Correcting for Model Changes in Statistical Postprocessing -- An approach based on Response Theory

Abstract

For most statistical postprocessing schemes used to correct weather forecasts, changes to the forecast model induce a considerable reforecasting effort. We present a new approach based on response theory to cope with slight model changes. In this framework, the model change is seen as a perturbation of the original forecast model. The response theory allows us then to evaluate the variation induced on the parameters involved in the statistical postprocessing, provided that the magnitude of this perturbation is not too large. This approach is studied in the context of simple Ornstein-Uhlenbeck models, and then on a more realistic, yet simple, quasi-geostrophic model. The analytical results for the former case help to pose the problem, while the application to the latter provide a proof-of-concept and assesses the potential performances of response theory in a chaotic system. In both cases, the parameters of the statistical postprocessing used - an Error-in-Variables Model Output Statistics (EVMOS) - are appropriately corrected when facing a model change. The potential application in an operational environment is also discussed.

arXiv comment33 pages, 11 figures. Accepted for publication in Nonlinear Processes in Geophysics

References in corpus (19)

• Dynamical Ensembles in Nonequilibrium Statistical Mechanics
• Dynamical ensembles in stationary states
• A review of linear response theory for general differentiable dynamical systems
• Forward and Adjoint Sensitivity Computation of Chaotic Dynamical Systems
• Sensitivity analysis on chaotic dynamical system by Non-Intrusive Least Square Shadowing (NILSS)
• Predictability of large-scale atmospheric motions: Lyapunov exponents and error dynamics
• Disentangling multi-level systems: averaging, correlations and memory
• Response Theory for Equilibrium and Non-Equilibrium Statistical Mechanics: Causality and Generalized Kramers-Kronig relations
• Evidence of dispersion relations for the nonlinear response of the Lorenz 63 system
• A proof of concept for scale-adaptive parameterizations: the case of the Lorenz '96 model
• Can we use linear response theory to assess geoengineering strategies?
• Stochastic perturbations to dynamical systems: a response theory approach
• The Modular Arbitrary-Order Ocean-Atmosphere Model: MAOOAM v1.0
• Hyperbolicity, shadowing directions and sensitivity analysis of a turbulent three-dimensional flow
• On the validity of linear response theory in high-dimensional deterministic dynamical systems
• On spurious detection of linear response and misuse of the fluctuation-dissipation theorem in finite time series
• Periodic Shadowing Sensitivity Analysis of Chaotic Systems
• Comparison of stochastic parameterizations in the framework of a coupled ocean-atmosphere model
• Sensitivity of long periodic orbits of chaotic systems