ClimateFiller: a python framework based on artificial intelligence and multi-source reanalysis data to diagnose and fill gaps in climate time series.

This framework implements various data-driven methods to make manipulating in-situ climate time series easier. It offers various services such as (1) using machine learning and ERA5-Land to fill in missing data and (2) using Isolation Forest, Local Outlier Factor, and quantiles to detect and eliminate outliers. It was tested on several Automatic Weather Stations (AWS) installed in Morocco.