Somewhat randomly, my thoughts turned to the Nenana Ice Classic this evening, only to find that the ice break up had only just occurred (3:48 pm Alaskan Standard Time, April 25). This is quite early (the 7th earliest date, regardless of details associated with the vernal equinox or leap year issues), though perhaps unsurprising after the warm Alaskan winter this year (8th warmest on record). This is in strong contrast to the very late break up last year.
Break up dates accounting for leap years and variations in the vernal equinox.
As mentioned in my recent post, the Nenana break up date is a good indicator of Alaskan regional temperatures and despite last year’s late anomaly, the trends are very much towards a earlier spring. This is also true for trends in temperatures and ice break up mostly everywhere else too, despite individual years (like 2013/2014) being anomalously cold (for instance in the Great Lakes region). As we’ve often stressed, it is the trends that are important for judging climate change, not the individual years. Nonetheless, odds on dates as early as this years have more than doubled over the last century.
Guest commentary from Drew Shindell
There has been a lot of discussion of my recent paper in Nature Climate Change (Shindell, 2014). That study addressed a puzzle, namely that recent studies using the observed changes in Earth’s surface temperature suggested climate sensitivity is likely towards the lower end of the estimated range. However, studies evaluating model performance on key observed processes and paleoclimate evidence suggest that the higher end of sensitivity is more likely, partially conflicting with the studies based on the recent transient observed warming. The new study shows that climate sensitivity to historical changes in the abundance of aerosol particles in the atmosphere is larger than the sensitivity to CO2, primarily because the aerosols are largely located near industrialized areas in the Northern Hemisphere middle and high latitudes where they trigger more rapid land responses and strong snow & ice feedbacks. Therefore studies based on observed warming have underestimated climate sensitivity as they did not account for the greater response to aerosol forcing, and multiple lines of evidence are now consistent in showing that climate sensitivity is in fact very unlikely to be at the low end of the range in recent estimates.
D.T. Shindell, "Inhomogeneous forcing and transient climate sensitivity", Nature Climate change, vol. 4, pp. 274-277, 2014. http://dx.doi.org/10.1038/nclimate2136
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.
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