Results 11 to 20 of about 24,876,673 (286)
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
On optimal solution error covariances in variational data assimilation problems [PDF]
, 2010 The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find unknown parameters such as distributed model coefficients or boundary conditions. The equation for the optimal solution error
Le Dimet, F.X. +3 more
core +4 more sources
Displacement data assimilation [PDF]
Journal of Computational Physics, 2017 26 Pages, 9 figures, 5 ...
W. Steven Rosenthal +3 more
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The Efficiency of Data Assimilation [PDF]
Water Resources Research, 2018 AbstractData 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 all of the information available from models and observations.
Grey Nearing +5 more
openaire +2 more sources
Scale-dependent background-error covariance localisation [PDF]
Tellus: Series A, Dynamic Meteorology and Oceanography, 2015 A new approach is presented and evaluated for efficiently applying scale-dependent spatial localisation to ensemble background-error covariances within an ensemble-variational data assimilation system.
Mark Buehner, Anna Shlyaeva
doaj +1 more source
Data Assimilation in Reduced Modeling [PDF]
SIAM/ASA Journal on Uncertainty Quantification, 2017 We consider the problem of optimal recovery of an element $u$ of a Hilbert space $\mathcal{H}$ from $m$ measurements obtained through known linear functionals on $\mathcal{H}$. Problems of this type are well studied \cite{MRW} under an assumption that $u$ belongs to a prescribed model class, e.g. a known compact subset of $\mathcal{H}$.
Binev, Peter +5 more
openaire +5 more sources
A High Resolution Reanalysis for the Mediterranean Sea
Frontiers in Earth Science, 2021 In order to be able to forecast the weather and estimate future climate changes in the ocean, it is crucial to understand the past and the mechanisms responsible for the ocean variability.
Romain Escudier +13 more
doaj +1 more source
, 2015 <p>Submitted - <a href="/records/5b3bk-adp93/files/1506.07825.pdf?download=1">1506.07825.pdf</a></p>
Law, Kody +2 more
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Remote Sensing, 2021 Microwave temperature sounding observations from polar-orbiting meteorological satellites have been widely used for research on climate trends of atmospheric temperature at different heights around the world.
Xinlu Xia, Xiaolei Zou
doaj +1 more source
, 2016 Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places data assimilation into the broader context of inverse problems and the theory, methods, and algorithms that are used for their solution.
Asch, Mark +2 more
openaire +4 more sources