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.
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.
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.
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