29 December 2016

The Smoking Gun of Arctic Warmth Leads To A Stunning Indictment

Posted by Dan Satterfield

High Arctic Temp.s over the past 12 months. The black line is the average from 1981-2010. Red shows above normal temps. Note the incredible warmth all year that goes even to greater extremes in the last two months.

High Arctic Temp.s over the past 12 months. The black line is the average from 1981-2010. Red shows above normal temps. Note the incredible warmth all year that goes even to greater extremes in the last two months.

It normally takes many months to get a paper through peer review and into a journal, but a group of scientists has released their detection and attribution study early, and it’s a stunning indictment. We now know the culprit for the astonishing Arctic warmth of November and December. It seemed very likely that the guilty party was rising greenhouse gasses with Arctic amplification as the accomplice, and that’s JUST what the evidence shows. It’s overwhelming, and the defendants have no choice but to throw themselves upon the mercy of the court.

The analysis shows that even in our present climate that is around a degree warmer than 1900, this heat is unusual, but would happen once every 50-200 years. The odds of it happening in the climate of 1900 are astronomically tiny, however, if we warm another degree, this will be a nearly commonplace event.

The study is here, and for those that do not want to read the whole thing here are the conclusions:

We have investigated the rarity of the November-December 2016 average temperature around the North Pole and assessed how much November-December average temperatures have changed over the past century using observations over a wider region. We also attempted to quantify how much high Arctic temperatures have changed due to anthropogenic emissions in two climate model ensembles.

The observations and the bias-corrected CMIP5 ensemble point to a return period of about 50 to 200 years in the present climate, i.e., the probability of such an extreme is about 0.5 percent to two percent every year, with a large uncertainty. This is rare, but it should be kept in mind that we are focusing on this particular November–December period precisely because an unusual event has occurred. For a random two-month period it would be between six and 12 times more likely. The prescribed SST design of the HadAM3P simulations precludes estimating an absolute return period.

The observations show that November–December temperatures have risen on the North Pole, modulated by decadal North Atlantic variability. For all phases of this variability a warm event like the one of this year would have been extremely unlikely in the climate of a century ago. The probability was so small it is hard to estimate, but less than 0.1 percent per year. The model analyses show that the event would also have been extremely unlikely in a world without anthropogenic emissions of greenhouse gases and aerosols, attributing the cause of the change to human influences. This also holds for the warm extremes caused by the type of circulation of November 2016. If nothing is done to slow climate change, by the time global warming reaches 2 ºC (3.6 ºF) events like this winter would become common at the North Pole, happening every few years.

What this study took great pains to do was to show that this warmth is almost certainly not a natural oscillation in the Arctic climate. Such oscillations exist, but when they are subtracted out, this year stands out like a big red sore thumb. Chris Mooney at the Washington Post has a good summary of this study as well.

Important Note: The study I linked to above uses what is called the ERA-Interim Reanalysis, and it may be unfamiliar, so here’s an explanation:

When we run a numerical model to forecast the weather, we face a real problem in giving it an accurate starting point. In a perfect world, we’d have an observation for every point in the grid, at the surface, and at every pressure level in the model all the way up to the top. This, of course, is not possible so we have to interpolate to all the grid points using the data that we have, and the European ECMWF model uses a very sophisticated “4D-Var” method to do this. I think this is one of the main reasons why the model is superior to others run by Japan, Canada, and NOAA.

It also became apparent that these modern methods of making an analysis of all the data could be used to improve our past analyses and make a data set of the what the atmosphere was doing in the past. These data analyses have been done, and are invaluable in analyzing how the atmosphere is changing as the planet warms. The European Center for Medium Range Forecasting has called their set the ERA-Interim. You can read more about how it works HERE.