Preconditioners for variational data assimilation
Abstract: Data assimilation algorithms allow users to inject measurement information into dynamical systems to improve state estimates and initialise forecasts. Variational data assimilation methods solve a non-linear least squares problem, of which a large proportion of the computational cost is made up of iterative methods applied to a linearised problem. In this talk I will discuss how preconditioners can be used to accelerate the solution of the linear least squares problems, taking into account the underlying structure of the problem of interest.
I will also discuss recent work to embed the variational data assimilation problem within Firedrake (firedrakeproject.org), motivated by the need to validate our novel approaches on a wider variety of challenging test problems. This work is in conjunction with John
Pearson, David Ham and Joshua Hope-Collins.
Join Zoom Meeting
https://cwi-nl-zoom.zoom.us/j/89682537232pwd=XozxwaMIxRTNapY4rH3dVlO2dx0R8I.1
Meeting ID: 896 8253 7232
Passcode: 738509
