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OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement data-assimilation and calibration for arbitrary numerical models. OpenDA wants to stimulate the use of data-assimilation and calibration by lowering the implementation costs and enhancing the exchange of software among researchers and end-users.

A model that conforms to the OpenDA standard can use all the tools that are available in OpenDA. This allows experimentation with data-assimilation/calibration methods without the need for extensive programming. Reversely, developers of data-assimilation/calibration software that make their implementations compatible with the OpenDA interface will make their new methods usable for all OpenDA users (either for free or on a commercial basis).

OpenDA has been designed for high performance. Hence, even large-scale models can use it. Also, OpenDA allows users to optimize the interaction between their model and the data-assimilation/calibration methods. Hence, data-assimilation with OpenDA can be as efficient as with custom-made implementations of data-assimilation methods.

OpenDA is an Open Source project. Contributions are welcome from anyone wishing to participate in the further development of the OpenDA toolset.

Features of OpenDA

Data-assimilation methods

  • Ensemble KF (EnKF)
  • Ensemble SquareRoot KF (EnSR)
  • Steady State KF
  • Particle Filter
  • 3DVar
  • DudEnKF (still under research)
  • DudEnSR (still under research)

Parameter estimation (calibration) methods:

  • Dud
  • Sparse Dud
  • Simplex
  • Powell
  • Gridded full search
  • Shuffled Comples Evolution (SCE)
  • Generalized Likelihood Uncertainty Estimation (GLUE)
  • (L)BFGS
  • Conjugate Gradient: Fleetjer-Reeves, Polak-Ribiere, Steepest Descent
  • Uncertainty Analaysis methods
  • GLUE

Language interfaces

  • C/C++
  • Java
  • Fortran77/90

These files are part of the OpenDA software. For more information see our website at