This graphic, by Boggis Makes Videos and put on YouTube just a few days ago, breaks all the rules of how to make effective, understandable graphs for the general public. However, if you follow all those rules, it is difficult or impossible to get certain message across. Therefore, this graphic is necessary if a bit difficult. I would like you to watch the graphic several times with a prompt before each watching so that you fully appreciate it. This will only take you six or seven minutes, I’m sure you weren’t doing anything else important.
Pass 1: How to read the graph
This graph’s basic data are temperature anomaly, not temperature, but difference in observed temperature averaged out over a month, using a baseline of 1961-1990. Global warming was already underway for this period, but it still works as a baseline. Anyway notice the scale shown at the beginning of the presentation.
The Graph shows the temperature anomaly across latitude, using a circle meant to represent the earth, so the north pole is on top, the south pole on the bottom, the equator half way between, etc.
The height of the graph’s bars, as well as their color, show the anomaly, but the beginning of the graphic shows you how far out, in standard deviations, the values are.
The Graphic display starts at 1900. The values are shown for each month, but they are 12 month moving average values, otherwise this graphic would give you a seizure.
So watch the first 20 seconds or so as many times as you need to, to fully understand these details.
Pass 2: It is getting warmer and weirder
On the first pass, just note that as the earth gets warmer, at sea and on land (see the two graphics at the bottom). Notice that the variation from year to year as well as the increase in temperature really takes off in the 1980s. Notice that the surface warmth values increase dramtically starting in the 1990s. Notice that things get really wild over just the last ten years or less.
Pass 3: Ends and middles
On your third pass, and this may take a few passes, notice the difference between the equatorial, temperate, and polar regions, as well as the difference between the two poles.
Consider that the increased warming in arctic regions compared to other regions affects many aspects of our weather.
Consider that the increases in temperate and tropical regions means that over some periods of time an increasingly lager area of the earth becomes uninhabitable without air conditioning.
Notice that the northern and southern hemisphere don’t have the same exact pattern.
Scott Adams is the creator of Dilbert, the once funny but now highly repetitive cartoon about a nerd who has a job in an office.
Dr. Gavin Schmidt is high up in the top ten list of world class climate scientists. He is Director of the currently under siege GISS Unit of NASA, where much of the climate science done by that agency is carried out. If you read my blog, you’ve read his work, because you also read RealClimate, where GS writes about climate science in a manner designed to be understandable to the intelligent, honestly interested, thoughtful individual.
Adams has a history of going after core science concepts, often substituting scientific reality with his own. He has done so with climate science.
And, he’s done it again. In a recent blog post (of yesterday) Adams tries to “convince skeptics that climate change is a problem”
This is a re-hash of earlier posts he’s written, in which he does the old denial two step. Of course climate change is real, he says. I’m not a scientist, he says. I don’t know jack about climate science in particular, he says. Then, he uses up piles of ink telling climate scientists how they’ve got all the science wrong.
His objective, I assume, is to spread and nurture doubt about climate science and science in general.
Dr Schmidt caught a tweet of Adams’, pointing to his absurd blog post, and responded with a series of tweets addressing all the things.
I wanted to preserve this excellent, well documented and richly illustrated TweetTextBook, and it occurred to me that you might want to see it too. So, here are the tweets.
Feel free to add additional relevant tweets to the comments, if you like. I hope this doesn’t break the Internet.
But since I'm in the mood for a totally futile exercise, here's why his points are disingenuous at best. Let's start with models… 1/n
The World Meteorological Organization has announced that they expect 2015 to be the warmest year on record, and that we are in the warmest five year period on record. We are speaking here of global surface temperatures, though similar descriptions probably apply to the upper 2000 meters or so of the ocean as well.
The global average surface temperature in 2015 is likely to be the warmest on record and to reach the symbolic and significant milestone of 1° Celsius above the pre-industrial era. This is due to a combination of a strong El Niño and human-induced global warming, according to the World Meteorological Organization (WMO).
The years 2011-2015 have been the warmest five-year period on record, with many extreme weather events – especially heatwaves – influenced by climate change, according to a WMO five-year analysis.
“The state of the global climate in 2015 will make history as for a number of reasons,” said WMO Secretary-General Michel Jarraud. “Levels of greenhouse gases in the atmosphere reached new highs and in the Northern hemisphere spring 2015 the three-month global average concentration of CO2 crossed the 400 parts per million barrier for the first time. 2015 is likely to be the hottest year on record, with ocean surface temperatures at the highest level since measurements began. It is probable that the 1°C Celsius threshold will be crossed,” said Mr Jarraud. “This is all bad news for the planet.”
Greenhouse gas emissions, which are causing climate change, can be controlled. We have the knowledge and the tools to act. We have a choice. Future generations will not.”
They have some nice graphics:
Caption for the graphic at the top of the post:
Global annual average near-surface temperature anomalies from HadCRUT18.104.22.168 (Black line and grey area indicating the 95% uncertainty range), GISTEMP (blue) and NOAAGlobalTemp (orange). The average for 2015 is a provisional figure based on the months January to October 2015. Source: Met Office Hadley Centre.
NOAA has just published September’s global surface temperature, which turns out to be 0.90C above their baseline (20th century average). According to NOAA, this is the highest value for September on record, 0.19C higher than last year, which was also a record. The graph above shows the year to date average, though September, for NOAA’s entire data set.
Ed Hawkins, a climate scientist at the University of Reading, recently tweeted a graph he produced to show global surface temperatures since 1850, noting that 2015 year to date broke his graph.
Using NASA GISS data, climate scientist John Abraham broke his graph too:
Using the NOAA data, I made the following chart, showing annual surface temperature measurements for their entire record through 2014. Then, I added an estimate for 2015, based on year to date numbers.
Every year the sea ice that covers the northern part of the Earth expands and contracts though the winter and the summer. The minimum extent of the sea ice is usually reached some time in September, after which it starts to reform.
Human caused greenhouse gas pollution has increased the surface temperatures of the earth, as measured on the land at about heat height with thermometers, and on the sea at the surface, mainly with satellites. Warming of the surface has continued apace for several decades, though with some expected squiggling up and down in how fast that is happening.
Greenhouse gas, mainly CO2, causes warming because of its heat trapping properties, and this warming (and the CO2 itself) set in motion a number of feedback systems that either push against warming or increase warming. Most of these feedback systems, unfortunately, are what we call “positive” feedbacks, though they are not “positive” in a good way. They are effects that increase the amount of warming beyond what would happen from just the CO2. One of the biggest global effects is an increase in the amount of water vapor carried by the atmosphere. Since water vapor is also a greenhouse gas, more CO2 -> more greenhouse effect -> more water vapor -> more greenhouse effect.
One of the bad effects of greenhouse warming is the melting of more ice in the Arctic during the summer. On average, less and less ice is left by the end of the melt season in September. Again, this amount squiggles up and down a bit, but it is a persistent downward trend. Since ice reflects sunlight away from the earth, a decrease in ice cover in the Arctic means more warming. This has both regional effects (such as an increase in melting of land-based Greenland glaciers) and a global effect. The regional effect is very important, because this has resulted in a phenomenon known as Arctic Amplification. This refers to the fact that of all the different regions of the earth, the Arctic is warming more than most other regions. The large scale systems of air movement that make up much of our climate, and thus control much of our weather, are shaped and driven in large part by the redistribution of heat form tropical areas (where the sun has a stronger warming effect) outward towards the poles. This redistribution shapes trade wind patterns and determines the location and strength of the jet streams. The relatively warmer Arctic has changed the basic shape and pattern of these major climatic features in ways that have caused significant changes in weather. The drought in California is caused in part by the persistence of a large jet stream meander caused, almost certainly, by Arctic Amplification and other changes in heat distribution in the northern latitudes. Another change is the increase in large scale precipitation events. Here in the twin cities, for example, the frequency of 3″ plus rainstorm over the year has changed from about one every two years to one every year, on average. Rainfall events of between 1 and 2 inches, and between 2 and 3 inches, have also increased.
There are two major properties of Arctic ice that should be considered. One, just discussed, is extent. Extent matters because of its direct effect on albedo, the reflection of sunlight back into space. Less ice extent, caused by warming, means even more warming. The other property is ice volume. Ice volume builds up over time. Thick ice includes ice from previous years that didn’t melt. The system is complex and dynamic, but a healthy Arctic ice ecosystem has a good amount of thick high-volume ice that persists through the melt season and forms the anchor against which annually re-freezing surface ice forms. The less ice volume, the less stable the Arctic Sea ice is, and the more difficult it becomes to reform. Exactly how this effect works depends on exactly which part of the Arctic one is in.
Over the last several decades, the volume of Arctic Sea ice has reduced by something like 80%. This is not good.
Andy Lee Robinson has made an amazing and highly instructive graphic showing the decline in Arctic Sea ice volume over the years. Here is the most updated version showing data up through this year, based on these data:
This is an animated visualization of the startling decline of Arctic Sea Ice, showing the minimum volume reached every September since 1979, set on a map of New York with a 10km grid to give an idea of scale. It is clear that the trend of Arctic sea ice decline indicates that it’ll be ice-free for an increasingly large part of the year, with consequences for the climate.
The rate of ice loss in the Arctic is staggering. Since 1979, the volume of Summer Arctic sea ice has declined by more than 80% and accelerating faster than scientists believed it would, or even could melt.
Based on the rate of change of volume over the last 30 years, I expect the first ice-free summer day in the Arctic Ocean (defined as having less than 1 million km² of sea ice) to happen between 2016 and 2022, and thereafter occur more regularly with the trend of ice-free duration extending into August and October.
By the way, those interested in computer technology will note that Andy’s graphic is produced on the most powerful and stable operating system, Linux, using OpenSource tools.
I produced the animation using hand-written perl and php code to create povray scripts, and scheduling task distribution using MySQL between 7 linux servers working in parallel to render 810 frames at 1920 x 1080 resolution. The “farm” renders 22 frames simultaneously taking between 1-2 hours per frame. On completion, ffmpeg combines the individual frames and music into a high quality mp4 video.
So, that’s cool.
Anyway, Andy has also created the now famous Sea Ice Death Spiral graphic, showing Arctic Sea ice volume since 1979, in a particularly helpful graphic style. Notice that the sea ice volume is fairly stable for several years, then starts to decline rapidly and continues to do so thereafter.
Sea ice extent has followed a similar pattern. Let’s have a look at this year in relation to the last several decades. First, this graphic made using the interactive graphing tool at the National Snow and Ice Data Center shows this year’s ice in relation to the average and standard deviation since 1979. Here we see that the ice extent has been following the lowest end of the two standard deviation spread. The lowest extent shown here is the fourth lowest since records began:
To add even more perspective, the next to graphics show the first ten years in the NSIDC data set, followed by the last ten years. In both cases, the thick black line is the average for the entire data set. This comparison clearly indicates that things have changed in the Arctic:
One of the things that people who wish to deny climate science usually start whinging about at this point in the discussion is that the Antarctic has had an increase in sea ice, and that somehow this all evens out. Let me briefly explain why this is incorrect.
There has been an increase in the extent of sea ice in the Antarctic, but there are at least two (maybe three) reasons for this. First, there has been a major increase in winds in the southern hemisphere caused by climate change. This includes winds coming off the Antarctic continent. These winds break up the sea ice and blow it around, opening areas between blocks of floating ice, which then freeze quickly. This causes an increase in extent of the ice. The other is the increase in fresh water entering the sea around Antarctic because the glaciers are melting. This fresh water allows the sea to freeze at a higher temperature, causing more ice. There may be other reasons having to do with currents of both air and water, and rainfall, also caused by climate change. So, climate change causes these changes in sea ice at both poles.
The increase in maximum sea ice in the Antarctic does not increase albedo because it happens in the dark. So the decreased global albedo in the Arctic is not offset by changes in the Antarctic. All of the regional ecological changes affecting sea life and so on can not be offset between the Arctic and Antarctic, because they are on opposite ends of the planet. Also, note, that this year we did not see an increase in Antarctic sea ice. Overall it is expected that global warming will turn around the Antarctic sea ice amount, and also, we are expecting Antarctic glaciers to begin melting at a higher rate over the next decade or so. It will be interesting to see what eventually happens. In any event, keep in mind that the Arctic and Antarctic are very different geographical regions. The Arctic is a sea surrounded by continents. The Antarctic is a continent surrounded by sea. We could not possibly expect the same things to happen in these two areas. The comparison often made by climate science contrarians is absurd.
That is a good question, and difficult to answer. If it turns out to be, it will be the warmest calendar year in the instrumental record, which goes back into the 19th century.
Regardless of what El Nino (ENSO) does, 2015 will be a warm year. Why? Because everything is warm and getting warmer and even if 2015 is less warm than 2014, it will be warm. There is no other possibility.
Even without the effects of El Nino, though, it is possible that 2015 will be warmer than 2014 because we see a lot of heat out there. If the present, relatively weak El Nino continues for a while, it will likely increase the chance that 2015 will be warmer than 2014. But current predictions suggest that 2014 will not only continue to have a strengthening El Nino, but El Nino conditions may either continue or repeat over 2015 and beyond. If that happens, not only is 2015 likely to be the warmest year in the instrumental record (since 1880) but 2016 may be in the running to be even warmer.
So far each month of 2015 has been very warm (see graph above) overall (the “zero” on the Y-axis of that graph represents the 20th century mean surface temperature). This month, April, is not excessively warm. Likely when April is plotted for 2015 on this graph, it will be either cooler then or around the same as last April.
Obviously we won’t know until the year is over, and given that climate change is a medium term phenomenon best measured in decades, we shouldn’t be in such a hurry to know these numbers. But, given that climate change is the existential issue of our day and the data become available month by month, we are not going to ignore the march of surface temperatures. We are going to, rather justifiably, be interested in what happens, month by month, as it happens.
At the end of the month, climate scientists such as my friend John Abraham, who is tracking global temperatures daily, will be able to produce a very good estimate of what the major data bases (such as NASA GISS, used here) will say, but those data bases won’t be officially updated until around the middle of the following month or so. So stay tuned.
Added: For those keeping track, I made a new version of the above graph. The red line represent the monthly anomaly values required (on average) for the rest of the year for 2015 to equal 2014. I also extended the Y-axis to 100 because the warmest month in the GISS database is in the 90s, just in case such a very warm month occurs. It is likely that April 2015 will not e as warm as April 2014 but it will likely be above the red line.
The New York Times put the news of 2014 being the warmest year on their front page, in the precious space known as “Above The Fold.” But, the venerable paper of record continues to give credence to science denialists by calling them “skeptics,” and continues to imply that there really is a debate between consensus based science and politically motivated denial of science. To underscore this point I created the above graphic.
This is serious. A highly regarded and widely recognized planetery physicist put together the most dangerous scientific ingredients that exist: skepticism of the established science, a comprehensive list of hypotheses that stood in opposition to that established science, a huge amount of data, a healthy amount of funding including a good chunk from energy companies that mainly sell fossil carbon based fuels, and a hand selected research team of others who were also skeptics.
In the end, he came up with an explanation for what people call Global Warming. Personally, I believe him. I think he has it right. Whatever you were thinking as the cause of global warming, you have to look at this work and if you have not come to the same conclusion, you should reconsider.
Here’s an interview which includes an explanation of the whole process.
With what may be the warmest year in centuries about to close, I thought it would be fun to have a graphic comparing the march of global average temperature over several years about a century ago with the present state of affairs. This graphic is based on NASA’s data, using John Abraham’s estimate for the 2014 temperature (it might end up being a tiny bit different). There is more information about those sources here.
[click on the graphic to get to a larger version]
Just to be clear on how to read the graph … the red dot is not anywhere in particular on the horizontal scale. The X and Y axis simply plot global average temperatures estimated for 1895 to 1933, a series of years that has 1914, a century ago, in the middle of it. This early sequence of data is meant to represent “pre-industrial” temperatures, and here that is compared using the single red to today, positioned correctly on the vertical scale (of temperature). Note, however, that 1895 to 1933 is not really pre-industrial. Human produced greenhouse gases were already being added to the atmosphere by then, though not to the same degree as more recent decades.
You will hear people say that even if 2014 is the warmest year on record, that it is not statistically significantly warmer than the next warmest year. That is absurd. One would have to have a very poor understanding of how statistics works to make such a statement non-ironically. But to make the point even more clear than I might if I explained why that is a dumb thing to say, statistically, I produced this graph which shows that today it is much warmer than it was not so long ago.
ADDED: A question has been raised as to whether or not I chose the proper scale on the Y-axis. I did. My intention was to show variation and average temperatures for several decades near the beginning of the industrial period, centering on 100 years ago, and to put the current year in context of that. This graph does that nicely, with no strangeness about axes other than the carefully explained fact that the clearly labeled 2014 datum is not scaled to the time scale on the bottom. The nature and variation of the entire instrumental curve is readily available and there are dozens of graphs here on this blog and elsewhere that show this (I placed one at the top of the post for your convenience). The point of this graph was to remove the ascending values and obviate the rather absurd question of statistical difference between the highest and second highest ranked years. As explained.
But the Y-axis problem emerges as a more general climate science denial meme (other than, and beyond, the relatively valid and honest question of how to best scale the Y-axis on a graph like this). And in relation to that, I’ve made a NEW ENTRY IN MY FAQ. Please have a look. There are some fun graphs.
To demonstrate two ways in which people get this wrong. First, an actual scientist type person simply believing (incorrectly) that all scales must start at zero (maybe they do in his field), and second, a climate science denialist actually arguing that the joke graph shown in the tweet is the best way to show global temperature change.
You might have to click on the pic to be able to read it:
The Road to Paris is a web site created by the ICSU, “…a non-governmental organization representing a global membership that includes both national scientific bodies (121 National Members representing 141 countries) and International Scientific Unions (30 Members),” founded in 1931. If the ICSU had not existed when the UN was formed, the UN would have formed it. Think of the ICSU as the UN of Science. More or less.
Anyway, Road to Paris refers to the 2015 international meetings on climate change, and the purpose of the web site is to provide excellent information about climate change, up to date, so those engaged in that process, either as direct participants or as onlookers, will be well informed.
“Fishing in pink waters: How scientists unraveled the El Niño mystery” is an amazing piece of work written by Daniel Gross (I made minuscule contributions), looking at the history of the science of the El Nino Southern Oscillation, which is one of the most important climate or weather related things on this planet. This is timely, because we are expecting an El Niño to form over the winter. Maybe. Well, eventually we will have an El Niño. (It has been an unusually long time since the last strong one.)
Not really a fully fledged blog post, just a quick link pointing you to something interesting.
More than 100%? Sounds funny, doesn’t it? Let me rephrase. Humans have caused so much climate change that some of the climate change changed some of the climate back.
Still sounds kinda funny.
OK, try again: Humans have caused a whole bunch of global warming. Nature has caused a small amount of global cooling, which has offset a little of the human caused global warming. But also, humans have caused a little bit of global cooling as well.
Did you ever read a textbook on economic history, or an in-depth article on the relative value of goods over the centuries expressed in current US dollars? Have you ever encountered a graphic that shows long term trends in rainfall patterns or other climate variables, using a couple of simple lines, designed to give a general idea of relative conditions during different eras? Here are a few examples of what I’m talking about.
This is a graphic made by a major investment firm culling information from dozens or perhaps hundreds of sources into a single graphic. This is the graphic as it was initially provided by the researchers
This is a graph of oxygen concentration in the Earth’s atmosphere. It is culled from a large number of different sources. This is the graphic, based on numerous proxyindicattors, as published in a peer reviewed paper:
This is a compilation from many different sources of stock market values assembled to show waves in stock market behavior over the last few centuries:
This is a set of climate related variables show in relation to human “civilization” over 18,000 years (n.b.: the term “civilization” is reserved in archaeology and prehistory for specific phenomena which did not occur before about 10,000 years ago).
In all these cases complex sources were culled in the peer reviewed literature 0r professional research literature, and turned into summary views of something happening over time. The graph itself is meant to show a derived variable, not the underlying complexity of the data. The graph is the sausage. The making of the sausage is laid out in the original documents, in some case in the peer reviewed paper the graphic appears in.
Here, Judith Curry makes the argument, in an excessively tl;dr blog post, that climate scientist Michael Mann acted inappropriately, perhaps fraudulently, or perhaps as a matter of scientific misconduct, when the IPCC published a version of his famous Hockey Stick Graph that instead of looking like this:
Looked like this:
For the record, here is the original version of that graphic from the peer reviewed paper. Note that it indicates where the data come from but that was back in the late 20th century when in order to have color graphics in your paper you had to hire monks to draw them and there weren’t any monks available.
And here is the same graph in a similar updated paper a year later, looking much better:
Mann’s graphic representation of climate change, the Hockey Stick, is not fraudulent. But it is verified, real, and important. There are people in the climate discussion who make up graphs, of course (see this) but Mann is not one of them.
So Judith Curry and the flock of winged monkeys and child molesters that comment on her blog are arguing that Mann carried out scientific misconduct when he did something that is normal to do, and in fact, that he didn’t actually do. This is an “own goal” for Curry because it is a clear cut case of making up a version of reality in order to denigrate a fellow scientist and discredit his research on the basis of color coding rather than the science. Curry has credentialed herself a denialist.
If you ever see an image like this used by a climate science denialist, ACCUSE THEM OF FRAUD AND MISCONDUCT because this graph shows NOTHING about the multiple sources used to create the single black line squiggle therefore it is ILLEGAL.
Sorry… I get carried away sometimes. Anyway, I have a pro tip for those who are following along with the climate change discussion: Individuals who study climate change from any perspective (as a climate change scientist, some other kind of scientist, policy maker, communicator, interested citizen) should realize that some depictions or summaries are underlain by extensive and complex literature. A proper scholarly approach, even by an avocational scholar or journalist, requires keeping that in mind and digging beneath the surface where needed. So if you see a monochromatic hockey stick like curve, or any climate squiggle, hopefully there is a reference to where it comes from and then you can dig around and reconstruct the scholarship, if you are reasonably smart, reasonably diligent, not lazy, and well intentioned.
Or you can be one of Judith Curry’s followers and just whine about it.
Finally, here’s a recent version of the Hockey Stick Graph showing the many ways it has been verified. Checkmate, denialists.
A new paper advances our understanding of the link between anthropogenic global warming and the apparent uptick in severe weather events we’ve been experiencing. Let’s have a look at the phenomenon and the new research.
Climate Change: The Good, The Bad, and the Ugly.
It is mostly bad. Sometimes it is ugly. I was looking at crop reports from the USDA and noticed an interesting phenomenon in Minnesota, that is repeated across much of the US this year: Fewer acres are in crops but among those acres that are planted there is a high expected per-acre yield. The higher yield will make up for the lost acreage this year. Unfortunately, that is about as good as it gets.
The lost acreage, at least in Minnesota as I understand it, comes from a late spring followed by a wet early summer. And holy crap was it wet, and fairly cool. My own tomatoes were utterly confused. One plant produced a single tomato that ripened a month and a half early, then waited for weeks to make its next move. I think organisms do that sometimes; when they think they are about to die they reproduce desperately, which for a tomato plant, is producing one premature tomato and then trying to not be noticed for a while. In any event, many Minnesota farmers live with an interesting conflict. There are parts of their farms they can’t plant in a given year because it stays too wet too long, and that varies from year to year. The rest of the farm is irrigated much of the summer. This year, it seems that there has been enough extra rain to increase productivity of the irrigation season, but acreage was lost between the encore of a sort of Polar Vortex mimic and a lot of rain.
The extra productivity was a lucky break, and is limited in its effects. The same weather phenomenon that made June nearly the wettest month ever in the upper plains has contributed significantly to a longer term drought in California, which is on the verge of ruining agriculture there. Severe flooding or extreme dry can do much more damage to agriculture than is accounted for by minor increases in productivity because of the extra water vapor provided by Anthropogenic Global Warming.
And the floods can be downright dangerous. I was talking to my friend and former student Rusty several months ago about the flooding in Colorado. I asked her about how her husband was doing (they both happen to be climate scientists by the way).
“Oh he’s probably fine but I’ve not heard from him in three days. His cell phone battery is probably out. I imagine he’s clinging to some high ground up on the Front Range about now.”
He is a volunteer first responder and had headed up into the canyons year boulder during the big floods there. Which were like the big floods in Calgary. And Central Europe. And the UK. And that rainy June here. And the flooding that just happened in several parts of the US.
All of it, all of those floods, and some significant drought, and the Polar Vortex that hit the middle of North America last winter, all caused, almost certainly, by the same phenomenon.
Wildfires are probably enhanced by recent weather phenomenon as well, with extreme rains causing the build up of fuel, followed by extreme dry providing the conditions for larger and more frequent fires.
On the more extreme end of effects for severe weather is the Arab Spring phenomenon. It is one thing to have a bad year for corn because of a wet spring. It is worse to have a multi year drought that could seriously affect our ability to buy almonds, avocados and romaine from California. But what happens when an agricultural system fails for several years in a row, the farmer abandon the land and move to the cities where they become indigent, a civil war breaks out, and next think you know a Caliphate is formed, in part on the wreckage of one or two failed regimes, failed in large part because of severe weather conditions caused by human induced climate change?
AGWAAQRaRWaWW. Rhymes with “It’s stuck in my craw, paw!”
Let me parse that out for you.
AGW -> AA -> QR-RW -> WW
AGW – Anthropogenic Global Warming
Anthropogenic global warming (AGW) is caused mainly by added CO2 in the atmosphere from burning fossil fuel. By definition, the burning of fossil fuels is the release of energy by separation of carbon previously attached to other atoms by biological processes typically a long time ago, and over a long period of time. We humans are spending a century or two releasing tens and tens of millions of slow storage of Carbon, all at once in geological time, causing the chemistry of our atmosphere to resemble something we’ve not seen in tens of millions of years.
AA – Arctic Amplification
The CO2 by itself would warm the Earth to a certain degree, but it also produces what are called positive feedbacks. Which are not positive in a good way. For example, added CO2 means there is more water vapor in the atmosphere (because of more evaporation and ability for the atmosphere to hold water). Water vapor is, like CO2, a greenhouse gas. So we get even more warming. In the Arctic, there are a number of additional positive feedbacks that have to do with ice. The Arctic, with its additional positive feedbacks, warms more than other parts of the planet. This is called Arctic Amplification.
QR-RW – Quasi-resonant Rossby waves
Normally, heat from the equator makes its way towards the poles via air and sea. Giant currents of air are set up by a combination of extra equatorial heat and the rotation of the earth. Part of this system is the so-called “trade winds” (winds that typically blow in a typical direction) and the jet streams.
The jet streams occur at high altitude between major bands of trade winds that encircle the earth. The trade-wind/jet stream systems are typically straight rings that encircle the earth (a bit like the bands on the major gas planets) and the jet streams move, normally, pretty straight and pretty fast. But, with the warming of the Arctic, the differential between the equator and the poles is reduced, so all sorts of strange things happen, and one of those things is the formation of quasi-resonant Rossby waves.
A Rossby wave is simply a big giant meander in the jet stream. Quasi-resonant means “almost resonant” and resonant means that instead of the meanders meandering around, they sit in one place (almost).
It appears that Quasi-resonant Rossby waves set up when there is a certain number (roughly a half dozen) of these big meanders. When this happens, the jet stream slows down. The big bends in the jet streams block or stall weather patterns, and the slow moving nature of the jet stream contributes to the formation of either flash droughts (as Paul Douglas calls them) where several weeks of nearly zero rain menace a region, or extensive and intensive rainfall, like all the events mentioned above.
The recent decade has seen an exceptional number of boreal summer weather extremes, some causing massive damage to society. There is a strong scientific debate about the underlying causes of these events. We show that high-amplitude quasi- stationary Rossby waves, associated with resonance circulation regimes, lead to persistent surface weather conditions and therefore to midlatitude synchronization of extreme heat and rainfall events. Since the onset of rapid Arctic amplification around 2000, a cluster of resonance circulation regimes is ob- served involving wave numbers 7 and 8. This has resulted in a statistically significant increase in the frequency of high- amplitude quasi-stationary waves with these wave numbers. Our findings provide important new insights regarding the link between Arctic changes and midlatitude extremes.
The effects of climate change have occurred (and will occur) on a number of time scales. Over a century we’ve had a foot of sea level rise, which is showing its effects now. Storminess, in the form of changes in tornado regimes and tropical storms, has probably been with us for a few decades. But Agwaaqrarwaww has probably only been with us since about the beginning of the present century.
Followed by this graphic, which I made, with the intention of more clearly showing the trend in QR events:
I sent that to one of the authors, which may have inspired the production of a different graphic but showing the same trend, for the current paper:
Look how recent this phenomenon is. It is now, current, happening at sub-climate time scales. We don’t know enough about it, and we need to address it.
I asked Stefan Rahmstorf, one of the paper’s author and the scientists I was exchanging graphics with, to elaborate on the signficance of this recent study and to explain why it is important. He told me, “Previous studies have failed to find trends linked to global warming which could explain the recent spate of unusual extreme events. For example they have looked at trends in the occurrence of blocking or in the speed of the jet stream. But you need to know what you are looking for in order to find it. The planetary wave equation reveals what the resonance conditions are which make the waves grow really big, causing extreme weather. So we knew what trends to look for.”
I also asked him if severe weather events post dating the end of his study period conform to expectations as Rossby Wave events. “I can’t say for sure because we have not done the analysis for the very latest data yet – studies like this take time,” he told me. “But I suspect there have been more resonance events. They are not necessarily constrained to July and August either. The record flooding in May/June 2013 in Germany of the Danube and Elbe rivers, for example, was associated with large planetary wave amplitudes. Dim Coumou has assembled a young research team now that will work on further data analysis.”
Prof Ted Shepherd, a climate scientist at the University of Reading, UK, but not involved in the work, said the link between blocking patterns and extreme weather was very well established. He added that the increasing frequency shown in the new work indicated climate change could bring rapid and dramatic changes to weather, on top of a gradual heating of the planet. “Circulation changes can have much more non-linear effects. They may do nothing for a while, then there might be some kind of regime change.”
Shepherd said linking the rise in blocking events to Arctic warming remained “a bit speculative” at this stage, in particular because the difference between temperatures at the poles and equator is most pronounced in winter, not summer. But he noted that the succession of storms that caused England’s wettest winter in 250 years was a “very good example” of blocking patterns causing extreme weather during the coldest season. “The jet stream was stuck in one position for a long period, so a whole series of storms passed over England,” he said.
I’m not convinced that the seasonality of Arctic Amplification matter much here, and I note that we’ve not looked closely at the Antarctic. Also, “blocking patterns” and QR waves are not really the same exact thing. They may be different features of the same overall phenomenon, but QR Rossby Waves are a more general phenomenon, and a “blocking” is something that happens, probably, when that phenomenon interacts with certain kinds of storms.
It occurs to me that there is a huge difference between Agwaaqrarwaww happening randomly in space vs. blocking and steering waves setting up for long periods of time over the same place, and appearing in those places typically. Like Godzilla. We know that over time Godzilla will usually destroy Tokyo and not London, because Godzialla, while sometimes random, is usually geographically consistant. Can we expect Rossby Waves to usually causae drought in California, flooding on the Front Range or Rockies, and drenching rains in the Upper Midwest and Great Lakes Region, for example? I asked Stefan about that as well.
“We have not looked at this aspect yet, but the recent paper by Screen and Simmonds has indeed found such a preference of the wave troughs and crests to sit in certain locations.