Alberto Carrassi

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Alberto Carrassi

Research interests

My research interests focus on the development of efficient methods to assimilate and combine data with numerical models of environmental systems. I work at the bridge between applied mathematics and geosciences and my main expertise is in dynamical systems and stochastic filtering applications to geophysics. I am interested in fundamental issues in the theory of data assimilation and in efficient methods to quantify uncertainty in high-dimensional problems such those encountered in climate science. 

Some specific areas of research include:

  • Assimilation in the unstable subspace
  • Treatment of model error in data assimilation
  • Ensemble Kalman filtering
  • Adaptive observations
  • New applications of the data assimilation: model selection, attribution of climate change 

Together with Laurent BertinoI lead the Data Assimilation group at NERSC. I currently coordinate three international projects on efficient reduced order methods for data assimilation in high-dimensional chaotic system (REDDA from the Norwegian Research Council), on Bayesian data assimilation (EmblAUS from the Nordic Countries Research Council) and on data assimilation for Lagrangian sea-ice models (DASIM from the US Office of Naval Research). I also work in the framework of the Nordic Countries Centre of Excellence on ensemble-based data assimilation EmblA.

Recent publications 

The complete list of my published papers is below. 

 The papers currently under revision are:

  1. Grudzien, C., A. Carrassi and M.Bocquet, 2018. Asymptotic forecast uncertainty and the unstable subspace in the presence of additive model error. J. Uncertainty Quantification (Available here). 
  2. Carrassi, A., M. Bocquet, L. Bertino and G. Evensen, 2018. Data assimilation in the geosciences. An overview on methods, issues and perspectives. WIREs Climate Change. (Available here).
  3. Metref, S., A. Hannart, J. Ruiz, M. Bocquet, A. Carrassi and M. Ghil, 2018. Estimating model evidence using ensemble-based data assimilation with localization - The model selection problem. Q. J. Roy. Meteorol. Soc. (Available here
  4. Raanes, P., M. Bocquet and A. Carrassi, 2018. Adaptive covariance inflation in the ensemble Kalman filter by Gaussian scale mixtures.  Q. J. Roy. Meteorol. Soc. (Available here)
  5. Grudzien, C., A. Carrassi and M. Bocquet, 2018. Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error. Nonlin. Processes Geophys. Discuss. (Available here


I am currently supervising three postdocs: Ali Aydogdu (postdoc, 2017- ), Colin Grudzien (postdoc, 2016 - ) and Patrick Nema Raanes (postdoc, 2016 - ), and co-supervising one PhD student, Francine Janneke Schevenhoven, at the University of Bergen, Gephysical Department.  

Past supervision: Matthias Rabatel (postdoc, 2016-2017), Maxime Tondeur (MsC student, 2016-2017, Ecole des Mines, France) and Robin Weber (MsC student, 2013-2014, Un. of Heidelberg, Germany).

News ... 

  • Following the success of its last year 1st edition, we have lunched this year as well the 4-days summer school Crash Course on Data Assimilation at NERSC, on 22-25 May, 2018
  • The BsC and MsC course on Data Assimilation at Dept. of Mathematics of the University of Bergen started on September 2017. 
  • The Springer book "Mathematical paradigms of Climate Science" has been published and it contains a chapter about model error treatment in DA I co-authored with Stephane Vannitsem.


-- BsC/MsC Course on Data Assimilation at Dept. of Mathematics (University of Bergen).

   September-November 2017. Co-lectured with Geir Evensen, Laurent Bertino and Patrick Raanes

   The full description of the course along with its schedule can be found here, or via the Math department webpage here.

   Exams date: 30th November and 1st December.   

-- Short course "Data assimilation in the geosciences - an overview". SC1.13/NP8.5, EGU 2018. Vienna, Austria, 08-13 April. 

   Co-lectured with Olivier Talagrand and Marc Bocquet. 

Editorial and committee appointments 

Editor for Nonlinear Processes in Geophysics 

Member of scientific committee: EnKF annual workshop, EGU Session NP5.1 on Inverse problems and data assimilation in geophysics, SIAM Conference on applications of dynamical systems 

Upcoming and recently attended meetings   

  1. EGU 2018, 08-13 April 2018, Vienna, Austria
  2. SIAM conference on uncertainty quantification, 16-19 April 2018, Garden Grove, USA
  3. "Numerical modelling, Predictability and Data Assimilation in Weather, Ocean and Climate", A Symposium honoring Anna Trevisan, 17-20 October, Bologna, Italy  
  4. "SIAM Conference on Mathematical and Computational Issues in the Geosciences", 11-14 September 2017, Erlangen, Germany
  5. "WMO Data Assimilation Symposium", 11-15 September 2017, Florianopolis, Brasil

Recent lectures at international schools   

  1. Crash-Course on data assimilation: Theoretical foundation and advanced applications with focus on ensemble methods "06-09 June 2017, Bergen, Norway.
  2. "Summer School on Data Assimilation and its application in oceanography, hydrology, risk & safety and reservoir engineering", 17-28 July 2017, Sibiu, Romania. 


There are not open vacancies in the group at the moment, but more opportunities will come up soon. If you are interested in working with me in the DA group at NERSC as PhD or Postdoc, here are some lines of research I am currently prioritising:

  • Reduced order ensemble-based methods
  • Efficient particle filters
  • Coupled data assimilation  

Some of them have already attached funding. For others we can explore possible sources.

Not-Science related...

 I am a certified Iyengar Yoga teacher (level: Base 2) and currently teach at yogarommet in Bergen. It would be great to meet you there !

Peer Review Publications and Books

34 total publications.


  1. Palatella L, Carrassi A, Trevisan A. Lyapunov vectors and assimilation in the unstable subspace: theory and applications. Journal of Physics A: Mathematical and Theoretical. 2013;46(25):254020.


  1. Carrassi A, Vannitsem S. Accounting for Model Error in Data Assimilation. In: Oberwolfach Reports. Mathematical and Algorithmic Aspects of Atmosphere-Ocean Data Assimilation. 2012. p. 3417 - 3471.


  1. Carrassi A, Vannitsem S. TREATMENT OF THE ERROR DUE TO UNRESOLVED SCALES IN SEQUENTIAL DATA ASSIMILATION. International Journal of Bifurcation and Chaos. 2011;21(12):3619 - 3626.