Forcing Configuration

The forcing.json file configures the input dataset for SINDBAD experiments, defining how forcing data is processed and integrated into model runs.

Data Dimensions

The data_dimension section specifies the structure of input forcing datasets, enabling proper data processing for spatial and temporal operations.

"data_dimension": {
    "time": "Name of the time dimension in the dataset",
    "permute": "Order of dimensions in the processed data",
    "space": "List of spatial dimensions"
}

Default Forcing Settings

The default_forcing section defines default attributes for all forcing variables. These settings apply unless overridden in individual variable configurations.

"default_forcing": {
    "additive_unit_conversion": "Flag for additive (true) or multiplicative (false) unit conversion",
    "bounds": "Valid data range after unit conversion",
    "data_path": "Path to the data file (absolute or relative to experiment base)",
    "depth_dimension": "Name of depth dimension (null if none)",
    "is_categorical": "Flag for categorical variables",
    "standard_name": "Descriptive variable name",
    "sindbad_unit": "Unit used within SINDBAD",
    "source_product": "Data source identifier",
    "source_to_sindbad_unit": "Unit conversion factor",
    "source_unit": "Original data unit",
    "source_variable": "Variable name in source file",
    "space_time_type": "Data type classification"
}

Spatial Subsetting

The forcing_mask section configures spatial subsetting of forcing data, enabling experiments on specific regions without creating new datasets.

"forcing_mask": {
    "data_path": "Path to the mask file",
    "source_variable": "Mask variable name in the file"
}

Note Temporal subsetting is configured in the time section of experiment.json. :::

Variable Configuration

The variables section lists all forcing variables required for the experiment. Only settings that differ from default_forcing need to be specified.

"variables": {
    "f_variable_name": {
        "bounds": "Valid range for the variable",
        "standard_name": "Descriptive name",
        "sindbad_unit": "SINDBAD unit",
        "source_unit": "Original unit",
        "source_variable": "Variable name in source file"
    }
}

Variable Naming Convention

• Use f_ prefix for forcing variables loaded from data files

• This convention distinguishes them from variables computed within SINDBAD

Data Validation

• Values outside specified bounds are truncated, not replaced with NaN

• Ensure all required variables are available in the forcing dataset

• Verify unit conversions and data types match model requirements