I dedicate this book to my wife Liisa Moilanen, with whom we have discussed the matters included in this book. Liisa is a researcher and I have got priceless help to carry out this book.
The climate model is often referred to while talking about climate change. I thought I would find out what it consists of. What I did find on the internet was that the carbon dioxide in the climate rises the climate temperature. Another thing was that the climate change models are so large that supercomputers were needed to calculate the million lines large models. I have not seen any presentation meant for the public describing the climate change model of the climate researchers. I wanted to figure out climate change with mathematical models and calculations. I have fortunately the university education to do modelling research and several years of experience modelling industrial processes.
It was quite easy to find data of climate temperature, carbon dioxide concentration, ocean acidity, polar ice cap extent etc. I am used to the way of working that all processes can be described with relatively simple models, which can be detailed if needed. It is always a better way to start the simple way to get a closer look at the problem before proceeding to more complex models. I decided to use Excel as my basic tool for modelling.
While calculating preliminary data correlations I found a very surprising dependence, the one-year old ocean acidity value gives a slightly better correlation than the climate carbon dioxide to the climate temperature. This finding promised an interesting examination.
The starting point for my examination was the doubt that the climate change models give false predictions for global warming. The long-term measurements were available on the internet as well as the Excel calculating programs. The dependencies between the variables could be calculated and analysed with those tools. The global energy change model was the result. Besides:
The calculations and data, which have led to the conclusions above, are presented in this book.
It is time now to correct the understanding about climate change and proceed to the actions according to the more detailed understanding of climate change. The means are fortunately the same regardless of the objective: to prevent climate change or acidification. All groups: the state, municipalities, companies as well as the citizens have to take part in the fight against the global energy change. With good examples and right commercial limitations in foreign trade we may get other countries to fight against the carbon dioxide increase in the climate.
The most important factor in the global energy change is the acidification of oceans and the chemical reactions, which bind and release heat. The importance of which was revealed with the calculations and changed my judgement about climate change completely. I would like to change the concept “climate change” to “global energy change”.
It is important to notice that the chemical energy storing of the oceans overpowers the destructive evolution, which will lead to biota destruction and intensifying of the El Niño phenomenon. That for one will lead to extreme weather behaviour.
I will go through the evidence material of the global energy change as detailed as possible using the data collected scientifically for calculations. I will publish the original and calculated data accurately. I will start with the basic model of climate change, which I suppose to be the basic model of the climate researchers.
Let us make the simplest model and let us examine the suitability of it to describe climate change.
The basic model has a linear dependency between the climate carbon dioxide and the climate temperature, which can be expressed in the form:
T = c * CO2 + T0
where c = constant coefficient
T0 = constant
The calculations of the model parameters as well as derivative model parameters presented in the next chapter are presented in the end of this book in chapter The basic model and its derivative model, calculations.
In all calculations the filtered values of the measurements are used, which is shown with a little “s” letter at the end of the measurements.
The calculated correlation between climate carbon dioxide CO2s and climate temperature Ts was 0,985.
The calculated regression line is presented on equation 1:
Equation 1:
Ts = 0,0153*CO2s-5,103
Using the regression equation, the climate warming has been calculated and it is presented in table 1 in column T(CO2s). The results are also presented in figure 1(= T(CO2s)) together with the measured climate temperature T values. The blue curve represents the measured climate temperature values while the red curve represents with the model calculated values.
Figure 1
The result of the basic model calculation seems to follow rather well the climate temperature. If you look at the measured values, they seem to become slightly curved. This could mean that the temperature dependency on the climate carbon dioxide is nonlinear.
The calculation result accuracy of the basic model was not quite convincing, so let us continue to develop a more accurate model.
The dependency between climate carbon dioxide and temperature was examined in the basic model. Let us investigate now the dependency between the climate carbon dioxide change (=derivative) and temperature. The derivative model describes sometimes better the changes and can be a better model than the basic model.
The calculations showed that the correlation between the filtered derivative value dCO2s and filtered climate temperature value Ts was 0,954. The value is slightly weaker than the correlation of the basic model. This is probably due to the disturbance vulnerable measurement calculation. That is why, the calculated measurement should be filtered more strongly but we would lose then the predictability.
The table 1 includes also the carbon dioxide filtered derivative value in the column dCO2s. In the column T(dCO2s) are the calculated values of the derivative model using the regression equation 2:
Equation 2:
Ts = 0,875 * dCO2s – 1,060
The derivative model results are presented also in figure 1 with grey colour.
The derivative model calculations seem to follow rather well the measured values of the climate temperatures. The same comments as with the basic model are valid. That is the reason to continue to check the possible non-linearities.
Let us examine if the nonlinear model would describe the climate change better than a linear model.
The nonlinearity is easily checked by using the graphical possibility to present the two variables with Excel scatter feature. This is what is done with the variable pairs CO2s / Ts and dCO2s / Ts. The results can be seen in the figures 2 and 3.
Figure 2
Figure 3
It can easily be seen the nonlinearity between the variables CO2s and Ts in figure 2 especially with the higher variable values.
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