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Chemtrails empirical data tracker - temperature comparisons

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posted on Oct, 17 2011 @ 06:33 PM
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Originally posted by ProudBird
reply to post by Thermo Klein
 


These numbers were in your Opening Post, and then repeated in the post I am now "replying" to:


Originally posted by Thermo Klein
Temperature data:
27 Sep - 79 high, 56 low
28 Sep - 83 high, 58 low
29 Sep - 85 high, 59 low
30 Sep - 85 high, 58 low

I'll post in the next few days if the temperature does go significantly higher than expected.


I haven't yet seen anyone mention......the temperatures, there, are meaningless when discussing contrail formation conditions. Because, those are at the surface.

I see a pattern here of misconceptions. Firstly, the use of surface temperatures is pointless, not sure why it is thought to be relevant.



This was based on an observation by me, in person, that after supposed chemtrail spraying it's "significantly" hotter than expected the next day. After noticing this several times I wanted to track it in this thread.

I didn't make any statement as to why this is happening; it's simply gathering of empirical evidence that may or may not be related. If this starts becoming a common occurance after trails that persist are layed down, then we could look into what types of chemicals may stay in the air, keep hot air from rising/dissipating, etc. Again, not claim, just gathering data.

ETA: I recognize ground temperatures and high altitude temperatures may or may not have a correlation - I haven't looked into the science of it yet as it's not what I'm researching and is actually irrelevant to what I'm researching - which is the temperature after-affects of chemtrail spraying.



edit on 17-10-2011 by Thermo Klein because: (no reason given)




posted on Oct, 17 2011 @ 08:18 PM
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reply to post by Thermo Klein
 


You should also take into account the amount of cloud cover, otherwise any data you gather pertaining to the amount of trails and ground temperature is pretty pointless. Although, you haven't really set up any controls, so this data is more or less useless.

If you do find a correlation, don't be quick to establish a causal relationship!



posted on Oct, 17 2011 @ 08:53 PM
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reply to post by Thermo Klein
 



Oh.


....that after supposed chemtrail spraying it's "significantly" hotter than expected the next day. After noticing this several times I wanted to track it in this thread.



Observation does not always equal causation.

Might want to be careful to also document every instance of weather forecasts being in error, in terms of forecast/actual temperatures for the following day.....not just when the previous day has a lot of contrails observed.

Get it?

e.g. : --- Monday is clear all day, high 59°F/15°C. No clouds at all.

Forecast for Tuesday is to be 56°C/13.3°C.

But, actual temperature on Tuesday turns out to be, 65°F/18.3°C. No clouds, no contrails the previous day (Monday).


Or, something similar. You see, one must consider many factors in an erroneous temperature forecast, because weather doesn't always behave as you expect, since many influences can tip certain factors.

Have fun, if you want to make a hobby of it....seems it would be easier, though, to research into the data that atmospheric scientists have done already, along similar lines. Studying whether there are significant effects from contrails, and if so, to what extent.



posted on Oct, 17 2011 @ 11:34 PM
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Originally posted by adeclerk
reply to post by Thermo Klein
 


You should also take into account the amount of cloud cover, otherwise any data you gather pertaining to the amount of trails and ground temperature is pretty pointless. Although, you haven't really set up any controls, so this data is more or less useless.

If you do find a correlation, don't be quick to establish a causal relationship!


alright, who took over adeclerk's computer!


very good point about not establishing a causal relationship. In college I was a proctor for a Research Methods class. Think I got that part covered



also, to ProudBird - same goes about the research and causality. Good points.




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