Program

Addressing Nonlinearity in Data Assimilation

Formulation and use of 3D-hybrid and 4D-hybrid ensemble covariances in the Météo-France global data assimilation system

A Hybrid Ensemble-Variational Approach for Greenhouse Gas Source Inversions in the Integrated Forecasting System (IFS)

Learnings from petroleum reservoir history matching

Empirical optimal vertical localization derived from large ensembles

Improving Forecasts of Land Surface Carbon Cycling using the Data Assimilation Research Testbed (DART)

Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology

The impact of Aolus satellite wind lidar observation in the global NWP system of DWD

Towards coupled air-sea data assimilation in a regional model

Towards the inversion of plumes from power plants and industrial sites in satellite CO2 images using deep neural networks

Testing a WRF-based modelling chain for operational forecasting under different data assimilation inputs

Estimation of Ocean Biogeochemical Parameters in an Earth System Model Using ensemble data assimilation methods

On Gaussianity and nonlinearity in state- and parameter estimation in earthquake cycle models

Lightning data assimilation: impact on precipitation and lightning forecast

Assimilation of Camera Cloud Motion Vectors (CAM-CMVs) into a Regional NWP system

Farewell hybrid covariances: Moving to fully ensemble-derived background-error covariances for NWP at Environment and Climate Change Canada

Recent Development of Multiscale Data Assimilation for Numerical Weather Prediction

The Weak Temperature Gradient approximation as a balance principle for convective-scale data assimilation

Synergistic assimilation of cloud and dynamical information based on cloud-dependent background field error covariance

Benefit and challenges in assimilating near-surface temperature and humidity observations in complex terrain

Weakly Constrained LETKF for Convective-Scale Data Assimilation

Improving short range prediction of convective weather systems using a 1000-member ensemble Kalman filter with 30-second update

A bias-kalman-filter for operational storm-surge forecasting

Added value of assimilating ground observations from personal weather stations in a convective-scale numerical weather prediction system

Toward efficient control of extreme weather events

Assimilation of 3D radar information at convective scales at Deutscher Wetterdienst (DWD)

New possibilities with AROME 3d-Envar: assimilation of MTG/LI Flash Extend Accumulation (FEA) and direct assimilation of ground-based radar reflectivity

Measures of imbalance in convective-scale data assimilation

Comparing the assimilation of visible and infrared satellite observations to radar reflectivity for convective-scale numerical weather prediction

Intelligent Camera Cloud Operators for Convective Scale Numerical Weather Prediction

Predictability of moist convection through ensemble convective-scale all-sky satellite data assimilation

A 3DEnVar scheme for the operational convective scale NWP system Arome-France.

Model error correction with data assimilation and machine learning - from theory to the ECMWF forecasting system

Data Learning 2.0: integrating Data Assimilation with Machine Learning to deal with limitations in models and data

Emulating 3D-Var Data Assimilation using Variational Autoencoder

Hybrid Data Assimilation - Machine Learning for Model Error Estimation and Correction: application to the ECMWF IFS model

Hybrid NWP-Machine Learning or End-to-End Learning?

Data Assimilation and Predictability by Machine Learning Approach

Developing observation operator based on machine learning model for satellite data assimilation

Mitigating sampling errors in ensemble data assimilation with Probit-space Ensemble Size Expansion (PESE)

Advances in high dimensional nonlinear filtering - intermediate updates and novel localisation strategies

Bridging traditional data assimilation and optimal transport

A kernel extension of the Ensemble Transform Kalman Filter

Using Koopman and Perron Frobenius Operators For Non-Linear Data Assimilation

A new computational approach for spatially correlated observation error statistics in data assimilation

The importance of anchor observations in data assimilation

Towards an operational assimilation of RAMAN lidar temperature and mixing ratio profiles with COSMO/KENDA-1

Adaptive Meshing for Ensemble Based Data Assimilation

Tailoring data assimilation to discontinuous Galerkin models

Nongaussian based Kalman Filters

A New Localization Method for Non-Gaussian Variations of the EnKF: “The Ensemble Squeeze Localization”

Continuous nonlinear data assimilation

Data assimilation for a two-layer quasi-geostrophic model using an Ensemble Synchronization Particle Filter

Continuous Data Assimilation: A Nonlinear Algorithm & Connection to Physics

Rank Histogram Estimators for Multi-level Data Assimilation

Parameter estimation for nonlinear PDEs

Is there a relationship between cornered--hat methods and a residual approach to estimate system uncertainty?

Assimilation of nonlinear observations using the maximum likelihood ensemble filter with exact Newton optimization

Improving background error covariance estimation with Multilevel Monte Carlo Methods

Soft Re-Centred Ensemble of Data Assimilations

Incorporating non-Gaussian observation errors into variational methods

Destination Earth, digital twins, data assimilation, deep learning

Convolutional Neural Network-based Adaptive Localization for an Ensemble Kalman Filter

Generating background error covariances for hydrometeors with conditional generative adversarial networks

The GLObal-to-Regional ICON Digital Twin for high-impact weather applications

Designing new DA software for Operational Global NWP

Scale-dependent background-error covariance modelling, with application to global ocean data assimilation

A neural network-based forward operator for assimilating near-infrared satellite images

Assimilation of Transformed Retrievals from IASI radiances at the Met Office

Data-Driven Tools: From Ideal models to Geophysical systems

Advanced diagnostic tools to assess the observations impact in the analysis and forecast

The Mean-Field Ensemble Kalman Filter: Gaussian and Particle Approximations

A Hybrid Differential-Ensemble Linear Forecast Model for 4D-Var