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Prof. Gerald Schuller


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Climate Change Calculated

Part 1

Can we trust media reports and scientists with respect to climate change? Natural sciences are made such that their results can be checked and verified by computations. In this way we can also check media reports. In the first part of the series we answer the question: Is the oberved increase of the concentration of carbon dioxide due to human activity, and if yes, to which degree?

YouTube Link:

Pdf Slides

Python Script 1

Python Script 2

CSV file 1

CSV file 2

CSV file 3


In part 2 of the series we answer the question: does the CO2 concentration influence the global temperature? We look at the physical foundations of the green house effect of CO2, and calculate the resulting expected global temperature increase.

YouTube Link:

The files for it:

Pdf of the slides

Python script

CSV file


In the 3rd part of the series we answer the question: What sea-level rise can we expect? We look at the latent heat of ice and calculate the melting speed using the radiative forcing of the increased CO2 concentration in the atmosphere, andcalculate the rise of the sea level using the surface area of the oceans.

YouTube Link:

Pdf of the slides

The links from the slides:


In part 4 we answer the question: what can we do? We look at the composition of Germanys electricity generation, the development of technologies for renewable energy and the development of their costs.

YouTube Link:

Pdf of the slides


Climate Change Calculated, Special on Corona Virus:

Here I show the connection of climate change and new viruses, and show a statistical logistic model to predict the spread of the COVID-19 virus for 15, 30, and 100 days.

YouTube Link:

Pdf of the slides

Link to the Python program


Climate Change Calculated, Corona Update

In this episode I show the changes in climate that we had last winter and through the Corona virus.

Then I will compare my model for the Corona spread with data from the Johns Hopkins University, update my model with that data, and show comparisons of the daily factor of increase for different countries.

Comparing the data with my model, the effects of the measures from March 20 on become clearly visible. 

Then I will use my updated model for predictions for April, and for a 150 day long term prediction.

YouTube Video link

The pdf of the slides

Python Programs:

With the following program you can follow the factor of daily increase of the corona cases, starting on April 1st. It loads the latest data every time it starts from Github. We need a factor of 1.02 (doubling every 35 days), and you can see how we are slowly approaching it, and that South Korea is already there:


Climate Change Calculated, Corona Update 2

in this episode I analyse the current state of the spread of SARS-cov2, calculate the density of the concorrently sick people, and their factor of increase, and compare the developments in Germany and the US.

YouTube Video Link:

Slides (PDF)

Python program for calculating the plots

Jupyter notebook in github and Google Colab:


Climate Change Calculated, Corona Update 3

in this episode I compute the Under Detection Rate of Corona infections, and present an online Corona Program for computing the under detection rate, and a 30 or 90 day prediction of the concurrently sick.

Slides Pdf

Jupyter notebook in github and Google Colab: