Changes between Version 4 and Version 5 of SoftwarePackage

Timestamp:

Sep 26, 2011, 4:38:17 PM (13 years ago)

Author:

lnerger

Comment:

--

SoftwarePackage

@@ -58 +58 @@
 
 The following example implementations are included in the directories in `testsuite/src/`:
- * dummymodel_1D
+ * `dummymodel_1D`
    * This is the example implementation in which PDAF is fully connected to a model. The model is trivial: At each time step simply the time step size is added to the state vector. We recommend this example as the starting point to look into the online implementation of PDAF.
- * dummymodel_1D_si
+ * `dummymodel_1D_si`
    * This directory contains an analogous example implementation to `dummymodel_1D`. This variant, however, uses the simplified interface of PDAF. In this case, predefined names of the user-supplied subroutines are used such that there is no need to specify them in the call to the interface of PDAF. (The interface looks simpler in this case, but the subroutine names are fixed) 
- * offline_1D
+ * `offline_1D`
    * This example shows the usage of PDAF as an offline tool. In the offline configuration one computes manually the ensemble integrations and supplies this information to PDAF through files. For simplicity, this example does not use files, but generates dummy-information in the code itself. This example is the starting point to look into the offline implementation of PDAF.
- * lorenz63
+ * `lorenz63`
   * This directory currently only contains the forward Lorenz-63 model. It can be used as a training test case for an implementation using PDAF.
- * lorenz96
+ * `lorenz96`
   * This directory contains the forward Lorenz-96 model as well as a full data assimilation implementation of the model with PDAF. This model can be configured to have a sufficiently large state dimension to test low-rank filter algorithms like the SEIK filter. (We have using this model for example in the study: Janjić, T., Nerger, L., Albertella, A., Schröter, J., Skachko S. (2011). On domain localization in ensemble based Kalman filter algorithms. Monthly Weather Review, 139, 2046-2060 ( doi:10.1175/2011MWR3552.1).)