4 citations · 6 across the 6 of their papers we have counts for
6 papers
Space-Time Decomposition of Kalman Filter
Luisa D'Amore, Rosalba Cacciapuoti
We present an innovative interpretation of Kalman Filter (KF, for short) combining the ideas of Schwarz Domain Decomposition (DD) and Parallel in Time (PinT) approaches. Thereafter…
Parallel framework for Dynamic Domain Decomposition of Data Assimilation problems a case study on Kalman Filter algorithm
Rosalba Cacciapuoti, Luisa D'Amore
We focus on Partial Differential Equation (PDE) based Data Assimilatio problems (DA) solved by means of variational approaches and Kalman filter algorithm. Recently, we presented a…
Domain Decomposition in space-time of 4D-VAR Data Assimilation problem: a case study on the ROMS software
L. D'Amore, R. Cacciapuoti, A. Moore
Domain Decomposition of 4D-VAR Data Assimilation (DD-4DVAR) is made up of decomposition of the spate-time domain, solution of reduced forecast model and minimization of local 4D-VA…
Sensitivity Analysis of Domain Decomposition method for 4D Variational Data Assimilation (DD-4DVAR DA)
Luisa D'Amore, Rosalba Cacciapuoti
We prove consistence, convergence and stability of the Domain Decomposition in space and time method of 4DVAR Data Assimilation problem. We introduce the condition number of the pr…
DD-DA PinT-based model: A Domain Decomposition approach in space and time, based on Parareal, for solving the 4D-Var Data Assimilation model
Luisa D'Amore, Rosalba Cacciapuoti
We present the mathematical framework of a Domain Decomposition (DD) aproach based on Parallel-in-Time methods (PinT-based approach) for solving the 4D-Var Data Assimilation (DA) m…
A remark on Domain Decomposition approaches solving Three Dimensional Variational Data Assimilation models
Luisa D'Amore, Rosalba Cacciapuoti
Data Assimilation (DA) is a methodology for combining mathematical models simulating complex systems (the background knowledge) and measurements (the reality or observational data)…