This course hosted at MIT Open Course Ware explores visualization methodologies to conceive and represent systems and data, e.g., financial, media, economic, political, etc., with a particular focus on climate change data. The course is useful not only for Media and Communication Studies but also for Computer Science, and Statistics disciplines.
The tool allows a student to explore how isotopes can be used as indicators of paleoclimate and reconstruct the paleoclimate using data from the Vostok ice core.
In this laboratory activity students use statistical methods to analyze historical temperature records of different cities and find significant patterns in the data over time.
This model/simulator shows the relationship between changes in Earth’s climate due to variations in the solar energy received by the planet over geological time scales. It shows that over long timescales ice age cycles (Milankovitch cycles) have occurred on earth due to changes in the orbital parameters (obliquity, precession, and eccentricity).
The tool allows a student to learn about the isotopes of oxygen (O18 and O16); to understand the relative distribution of these isotopes in the atmosphere, ocean and cryosphere; and to explore how these isotopes can be used as indicators of paleoclimate.
This exercise involves plotting global mean temperature from 1850 to 2000, run regression analyses on the data and to plot yearly global mean temperature anomalies.
In this exercise, students learn to use statistical methods on climate data from the Arctic. They run the linear regression on the average monthly extent of Arctic sea ice from 1979 to the present.
In this activity, students are provided with mean atmospheric CO2 concentration from the Mauna Loa observatory from 1950 to the present. This dataset and associated exercise can be used to teach introductory calculus and topics in differentiation such as polynomial differentiation, tangent line problem, and curve fitting amongst others.