I may have to use Gavin Schmidt's response: "It's complicated". Here is a fact-check article explaining this a bit better than my original post. My understanding is that homogenization is to REMOVE BIAS, not bias it to fit warming theory.https://www.factcheck.org/2015/02/nothing-false-about-temperature-data/ …
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Above I had NASA GISS http://data.giss.nasa.gov/gistemp RSS satellite http://www.remss.com/measurements/upper-air-temperature/ … (both of those easily played with on woodfortrees) Ocean heat from ARGO/NOAA https://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT/ … Proxy reconstructions from Pages 2Khttp://www.nature.com/ngeo/journal/v6/n5/full/ngeo1797.html …
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In terms of physical system signs of warming... Sea level rise data https://www.star.nesdis.noaa.gov/sod/lsa/SeaLevelRise/LSA_SLR_timeseries_global.php … Rising coral bleaching http://science.sciencemag.org/content/359/6371/80 … Declining sea ice http://psc.apl.washington.edu/wordpress/research/projects/arctic-sea-ice-volume-anomaly/ … Melting ice sheets https://www.nature.com/articles/s41586-018-0752-4.epdf …https://www.nature.com/articles/s41586-018-0179-y …
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This is a good insight into the bias corrections and adjustments to one dataset alone - in both directions and for good reasons. It simply takes a while to realize what might be wrong with the current 'standard' method. That's science.https://en.wikipedia.org/wiki/UAH_satellite_temperature_dataset#Corrections_made …
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