Use Case 2: Probability distributions

In the following RCAT is applied to calculate standard empirical probability distribution functions, PDF’s.

Create hourly PDF statistics and visualize the results

The target of this example is to calculate PDF’s based on hourly data of precipitation and T2m for the summer season.

STEP 1: Data input

Under section MODELS specify the paths to model data. Configure for two or more models, and select start and end years. Select months 6,7,8 in order to extract data for June, July and August.

model_1 = {
     'fpath': '<path-to-folder-1>',
     'grid type': 'reg', 'grid name': '<grid-name>',
     'start year': <start year>, 'end year': <end year>, 'months': [6,7,8]
     'date interval start': '<yyyy>-<mm>', 'date interval end': '<yyyy>-<mm>',
     'chunks_time': {'time': -1}, 'chunks_x': {'x': -1}, 'chunks_y': {'y': -1},
     }
model_2 = {
     'fpath': '<path-to-folder-2>',
     'grid type': 'reg', 'grid name': '<grid-name>',
     'start year': <start year>, 'end year': <end year>, 'months': [6,7,8]
     'date interval start': '<yyyy>-<mm>', 'date interval end': '<yyyy>-<mm>',
     'chunks_time': {'time': -1}, 'chunks_x': {'x': -1}, 'chunks_y': {'y': -1},
     }

We can skip the observations here and ignore OBS settings.

STEP 2: Variables

Set output directory under the SETTINGS section.

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 hourly data as input (freq set to 1hr).

Specify regions the regions key for which statistics will be selected for.

output dir = <path-to-output-directory>

variables = {
    'pr': {
        'freq': '1hr',
        'units': 'mm',
        'scale factor': 3600,
        'offset factor': None,
        'accumulated': True,
        'obs': None,
        'obs scale factor': None,
        'obs freq': 'day',
        'var names': None,
        'regrid to': None
        },
    'tas': {
        'freq': '1hr',
        'units': 'K',
        'scale factor': None,
        'offset factor': None,
        'accumulated': False,
        'obs': None,
        'obs scale factor': None,
        'obs freq': 'day',
        'var names': None,
        'regrid to': None
        },
    }

regions = ['Germany', 'France']

STEP 3: Select statistics

Under STATISTICS pdf will be specified. A list of bins will be used in the pdf. If not given here these bins will be defined automatically in RCAT by taking minimum and maximum of input data. This can be quite crude and not so representative, so it is suggested to define them here under the pdf key. They are specified in a dictionary where the keys are input variables and the values are the respective bin definitions. The bin definition is a list/tuple with start, stop and step values. For example, for precpitation a list of bins starting with 0 and ending with 50 using a step of 1 is defined here.

stats = {
   'pdf': {'bins': {'pr': (0, 50, 1), 'tas': (264, 312, 1)}}
    }

See the default_stats_config function in RCAT Statistics module for the default options for pdf.

STEP 4: Plotting

Under PLOTTING, set validation plot to True to enable plotting. Plotting of pdf’s will be line plots only (regions should therefore be specified). We only specify linewidths to be 3.

validation plot = True

line grid setup = {}
line kwargs = {'lw': 3}

STEP 5: Configure cluster

cluster type = slurm
nodes = 10
cluster kwargs = {'walltime': '02:00:00', 'cores': 24, 'memory': '128GB'}

STEP 6: Run RCAT

Run the analysis run from the command line (see Run RCAT in RCAT Configuration):

python <path-to-RCAT>/src/rcatool/runtime/RCAT_main.py -c config_main.ini

Output statistics files will be located in the sub-folder stats under the user-defined output directory.

Calculate PDF’s for daily maximum values instead

Say you would like to do the same statistical analysis as above, however, with a different temporal resolution and/or time statistic on the input data. For example, let’s assume that pdf’s should be calculated for daily maxmimum data instead. How can this be achieved?

This can be done using an option in the stats property (under SETTINGS) called resample resolution. It is specified by a list/tuple with two locations; the first index represents the time resolution sought after and the second location the statistic used for each sample in the resampling. In the example here data is resampled into daily maximum values:

stats = {
   'pdf': {'bins': {'pr': (0, 50, 1), 'tas': (264, 312, 1)}, 'resample resolution': ['D', 'max']}
    }

When set, run RCAT again.