In this post I present a trend chart which shows the September anomaly trends for the 5 major global temperature anomaly series and a table that shows how September 2010 ranks over the entire record for each series. The source data and RClimate script file links are provided.
Update 1: In a comment, ChristianP suggested the addition of a loess regression fit to the trend line chart. Thanks ChristianP.
Both of the satellite anomaly series, RSS and UAH, had their highest September anomalies in 2010. For the three station series, Sept, 2010 ranked 4th in the GISS series, 8th in the NOAA series and 11th in the Hadley series out of the 131 years data period (1880-2010) for these 3 series.
Please not that the plots show the climate agency monthly anomaly values with respect to each agency’s baseline period. For RSS and UAH, that is 1979-1998. For GISS it is 1951-1980 and for NOAA and Hadley, it is 1961-1990.
RClimate Script Details
Here are the data and RClimate Script links:
- Data Link (Use this link if you want to download CSV data file. See example script below if you’d like to read file directly into your R script.)
- RClimate Script link
I continue to improve my RClimate.txt file for readers who would like to reproduce/ analyze the data yourself. Here’s a 2-line snippet to show how you can source my RClimate.txt file and retrieve the monthly anomaly data for the 5 series.
source("http://processtrends.com/files/RClimate.txt") lota <- get_lota()
With just 2 lines of R Script you can source my RClimate.txt script file and call my lota_func() function to retrieve the temperature anomaly data for the 5 series into your R session.