| 15 | | Runnning a data assimilation experiment with the Lorenz-63 model is a two step process: First one runs the model without PDAF to generate a file holding the trajectory of a forward run. Then, one generates a file with observations and a file holding information on the covariance matrix (EOFs and singular values, see the [wiki:EnsembleGeneration page on ensemble generation]). The second file will be used to generate the initial ensemble with second-order exact sampling. Afterwards, one compiles the Lorenz-63 model with activated coupling to PDAF and runs the data assimilation experiments. |
| | 15 | Runnning a data assimilation experiment with the Lorenz-63 model is a two step process: First one runs the model without PDAF to generate a file holding the trajectory of a forward run. Then, one generates a file with observations by perturbing the forward run. |
| | 16 | |
| | 17 | Note, that in contrast to the Lorenz-96 model case, we initialize the ensemble by random sampling from the forward run. Using second-order exact sampling (see the [wiki:EnsembleGeneration page on ensemble generation]) is not useful for the Lorenz-63 model, as this would limit us to a maximum ensemble size of 4 states. |
