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Changes between Version 8 and Version 9 of FeaturesofPdaf

v8	v9
31	31	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.
32	32	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.
33		1. For the case that you don't want to touch you model code at all, PDAF offers an offline mode. In this case PDAF is compiled with the supporting routines to handle the observations separately from the model. Then the model and the assimilation step are excuted separately. However, we don't recommend this strategy, because it's computationally less efficient.
	33	1. PDAF also offers an offline mode. This is for the case that you don't want to touch you model code at all. In the offline mode, PDAF is compiled separately from the model together with the supporting routines to handle the observations. Then the model and the assimilation step are executed separately. While this strategy is possible, we don't recommend it, because it's computationally less efficient.
34	34
35	35	== Requirements ==