@MontyPython
so not even going to address the one point I made? typical.
I have read a lot of papers, most of them fall into one of several fallacies. the most common, that I have seen, I already mentioned. They reference the "preIndustrial era" which was artificially cool. so any return to normal looks like "warming" instead of returning to normal.
some other common fallacies:
1. other reliance on flawed understanding of how averages work. one day/month/year being hotter than the "average" doesn't mean something changed. the average is built of both higher and lower numbers, there is almost never a day that actually meets the assigned "average" value. case in point, lets say the average temperature of Dec 15 in Atlanta GA is 40 degrees fahrenheit. the last 5 Dec 15ths have been 41, 36, 43, 34, and 46. 46 HOLY CRAP its 6 degrees WARMER THAN AVERAGE. GLOBAL WARMING PROVVVVVVVVVVVVEEEEEEEEEEEEDDDDDDDD!!!!!!!!!! Its science, right? well, not really. those 5 temps still average to 40 degrees, even though there was never a 40 degrees, and we got up to 46 one year. if you read a lot of methodology they very rarely control for this.
2. the change in instrumentation. we use different, more precise equipment, and we get different values than we did before. in every other form of science there is a control any reading will be based on, climate change not so much.
3. variable changing outside of the actual weather and climate. most temperature readings are taken from the same spot year over year. makes sense. however the reality around those individual locations change pretty dramatically which effect the micro climate. more development means a greater heat island effect, which pushes the temperature up with out changing the actual macro climate. Micro vs macro is a big area of discussion in the actual field. but you won't address that either.
4. selective data reporting. again go and read any climate study and they will tell you all the data they throw out. some of it makes sense, like a solar eclipse, others don't make sense, they threw out rainy days. even though they were basing their historical data on days that included rain.
most of the papers when you sit down and read them do say what they are saying but they are throwing in some many qualifiers it begs the question why even say it?