588 citations
- Centre National de la Recherche ScientifiqueFR11 papers
- Sorbonne UniversitéFR10 papers
- Institut de Recherche pour le DéveloppementFR7 papers
- Institut Pierre-Simon LaplaceFR6 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR4 papers
- Laboratoire des Sciences du Climat et de l'EnvironnementFR4 papers
- Nansen Environmental and Remote Sensing Center4 papers
- Princeton UniversityUS4 papers
- CEA Paris-SaclayFR3 papers
- NOAA Geophysical Fluid Dynamics LaboratoryUS3 papers
- Centre National de Recherches MétéorologiquesFR2 papers
- Columbia UniversityUS2 papers
22 papers
Variable projection framework for the reduced-rank matrix approximation problem by weighted least-squares
Pascal Terray
In this monograph, we review and develop variable projection Gauss-Newton, Levenberg-Marquardt and Newton methods for the Weighted Low-Rank Approximation (WLRA) problem, which has…
Leveraging deterministic weather forecasts for in-situ probabilistic temperature predictions via deep learning
David Landry, Anastase Charantonis, Claire Monteleoni
We propose a neural network approach to produce probabilistic weather forecasts from a deterministic numerical weather prediction. Our approach is applied to operational surface te…
Learning 4DVAR inversion directly from observations
Arthur Filoche, Julien Brajard, Anastase Charantonis +1
Variational data assimilation and deep learning share many algorithmic aspects in common. While the former focuses on system state estimation, the latter provides great inductive b…
Semi-automatic tuning of coupled climate models with multiple intrinsic timescales: lessons learned from the Lorenz96 model
Redouane Lguensat, Julie Deshayes, Homer Durand +1
The objective of this study is to evaluate the potential for History Matching (HM) to tune a climate system with multi-scale dynamics. By considering a toy climate model, namely, t…
Explainable Artificial Intelligence for Bayesian Neural Networks: Towards trustworthy predictions of ocean dynamics
Mariana C. A. Clare, Maike Sonnewald, Redouane Lguensat +2
The trustworthiness of neural networks is often challenged because they lack the ability to express uncertainty and explain their skill. This can be problematic given the increasin…
Acute sensitivity of global ocean circulation and heat content to eddy energy dissipation time-scale
Julian Mak, David P. Marshall, Gurvan Madec +1
The global ocean overturning circulation, critically dependent on the global density stratification, plays a central role in regulating climate evolution. While it is well-known th…