How to Build a Climatic Map in 30 Lines of Code?

How to Build a Climatic Map in 30 Lines of Code?

Knowing the climate of a region / a country could be essential to study its ecosystem. Here I’m going to explain how to build that kind of map in a few lines of code! Here as we are focusing on climate data we are going to download the 2m temperature as well as rainfall.

Even if we do not need a lot of experience to do that kind of map let’s split the work and take some minutes to speak about the dataset.

0°) Dataset

To build a climatic map we need climate data! This is possible through Copernicus Climate Change Service (link to the website here & some wiki explication here).

Quickly Copernicus Climate Change Service is a European project fund by the European Commission. But why Copernicus you might ask? Because this part of the Copernicus Program which is an Earth Observation Program dedicated to giving a scientific picture of the health of our blue dot. But still why Copernicus you might ask? Nicolaus Copernicus is at the origin of modern astronomy. Copernicus program is at the origin of full, free, and open access to space data.

So now let’s dive into the data. Thanks to Copernicus Climate Change Service you can easily download data. Here as we are focusing on climate data we are going to download the 2m temperature as well as rainfall. This data is built on satellite measures, in-situ data, and models. (link)

Let’s download (netCDF format) the monthly reanalysis of the precipitation and the temperature from 1981 until 2019 above France. We should have 456 values for precipitation as well as temperature.

I°) Starter pack

So what do we need to work on this data?

One conda virtual environment design for geodata science with the following libraries :

  • *NumPy *(basic array management library) [link],
  • *matplotlib *(basic visualization management library) [link],
  • pandas (used to manage data) [link],
  • *geopandas *(used to manage geospatial data) [link],
  • xarray (used to manage netCDF data (here our climate data)) [link]
  • *rasterio *(mostly used to work on satellite imagery) [link]
  • rioxarray_ (rasterio xarray extension to combine both easily)[ [link]_](https://github.com/corteva/rioxarray)
  • Fiona (used to manage vector and here just for better visualization) [link]
  • sklearn (used for machine learning) [link]

Installation of this environment might be the longest task of this small article.

climate era5 satellite data-science copernicus

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

50 Data Science Jobs That Opened Just Last Week

Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.

Applications Of Data Science On 3D Imagery Data

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.

Data Science Course in Dallas

Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...

32 Data Sets to Uplift your Skills in Data Science | Data Sets

Need a data set to practice with? Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.

Data Cleaning in R for Data Science

A data scientist/analyst in the making needs to format and clean data before being able to perform any kind of exploratory data analysis.