Climate and Spatial Analysis Toolkit
This repository provides Python-based tools for climate trend and spatial data analysis, enabling users to explore, process, and visualize climate datasets with ease. It includes well-documented scripts for analyzing temperature, precipitation, and geospatial patterns.
Climate trend analysis for temperature and precipitation data Spatial analysis tools for computing satellite-based indices and geostatistical metrics Data visualization utilities for generating insightful charts and maps Clear, user-friendly documentation for setup, usage, and contribution
The toolkit supports multiple climate datasets, including ERA5, CHIRPS, and CMIP6, and leverages Python libraries such as: pandas, xarray, rasterio, fiona, shapely, rioxarray, cdsapi, numpy, cfgrib, matplotlib, gcsfs, and geopandas.
The project aims to empower researchers and analysts to better understand climate trends and spatial patterns, promoting open science and collaborative data analysis.
Refer to the README for installation and usage instructions. Contributions are welcome — feel free to fork the repository and enhance its capabilities.
Documentation: Comprehensive documentation is available in the docs/ folder of the repository.