The notebooks folder located under your home directory contains some examples for running data manipulation, analysis and visualization.

Quick Start Xarray-Matplotlib

Get started with Xarray and Matplotlib to visualize your datasets.

Quick Start Cartopy

Get started with Cartopy to produce maps and other geospatial data analyses.

Quick Start PyOphidia

The notebook provides some basic examples of how to use the Ophidia framework features for climate data analysis through its Python bindings, PyOphidia.

Quick Start Intake-esm

Search, discover and load CMIP6 datasets through the intake-esm data cataloging utility.

Quick Start GeoPy, Folium and hvPlot

Get started with GeoPy and Folium to deal with coordinates and interactive geographical maps, and hvplot to create interactive plots.

Quick Start CDO

Get started with CDO (Climate Data Operators) and its Python bindings to manipulate and analyse climate model data.

Tropical nights

Compute the Tropical Nights Climate Index (the number of days where the daily minimum temperature is greater than 20.0C) through PyOphidia.

Multi-model Analysis

Perform a simple multi-model analysis on scientific datasets.

Air Temperature Analysis

Perform a climate data analysis to compare the historical and the projected future temperature over the Europe spatial domain.

Frost Days

Compute the Frost Days Climate Index (the number of days where the daily minimum temperature is lower than 0C) in parallel with Dask.

Working with NetCDF data in R

The notebook shows how to open and work with geospatial data stored in NetCDF format using the ncdf4 R package.

Publish a research product on Zenodo

The notebook shows how to upload and publish a research product on Zenodo through the Zenodo REST API.

Precipitation Climate Index

Compute the annual count of days when precipitation exceeds a given threshold (e.g., 10mm)

Visualize climate data with R

The notebook shows how to read the metadata from a NetCDF file and visualize data on a map in R.