Arguments and Requirements

Arguments

The following table lists the available command-line arguments that can be passed to the BiasAdjustCXX tool. Please also have a look at the requirements section below.

Command-line arguments

Arguments	Description
--ref, --reference	path to observational/reference data set (control period)
--contr, --control	path to modeled data set (control period)
--scen, --scenario	path to data set that is to be adjusted (scenario period)
-v, --variable	variable to adjust
-k, --kind	kind of adjustment - one of: + or add and * or mult
-m, --method	adjustment method name - one of: linear_scaling, variance_scaling, delta_method, quantile_mapping and quantile_delta_mapping
-q, --quantiles	[optional] number of quantiles to respect (only required for distribution-based methods)
--1dim	[optional] required if the data sets have no spatial dimensions (i.e. only one time dimension)
--no-group	[optional] Disables the adjustment based on 31-day long-term moving windows for the scaling-based methods. Scaling will be performed on the whole data set at once, so it is recommended to separate the input files for example by month and apply this program to every long-term month. (only for scaling-based methods)
--max-scaling-factor	[optional] Define the maximum scaling factor to avoid unrealistic results when adjusting ratio based variables for example in regions where heavy rainfall is not included in the modeled data and thus creating disproportional high scaling factors. (only for multiplicative methods except QM, default: 10)
-p, --processes	[optional] How many threads to use (default: 1)
-h, --help	[optional] display usage example, arguments, hints, and exits the program

Requirements

• The variable of interest must have the same name in all data sets.

• The dimensions must be named “time”, “lat” and “lon” (i.e., time, latitudes and longitudes) in exactly this order - in case the data sets have more than one dimension.

• Executed scaling-based techniques without the --no-group flag require that the data sets exclude the 29th February and every year has exactly 365 entries (see Notes regarding the scaling-based techniques).

• For adjusting data using the linear scaling, variance scaling or delta method and the --no-group flag: You have to separate the input files by month and then apply the correction for each month individually e.g., for 30 years of data to correct, you need to prepare the three input data sets so that they first contain all time series for all Januaries and then apply the adjustment for this data set. After that you have to do the same for the rest of the months (see /examples/example_all_methods.run.sh in the repository).