Changes between Version 19 and Version 20 of FeaturesofPdaf

Timestamp:

Feb 12, 2012, 6:39:02 PM (12 years ago)

Author:

lnerger

Comment:

--

FeaturesofPdaf

@@ -29 +29 @@
  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 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 is called through a well-defined standard interface. This allows, for example, to switch between the LSEIK, LETKF, and LESTKF 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. 
@@ -51 +51 @@
  * Notebook Apple !MacBook, Mac OS X 10.6, gfortran, OpenMPI
  * SGI Altix ICE, SLES 10 operating system, ifort compiler 11.1, MVAPICH2
- * SGI Altrix Ultraviolet, SLES 11 operating system, ifort compiler 12.1, SGI MPT 2.05
+ * SGI Altrix UltraViolet, SLES 11 operating system, ifort compiler 12.1, SGI MPT 2.05
 
 == Test cases ==