zheng, Xiaojie, Huang, Jiale, Qureshi, Nasib, Li, Biying, Liu, Jingke, Zeng, Yueren, Nichols, Nancy N., Lin, Xiaoqing
Publikováno v:
In Industrial Crops & Products 15 October 2023 202
Autor:
Tabeart, Jemima M., Dance, Sarah L., Lawless, Amos S., Migliorini, Stefano, Nichols, Nancy K., Smith, Fiona, Waller, Joanne A.
Recent developments in numerical weather prediction have led to the use of correlated observation error covariance (OEC) information in data assimilation and forecasting systems. However, diagnosed OEC matrices are often ill-conditioned and may cause
Externí odkaz:
http://arxiv.org/abs/1908.04071
Publikováno v:
In Transportation Research Part D April 2023 117
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