{"id":14568,"date":"2019-12-05T17:25:45","date_gmt":"2019-12-05T17:25:45","guid":{"rendered":"http:\/\/www.wjst.de\/blog\/?p=14568"},"modified":"2019-12-15T13:25:05","modified_gmt":"2019-12-15T13:25:05","slug":"correlation-of-earth-temperature-and-global-mean-co2","status":"publish","type":"post","link":"https:\/\/www.wjst.de\/blog\/sciencesurf\/2019\/12\/correlation-of-earth-temperature-and-global-mean-co2\/","title":{"rendered":"Correlation of earth temperature and global mean CO2"},"content":{"rendered":"

For teaching purposes I need the CO2 <\/sub>concentration vs earth temperature by year (Keeling curve<\/a>). For that purpose we can use the Hadcrut 4 dataset created earlier <\/a>while the global mean CO2<\/sub>\u00a0mix ratios (ppm) can be found at https:\/\/data.giss.nasa.gov\/modelforce\/ghgases\/Fig1A.ext.txt<\/a>.
\nAfter unscrambling that file and merging it to Hadcrut4 we can plot it<\/p>\n

\r\nlibrary(patchwork)\r\np1 <- ggplot(temp, aes(x=year, y=annual)) + geom_point() + stat_smooth(method="loess", span = .6) +\r\n  scale_y_continuous( name="difference from baseline  [ oC ]", limits=c(-1,1) )\r\n\r\np2 <- ggplot(temp, aes(x=year, y=ppm )) +  geom_point() + stat_smooth(method="loess", span = .6) +\r\n  scale_y_continuous( name=expression('ppm CO'[2]) )\r\np1+p2\r\n<\/pre>\n
Here are the two time courses<\/p>\n
\"\"<\/a>
Time course of earth temperature (1850-2018) and CO2<\/sub> (1850-2011)<\/figcaption><\/figure>\n
while the correlation is higher than I expected<\/p>\n
\"\"<\/a>
Correlation of earth temperature and CO2<\/figcaption><\/figure>\n
 <\/p>\n
References<\/p>\n