Análisis de datos climáticos con R

Learn the Fundamentals of R Programming for Climate Analysis

This course provides a solid foundation in the R programming language, essential for data analysis and scientific computing. You'll also get a concise introduction to Geographic Information Systems (GIS) and how to leverage them with R.

Dive into the world of spatial data analysis with hands-on experience in downloading and processing climate data. We'll cover spatial analysis techniques, enabling you to perform in-depth studies of climate patterns across various geographic scales and time periods. Utilize freely available global databases to gain valuable insights.

What will you learn?

• Climate Data Processing: Master techniques for downloading and cleaning climate datasets.
• Spatial Analysis with R: Apply R to analyze climate data geographically.
• Temporal Analysis: Explore climate trends over time.
• Global Climate Diagnostics: Develop skills to diagnose space-time climate patterns worldwide.
• Understanding Climate Change Impacts: Answer critical questions about historical and projected climate changes.

Specifically, you will learn to:

• Analyze the historical precipitation patterns of a specific region.
• Assess projected changes in temperature and precipitation for a country.
• Identify regions experiencing the most significant temperature shifts.
• Determine areas facing future water scarcity based on different Shared Socioeconomic Pathways (SSPs) from the IPCC Sixth Assessment Report.
• Investigate temperature anomalies for a region and compare maximum and minimum temperatures to typical years.

While a basic understanding of GIS and R is helpful, the course includes a brief introductory overview to get you started. This course is ideal for anyone interested in using R for environmental science, climate science, or data science applications.