R

This year, the so-called warming stripes, which were created by the scientist Ed Hawkins of the University of Reading, became very famous all over the world. These graphs represent and communicate climate change in a very illustrative and effective way.

Recently I created a map of the distribution of gas stations and electric charging stations in Europe. How can you obtain this data? Well, in this case I used points of interest (POIs) from the database of Open Street Maps (OSM). Obviously OSM not only contains the streets and highways, but also information that can be useful when we use a map such as locations of hospitals or gas stations.

In this post, I will show how we can download and work directly with data from climatic reanalysis in R. These kind of datasets are combination of forcast models and data assimilation systems, which allows us to create corrected global grids of recent history of the atmosphere, land surface, and oceans.

Welcome to my blog! I am Dominic Royé, researcher and lecturer of physical geography at the University of Santiago de Compostela. One of my passions is R programming to visualize and analyze any type of data.