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These codes are used in the paper "Application of machine learning-based postprocessing to improve crowd-sourced urban rainfall outlooks".

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Crowd Sourcing Framework

Application of machine learning-based postprocessing to improve crowd-sourced urban rainfall outlooks

The framework uses three different codes for data generation using (i) STORM V1 (Storm_run.py), converting rainfall to categorical data (ii) Data Generation.ipynb, and scenario generation model fitting (iii) Scenarios and Model fitting.ipynb

The data used in the codes are available in the "Data" folder.

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These codes are used in the paper "Application of machine learning-based postprocessing to improve crowd-sourced urban rainfall outlooks".

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