Results 1 to 10 of about 20,890,964 (361)
Data Assimilation: The Schrödinger Perspective [PDF]
Acta Numerica 28 (2019) 635-711, 2018 Data assimilation addresses the general problem of how to combine model-based predictions with partial and noisy observations of the process in an optimal manner. This survey focuses on sequential data assimilation techniques using probabilistic particle-based algorithms.
S. Reich
arxiv +7 more sources
Deep Data Assimilation: Integrating Deep Learning with Data Assimilation [PDF]
Applied Sciences, 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 +3 more
semanticscholar +4 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 +4 more
europepmc +4 more sources
Effect of microphysics scheme and data assimilation on hydrometeor and radiative flux simulations in the Arctic [PDF]
Royal Society Open ScienceAlthough 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
The Efficiency of Data Assimilation [PDF]
Water Resources Research, 2018 Data assimilation is the application of Bayes' theorem to condition the states of a dynamical systems model on observations. Any real‐world application of Bayes' theorem is approximate, and therefore, we cannot expect that data assimilation will preserve
G. Nearing +5 more
semanticscholar +4 more sources
Data Assimilation for Chaotic Dynamics [PDF]
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV), 2020 Chaos is ubiquitous in physical systems. The associated sensitivity to initial conditions is a significant obstacle in forecasting the weather and other geophysical fluid flows. Data assimilation is the process whereby the uncertainty in initial conditions is reduced by the astute combination of model predictions and real-time data.
A. Carrassi +5 more
semanticscholar +5 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 +18 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 +16 more
semanticscholar +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 +6 more
doaj +1 more source