Changes between Version 10 and Version 11 of WikiStart

Timestamp:

Aug 23, 2010, 9:49:43 AM (14 years ago)

Author:

lnerger

Comment:

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WikiStart

@@ -10 +10 @@
 Data assimilation is used to combine observations of some system, like the ocean or the atmosphere, with a numerical model simulating this system. As both, the observations and the numerical model are not exact, the combined information of both sources can provide a better estimate of the true state of the system than each of the information sources alone.
 
-Performing data assimilation with advanced algorithms and large-scale models is computationally extremely demanding. However, when ensemble-based data assimilation algorithms are used, the assimilation system can use supercomputers very efficiently. PDAF simplifies the implementation of data assimilation systems for supercomputers using existing model code by the following:
+Performing data assimilation with advanced algorithms and large-scale models is computationally extremely demanding. However, with ensemble-based data assimilation algorithms supercomputers can be used very efficiently. PDAF simplifies the implementation of data assimilation systems for supercomputers using existing model code by the following:
 
  1. PDAF provides fully implemented, parallelized, and optimized ensemble-based algorithms for data assimilation. Currently, these are ensemble-based Kalman filters like the LSEIK, LETKF, and EnKF methods. 
- 1. PDAF is attached to the model source code by minimal changes to the code. These changes only concern the general part of the code, but not the numerics of it. In addition, a small set of routines is required that are specific to the model or the observations to be assimilated. These routines can be implemented like routines of the model.
- 1. PDAF is called through a well-defined standard interface. This allows, for example, to switch between the LSEIK and LETKF methods without additional coding. In addition, different observational data sets can be used within a single executable.
+ 1. PDAF is attached to the model source code by minimal changes to the code. These changes only concern the general part of the code, but not the numerics of the model. In addition, a small set of routines is required that are specific to the model or the observations to be assimilated. These routines can be implemented like routines of the model.
+ 1. PDAF is called through a well-defined standard interface. This allows, for example, to switch between the LSEIK and LETKF methods without additional coding.
  1. PDAF provides parallelization support for the data assimilation system. If your numerical model is already parallelized, PDAF enables the data assimilation system to run several model tasks in parallel within a single executable. However, PDAF can also be used without parallelization, for example to test small systems.
  1. PDAF does not require that your model can be called as a subroutine. Rather PDAF is added to the model and the formed data assimilation system can be executed pretty much like the model-program would without data assimilation.