Toolkit for the retrieval and preprocessing of climate and meteorological data
A collection of Python methods intended as a practical tool for fetching and preprocessing data related to climate and weather conditions, useful in climate science studies.
Developed by AMIGO s.r.l. for the ARIA project, part of the I-NERGY 2nd Open Call.
A Jupyter Notebook containing a collection of Python methods for the download, preprocessing, and plotting of climate data, with useful examples of their usage.
Developed by AMIGO s.r.l. for the ARIA project, part of the I-NERGY 2nd Open Call.
The notebook contains a download module that uses API calls to pull data from primary sources, requiring users to input their preferences in a dictionary-style parameter set.
The notebook also details a method for saving the collected data to a disk, highlighting a format suitable for the next stages of analysis. The notebook includes also a set of features for basic data manipulation. Users are instructed on exploiting data by choosing particular time frames and spatial regions and resampling data in new temporal timeframes.
To use the notebook, please register at the Copernicus Data Service (CDS) portal https://cds.climate.copernicus.eu/#!/home and obtain an authorization key.
Ensure you have the necessary libraries installed and follow the instructions within the notebook.