This repository contains Jupyter notebook training material for the Copernicus Climate Change Service (C3S) and the Copernicus Atmosphere Monitoring Service (CAMS). Some notebooks were produced for specific training events, but all can be used as standalone tutorials. Below is a description of each notebook, listed in reverse chronological order.

Each description includes a high level outline of the training content and objectives, describing the tools and data presented. If a notebook was developed for a particular training event, this event is also described. At the end of each description you can find links to run the notebook in Binder, in Colab and to view a rendered version in Nbviewer.

The notebooks with the prefix "Atmos-Training" have been developed for some of the practical sessions of the joint ESA, EUMETSAT and ECMWF organised training in atmospheric composition. For more information about this event, please visit https://atmosphere.copernicus.eu/3rd-eumetsatesaecmwf-joint-training-atmospheric-composition

This Jupyter notebook tutorial demonstrates how to access CAMS global atmospheric composition forecasts and CAMS global reanalysis data, using the Atmosphere Data Store (ADS) API. It also shows how to use Python to create basic visualisations.

The tutorial was developed for various training events in November and December 2021.

Run the tutorial here: , or view a rendered version here.

This Jupyter notebook tutorial demonstrates how to access CAMS global atmospheric composition forecasts and CAMS global reanalysis data, using the Atmosphere Data Store (ADS) API. It also shows how to use Python to create basic visualisations.

The tutorial was developed for a training event in September 2021 entitled, "Introduction and Access to Global Air Quality Forecasting Data and Tools". The event was organised together with the NASA Applied Remote Sensing Training (ARSET) Program. Please see more detials on this event here.

Run the tutorial here: , or view a rendered version here.

This Jupyter notebook tutorial provides step by step instructions on how to access C3S and CAMS data from the various catalogues, how to carry-out basic processing, such as calculation of climatology and anomalies, and how to visualise the data. The data includes C3S ERA5 reanalysis data of soil moisture, CAMS European Air Quality Forecast data for dust and PM10, and CAMS Global Near-Real-Time data for total Aerosol Optical Depth (AOD).

The tutorial was developed for a training event to data journalists on 23 February 2021.

Run the tutorial here: , or here: , or view a rendered version here.

This Jupyter notebook tutorial shows you how to access ERA5 data using the CDS API and how to analyse extreme values associated with a particular event (extreme temperature in Northern France in September 2020). The tutorial was developed for an online WEkEO training event on 12 November 2020.

Run the tutorial here: , or here: , or view a rendered version here.

This Jupyter notebook tutorial is in Italian and features and introduction to the Climate Data Store (CDS), the Copernicus Knowledge Base, the CDS Toolbox and API. The tutorial was developed for a training to Italian masters students on 19 November 2020.

Run the tutorial here: , or here: , or view a rendered version here.

This Jupyter notebook tutorial shows you how to create an index for wind chill from UERRA reanalysis data of temperature and wind speed. The tutorial was developed for an online WEkEO training event on 12 November 2020.

Run the tutorial here: , or here: , or view a rendered version here.

This Jupyter notebook tutorial demonstrates you how to access ERA5 data using the CDS API and how to calculate climatologies and trends of near-surface air temperature. The tutorial was developed for an online WEkEO training event on 12 November 2020.

Run the tutorial here: , or here: , or view a rendered version here.