19 citations · 20 across the 2 of their papers we have counts for
6 papers
Data assimilation for chaotic dynamics
Alberto Carrassi, Marc Bocquet, Jonathan Demaeyer +3
Chaos is ubiquitous in physical systems. The associated sensitivity to initial conditions is a significant obstacle in forecasting the weather and other geophysical fluid flows. Da…
On temporal scale separation in coupled data assimilation with the ensemble Kalman filter
Maxime Tondeur, Alberto Carrassi, Stephane Vannitsem +1
Coupled data assimilation (CDA) distinctively appears as a main concern in numerical weather and climate prediction with major efforts put forward worldwide. The core issue is the…
On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean-atmosphere systems
Stéphane Vannitsem, Wansuo Duan
The use of coupled Backward Lyapunov Vectors (BLV) for ensemble forecast is demonstrated in a coupled ocean-atmosphere system of reduced order, the Modular Arbitrary Order Ocean-At…
Correcting for Model Changes in Statistical Postprocessing -- An approach based on Response Theory
Jonathan Demaeyer, Stéphane Vannitsem
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 b…
Routes to long-term atmospheric predictability in reduced-order coupled ocean-atmosphere systems -- Impact of the ocean basin boundary conditions
Stéphane Vannitsem, Roman Solé-Pomies, Lesley De Cruz
The predictability of the atmosphere at short and long time scales, associated with the coupling to the ocean, is explored in a new version of the Modular Arbitrary-Order Ocean-Atm…
Model error and sequential data assimilation. A deterministic formulation
A. Carrassi, S. Vannitsem, C. Nicolis
Data assimilation schemes are confronted with the presence of model errors arising from the imperfect description of atmospheric dynamics. These errors are usually modeled on the b…