Instead of speculations based on partial drafts and attempts to spin the coverage ahead of time, you can now download the final report of the IPCC WG2: “Climate Change 2014:Impacts, Adaptation, and Vulnerability” directly. The Summary for Policy Makers is here, while the whole report is also downloadable by chapter. Notably there are FAQ for the whole report and for each chapter that give a relatively easy way in to the details. Note too that these are the un-copyedited final versions, and minor edits, corrections and coherent figures will be forthcoming in the final published versions. (For reference, the WG1 report was released in Sept 2013, but only in final published form in Jan 2014). Feel free to link to interesting takes on the report in the comments.
Archives for March 2014
Unforced variations: Mar 2014. Part II
This is mid-month open-thread for all discussions, except those related to Diogenes’ comments. People wanting to discuss with commenter Diogenes should stick to the previous UV thread. All such discussion on this thread will be moved over. Thanks.
The most common fallacy in discussing extreme weather events + Update
Does global warming make extreme weather events worse? Here is the #1 flawed reasoning you will have seen about this question: it is the classic confusion between absence of evidence and evidence for absence of an effect of global warming on extreme weather events. Sounds complicated? It isn’t. I’ll first explain it in simple terms and then give some real-life examples.
The two most fundamental properties of extreme events are that they are rare (by definition) and highly random. These two aspects (together with limitations in the data we have) make it very hard to demonstrate any significant changes. And they make it very easy to find all sorts of statistics that do not show an effect of global warming – even if it exists and is quite large.
Would you have been fooled by this?
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How Many Cans?
XKCD, the brilliant and hilarious on-line comic, attempts to answer the question
The answer is, enough to cover the Earth with 10 layers of soda cans. However, the comic misses a factor of about two, which would arise from the ocean. The oceans have been taking up carbon throughout the industrial era, as have some parts of the land surface biosphere. The ocean contains about half of the carbon we’ve ever released from fossil fuels. We’ve also cut down a lot of trees, which has been more-or-less compensated for by uptake into other parts of the land biosphere. So as a fraction of our total carbon footprint (fuels + trees) the oceans contain about a third.
At any rate, the oceans are acting as a CO2 buffer, meaning that it’s absorbing CO2 as it tries to limit the change to the atmospheric concentration. If we suddenly pulled atmospheric CO2 back down to 280 ppm (by putting it all in cans of soda perhaps), the oceans would work in the opposite direction, to buffer our present-day higher concentration by giving up CO2. The land biosphere is kind of a loose cannon in the carbon cycle, hard to predict what it will do.
Ten layers of soda cans covering the whole earth sounds like a lot. But most of a soda can is soda, rather than CO2. Here’s another statistic: If the CO2 in the atmosphere were to freeze out as dry ice depositing on the ground, the dry ice layer would only be about 7 millimeters thick. I guess cans of soda pop might not be the most efficient or economical means of CO2 sequestration. For a better option, look to saline aquifers, which are porous geological formations containing salty water that no one would want to drink or irrigate with anyway. CO2 at high pressure forms a liquid, then ultimately reacts with igneous rocks to form CaCO3.
Further Reading
Tans, Pieter. An accounting of the observed increase in oceanic and atmospheric CO2 and
an outlook for the Future. Oceanography 22(4) 26-35, 2009
Carbon dioxide capture and storage IPCC Report, 2005
Can we make better graphs of global temperature history?
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?
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The Nenana Ice Classic and climate
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.
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New daily temperature dataset from Berkeley
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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It never rains but it pause
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.
Unforced variations: Mar 2014
This month’s open thread.