205 citations · 591 across the 28 of their papers we have counts for
32 papers
Information transfer as a new indicator of approaching local bifurcations: saddle-node, pitchfork and Hopf bifurcations
Stéphane Vannitsem, Carlos A. Pires, X. San Liang
Early warning signals are key tools for anticipating qualitative changes in the dynamics of complex systems. In this work, we investigate whether an information-theoretic measure d…
Multivariate phase-space interpretation of ensemble forecasts: A comparison of physical and AI models
Martin Bonte, Stéphane Vannitsem
Ensemble forecasts from the ECMWF's Integrated Forecasting System (IFS) and the Artificial Intelligence Forecasting System (AIFS-ENS) are compared using a multi-dimensional evaluat…
Intermittency-induced transitions in fast-slow dynamical systems
Alessandro Barone, Alberto Carrassi, Jonathan Demaeyer +1
Intermittent dynamics are ubiquitous in the Earth system and often arise from the interaction of processes evolving on different time scales. In this work, we investigate how inter…
Revisiting the Dynamical Properties of Pedlosky's Two-Layer Model for Finite Amplitude Baroclinic Waves
Nicolas De Ro, Jonathan Demaeyer, Stéphane Vannitsem
Baroclinic instability is a fundamental mechanism driving atmospheric dynamics. In this work, we revisit Pedlosky's two-layer model for finite amplitude baroclinic waves - a semina…
Spread/Error relationship and spatial error structure of precipitation ensemble nowcasting: Comparison of STEPS and generative AI
Martin Bonte, Lesley De Cruz, Fabian Debal +1
The predictability of the generative AI-based nowcasting model LDCast (trained on another region) is evaluated over Belgium, together with the pysteps implementation of the nowcast…
Structural Origins and Real-Time Drivers of Intermittency
Alessandro Barone, Alberto Carrassi, Thomas Savary +2
In general terms, intermittency is the property for which time evolving systems alternate among two or more different regimes. Predicting the instance when the regime switch will o…
Predictability of north Pacific blocking events : Analogue based analysis of historical MIROC6 simulations
Anupama K Xavier, Oisín Hamilton, Davide Faranda +1
Atmospheric blocking exerts a profound influence on mid-latitude circulation, yet its predictability remains elusive due to intrinsic non-linearities and sensitivity to initial-con…
Using Unstable Periodic Orbits to Understand Blocking Behaviour in a Low Order Land-Atmosphere Model
Oisín Hamilton, Jonathan Demaeyer, Michel Crucifix +1
Unstable Periodic Orbits (UPOs) were used to identify regimes, and transitions between regimes, in a reduced-order coupled atmosphere-land spectral model. In this paper we describe…
Sources of low-frequency O variability in coastal ice cores from Dronning Maud Land
Stéphane Vannitsem, David Docquier, Sarah Wauthy +2
The low-frequency variability of the O recorded in ice cores (FK17 and TIR18) recently drilled at two different locations in Dronning Maud Land (Antarctica), is investigate…
Causal dependencies and Shannon entropy budget -- Analysis of a reduced order atmospheric model
Stéphane Vannitsem, Carlos A. Pires, David Docquier
The information entropy budget and the rate of information transfer between variables is studied in the context of a nonlinear reduced-order atmospheric model. The key ingredients…
Impact of tropical teleconnections on the long-range predictability of the atmosphere at midlatitudes: A reduced-order multi-scale model perspective
Stephane Vannitsem
Teleconnections between the tropical and the extratropical climates are often considered as a potential source of long-term predictability at seasonal to decadal time scales in the…
Variability and Predictability of a reduced-order land atmosphere coupled model
Anupama K Xavier, Jonathan Demaeyer, Stéphane Vannitsem
This study delves into the predictability of atmospheric blocking, zonal, and transition patterns utilizing a simplified coupled model. Initially, we comprehensively scrutinize the…
A general theory to estimate Information transfer in nonlinear systems
Carlos A. Pires, David Docquier, Stéphane Vannitsem
A general theory for computing information transfers in nonlinear stochastic systems driven by deterministic forcing and additive and/or multiplicative noises, is presented. It ext…
Multistability in a Coupled Ocean-Atmosphere Reduced Order Model: Non-linear Temperature Equations
Oisín Hamilton, Jonathan Demaeyer, Stéphane Vannitsem +1
Multistabilities were found in the ocean-atmosphere flow, in a reduced order ocean-atmosphere coupled model, when the non-linear temperature equations were solved numerically. In t…
Identifying efficient ensemble perturbations for initializing subseasonal-to-seasonal prediction
Jonathan Demaeyer, Stephen G. Penny, Stéphane Vannitsem
The prediction of the weather at subseasonal-to-seasonal (S2S) timescales is dependent on both initial and boundary conditions. An open question is how to best initialize a relativ…
Extratropical low-frequency variability with ENSO forcing: A reduced-order coupled model study
Stéphane Vannitsem, Jonathan Demaeyer, Michael Ghil
The impact of the El Niño-Southern Oscillation (ENSO) on the extratropics is investigated in an idealized, reduced-order model that has a tropical and an extratropical module. Unid…
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…
Statistical Postprocessing for Weather Forecasts -- Review, Challenges and Avenues in a Big Data World
Stéphane Vannitsem, John Bjørnar Bremnes, Jonathan Demaeyer +21
Statistical postprocessing techniques are nowadays key components of the forecasting suites in many National Meteorological Services (NMS), with for most of them, the objective of…
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…
Comparison of stochastic parameterizations in the framework of a coupled ocean-atmosphere model
Jonathan Demaeyer, Stéphane Vannitsem
A new framework is proposed for the evaluation of stochastic subgrid-scale parameterizations in the context of MAOOAM, a coupled ocean-atmosphere model of intermediate complexity.…
Exploring the Lyapunov instability properties of high-dimensional atmospheric and climate models
Lesley De Cruz, Sebastian Schubert, Jonathan Demaeyer +2
The stability properties of intermediate-order climate models are investigated by computing their Lyapunov exponents (LEs). The two models considered are PUMA (Portable University…