Changes between Version 4 and Version 5 of OnlineorOfflineImplementation

Timestamp:

Oct 3, 2010, 9:46:10 PM (14 years ago)

Author:

lnerger

Comment:

--

OnlineorOfflineImplementation

@@ -9 +9 @@
 There are also some user-supplied routines that are not required in the case of the offline implementation. In particular these are `U_distribute_state`, `U_collect_state`, and `U_next_observation`. However, the implementation of these routines should not pose a challenge. 
 
-Avoiding the need to touch the model code can generally lead faster to a working assimilation system. When the model code is modified in the online implementation, one has to take care that all transfers of information between the model and the data are consistent. In addition, it might be that some arrays, apart from the model fields in the state vector, need to be re-initialized before a new ensemble state is integration. Over all, this should not be a problem, if the person who performs the implementation does know the model well or has very good contacts to a person with this experience. If you don't really know the model code, it can be difficult to implement the online variant. 
+Avoiding the need to touch the model code can generally lead faster to a working assimilation system. When the model code is modified in the online implementation, one has to take care that all transfers of information between the model and the data are consistent. For example spatial information about the model grid can be necessary to implement the observation operator. This information is usually stored in one or more arrays of the model. Thus, it is recommended to use the information already available in the model. This, however, required that the person who performs the implementation understands the model code sufficiently well to identify the key arrays required for the online implementation of PDAF.   
+In addition, it might be that some arrays, apart from the model fields in the state vector, need to be re-initialized before a new ensemble state is integrated. This can required some understanding about the implementation of the model's time stepping scheme.
+Over all, this should not be a problem, if the person who performs the implementation does know the model well or has good contacts to a person with this experience. If you don't really know the model code, it can be difficult to implement the online variant. 
 
 When the assimilation system uses a large-scale model, there are more considerations about online and offline systems. In the online mode, a single ensemble has to be run using a rather large number of processors. In case of the offline mode, the integration of each ensemble member state can be performed using a single run with a smaller number of processors. When these runs are completed, the assimilation executable is run. Here the number of processors can be set rather independently from the number user for the model runs (This will depend on file output). In this respect the consideration is how to obtain the best throughput of the assimilation system. As large-scale models are typically run on computers using a batch or scheduling system one has to takes its configuration into account. Is it more likely that the single but large job is executed, or are a larger number of smaller jobs more likely to be executed. If the batch system only allows a very limited number of concurrent jobs of a single user, then the ensemble integration wil become essentially serial. (However, there can be possibilities to execute several parallel model integrations within a single batch job)