I’m writing this post to see if our audience can help out with a challenge: Can we collectively produce some coherent, properly referenced, open-source, scalable graphics of global temperature history that will be accessible and clear enough that we can effectively out-compete the myriad inaccurate and misleading pictures that continually do the rounds on social media?
I am always interested in non-traditional data sets that can shed some light on climate changes. Ones that I’ve discussed previously are the frequency of closing of the Thames Barrier and the number of vineyards in England. With the exceptional warmth in Alaska last month (which of course was coupled with colder temperatures elsewhere), I was reminded of another one, the Nenana Ice Classic.
Guest commentary from Zeke Hausfather and Robert Rohde
Daily temperature data is an important tool to help measure changes in extremes like heat waves and cold spells. To date, only raw quality controlled (but not homogenized) daily temperature data has been available through GHCN-Daily and similar sources. Using this data is problematic when looking at long-term trends, as localized biases like station moves, time of observation changes, and instrument changes can introduce significant biases.
For example, if you were studying the history of extreme heat in Chicago, you would find a slew of days in the late 1930s and early 1940s where the station currently at the Chicago O’Hare airport reported daily max temperatures above 45 degrees C (113 F). It turns out that, prior to the airport’s construction, the station now associated with the airport was on the top of a black roofed building closer to the city. This is a common occurrence for stations in the U.S., where many stations were moved from city cores to newly constructed airports or wastewater treatment plants in the 1940s. Using the raw data without correcting for these sorts of bias would not be particularly helpful in understanding changes in extremes.
There has been a veritable deluge of new papers this month related to recent trends in surface temperature. There are analyses of the CMIP5 ensemble, new model runs, analyses of complementary observational data, attempts at reconciliation all the way to commentaries on how the topic has been covered in the media and on twitter. We will attempt to bring the highlights together here. As background, it is worth reading our previous discussions, along with pieces by Simon Donner and Tamino to help put in context what is being discussed here.