Seeing the environmental forest

Spencer and Christy recently released a new version (version 6.0) of the UAH satellite temperature data . To see how their data has changed, I've compared the 6.0 version to the earlier 5.6 version and compared both to RSS, similar to what I did before . All calculations were made using annual data. The difference between UAH 5.6 and UAH 6.0 is quite dramatic, especially since 2000, and the difference has grown over time. Difference calculated by subtracting annual version 6.0 values from the respective 5.6 values.   Comparing both UAH versions to RSS shows that while version 5.6 was consistently warmer than RSS since 2003, version 6.0 has a tendency to run cooler than RSS since 1998. The effect all the changes from 5.6 to 6.0 had on the calculated trend was drastic. Since 1990, the average version 6.0 trend is 0.0094ºC/year lower than the same trend in version 5.6.  For version 5.6, only the trends since 1997, 1998, and 2000 were not statistically significa...

An old friend posted an " article " by Tom Luongo, a former chemist (B.S. from the University of Florida) who now writes the Resolute Wealth Newsletter, on Facebook.  Unfortunately, that article is chock full of lies about climate science.  Since Facebook comments aren't the best forum for debunking Gish Gallops, I'm taking the liberty of debunking them here. [Update: Since Luongo got most of his claims from John Casey, I've written something about his brand of science here .]

WUWT published a piece by Danle Wolfe which purports to measure the correlation between CO 2 and global temperature.  As you can probably predict, Wolfe's conclusion is that there is no relationship. "Focusing on the most recent hiatus below, both visually and in a 1 st order linear regression analysis there clearly is effectively zero correlation between CO 2 levels and global mean temperature."  Unfortunately for Wolfe, all he's produced is a fine example of mathturbation as well as an example of forming a conclusion first then warping the evidence to fit.

The Berkeley Earth team released a new temperature analysis that includes both land and ocean surface temperatures .  They used their existing land data and merged it with HadSST data (note: not HadSST3 as I originally wrote), using kriging to interpolate temperatures where data did not directly exist.  In this, their methodology is similar to the recent Cowtan and Way ( 2013 ) paper, however, Cowtan and Way used HadSST3 for their ocean data.  I've compared their new results over the past 30 years (Jan 1984-Dec 2013) to GISS, HadCRUT4, NCDC, UAH, and Cowtan and Way's results, first standardizing all temperature anomalies to the 1981-2010 baseline.  Why the past 30 years?  Thirty years is generally considered the standard time period for measuring climate.  All trends mentioned in this article are calculated using linear regression corrected for autocorrelation.