 “Fingerprint” of humanity’s climate impact seen in the seasonsEnvironmental | 207921 hits | Jul 20 7:26 am | Posted by: DrCaleb  Yet another accurate model prediction—seasonal patterns around the world.Commentsview comments in forum Page 1 You need to be a member of CKA and be logged into the site, to comment on news. |
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Until you can provide a control subject for comparison, it's conjecture.
In any case, did I read that "article" wrong or is somebody predicting the past then asking us to be amazed?
Until you can provide a control subject for comparison, it's conjecture.
Climate studies aren't performed 'double blind'. Fallacy of Exclusion.
http://www.wolframalpha.com/input/?i=climate
Until you can provide a control subject for comparison, it's conjecture.
Climate studies aren't performed 'double blind'. Fallacy of Exclusion.
http://www.wolframalpha.com/input/?i=climate
We could use Venus as the control subject, runaway greenhouse effect at its finest.
Until you can provide a control subject for comparison, it's conjecture.
In any case, did I read that "article" wrong or is somebody predicting the past then asking us to be amazed?
What's ironic is that I have yet to hear of one of these climate models that accurately predict the known past.
By that I mean if you take the data set for the 1930's and enter it into most any climate model it will consistently predict the 1940's and 1950's as being warmer.
Even though in reality they were significantly cooler.
That's the thing about these models is their inherent bias. No matter what data you input (including random numbers) the majority of these models will predict a warming trend.
What's ironic is that I have yet to hear of one of these climate models that accurately predict the known past.
No, what is ironic is the number of times I've shown you that every climate model is tested in this way before it's used to predict the future.
https://www.ceh.ac.uk/our-science/scien ... ate-models
What's ironic is that I have yet to hear of one of these climate models that accurately predict the known past.