tutorial2.rst

Cycled experiment

#### Configure your experiment Define simulation specific variables in [config/cfg.py](https://github.com/lkugler/DART-WRF/blob/master/config/cfg.py). Define paths for python, ncks, etc. in [config/clusters.py](https://github.com/lkugler/DART-WRF/blob/master/config/clusters.py). Dependencies are numpy, pandas, scipy, xarray, netCDF4. Install non-standard packages with pip install docopt slurmpy --user. Workflow is defined using meta-routines (functions) like run_ENS which are defined in scheduler.py.

#### Prepare initial conditions (from input_sounding) 1) Define starting time: begin = dt.datetime(2008, 7, 30, 6) 2) WRF needs directories with certain files: id = prepare_WRFrundir(begin) 3) Create 3D initial conditions from input_sounding etc.: id = run_ideal(depends_on=id)

### Run free forecast Let's say you want to run a free forecast starting at 6z, which you want to use as prior for an assimilation at 9z. Then you need can use the above defined 3 steps to create initial conditions. Then you can run an ensemble forecast using: ``` id = run_ENS(begin=begin, # start integration from here

end=end, # integrate until here input_is_restart=False, output_restart_interval=(end-begin).total_seconds()/60, depends_on=id)

``` where begin & end are dt.datetime objects.

### Assimilation experiment #### Assimilate To assimilate observations at dt.datetime time use this command:

id = assimilate(time, prior_init_time, prior_valid_time, prior_path_exp, depends_on=id)

#### Update initial conditions from Data Assimilation In order to continue after assimilation you need the posterior = prior (1) + increments (2)

1. Set prior with this function:

id = prepare_IC_from_prior(prior_path_exp, prior_init_time, prior_valid_time, depends_on=id)

where path is str, times are dt.datetime.

2. To update the model state with assimilation increments, you need to update the WRF restart files by running

id = update_IC_from_DA(time, depends_on=id)

After this, the wrfrst files are updated with assimilation increments (filter_restart) and copied to the WRF's run directories so you can continue to run the ENS after assimilation using

``` id = run_ENS(begin=time, # start integration from here

end=time + timedelta_integrate, # integrate until here restart_path=cluster.archivedir+prior_init_time.strftime('/%Y-%m-%d_%H:%M/'), output_restart_interval=timedelta_btw_assim.total_seconds()/60, depends_on=id)

``` where times are dt.datetime; timedelta variables are dt.timedelta.

### Examples [scheduler.py](https://github.com/lkugler/DART-WRF/blob/master/scheduler.py) [generate_free.py](https://github.com/lkugler/DART-WRF/blob/master/generate_free.py)

## Finally

### SLURM submissions scheduler.py submits jobs into the SLURM queue with dependencies, so that SLURM starts the jobs itself as soon as resources are available. Most jobs need only one node, but model integration is done in a SLURM job array across e.g. 10 nodes: ``` $ squeue -u whoami --sort=i

JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)

1710274 mem_0384 prepwrfr lkugler PD 0:00 1 (Priority) 1710275 mem_0384 IC-prior lkugler PD 0:00 1 (Dependency) 1710276 mem_0384 Assim-42 lkugler PD 0:00 1 (Dependency) 1710277 mem_0384 IC-prior lkugler PD 0:00 1 (Dependency) 1710278 mem_0384 IC-updat lkugler PD 0:00 1 (Dependency) 1710279 mem_0384 preWRF2- lkugler PD 0:00 1 (Dependency)

1710280_[1-10] mem_0384 runWRF2- lkugler PD 0:00 1 (Dependency)

1710281 mem_0384 pRTTOV-6 lkugler PD 0:00 1 (Dependency) 1710282 mem_0384 Assim-3a lkugler PD 0:00 1 (Dependency) 1710283 mem_0384 IC-prior lkugler PD 0:00 1 (Dependency) 1710284 mem_0384 IC-updat lkugler PD 0:00 1 (Dependency) 1710285 mem_0384 preWRF2- lkugler PD 0:00 1 (Dependency)

1710286_[1-10] mem_0384 runWRF2- lkugler PD 0:00 1 (Dependency)

1710287 mem_0384 pRTTOV-7 lkugler PD 0:00 1 (Dependency)

```

### Easily switch between clusters Define cluster specific variables in `config/clusters.py `: ```python

clusterA = ClusterConfig() clusterA.name = 'vsc' clusterA.userdir = '/home/pathA/myuser/' ... clusterB = ClusterConfig() clusterB.name = 'jet' clusterB.userdir = '/home/pathB/myuser/' ```