OpenDA

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
• DELSA

Language interfaces

• C/C++
• Java
• Fortran77/90

These files are part of the OpenDA software. For more information see our website at http://www.openda.org