In this section I describe three possible topics for a final project. I recommend Topic 1 as the most appropriate for this class because it uses many of the tools we have learned and it is scientifically timely. If students have other projects they would like to address feel free to propose them.

Topic 1. Changes in atmospheric carbon dioxide over the past 40 years

Topic 2. Ocean sedimentation and Milankovitch cycles

Topic 3. Seasonal winds on the North East Pacific Ocean from buoy data

For each one of these topics I will provide a few references to web sites where information about the topic as well as data on the topic can be found. I also suggest for each topic the minimum that you should provide for the project.

Topic 1. Changes in atmospheric carbon dioxide over the past 40 years

Objective: Global Warming is a potential hazard to the planet because of the buildup of greenhouse gases (such as carbon dioxide) in the atmosphere. It is claimed that the buildup of CO2 is directly related to the increase in the human population of our planet. Support or refute this claim using population data from the US census department and CO2 data from Keeling.

Reference:

Project output:

- Statement of the project objective

- Why are the chosen data a good basis for achieving the objective

• Conclusions; Does the analysis of the data support the claim and how well ? If it does support the claim how well does it do this.

Step A Use least squares method to fit a model to human population data

Use data from 1950 to year 2000

Step2. Define a model such that model(t)= a*exp(b*(t-1950))

Step3. Define S to be the sum of squared differences between the data and the model

Step4. Use Solver to minimise S by varying "a" and "b".

How do you quantify what the error estimates on a and b are ???

Step B Use least squares method to fit a model to atmospheric CO2 data

In this step we will get atmospheric CO2 data from the web and we will test the hypothesis that the excess CO2 produced since 1950 is the result of human activity and directly related to the population of the planet.

Step1. You can get the CO2 data from

Step2. Define a model based on the hypothesis that the CO2 has a population generated component and an annual variation associated with the "breathing" of our planet. That is we can say;

Model(t)=c1+c2*population+c3*cos(2*pi*t/12+c4), where the unit of t is 1 month.

For the population we can use the result found in the previous example.

Step3. Define S to be the sum of the squared differences between the model and the data

Step4. Use SOLVER to minimise S by varying c1, c2, c3, c4

Step5. Generate statistics and graphs showing how well (or how poorly) the model fits the data.

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Here is a little Visual Basic Sub to reformat the CO2 data

Sub undoco2()

' Declare variables

Dim RowNum As Integer, colnum As Integer, currcell As Range, nextcol As Integer, temp As Single

' RowNum = ActiveCell.Row ' intialize row number

' colnum = ActiveCell.Column ' intitialize col number

RowNum = 12

rowout = 54

colout = 2

Set currcell = ActiveSheet.Cells(RowNum, colnum) ' go to first cell

Set outcell = ActiveSheet.Cells(rowout, colout)

Do While currcell.Value <> "" ' do while cell not empty

colnum = 1

For counter = 1 To 12

colnum = colnum + 1

rowout = rowout + 1

Set currcell = ActiveSheet.Cells(RowNum, colnum)

Set outcell = ActiveSheet.Cells(rowout, colout)

outcell.Value = currcell.Value

Next

RowNum = RowNum + 1

Loop

End Sub

Topic 2. Ocean sedimentation and Milankovitch cycles

Objective: It is claimed that variations in Earth’s orbit around the sun cause climatic variations which in turn cause sea-level to change, sedimentation rates to change and in the end cause cyclic bedding in deep-sea sediments. The objective is to demonstrate the accuracy or otherwise of this claim.

References:

Project output:

- Statement of the project objective

- What are the variations with time in the heating of the earth that are associated with Earth’ s orbit

- What are the variations with time in the properties of deep-sea sediments

- Conclusions; Is the original claim supported by the the data and how well?

Topic 3. Seasonal winds on the North East Pacific Ocean from buoy data

Objective: A shipping company wants to know how the winds offshore vary with the time of year and the probability that they will encounter winds over 30 knots during a typical year.

References:

Project output:

- Satement of the objective.

- Source of the data and how the data were obtained

- Analysis of the data and presentation of results relating to the objective.

- Conclusions