Summer school Data Assimilation and its applications – big data challenge
July 21th – August 1th 2025
The primary objective of the project is to educate and to familiarize graduate students (MSc and PhD students) with the basic fundamental concepts, as well as in-depth topics, of the data assimilation paradigm and its applications.
The secondary objective is to setup the arena for discussions and debates around the big data challenge present in almost all the practical applications of these methodologies: hydrology, atmospheric sciences, oceanography and geosciences.
The mixture between the fundamental concepts/theoretical background presented in the first week of the event and their implementation in different fields of applications in the second week, is a unique opportunity to grasp the full understanding of the data assimilation world and its challenges.
The objective in data assimilation is generally to find the state of some system.
To find the state one can use a model, but the modelled estimate is subject to uncertainties from simplifications and weak assumptions. The model input uncertainties e.g. imperfect forcing data and uncertain model parameters are also an important source of uncertainties.
One could also just observe the state using either ground-based observations or remote-sensing. Remote-sensing offers many advantages.
Data assimilation is a way to combine models and observations in an optimal way to obtain an estimate of the state that is better than that from models or observations alone. The optimal estimate should be closer to the truth than either the observations or the model.
The huge dimension of the numerical models of the climate system, the vast amount of Earth observational data at our disposal, and the pressure to deliver timely accurate forecasts, have motivated an extraordinary research activity that has led to enormous advances which have subsequently spread out to other domains of science.
At the same time, geophysical DA is an exemplar of a Big Data problem: models have O(109) and the observational datasets O(108). Computationally efficient state estimation and uncertainty quantification must be carried out using massive datasets and huge dynamical models.
8th Summer School on Data Assimilation and its applications Oceanography, Atmospheric Sciences, Risk & Safety and Reservoir Engineering
Our purpose is to get together experts in the field of data assimilation from different schools (statistics, decision analysis, system and control, pure mathematics, engineering, etc.) and to make use of their knowledge by:
- educating graduate students, young and senior researchers;
- transferring knowledge from the best lecturers to the students;
- exposing the Romanian students, academics and researchers to the most recent theoretical/algorithmic approaches and their applications;
- having extensive discussions and exchanging ideas;
- working hands-on with academic and commercial dedicated software.
This summer school targets primarily students and researchers at an early stage of their career with/without previous experience in data assimilation.
Location and period
Location:Corplul N str. Politehnicii nr. 1, Brasov, Romania
Period: July 21th – July 1th 2025
Speakers and topics
The two weeks will cover the theory and applications
Andreas Stordal and Patrick Raanes (NORCE, Norway)
– Ensemble methods, Theory and Phyton exercises
Geir Evensen (NORCE, Norway)
– An integrated story for ensemble methods
Prof. Femke Vossepoel (TU Delft )
– Particle filters
Prof. Arnold Heemink (TU Delft )
– Variational methods
Tina Nane (TU Delft )
– Bayesian Belief Networks
Anca Hanea (CEBRA, Melbourne, Australia)
– Risk quantification, risk management, Expert Judgment and Safety issues
Laurent Bertino (NANSEN center, Norway)
– Oceanography and Environmental Applications
Gosia Kaleta (Shell, The Netherlands)
– Energy related topics
Matteo Ravasi (KAUST, Saudi Arabia)
– Inverse modelling and Machine Learning in Geophysics
Prof. Dr. Martin Verlaan (TU Delft and Deltares, The Netherlands) & Nils van Velzen (Vortech, The Netherlands)
– The Open DA paradigm – theory and the toolbox
Prof. Olga Lucia Montoya (Universidad EAFIT)
– Atmospheric Data Assimilation related topics
Jimmy Zurcher (Equinor)
– Geomodelling and parameterization as basis for decision making
Participants
The lectures and workshops are intended for (graduate) students, however academics, researchers and practitioners may find them entertaining and useful.
Accommodation
TBD
Important: please let us know of any dietary preferences or constraints that you might have amongst the whole group of participants.
Registration fee
- Students 800 €*
- Researchers and Academia 1000 €
* Romanian students can apply for scholarships.
Information about the weekend
TBD
Contact
If you are interested in participating please contact Remus Hanea (rhane@equinor.com) and please attach a CV, short description of your research topic, university of origin and a short motivation for your interest in this event.
For more general enquires please contact Anca Hanea (anca.hanea@unimelb.edu.au).
Organizer committee
Remus Hanea, email: rhane@equinor.com , phone: 004746836687
Anca Hanea, email: anca.hanea@unimelb.edu.au
Prof. Cătălin Bogdan Ciobanu – UNITBV, email: catalin.ciobanu@unitbv.ro