python-cmethods 0.5

Collection of bias adjustment procedures for multidimensional climate data

Bias-Adjustment-Python

Collection of different scale- and distribution-based bias adjustment techniques for climatic research. (see examples.ipynb for help)

Bias adjustment procedures in Python are very slow, so they should not be used on large data sets. A C++ Implementation that works way faster can be found here: https://github.com/btschwertfeger/Bias-Adjustment-Cpp.

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Run adjustment:

python3 do_bias_correction.py   \
    --obs input_data/obs.nc     \
    --contr input_data/contr.nc \
    --scen input_data/scen.nc   \
    --method linear_scaling     \
    --variable tas              \
    --unit '°C'                 \
    --group time.month          \
    --kind + 

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Methods implemented by Benjamin T. Schwertfeger:

Method	--method parameter
Linear Scaling	linear_scaling
Variance Scaling	variance_scaling
Delta Method	delta_method
Quantile Mapping	quantile_mapping
Quantile Delta Mapping	quantile_delta_mapping

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Notes:

• Linear and variance, as well as delta change method require --group time.month as argument.
• Adjustment methods that apply changes in distributional biasses (QM. QDM, DQM; EQM, ...) need the --nquantiles argument set to some integer.
• Data sets should have the same spatial resolutions.
• Computation in Python takes some time, so this is only for demonstration. When adjusting large datasets, its best to the C++ implementation mentioned above.