20th international EnKF workshop (2025)

The ensemble Kalman filter (EnKF) and its versatile variants are renowned for their remarkable data assimilation capabilities in diverse domains such as atmospheric, oceanic, hydrologic, biomedical, biologic, and petroleum reservoir systems. By providing a platform for thought-provoking presentations and meaningful discussions, the EnKF workshop seeks to foster collaboration among technical experts, practitioners, researchers, and students. Together, we will showcase cutting-edge research findings, exchange practical insights, and collectively explore uncharted territories by identifying crucial challenges. Join us to deepen your knowledge, expand your network, and contribute to the advancement of data assimilation.

Venue

• Ullensvang Hotel, Norway.
• June 16 - 18, 2025.
• The local climatology
• Physical attendance only (no virtual participation or videoconferencing).
• There are excellent hiking opportunities in the area, and the program includes a guided hike, possibly including vistas of the Folgefonna glacier.
• The hotel includes pools with spa facilities, with access to the fjord for more daring swimmers.

Images from venue

The day-long hike to scenic Trolltunga (pictured here) has its starting point about 1 hour’s drive away from the hotel. The path is very well trodden in tourist season. We will not be able to assist with the planning of a trek to Trolltunga, but wish to note that

• Parking at the starting point for the trek must be booked (preferably weeks) in advance.
• Public transport (stage 1, stage 2) is also possible.

Program

Travel to/from Bergen must be arranged by participants individually, to fit around the program. Inbound flights will need to be on June 15 or earlier.

• The WS/WS will be a communal effort to advance DA research and applicability.
• Posters are on display throughout the workshop, and should be presented during both poster sessions. Size: max A0, preferably upright (portrait).
• Talks should have a run time of 22 min, to be followed by 8 min. Q&A.
• This conference does not publish papers or proceedings.

Invited speakers

• 

  Ian Grooms

  University of Colorado, Boulder, USA
  Ensemble data assimilation on the simplex: Application to the ice thickness distribution
• 

  Marc Bocquet

  Cerea, École des Ponts and EdF R&D, France
  ML and DA
• 

  Jeffrey Anderson

  NSF NCAR, USA
  A Quantile-Conserving Ensemble Filtering Framework for Non-Gaussian and Nonlinear Data Assimilation
• 

  Kjetil Bjørke

  Equinor, Norway
  Big reservoir applications of ensemble methods

Presentations

Patrick Laloyaux	talk	Using Data Assimilation tools to explain ECMWF machine learning models
Dana Grund	talk	Calibration of High-Resolution Atmospheric Models
Luxi Yu	talk	Advancing Bioprocessing with Ensemble Kalman Filters: From State Estimation to Knowledge Transfer
Alexandre A. Emerick	talk	Machine Learning-Based Localization for Scalar Parameters in Data Assimilation
Jeffrey Anderson	talk	A Quantile-Conserving Ensemble Filtering Framework for Non-Gaussian and Nonlinear Data Assimilation
Marc Bocquet	talk	Are ensemble-based data assimilation methods necessary for accurate filtering?
Masashi Minamide	talk	Improving Tropical Cyclone Intensification Prediction using High Resolution All-sky GOES Satellite Data Assimilation
François Counillon	talk	Alternative methods for mitigating model bias in Earth System models
Sébastien Barthélémy	talk	Super-resolution data assimilation
Yiguo Wang	talk	Achievements of the CoRea Project in Coupled Climate Reanalysis
Ian Grooms	talk	Ensemble data assimilation on the simplex: Application to the ice thickness distribution
Yue Ying	talk	Advancing the TOPAZ ocean and sea ice data assimilation system: Algorithmic innovations enabled by NEDAS
Yong Do Kim	talk	Using Multipoint Statistics and Connected Region Multiplier for Generating Initial Ensemble with Limited Reservoir Models
Rebecca Gjini	talk	Derivative-free, ensemble-based optimization for inverse problems with time-averaged data and chaotic dynamics
Leire Retegui-Schiettekatte	talk	Analyzing the performance of ensemble-based disaggregation in GRACE(-FO) Terrestrial Water Storage Data Assimilation and exploring a deterministic alternative
Andreas Størksen Stordal	talk	Weight correction and evidence computation for iterative ensemble methods
Max Ramgraber	talk	Adaptive and scalable triangular measure transport filters
Kjetil Bjørke	talk	History Matching the Troll Reservoir Model with Ensemble
Zhuo-Ran Liu	poster	Generalized Approximate Bayesian Inference with an Equivariant Neural Operator Framework
Luxi Yu	poster	Advancing Bioprocessing with Ensemble Kalman Filters: From State Estimation to Knowledge Transfer
Gabriel Serrao Seabra	poster	Leveraging Diffusion Posterior Sampling for Data Assimilation in Geological Carbon Storage Projects
Niklas Becker	poster	Ensemble methods for methane emission estimation
Claire Lauvernet	poster	Combining multisource water and pesticide data with coupled surface/subsurface hydrological modeling to reduce its uncertainty.
Lige Cao	poster	Impact of Instantaneous Parameter Sensitivity on Ensemble-Based Parameter Estimation: Simulation With an Intermediate Coupled Model
Geir Evensen	poster	Ensemble History Matching: Conditioning Reservoir Models on Dynamic Data
Karoline Holand	poster	Optimized inflow forecasts for Norwegian hydropower plants during snowmelt periods
Sergey Alyaev	poster	AI-Enhanced Well-Steering: Open Workflow Implementation with Latent Space Geomodeling and Uncertainty Quantification
Rolf Lorentzen	poster	Multi-Data Assimilation of the Smeaheia CO2 Storage Model
Kristian Fossum	poster	Incorporating Jacobian Information in Ensemble Kalman Inversion for Real-Time Geosteering
Mathias Methlie Nilsen	poster	Hessian Approximations for Non-Gaussian Ensemble-based Optimization
Dean Oliver	poster	Stacking forecasts from multimodal models and scenarios
Xiaodong Luo	poster	A scaling method to improve covariance matrix estimation and its application in ensemble-based reservoir history matching
Hibat Errahmen Djecta	poster	Solving Geosteering as a Partially Observable Markov Decision Process: Integrating Data Assimilation and Reinforcement Learning
Patrick N. Raanes	poster	'Ensemblized' linear least squares (LLS)

Photos

Pictures from workshop

Background

The EnKF is a data assimilation method that was co-invented and has been continuously developed by researchers at NORCE and NERSC. Over the last three decades, the EnKF and related ensemble methods, has emerged as a highly effective and widely adopted approach for data assimilation in large-scale models, and have made profound impacts on the advancements of various disciplines and promoted value creations for relevant industries.

Purpose

While the fundamental concept of ensemble methods is simple, practical implementations often demand problem-specific modifications for success. Our workshop aims to bridge the expertise of specialists from various fields to investigate the foundations and interconnections of EnKF-related methods that have demonstrated effectiveness in diverse environments. In so doing, we strive to enhance the robustness and efficiency in applications. Beyond practical applications, this gathering also facilitates the exchange of innovative research ideas, methods, algorithms, and workflows with the potential to further enhance the performance of EnKF and related approaches.

History

In 2006, the inaugural EnKF workshop was held in Voss, Norway, marking the beginning of an annual tradition. Throughout the years, the EnKF workshop has consistently attracted participants from a wide range of scientific disciplines. The cross-pollination of ideas and the exchange of scientific advancements have fostered vibrant discussions and elevated the workshop’s scientific calibre to a high level. As a result, the annual international EnKF workshop has now established itself as a paramount event within the data assimilation community.

Full listing of previous workshops

Sponsors

REMEDY

Please contact enkf@data-assimilation.no if you want to sponsor the workshop.