Use Case 1: Annual & and Seasonal Cycles¶

In this example annual and seasonal statistics will be calculated and in most steps, changes are made in different sections of the configuration file, src/config/config_main.ini. It is recommended to copy this file to your experiment folder. Detailed information of what can be configured and how can be found in RCAT Configuration.

How to calculate monthly and seasonal mean statistics?¶

Daily data from two models is used as input for calculation of monthly and seasonal means at each point of their respective (native) grids. Statistical results are written to disk in netcdf files; a separate file for each model and statistic (and sub-region if specified). No plotting is done here.

STEP 1: Data input¶

Under section MODELS you’ll specify the path to model data. Configure for two models – arome and aladin – using the same time period and months. Since the annual and seasonal cycles will be calculated, all months are chosen.

arome = {
     'fpath': '/nobackup/rossby21/rossby/joint_exp/norcp/NorCP_AROME_ERAI_ALADIN_1997_2017/netcdf',
     'start year': 1998, 'end year': 2002, 'months': [1,2,3,4,5,6,7,8,9,10,11,12]
     }
aladin = {
     'fpath': '/nobackup/rossby21/rossby/joint_exp/norcp/NorCP_ALADIN_ERAI_1997_2017/netcdf',
     'start year': 1998, 'end year': 2002, 'months': [1,2,3,4,5,6,7,8,9,10,11,12]
     }

In this example we will not use any observations so no modifications are needed in the OBS section.

STEP 2: Variables¶

Under SETTINGS the full path to output directory should be defined. If folder doesn’t exist already it will be created by RCAT.

output dir = /nobackup/rossby22/sm_petli/analysis/test_analysis

The key variables defines which variables to analyze along with some options regarding that particular variable. Since only models will be analyzed here, ‘obs’ is set to None. Further, models will be kept at their respective grids, thus ‘regrid to’ is also set to None. Statistics is configured for T2m (tas) and precipitation (pr) with daily data as input (‘freq’ set to ‘day’).

variables = {
    'pr': {'freq': 'day', 'units': 'mm', 'scale factor': None, 'accumulated': True, 'obs': None, 'regrid to': None},
    'tas': {'freq': 'day', 'units': 'K', 'scale factor': None, 'accumulated': False, 'obs': None, 'regrid to': None},
    }

regions = ['Scandinavia']

regions is a list of pre-defined regions – see available regions in geosfuncs module. Statistics will be selected for the specified sub-regions.

STEP 3: Select statistics¶

Under STATISTICS seasonal and annual cycles are chosen.

stats = {
    'annual cycle': 'default',
    'seasonal cycle': {'thr': {'pr': 1.0}},
    }

The ‘default’ property means that default options for the particular statistic are used. All default options can be seen in the default_stats_config function in the statistics module. For seasonal cycle, we choose to use a threshold for precipitation of 1.0 and so calculation is only based on wet days.

STEP 4: No plotting¶

Set validation plot to false – no plotting done in this example.

validation plot = False

STEP 5: Configure cluster¶

Under the CLUSTER section one should specify which type of cluster to use. Here, it is configured for a SLURM cluster. nodes specify the number of nodes to be used. In cluster kwargs a number of different options can be set (here specific for SLURM), for example walltime which is set to 2 hours.

cluster type = slurm
nodes = 10
cluster kwargs = {'walltime': '02:00:00'}

STEP 6: Run RCAT¶

To run the analysis run from terminal (see Run RCAT in RCAT Configuration):

python $HOME/git/rcat/src/RCAT_main.py -c config_main.ini

If successfully completed, output statistics netcdf files will be located in the sub-folder stats under the user-defined output directory. An img folder is also created, however, it will be empty as no plotting have been done.

Adding comparison to observations and visualize results¶

In order to include observations and visualize the end results, follow the procedure as in the previous example with the following changes introduced:

Under OBS section, choose same years and months as models

start year = 1998
end year = 2002
months = [1,2,3,4,5,6,7,8,9,10,11,12]

The variables property in SETTINGS section shall be modified:
- Include observations; ‘obs’: [‘EOBS20’, ‘ERA5’]. Also, scale factors are now included for observations as well.
- Since models and observations will be compared, taking differences, the data must be on the same grid. Therefore, set ‘regrid to’: ‘ERA5’. This means that all data will be interpolated to the ERA5 grid. Further, the ‘regrid method’ needs to be set – bilinear for T2m and conservative for pr.
variables = { 'pr': {'freq': 'day', 'units': 'mm', 'scale factor': None, 'accumulated': True, 'obs': ['EOBS20', 'ERA5'], 'obs scale factor': [86400, 86400], 'regrid to': 'ERA5', 'regrid method': 'conservative'}, 'tas': {'freq': 'day', 'units': 'K', 'scale factor': None, 'accumulated': False, 'obs': ['EOBS20', 'ERA5'], 'obs scale factor': None, 'regrid to': 'ERA5', 'regrid method': 'bilinear'}, }
Under PLOTTING, validation plot should be set to True to enable plotting. It is possible to configure the visualization in different ways, for example various map configurations in map plots or the looks of line plots. However, for simplicity here, the default configurations will be used, which means setting all properties to an empty dictionary ({}).
validation plot = True map configure = {} map grid setup = {} map kwargs = {} line grid setup = {} line kwargs = {}

With these modifications in place, run RCAT again (STEP 6 above).