Data Assimilation

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Julien Brajard

Research
Area of Expertise: 
computer science
data assimilation
geo-sciences
mathematics
oceanography
remote sensing
statistics

My work is in the field of remote sensing, inverse modelling, machine learning and data assimilation. The objective is to propose new methodologies in order to extract knowledge from data and physical systems, more specifically in oceanography.

Those methodologies were apply to estimate and forecast key variables and their associated uncertainty in the ocean such as phytoplankton and surface currents. The methodologies developed were using remote sensing data (satellite sensors).

Employment
Research Group: 
Data Assimilation
Job Position: 
Researcher

Summer School: “Crash Course on Data Assimilation - Theoretical foundations and advanced applications with focus on ensemble methods”

The Nordic Centre of Excellence Ensemble-based data assimilation for environmental monitoring and prediction - EmblA coordinated by the Nansen Center organises a 4-days summer school for PhD-level students and early stage scientists with beginner or no notions of data assimilation.

EmblAUS: Ensemble-based data Assimilation for environmental monitoring and prediction in the Unstable Subspace

Bayesian Data Assimilation  

EmblAUS is a part of the Nordic Center of Excellence EmblA. It is structured along two tasks:

Task 1 – Mathematical Formalism (12 months)

Task 2 – Numerical Analysis (12 months)

EmblAUS employs one postdoctoral scientist: Patrick N. Raanes 

Project Details
Funding Agency: 
NordForsk
Coordinating Institute: 
Nansen Environmental and Remote Sensing Center
Project Status: 
Completed

DASIM: Data Assimilation for a new generation of Sea Ice Models

DASIM II follows the 1-year pilot project DASIM I and will explore the mathematical issues for assimilating data in modern sea-ice models

DASIM comes as the natural fusion between the recent achievements in Lagrangian Data Assimilation (LaDA) and sea-ice modelling. Most existing models treat the sea-ice as a visco-plastic and are unable to describe important features such as cracks, leads, and ridges. Only recently has sea-ice motion been described with Lagrangian dynamics.

Project Details
Funding Agency: 
Office of Naval Research
Coordinating Institute: 
Nansen Environmental and Remote Sensing Center
Project Status: 
Completed

REDDA: Reduced subspace in big data treatment: A new paradigm for efficient geophysical Data Assimilation

Big Data methods in geosciences

Environmental science has been a primary challenge test-ground for Data Assimilation. 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.

Project Details
Funding Agency: 
Research Council of Norway
Coordinating Institute: 
Nansen Environmental and Remote Sensing Center
Project Status: 
Completed

DADA: Detection and Attribution of climate change based on Data Assimilation

DADA is a theoretical project aimed at developing new strategies and methods for the detection and attribution of climate change based on data assimilation.

How can observations be used to best evidence the influence on climate of human activities, among other forcings ? Statistical methods of Detection and Attribution (D&A) were designed to answer this question which is of high societal relevance when it comes to adaptation and mitigation policy.

Project Details
Funding Agency: 
Agence Nationale Francaise de la Recherche
Coordinating Institute: 
Nansen Environmental and Remote Sensing Center
Project Status: 
Completed

ES-PhD: Ensemble Smoother - Patrick Raanes

Research on the ‘Ensemble Smoother’ (ES) method for parameter estimation (history matching) and model conditioning.

Project tasks include:

  • Evaluation of ES for parameter estimation in a number of known test problems of varying complexity to evaluate ES performance with respect to other traditional methods
  • Evaluation, implementation and testing of recently proposed iterative smoother algorithms
  • Development, implementation and testing of new iterative smoother algorithms
  • Application and demonstration of smoother algorithms in agree field examples.
Project Details
Funding Agency: 
Statoil E&P
Coordinating Institute: 
Nansen Environmental and Remote Sensing Center
Project Status: 
Completed
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