Brief introduction to OpenDA native components
Current practice in data assimilation software
Data assimilation techniques are widely used in various modeling areas like
meteorology, oceanography and chemistry. Most implementations of data
assimilation methods however are custom implementations specially designed
for a particular model. This is probably a consequence of the lack of
generic data assimilation software packages and tools. An advantage of
these custom implementations is that they are in general very
computationally efficient. But the use of custom implementations has a
number of significant disadvantages:
- Costs - The development and implementation of these methods is very
time consuming and therefore expensive.
- Incompatibility - It is very hard to reuse these data assimilation
methods and tools for other models than they were originally developed for.
How OpenDA improves the situation
The OpenDA project tries to enhance the reuse of data assimilation software
by offering a modular framework for data assimilation, containing methods
and tools that can be easily applied for general applications. OpenDA is set
up in order to be as computationally efficient as possible, without losing
its generic properties. The aim is that applications developed with OpenDA
have a comparable computational performance as custom implementations.
OpenDA offers support for both users and developers of data assimilation
methods. For users it allows models to be quickly connected to the OpenDA
framework and hence to all the methods that are available in OpenDA. For
developers, OpenDA offers efficient basic building blocks that save a lot of
programming work and at the same time makes the new data assimilation
software directly connectable to all OpenDA compliant models.
How OpenDA works
OpenDA provides a generic framework for data assimilation. It is aimed both
at model programmers that want to use data assimilation methods and at
developers of data assimilation methods.
OpenDA for model programmers
For model programmers, OpenDA provides a rich set of data assimilation
methods. To use them, you have to make your model OpenDA compliant. Once
your model can interact with OpenDA, all the OpenDA methods are at your
What is OpenDA compliant?
Making your model OpenDA compliant involves implementing a number of
routines that are going to be called from the data assimilation methods.
The set of routines that you must implement is called the stochastic model
interface. There are other interfaces as well, each one defining a specific
entity called a component. You will read more about components in the next
How OpenDA calls your implementation of the interface routines
OpenDA connects your implementations of these methods to their standard
names. These standard names are used in the implementation of the
data assimilation methods. There are provisions for working with black-box
models(i.e. models for which you do not have the source code), but this
will not be discussed in this document.
Providing your observations
Likewise, your observations must be provided in a OpenDA compliant way. For
the observations there is also a set of routines, called the stochastic
observer interface. Usually, you will not implement the interface but
convert your observations to a format that can be handled by the standard
OpenDA implementation of the stochastic observer component.
OpenDA for developers of data assimilation methods
For developers of data assimilation methods, OpenDA offers a
platform for quickly building data assimilation methods that can be used
from a wide range of models. OpenDA provides various sets of routines that
can be used as building blocks. Such a set is called a component. You will
read more about components in the section Components.
Routines to interact with models
First of all, OpenDA specifies a set of routines to interact with the model
to which the data assimilation must be applied. Each OpenDA compliant model
implements these routines (otherwise it will not be OpenDA compliant). The
specification of this set of routines is called the stochastic model
Routines to interact with observations
A second set of routines that is essential for data assimilation methods
comprises routines to interact with the observations. These include
routines to retrieve values and routines to retrieve meta-information.
Basic building blocks
Finally, there are various sets of basic building blocks (e.g. for handling
vectors, matrices and time). These interact seamlessly with the other OpenDA
components to let you construct data assimilation methods with a minimum of