Extreme Climate Events DIFUSE Module

Contributors: Justin Mankin (Professor of Geography), Elizabeth Bauman ('22), Scott Pauls (Professor of Mathematics, DIFUSE PI)

This module was developed through the DIFUSE project at Dartmouth College and funded by the National Science Foundation award IUSE-1917002.

	This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Module Overview

Module Objective

The problem sets were designed to introduce students to important concepts/applications in Python and to connect the lecture content. In order to keep the problem sets simple and not overwhelm the students, the problem sets were broken up into five separate, shorter assignments. The contents of the problem sets are outlined below to indicate after which lectures the problem sets should be introduced.

Student Learning Objectives

1. Demystify scientific computing and programming using Python
2. Recognize commonly used data in climate science
3. Apply Python computing methods to climate data
4. Interpret results generated from scientific computing

Module Description

Students code in python to facilitate analysis and understanding of climate data sets that relate to extreme events. Before this module, the course had a series of python tutorials for students but the examples were not related to the course. This module redesigned the python notebooks to teach coding through manipulation and analysis of climate data sets, linking to course topics as the term progressed.

Data

The module uses a variety of data including NAO/AO, disaster numbers, wave height, latent heat, flood return periods, net radiation, heat waves, surface pressure.

Platform

Python notebooks using Google CoLab.

Schedule and Links

Use this page to get an idea of the timeline of the module, what components are involved, and what documents are related to each component. This is the schedule intended for module deployment by the DIFUSE team, though instructors are welcome to modify the timeline to fit their course environment.

Date	In/Out of Class	Assignment Description	Linked course content	Assignment Files (Linked to Repository Contents)
Week 1	Out of class	Set #1: Explore basic principles of Python, Learn commonly used functions to explore simple, relevant climate data	Units in climate science (force; temperature conversion), Expensive disasters	Python Notebook #1
Week 3	Out of class	Set #2 Learn how to use open source packages, Explore additional data structures in Python	Different disaster reporting sources	Python Notebook #2
Week 5	Out of class	Set #3: Generate various types of plots to visualize climate data, Interpret results from generated plots	NAO/AO, Disaster numbers, Wave height	Python Notebook #3
Week 7	Out of class	Set #4: Extend understanding of additional, useful functions; reate own functions to calculate simple formulas	Latent heat, Quantifying water as an energetic quantity, Flood return periods, Net radiation equations	Python Notebook #4
Week 9	Out of class	Set #5: Explain data structures commonly used in climate science, Accumulate and apply skills from previous problem sets	Heat waves, Surface pressure	Python Notebook #5

Course Information

This module was created for a geography course, Climate Extremes on a Warming Planet, at Dartmouth College. The course looks at drought, famine, floods, landslides and other extreme weather events through the lens of climate change. This course has no prerequisites and satisfies a "Science" distributive requirement. Consequently, students from all class years take the course and their mathematical and programming backgrounds are heterogeneous.

	This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

For instructors and interested parties, the history of this repository (with detailed commits), can be found here.