General sensitivity analysis in data assimilation

Sensitivity analysis in variational data assimilation and applications

Mathematical aspects of sensitivity analysis in unconstrained optimization are reviewed and the sensitivity equations of a variational data assimilation system (VDAS) to observations, background estimate, and to the specification of the associated error-variances are derived from the first order optimality condition. The error-variance sensitivity is introduced as a feasible approach to provide...

Sensitivity and Stability Radius in Data Envelopment Analysis

Continuous Data Assimilation Using General Interpolant Observables

We present a new continuous data assimilation algorithm based on ideas that have been developed for designing finite-dimensional feedback controls for dissipative dynamical systems, in particular, in the context of the incompressible two-dimensional Navier–Stokes equations. These ideas are motivated by the fact that dissipative dynamical systems possess finite numbers of determining parameters ...

Reduced-order Observation Sensitivity in 4d-var Data Assimilation

Observation sensitivity techniques have been initially developed in the context of 3D-Var data assimilation for applications to targeted observations (Baker and Daley 2000, Doerenbecher and Bergot 2001). Adjoint-based methods are currently implemented in NWP to monitor the observation impact on analysis and short-range forecasts (Fourrié et al. 2002, Langland and Baker 2004, Zhu and Gelaro 2008...

SENSITIVITY ANALYSIS OF EFFICIENT AND INEFFICIENT UNITS IN INTEGER-VALUED DATA ENVELOPMENT ANALYSIS

One of the issues in Data Envelopment Analysis (DEA) is sensitivity and stability region of the speci c decision making unit (DMU), included ecient and inecient DMUs. In sensitivity analysis of ecient DMUs,the largest region should be found namely stability region thatdata variations are only for ecient DMU under evaluation and the data for the remainingDMUs are assumed xed. Also ecient DMU u...