These Computational Guided Inquiry (CGI) modules are intended for undergraduate courses in Geosciences, Economics, Computer Science, Physics, Quantum Mechanics, Thermodynamics, and Environment Science, from intro-level to advanced. Each is a stand-alone module corresponding to one of these disciplinary topics. Modules are typically designed to be completed in two to three class periods (or one to two lab sessions) and include homework assignments. Through these modules, student learning of disciplinary topics is enhanced through participating in guided inquiry in an active-learning framework scaffolded by a computational tool, using real-world polar research and data. Student engagement is fostered by linkages made between polar research and climate change.

Argentina - Patagonia - El Calafate 031 - Perito Moreno Glacier

Economics: Sea level rise

This module was initially developed by Lea Fortmann and was edited by Isha and Justin
This intro- to intermediate-level module is framed from the perspective of a city planner trying to determine how much to spend on a local seawall given different scenarios of sea level rise and the associated storm surge and higher flood levels that come with it due to polar ice melt. Students refer to Climate Central's Risk Finder website for data on the probability of flooding under four different sea level rise scenarios. Combined with data on the number of homes affected under different flood levels, students calculate and graph marginal expected damage curves to make a recommendation on building a seawall based on marginal benefits and costs. Explore this module...


Economics: Total Economic Valuation of the Arctic

This module was initially developed by Lea Fortmann, with help from Isha and Justin
This intro- to intermediate-level module involves students conducting a partial replication of a paper from the peer reviewed journal Ecosystem Services that involves estimating the total economic value of ecosystem services in the arctic. Students gather original data from a select number of sources used by the author and then calculate the annual value of the arctic in an Excel spreadsheet. The analysis focuses on the assumptions made in the calculation and covers topics on willingness-to-pay and contingent valuation, replacement costs, and ecosystem services valuation. Explore this module...


Physics: Permafrost

This module was initially developed by Penny Rowe and Steven Neshyba
Students learn what permafrost is, the implications of permafrost thawing due to climate change, and how to calculate heat diffusion through permafrost in this intro-level module. Student activities include watching a video about permafrost, checking out a journal article, and downloading, plotting and analyzing permafrost data. They learn about how permafrost temperature changes with depth underground, seasonally, and annually, and calculate heat flow through permafrost. Explore this module...

ice core

Tools and Methods in Environmental Science: Ice Cores

This module was initially developed by Emma Sevier, Steven Neshyba, and Penny Rowe.
Students gain experience with tools and methods of Environmental science through exploring the paleoclimate record using ice cores as climate proxies in this intro-level module. They learn what causes natural climate change and how it is recorded in ice cores, exploring glacial-interglacial cycles and correlations between carbon dioxide and temperature in the past million years, using ice core data. Explore this module...

Arctic Sea Ice Landscape

Thermodynamics: Sea ice melt

This module was initially developed by Steven Neshyba and Penny Rowe
Students learn about thermodynamics topics through calculation of the amount of heat required to melt Arctic sea ice. They start by watching an online animation of changing polar ice with time. They next download data of Arctic ice extent and volume. Working in a Jupyter Notebook, they use thermodynamic principles and equations to plot the phase diagram of water, find the freezing point depression of Arctic sea ice in equilibrium with sea water, and compute the change in the enthalpy of fusion of water resulting from that temperature depression. This intermediate-level module has also been adapted for a lower-level Engineering Physics Course. Explore this module...


Quantum mechanics: Polar spectra

This module was developed by Penny Rowe, Steven Neshyba and Aedin Wright
Students learn about the greenhouse effect by examining a "forbidden" rovibrational band in the infrared emission spectra of Earth's atmosphere, recorded from the surface at South Pole Station. By weighting rotational energy degeneracies with a Boltzmann factor, they simulate the R-branch of the band; the result is a rudimentary estimate of the average temperature of the troposphere above the South Pole. A second activity simulates radiative emission in a saturated part of the spectrum as a Planck Blackbody, which yields the temperature of the atmosphere just above the surface. All computations and graphical displays are done in Jupyter Notebooks. This intermediate-level module has also been adapted for a lower-level Engineering Physics Course. Explore this module...

Northwest Passage

Computer Science: Images of Arctic Ice

This module was developed by Haiyan Cheng, Penny Rowe, and Steven Neshyba

Students apply image-processing techniques to images of the Arctic in this intermediate-level module. Students learn about climate change and its impacts on melting of polar sea ice, and explore satellite-based images of the polar regions. They download a satellite-based image of the Arctic and learn about how images are stored, apply image-filtering techniques such as noise removal and edge detection, and explore scene identification using true- and false-color images. Explore this module...


Statistics: Predicting Temperature from Ice Cores

This module was developed by Penny Rowe, James Bernhard, and Jacob Price

Students apply statistical tools to polar research and data. This includes creating scatterplots in RStudio of temperature with time for the modern Arctic and the modern global average, demonstrating polar amplification; computing coefficients of linear regression to reconstruct the temperature record for the past 800,000 years from the isotopic record in ice cores; and computing correlation coefficients between CO2 and temperature. Explore this module...

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