Results 1 to 10 of about 25,102,445 (228)

Displacement Data Assimilation [PDF]

Journal of Computational Physics, 2016
We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where feature ...
Mariano, Arthur J., Restrepo, Juan M., Rosenthal, W. Steven, Venkataramani, Shankar C.   +3 more
core   +3 more sources

The analog data assimilation [PDF]

Monthly Weather Review, 2017
In light of growing interest in data-driven methods for oceanic, atmospheric, and climate sciences, this work focuses on the field of data assimilation and presents the analog data assimilation (AnDA).
Ailliot, Pierre, Fablet, Ronan, Lguensat, Redouane, Pulido, Manuel Arturo, Tandeo, Pierre   +4 more
core   +7 more sources

Data assimilation in operator algebras. [PDF]

Proc Natl Acad Sci U S A, 2023
We develop an algebraic framework for sequential data assimilation of partially observed dynamical systems. In this framework, Bayesian data assimilation is embedded in a nonabelian operator algebra, which provides a representation of observables by multiplication operators and probability densities by density operators (quantum states).
Freeman D, Giannakis D, Mintz B, Ourmazd A, Slawinska J.   +4 more
europepmc   +4 more sources

Deep Data Assimilation: Integrating Deep Learning with Data Assimilation

Applied Sciences (Switzerland), 2021
In this paper, we propose Deep Data Assimilation (DDA), an integration of Data Assimilation (DA) with Machine Learning (ML). DA is the Bayesian approximation of the true state of some physical system at a given time by combining time-distributed ...
Rossella Arcucci, Yike Guo
exaly   +2 more sources

Effect of microphysics scheme and data assimilation on hydrometeor and radiative flux simulations in the Arctic [PDF]

Royal Society Open Science
Although clouds are a major factor influencing atmospheric environments in the Arctic, numerical simulations of Arctic clouds are uncertain. In this study, the effects of microphysics scheme and data assimilation (DA) on the simulation of clouds ...
Dae-Hui Kim, Hyun Mee Kim
doaj   +2 more sources

Land Data Assimilation: Harmonizing Theory and Data in Land Surface Process Studies

Reviews of Geophysics
Data assimilation plays a dual role in advancing the “scientific” understanding and serving as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has evolved into a distinct discipline within geophysics, facilitating the ...
Xin Li, Feng Liu, Chunfeng Ma
exaly   +2 more sources

Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0.0): EnVar implementation and evaluation [PDF]

Geoscientific Model Development, 2022
On 24 September 2021, JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the Model Prediction Across Scales – Atmosphere (MPAS-A) built on the software framework of the Joint Effort for Data assimilation Integration (JEDI) was publicly released for
Z. Liu, C. Snyder, J. J. Guerrette, B.-J. Jung, J. Ban, S. Vahl, S. Vahl, Y. Wu, Y. Wu, Y. Trémolet, T. Auligné, B. Ménétrier, A. Shlyaeva, S. Herbener, E. Liu, E. Liu, D. Holdaway, D. Holdaway, B. T. Johnson   +18 more
doaj   +1 more source

Bivariate sea-ice assimilation for global-ocean analysis–reanalysis [PDF]

Ocean Science, 2023
In the last decade, various satellite missions have been monitoring the status of the cryosphere and its evolution. Besides sea-ice concentration data, available since the 1980s, sea-ice thickness retrievals are now ready to be used in global operational
A. Cipollone, D. S. Banerjee, D. S. Banerjee, D. S. Banerjee, D. Iovino, A. Aydogdu, S. Masina   +6 more
doaj   +1 more source

Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review [PDF]

IEEE/CAA Journal of Automatica Sinica, 2023
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
Sibo Cheng, César A. Quilodrán Casas, Said Ouala, A. Farchi, Che Liu, P. Tandeo, Ronan Fablet, D. Lucor, B. Iooss, J. Brajard, Dunhui Xiao, T. Janjić, Weiping Ding, Yike Guo, A. Carrassi, M. Bocquet, Rossella Arcucci   +16 more
semanticscholar   +1 more source

Score-based Data Assimilation [PDF]

Neural Information Processing Systems, 2023
Data assimilation, in its most comprehensive form, addresses the Bayesian inverse problem of identifying plausible state trajectories that explain noisy or incomplete observations of stochastic dynamical systems.
François Rozet, Gilles Louppe
semanticscholar   +1 more source