This is an online course in Climate Change by the National Resource Centre (NRC) on Climate Change at the Indian Institute of Science Education and Research (IISER), Pune as part of the Annual Refresher Programme in Teaching (ARPIT), Department of Higher Education, Ministry of Human Resources Development, Government of India.
A teaching module that demonstrates the use of linear and quadratic regression to analyze Arctic sea ice extent data and the use of graphs, sample correlations, and multiple regression to analyze atmospheric CO2 level data, solar irradiance data, and average global temperature data.
A classroom/laboratory activity to model temperature data by using trigonometric functions.
A classroom/laboratory activity to analyze CO2 emissions data by using Riemann sums for the calculation of area under the curve.
A classroom/laboratory activity to learn and apply polynomial differentiation and to solve tangent line problems for global average CO2 data.
A classroom/laboratory activity to model how changes in the radiation entering or leaving the Earth affect the temperature of the planet.
A teaching manual for instructors that integrates sustainability themes with mathematics topics for courses or projects in algebra, pre-calculus, or math for liberal arts.
A laboratory activity to create an energy balance model for planet Earth and obtain numerical solutions for the differential equations in the model.
An e-learning course to create climate models in Python through hands-on programming exercises.
|A model/simulator to explore the Gaia hypothesis and the concepts of albedo and hysteresis through the example of daisies (living organisms) and their interaction with temperature (climatic factor).|
A classroom/laboratory activity to learn about linear slope, trends, confidence intervals, and Student’s t-distribution by calculating trends and uncertainties using hurricane data records over 40 years.
A classroom/laboratory activity to learn about statistical methods to analyze average annual temperatures of major cities in the world (New York and Sydney) and to determine trends in the data.
A classroom/laboratory activity to calculate the mean daily temperature using hourly temperature data and to compare different statistical techniques for determining this value.
A classroom/laboratory activity to learn about regression analysis of data by using global temperature data over a period of 150 years.
A classroom/laboratory activity to perform linear regression on climate data from the Arctic.