**Steven Mosher's Blog**, and kindly contributed to R-bloggers)

UPDATE: Ron Broberg has a more definitive explanation of the difference which indicates that 5sig issue is not the main cause of the difference. See his exposition here

A short update. I’m in the process of integration the Land Analysis and the SST analysis into one application. The principle task in front of me is integrating some new capability in the ‘raster’ package. As that effort proceeds I continue to check against prior work and against the accepted ‘standards’. So, I reran the Land analysis and benchmarked against CRU. Using the same database, the same anomaly period, and the same CAM criteria. That produced the following

My approach shows a lot more noise. Something not seen in the SST analysis which matched nicely. Wondering if CRU had done anything else I reread the paper.

” Each grid-box value is the mean of all available station anomaly values, except that station outliers in excess of ﬁve standard deviations are omitted.”

I dont do that! Curious, I looked at the monthly data:

The Month were CRU and I differ THE MOST is Feb, 1936.

lets look at the whole year of 1936

First CRU

**no conclusions yet**, just a curious place to look. More later as time permits. If you’re interested double check these results.

**leave a comment**for the author, please follow the link and comment on his blog:

**Steven Mosher's Blog**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...