carmar wrote:
Incorrect.
If CO2 is not the independent variable, then the relationship of CO2 to temp is spurious correlation.
This statement makes absolutely no scientific sense, whatsoever.
Whether or not CO2 increase is relevant to time or independent of it has no bearing, at all, as to whether increased CO2 increases the Green House effect.
It is known that increased C)2 increases the greenhouse effect- Heavily.
https://en.wikipedia.org/wiki/Greenhouse_gashttps://www.epa.gov/ghgemissions/source ... -emissionsWhat matters in this topic is whether human actions are responsible for this increase.
carmar wrote:Further, if time is always relevant to rate of change, then all relations in this universe are solely governed by time. Humans do not control time, hence humans cannot control CO2, temperature, et al.
Your argument on this is used to claim that time is not relevant to Climate Change. Again:
It is relevant because it is an examination of the rate of change prior to and after Human Industrialization.
Look at this:
It is very clear.
carmar wrote:One example of where time is not the independent variable:
I drive while texting and drinking my coffee. The total number of texts I make, per trip, governs the number of times I spill coffee. Former is independent, latter is dependent. Time is not the independent variable in this example. The trip could be the exact same duration every time (say, a commute to work), hence no variation in duration, however, there can be variation in the number of spills because the number of texts correlates.
This is not relevant. The topic here is about the INCREASE of CO2 in the atmosphere Over Time and the time periods that show the most increase. You cannot remove Time from this. See the above Graph,
Your example of Coffee and Texts is a slope, but is a Correlation graph, not a rate of change graph. Both a correlation and a rate of change use a slope and both can be graphed in the same manner. However, rate of change is the amount of change over the amount of time. Correlation is on factor compared to the other factor.