How to use data from CDS to compute an agroclimatic indicator, specifically, the "Warm and wet days" (WW) indicator
OC and SST datasets from CDS: subset and download, visualise time series, aggregate daily to monthly, calculate anomalies
Practical introduction to the Sea level gridded data: plotting data during an El Niño event and over a strong current
Surface Albedo product. Three case studies: data retrieval, visualisation, time-series creation, set up Python environment
LAI and fAPAR retrieved with satellite remote sensing. Computation of inverse variance weights
An introduction to the different sources of climate data and how to find them.
Learn about the various data sources, and strategies to find climate data: processing, choosing projections, scenarios, ensembles and variables.
Learn about Essential Climate Variables, the different types of climate data resources, and their respective pros and cons.
Explore the different types of measurements, the types of observing systems and their measurement uncertainty.
This lesson teaches users the basics of climate reanalysis. The lesson explains how reanalyses are made, an overview of global reanalyses datasets, and their strengths and limitations.
Uncover how climate models work and how they can be evaluated. Differences between climate projections, predictions and scenarios are explained.
