In order to prolong the lead time of the flood forecasts, numerical weather prediction (NWP)
models are more and more widely used to provide high-resolution rainfall forecasts as the …

In statistical data assimilation one evaluates the conditional expected values, conditioned on
measurements, of interesting quantities on the path of a model through observation and …

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-
by-synthesis approach toward understanding mechanisms of nervous system functions. We …

We present an efficient method for estimating variables and parameters of a given system of
ordinary differential equations by adapting the model output to an observed time series from …

Consider the supremal functional 1 E_ ∞ (u, A):= ‖ L (⋅, u, D u) ‖ _ L^ ∞ (A),\quad A ⊆ Ω,
E∞(u, A):=‖ L (·, u, D u)‖ L∞(A), A⊆ Ω, applied to W^ 1, ∞ W 1,∞ maps u: Ω ⊆ R ⟶ R^ N …

We prove the existence of vectorial Absolute Minimisers in the sense of Aronsson to the
supremal functional $ E_\infty (u,\Omega')\!=\!\|\mathscr {L}(\cdot, u,\mathrm {D} u)\| _ {L^\infty …

We present a continuous time state estimation framework that unifies traditionally individual
tasks of smoothing, tracking, and forecasting (STF), for a class of targets subject to smooth …

Data assimilation variational principles (4D‐Var) exhibit a natural symplectic structure
among the state variables x (t) and. We explore the implications of this structure in both …

An optimization based state and parameter estimation method is presented where the
required Jacobian matrix of the cost function is computed via automatic differentiation …

Error breeding is a popular and simple method to generate flow‐adapted perturbations for
use in ensemble forecasting. It has traditionally been believed that the norm type used in …