Computational Tools in Climate Science: Part 3 - Remote Sensing
NFDI4Earth
About This Course
Welcome to the "Remote Sensing" course. This is the third part of the "Computational Tools for Climate Science" course series! Today’s focus is on satellite remote sensing for climate applications. Various international agencies and organizations have been using environmental satellite to monitor our earth system since the late 1970s. With more than 40 years of long-term satellite data records, we can understand the change of different components of the earth system, including land, ocean, atmosphere. More importantly, the long-term remote sensing data can help us study the impact of climate change on natural and human systems, such as ecosystem’s response to climate and climate impact on agriculture systems.
During today’s curriculum, you will learn the fundamental concepts of satellite remote sensing, different sources of satellite remote sensing data for climate applications, how to access remote sensing datasets using python, and how to apply selected remote sensing datasets for climate applications. After today’s content, you should be familiar with basic concept of satellite remote sensing and basic computational tools to access and analyze satellite remote sensing data for climate applications.
Level
Intro, Beginner, Intermediate
Requirements
Prerequisites include some introductory programming skills in Python, as well as core math and science concepts. We expect participants to be familiar with fundamental Python and data storage concepts (variables, lists, dictionaries, data formats) as well as some key Python libraries like NumPy, matplotlib, cartopy, datetime, pandas, and Xarray.
Subject Area
Geosciences
Learning Objectives
- Understand the theory, technology, and availability of satellite remote sensing for climate applications.
- Access and analyze satellite remote sensing products for climate applications.
What You Will Learn
- Introduction to Remote Sensing
- Remote Sensing
- Exploring Satellite Climate Data Records
- Visualizing Satellite CDR - Global Vegetation Mapping
- Understanding Climatology Through Precipitation Data
- Calculating Anomalies Using Precipitation Data
- Large Scale Climate Variability - ENSO
- Impact of Climate Variability - Precipitation
- Comparing Satellite Products With In Situ Data
Resources
Computational Climate Science syllabus by Climatematch
Computational Computational Tools in Climate Science by Climatematch
Computational Tools for Climate Science Course by neuromatch