Climate Change Education Across the Curricula, Across the Globe

Climate Change Education Across the Curricula

Tag: Mathematics & Statistics

Teaching Module: Climate Change Mathematics by NASA

Posted by on in Earth Sciences, Environmental Sciences, Mathematics and Statistics

A teaching module by NASA makes the use of basic mathematics, algebra, geometry, trigonometric functions and statistics to understand earth science and climate change. This teaching module consists of a range of topics, for different grade levels, and relates them to mathematical modelling. The topic covered are as stated below:

  1. Fractions and Chemistry
  2. Counting Atoms in a Molecule
  3. Parts per Hundred
  4. Parts per Thousand
  5. Kelvin Temperatures and Very Cold Things
  6. Does Anybody Really Know What Time It Is? 
  7. Ancient Eclipses and the Length of Day 
  8. Earth’s Polar Wander – The Chandler Wobble 
  9. Identifying Materials by their Reflectivity 
  10. Reflectivity Fingerprints
  11. Graphical Reflectivity Measurements 
  12. Electricity – Watts and Kilowatts
  13. Energy in the Home
  14. Energy Consumption in an Empty House! 
  15. Annual Electricity Consumption in a Home
  16. Carbon Dioxide Production at Home
  17. US Electrical Energy Consumption
  18. World Electricity Consumption and Carbon Dioxide 
  19. Earth’s Atmosphere
  20. Carbon Dioxide Production and Sequestration
  21. Carbon Dioxide Increases
  22. Modeling the Keeling Curve with Excel
  23. Carbon Dioxide – Where does it all go?
  24. A Simple Model for Atmospheric Carbon Dioxide 
  25. Carbon Dioxide Increases During the Last 2000 Years
  26. Carbon Dioxide Changes During the Last 400,000 Years 
  27. Solar Insolation Changes and the Sunspot Cycle
  28. The Solar Constant Since 1600
  29. Scientists Track the Rising Tide
  30. A Satellite View of Downtown Las Vegas
  31. Exploring Washington DC from Space! 
  32. Paris – In a Different Light
  33. Glacier Retreat
  34. Estimating Biomass Loss From a Large Fire 
  35. Earth – A Matter of Gravity!
  36. Magnetic Earth and the Lithosphere 
  37. Studying Ocean Plankton From Space 
  38. NASA Satellite Sees Carbon Dioxide 
  39. Carbon Production in the US – 2002 
  40. Earth’s Carbon Metabolism – Revealed
  41. The International Space Station and Atmospheric Drag 
  42. Satellite Drag and the Hubble Space Telescope 
  43. Earth’s Rotation Changes and the Length of the Day 
  44. The Global Warming Debate and the Arctic Ice Cap 
  45. The Great Gulf Oil Catastrophe of 2010
  46. Recent Events: A Perspective on Carbon Dioxide

Use this tool to help students find answers to:

  1. What is ‘reflectivity’? Graph the measurements of commonly mentioned materials as per their reflectivity index.
  2. What is ‘Keeling Curve’? What does it say about carbon dioxide concentrations over time?
  3. How is carbon dioxide concentration calculated using satellite imagery?

About the Tool

Tool NameEarth Math Educator Guide
DisciplineEarth Sciences, Mathematics and Statistics, Environmental Sciences
Topic(s) in DisciplineAlgebra, Data Analysis, Probability, Trigonometry, Fractions and Decimals, Energy Consumption, Visualization, Graphs, Atmospheric Carbon Dioxide, Keeling Curve, Carbon Sequestration, Glacier Retreat
Climate TopicIntroduction to Climate Change; Climate Variability Record; Planetary Climate
Type of toolTeaching Module
Grade LevelMiddle School, Highschool
LocationGlobal
LanguageEnglish
Translation 
Developed byNASA
Hosted atNANA STEM Engagement Website 
LinkLink
AccessOnline/ Offline
Computer SkillsBasic

Teaching Module: Predict the Climate by throwing a dice

Posted by on in Mathematics and Statistics

A teaching module that uses a dice and Excel to demonstrate the difference between experimental and theoretical probabilities. It also uses temperature and precipitation data to calculate moving average, identify trends in time series, and learn about data visualization.

This teaching module provides multiple resources under 4 categories:

  1. Teachers’ notes for ‘Using sample data sets’ for offline teaching.
  2. Teachers’ notes, students’ notes, sample spreadsheet, presentation and presentation notes for ‘ Using dice as Climate Model’ for offline teaching using a computer.
  3. Teachers’ notes and students’ worksheet for ‘Investigating climate data using climateprediction.net results’ for online teaching, and
  4. Presentation and teaching notes for designing statistical questionnaire

Students will ​​learn about Excel functions, such as RAND, IF, and AVERAGE. They will also learn about visualization, modeling, probability and time series through climate modeling. Furthermore, students will also learn basic methodology used while designing questionnaires. 

Use this tool to help students find answers to:

  1. If you throw a dice 100 times, can you predict the climate? What is the probability that the 101st throw will be 4?
  2. Using climatepredictions.net to run temperature models, calculate the percentage error for each model.
  3. How is climate predicted? Why does climate prediction require the use of multiple models run over long periods of time? 

About the Tool

Tool NameKey stage 3 & 4 Maths
DisciplineMathematics and Statistics
Topic(s) in DisciplineProbability, Average, Moving Average, Mean, Time Series, Visualization, Questionnaire Formulation
Climate TopicClimate Variability Record; Climate and the Atmosphere
Type of toolTeaching Module
Grade LevelHigh School
LocationGlobal
LanguageEnglish
Translation 
Developed byclimateprediction.net
Hosted atclimateprediction.net
LinkLink
AccessOnline/ Offline
Computer SkillsBasic

Differential Calculus using Methane Data

Posted by on in Mathematics and Statistics

A classroom/laboratory activity for Mathematics teachers to teach about Differential Calculus, specifically, about polynomial differentiation focusing on  Tangent Line Problem and Curve Fitting. This activity contains yearly data of the globally averaged marine surface methane from 1984 to 2019. Methane is a major contributor to greenhouse gas emissions – a potential cause of global warming.

Students will learn the use of scatter plot and curve fitting to derive the polynomial differentiation function. Further this activity will allow students to predict future methane concentrations.

Use this tool to help your students find answers to:

  1. What are polynomial differentiation functions?
  2. Derive a polynomial function using the given methane concentration date.
  3. Calculate future methane concentration using polynomial differentiation.

About the Tool

Tool Name Global Marine Surface CH4
Discipline Mathematics and Statistics
Topic(s) in Discipline Differential Calculus, Polynomial Differentiation, Tangent Line Problem, Scatter Plot, Curve Fitting
Climate Topic Classroom/Laboratory Activity
Type of Tool Video (64 mins)
Grade Level High School, Undergraduate
Location  Global
Language English
Translation –
Developed by Thomas J. Pfaff (Ithaca College)
Hosted at Sustainability Math
Link Link
Access Offline
Computer Skills Basic

Classroom/ Laboratory Activity: Teaching Differentiating Functions through Solar Energy Data

Posted by on in Mathematics and Statistics

A classroom/ laboratory activity titled, ‘Country Photovoltaic Energy Production’ from Sustainability Math by Thomas J. Pfaff, Ithaca College, USA, to teach differentiating functions – logistic and exponential, using a hands-on computer-based classroom activity that includes data of photovoltaic (solar) energy production of several countries from 1990 to 2016.

This data is provided in an Excel spreadsheet. The classroom activity also includes a Word document that contains directions on how to use different mathematical methods on the data provided. 

Students will learn how to apply their understanding of logistic and exponential functions and apply the Quotient (or Product) Rule to describe the rates of increase of photovoltaic energy production over time in several countries such as Germany, Italy, and USA, amongst others, in recent times. 

Use this tool to help your students find answers to:

  1. What are differentiating functions?
  2. Distinguish between logarithmic, exponential, and logistic differentiating functions.
  3. How has the rate of global solar energy production changed since 1990?
  4. How do the rates of solar energy production in select countries (from the given datasets) differ from that of the World?
  5. Discuss how the use of photovoltaic energy can be a viable alternative to fossil fuels to combat global warming.

About the Tool

Tool NameCountry Photovoltaic Energy Production
DisciplineMathematics and Statistics
Topic(s) in DisciplineLogarithmic, Exponential, Logistic Differentiating Functions, Quotient or Product Rule
Climate TopicEnergy, Economics and Climate Change; Climate Mitigation and Adaptation
Type of toolClassroom/Laboratory Activity
Grade LevelHigh School, Undergraduate
LocationGlobal
LanguageEnglish
Translation
Developed byThomas J. Pfaff
Hosted atSustainability Math 
Linkhttp://sustainabilitymath.org/calculus-materials/
AccessOnline, Offline
Computer SkillsBasic

Classroom/ Laboratory Activity: Differentiation and Wind Energy

Posted by on in Mathematics and Statistics

A classroom/ laboratory activity titled, ‘Wind Energy by Selected Countries and World’ from Sustainability Math by Thomas J. Pfaff, Ithaca College, USA, to teach polynomial and logistic differentiation using a hands-on computer-based classroom activity that includes wind energy production data of several countries from 1980 to 2016.

This data is provided in an Excel spreadsheet.The classroom activity also includes a Word document that contains directions on how to use different mathematical methods on the data provided.

Students will learn how to apply their understanding of polynomial and logistic differentiation and apply the Quotient (or Product) Rule to describe the rates of increase of wind energy production over time in countries such as China, Spain, USA, and the World.

Use this tool to help your students find answers to:

  1. What are differentiating functions?
  2. Describe polynomial and logistic differentiation using examples.
  3. How has the rate of global wind energy production changed since 1980?
  4. How do the rates of wind energy production in select countries (from the given datasets) differ from that of the World?
  5. Discuss how the use of wind energy can be a viable alternative to fossil fuels to combat global warming.

About the Tool

Tool NameWind Energy by Selected Countries and World
DisciplineMathematic and Statistics, 
Topic(s) in DisciplinePolynomial and Logistic Differentiation, Quotient or Product Rule
Climate TopicEnergy, Economics and Climate Change; Climate Mitigation and Adaptation; Climate Variability Record
Type of toolClassroom/Laboratory Activity
Grade LevelHigh School, Undergraduate
LocationGlobal
LanguageEnglish
Translation
Developed byThomas J. Pfaff
Hosted atSustainability Math 
Linkhttp://sustainabilitymath.org/calculus-materials/
AccessOnline, Offline
Computer SkillsBasic

Classroom/ Laboratory Activity: World Petroleum Consumption

Posted by on in Mathematics and Statistics

A classroom/ laboratory activity titled, ‘World Petroleum Consumption’ from Sustainability Math by Thomas J. Pfaff, Ithaca College, USA, to teach integration using a hands-on computer-based classroom activity that includes world petroleum consumption data from 1980 to 2016

This data is provided in an Excel spreadsheet. The classroom activity also includes a Word document that contains directions on how to use different mathematical methods on the data provided.

Students will learn how to apply their understanding of the relationship between a function and its integral and to set up and solve equations with an integral to describe the trend of world petroleum consumption over time. Additionally, they will also be able to answer how this global petroleum consumption is responsible for carbon emissions that have contributed towards post-industrial age global warming.

Use this tool to help your students find answers to:

  1. What is the relationship between a function and its integral?
  2. How has the world petroleum consumption changed since 1980?

About the Tool

Tool NameWorld Petroleum Consumption
DisciplineMathematics and Statistics
Topic(s) in DisciplineIntegration, Integral Function, Function
Climate TopicEnergy, Economics and Climate Change; Climate Mitigation and Adaptation
Type of toolClassroom/Laboratory Activity
Grade LevelHigh School, Undergraduate
LocationGlobal
LanguageEnglish
Translation
Developed byThomas J. Pfaff
Hosted atSustainability Math 
Linkhttp://sustainabilitymath.org/calculus-materials/
AccessOnline, Offline
Computer SkillsBasic

Model/Simulator: Modeling Earth’s Carbon

Posted by on in Earth Sciences, Mathematics and Statistics

A model/simulator to learn about the carbon cycle and carbon dioxide projections based on the observed CO2 concentrations from Land, Ocean and Atmospheric reservoirs.  The model includes four RCP scenarios based of fossil fuel emissions:

  1. Business as usual
  2. Slower Growth
  3. Big Reductions
  4. Very Aggressive

Students can simulate future carbon dioxide concentration, surface temperature, ocean surface pH and carbon fluxes through the use of this model. They will learn to calculate the projections based on various future scenarios for reservoirs of anthropogenic carbon.

Mathematics/Statistics teachers can use this resource to teach their students about models and the use of climate data to create models.

Use this tool to help your students find answers to:

  1. What is a carbon cycle? How does atmospheric CO2 impact land and ocean carbon concentration?
  2. Define the ‘business-as-usual’ scenario in the model.
  3. Based on the past projections, what will be the average surface temperature in each RCP scenario?

About the Tool

Tool NameEarth[carbon]
DisciplineEarth Sciences, Mathematic and Statistics 
Topic(s) in DisciplineCarbon Cycle, Atmospheric CO2, Surface Ocean pH, RCP Scenarios, Anthropogenic Carbon, CO2 emissions, Data Analysis, Statiscal Methods, Modelling, Data Projections
Climate TopicClimate Variability Record
Type of toolModel/Simulator
Grade LevelUndergraduate
LocationGlobal
LanguageEnglish
Translation
Developed bybiocycle.atmos.colostate.edu
Hosted atbiocycle.atmos.colostate.edu
LinkLink
AccessOnline, Offline
Computer SkillsBasic

Classroom/Laboratory Activity: Linear Regression using Global Temperatures

Posted by on in Mathematics and Statistics

A classroom/lab activity for Statistics teachers to teach about Linear Regression. This activity is based on a dataset on average global temperature anomalies from 1850 to 2019. 

Students will learn about introductory linear regression techniques and will learn to make scatter plots of the data provided. This tool will allow the student to understand changes in the average global temperatures since the industrial revolution. 

Use this tool to help your students find answers to:

  1. What is linear regression?
  2. Plot the average global temperature anomalies on a scatter plot.
  3. What are confidence intervals? What are the confidence interval slopes for global temperature at 25, 50, 100 and 150 years before 2019?
  4. How have human activities impacted average global temperatures since the Industrial revolution?

About the Tool

Tool Name Global Temperature Anomalies
Discipline Mathematics and Statistics
Topic(s) in Discipline Linear regression, Scatter Plot, Confidence Intervals
Climate Topic Climate Variability Record
Type of Tool Activity
Grade Level High School, Undergraduate
Location Global
Language English
Translation –
Developed by IPCC, Thomas J. Pfaff (Ithaca College)
Hosted at Sustainability Math
Link Link
Access Offline
Computer Skills Basic

Teaching Module: T-tests and Climate Data

Posted by on in Mathematics and Statistics

A teaching module by Wendy Van Norden, University of Wisconsin, that makes the use of T-tests to analyse dataset to study seasonal ice cover over Lake Mendota, US, to understand how climate change has impacted ice cover over 160 years.

This teaching module will have the following outcomes:

  1. Students will learn the use of Excel through a guided-inquiry process of the statistical tool (T-test) for comparing change in seasonal ice cover data over time. 
  2. Students will be introduced to statistical terms such as probability, variance, uncertainty, standard deviation, mean and T-test. 
  3. Students will understand the difference between annual variability versus long-term trends.

Additionally, students will ​​learn to use and investigate the IPCC Likelihood Scale and apply it to their statistical results.

Use this tool to help students find answers to:

  1. What is a T-test?
  2. Using T-test for the given data, calculate the probability of ‘ice off’ date being earlier than in the previous decades.

About the Tool

Tool NameProbabilities, Uncertainties and Units Used to Quantify Climate Change
DisciplineMathematics and Statistics
Topic(s) in DisciplineProbability, Variance, Uncertainty, Standard Deviation, Mean, T-test, P-value
Climate TopicClimate Variability Record; Climate and the Hydrosphere
Type of toolTeaching Module
Grade LevelHighschool
LocationGlobal
LanguageEnglish
Translation 
Developed byWendy Van Norden
Hosted atCLEAN Website
Linkhttps://cleanet.org/resources/42682.html
AccessOnline/ Offline
Computer SkillsBasic

Teaching Module: Introduction to Statistics through Weather Forecasting

Posted by on in Earth Sciences, Mathematics and Statistics

A teaching module by Ginny Brown, University Corporation for Atmospheric Research (UCAR), that uses climate data to teach statistical parameters such as mean, median, mode, extreme values, percent frequency of occurrence and time, range, standard deviation, and data anomalies. It also includes discussion on the use of statistical parameters that represent a climate or weather variable.

Students will learn the statistical parameters used in basic climate modeling. Additionally, they will also learn about climatology and forecasting.  

Use this tool to help students find answers to:

  1. Define the following:
    1. Mean
    2. Median,
    3. Mode,
    4. Frequency,
    5. Standard Deviation
    6. Data anomaly
  2. Explain what statistical parameters are best suited for weather prediction using wind and temperature data. 
  3. Describe the impacts of data quality on climate modeling.

About the Tool

Tool NameModule: Introduction to Statistics for Climatology – UCAR COMET
DisciplineMathematics and Statistics, Earth Sciences
Topic(s) in DisciplineMean, Median, Mode, Frequency, Standard Deviation, Data Anomalies, Climatology, Weather Forecasting
Climate TopicClimate Variability Record; Climate and the Atmosphere
Type of toolTeaching Module
Grade LevelHigh School
LocationGlobal
LanguageEnglish
Translation 
Developed byGinny Brown, University Corporation for Atmospheric Research (UCAR)
Hosted atCAMEL Climate Change Education
LinkLink
AccessOnline/ Offline
Computer SkillsBasic

Classroom/ Laboratory Activity: Statistical Methods Using Temperature Data

Posted by on in Mathematics and Statistics

A classroom/ laboratory activity titled, ‘US Historical Climate: Excel Statistical’ from Starting Point by R.M. MacKay, Clark College, USA, to calculate mean, variance, standard deviation, maximum, minimum, and trends estimates for historical temperature data.

This data is provided in an Excel spreadsheet in the activity. It also includes a PDF document with detailed instructions.  It further includes questions that you may wish to use in your classroom to explain statistical functions and methods and to initiate a discussion on the increase in average and mean temperature anomalies from 1895 to 1994.

Students will learn to use Excel for statistical calculations such as average, mean, variance and standard deviation. They will also learn the use of running mean filter and how to calculate statistical errors in a given data.

Use this tool to help your students find answers to:

  1. Define the following:
    1. Standard Deviation
    2. Variance 
    3. Running Mean
    4. Statistical Error
  2. How do the anomaly variance and standard deviations compare with the temperature variance and standard deviation?
  3. Knowing that Winter solstice is December 21, what is the lag in months between minimum solar input and minimum temperature?

About the Tool

Tool NameUS Historical Climate: Excel Statistical
DisciplineMathematic and Statistics 
Topic(s) in DisciplineExcel Functions, Statistical Functions, Mean, Variance, Standard Deviation, Statistical errors, Running Mean
Climate TopicClimate and the Atmosphere, Climate Variability Record
Type of toolClassroom/Laboratory Activity
Grade LevelHigh School, Undergraduate
LocationGlobal
LanguageEnglish
Translation
Developed byR.M. MacKay
Hosted atStarting Point: Teaching Entry Level Geoscience
LinkLink
AccessOnline, Offline
Computer SkillsBasic

Classroom/ Laboratory Activity: Polynomial Differentiation Using Temperature Data

Posted by on in Mathematics and Statistics

A classroom/ laboratory activity titled, ‘Global Average Temperature’ from Sustainability Math by Thomas J. Pfaff, Ithaca College, USA, to teach derivatives and polynomial differentiation using global average temperature data. This classroom/laboratory activity uses NASA’s data of  global annual mean surface air temperature from 1950 to 2018. 

This data is provided in an Excel spreadsheet in the activity. It also includes a Word document with detailed instructions.  It further includes questions that you may wish to use in your classroom to explain mathematical functions and methods and to initiate a discussion on the increase in global annual mean surface temperature due to anthropogenically forced global warming.

Students will learn about derivatives and differentiation. They will also understand function composition and tangent line problems. They will further learn how to apply polynomial differentiation to predict changes in global average temperatures from a given dataset.

Use this tool to help your students find answers to:

  1. What are derivatives and tangent line equations?
  2. Using an example, describe polynomial differentiation.
  3. What is the rate of change of global average temperatures?
  4. Predict the global average temperatures for 2030, 2050, and 2100.

About the Tool

Tool NameGlobal Average Temperature
DisciplineMathematic and Statistics 
Topic(s) in DisciplineDerivatives, Tangent Lines, Differentiation, Differentiation Rules, Function Composition, Polynomial Differentiation
Climate TopicClimate and the Atmosphere, Climate Variability Record
Type of toolClassroom/Laboratory Activity
Grade LevelHigh School, Undergraduate
LocationGlobal
LanguageEnglish
Translation
Developed byThomas J. Pfaff
Hosted atSustainability Math 
Linkhttp://sustainabilitymath.org/calculus-materials/
AccessOnline, Offline
Computer SkillsBasic

Classroom/ Laboratory Activity: Teaching Polynomial Differentiation with Arctic Sea Ice Data

Posted by on in Mathematics and Statistics

A classroom/ laboratory activity titled, ‘Arctic Sea Ice’ from Sustainability Math by Thomas J. Pfaff, Ithaca College, USA, to teach introductory derivatives, polynomial differentiation, and the application of derivatives. This hands-on computer-based classroom activity consists of datasets of Arctic Ice Data (1980-2017). 

This classroom activity includes three datasets of the extent of Arctic Sea Ice linked from NSIDC’s observations from 1980 to 2017. This data is provided in an Excel spreadsheet. The classroom activity also includes a Word document that contains directions on how to use different mathematical methods on the data provided.

Students will be able to apply their understanding of sixth degree polynomial differentiation, maxima/minima values, finding roots and inflection points through the use of datasets from the National Snow and Ice Data Center (NSIDC). They will further be able to initiate a discussion on the decrease in extent of Arctic Sea Ice due to the Ice Albedo Feedback and anthropogenically forced Global Warming through the links provided in the tool.

Use this tool to help your students find answers to:

  1. Using an example, describe polynomial differentiation.
  2. Has the speed of melting of Arctic Sea Ice changed from 1980- 2017?
  3. Discuss the Ice Albedo Feedback and Global Warming to explain the differences in rates of melting of and extent of Arctic Sea Ice over the past four decades.

About the Tool

Tool NameArctic Sea Ice
DisciplineMathematic and Statistics 
Topic(s) in DisciplineDerivatives, Polynomial Differentiation, Function Graph, Extrema, Concavity, Roots, Inflection Points, Albedo Feedback, Global Warming
Climate TopicClimate and the Cryosphere; Climate Variability Record
Type of toolClassroom/Laboratory Activity
Grade LevelHigh School, Undergraduate
LocationGlobal
LanguageEnglish
Translation
Developed byThomas J. Pfaff
Hosted atSustainability Math 
Linkhttp://sustainabilitymath.org/calculus-materials/
AccessOnline, Offline
Computer SkillsBasic