22 | | * `fully parallel`: For this implementation one needs to use a parallel computed with a sufficient number of processes such that the data assimilation program run be run with a concurrent time stepping of all ensemble states. Thus, if one runs each mode task with '''n''' processes and the ensemble has '''m''' members, the program has to run with '''n''' times '''m''' processes. This parallelism allows for a simplified implementation as each model task integrated only one model state and the model is always going forward in time. |
23 | | * `fully flexible`: This variant allows to run the assimilation program in a way so that a model task (set of processors running one model integration) can propagate several ensemble states successively. In the extreme case, this could mean that one only a a single model task that is successively performing the integration of all ensemble states. The implementation for this variant is a bit more complicated, because one has to ensure that the model can jump back in time. |
| 22 | * '''fully parallel''': For this implementation one needs to use a parallel computed with a sufficient number of processes such that the data assimilation program run be run with a concurrent time stepping of all ensemble states. Thus, if one runs each mode task with '''n''' processes and the ensemble has '''m''' members, the program has to run with '''n''' times '''m''' processes. This parallelism allows for a simplified implementation as each model task integrated only one model state and the model is always going forward in time. |
| 23 | * '''fully flexible''': This variant allows to run the assimilation program in a way so that a model task (set of processors running one model integration) can propagate several ensemble states successively. In the extreme case, this could mean that one only a a single model task that is successively performing the integration of all ensemble states. The implementation for this variant is a bit more complicated, because one has to ensure that the model can jump back in time. |