There wasn’t a “pause” in global warming. The rate at which the plant’s surface warms because of human greenhouse gas pollution varies over time. Sometimes the warming is quicker, sometimes it is slower.
There are multiple reasons for a temporary slowdown in the temerature curve, including the temperature curve being a little inaccurate, the ocean taking heat away from the surface, atmospheric dust varying over time in how much sunlight is reflected away, and so on. I recently wrote up a detailed discussion of the latest thinking on this interesting scientific problem, based mostly on a current published commentary by Fyfe et al in Nature Climate Change. See: What is the “pause” in global warming?
Republican Representative from Texas’s 21st district, Lamar Smith has been on a crusade against science, and has been employing distinctively McCarthyistic tactics in order to intimidate researchers and damage the progress of, well, civilization, frankly.
Most recently he wrote an opinion piece that misrepresented the Fyfe et al paper. In response, one of the authors of this paper, Michael Mann, wrote this Open Letter to Smith on his Facebook page:
Our study does NOT support the notion of a “pause” in global warming, only a *temporary slowdown*, which was due to natural factors, and has now ended.
Our recent work, which you fail to cite, indicates that the record warmth we are now experiencing can only be explained by human-caused global warming.
Michael E. Mann
Distinguished Professor of Atmospheric Science
The Pennsylvania State University
You’ve heard much about the so-called “pause” or “hiatus” in global warming.
One of the implications of a multi-year “pause” in global warming is that the science of global warming must be somehow wrong, because with CO2 rising in atmosphere, due to human activity, how can the surface not warm? However, surface temperatures have been rising, but at a somewhat slower rate than at some other times.
The truth is that there is a lot of variation in that upward trending surface temperature value, measured as an anomaly above expected temperatures. Sometimes the variation pushes the rate of warming up, sometimes it pushes the rate of warming down. This has always happened, and will always happen.
So there was something of a lowering of rate of surface warming, but at the same time, no such reduction in rate of ocean warming. Most of the heat from global warming is added to the ocean, not the surface. So, the reality is, global warming has been continuing apace.
One of the factors involved in a slowdown is probably the fact that the Pacific Ocean has been absorbing more heat, for a longer period, relatively uninterrupted by large El Ninos (which reverse that trend), for longer than usual. This year’s El Nino is returning some of that heat to the atmosphere. But even before El Nino kicked in, we were having month after month of record breaking heat (with the very rare month not being a record breaker) for a long time.
Anyway, a couple of papers have recently been published that look once more at the “pause” and I wanted to point them out. The best way to get at these papers is to read the guest commentary by tephan Lewandowsky, James Risbey, and Naomi Oreskes on RealClimate.org: Hiatus or Bye-atus?
The idea that global warming has “stopped” has long been a contrarian talking point. This framing has found entry into the scientific literature and there are now numerous articles that address a presumed recent “pause” or “hiatus” in global warming. Moreover, the “hiatus” also featured as an accepted fact in the latest IPCC report (AR5). Notwithstanding its widespread use in public and apparent acceptance in the scientific community, there are reasons to be skeptical of the existence of a “hiatus” or “pause” in global warming …. We have examined this issue in a series of three recent papers, which have converged on the conclusion that there is not now, and there never has been, a hiatus or pause in global warming.
There is some confusion about the way we talk about global warming. Most of this confusion arises during the communication of science to the public or to policy makers. Part of this confusion rests within the science itself; There is no meaningful confusion about the nature of global warming or how it is observed, but there are some terminological glitches of the kind that arise in science all the time, and that rarely matter to the science itself.
The most commonly used indicator of global warming is a graph that is meant to show the effects of global warming over time. This may be by decade, yearly, or monthly, or using a moving average using a period such as 12-months or some other time period. This is an example:
NASA GISS TEMP ANOMALY 1880-PRESENT
The vertical axis is temperature anomaly, the standard way scientists measure changes in heat over time. Each data point is calculated from thousands of roughly head-height thermometers across the Earth’s land surface, combined with a measure of global sea surface temperatures. As we go back in time there are fewer data sources, and the sea surface temperature is measured differently. During any given year, there are parts of the globe that are underrepresented. The way these deficiencies in the data are addressed varies across the major data sets (from the US, Great Britain, or elsewhere) though all the different data sets use most of the same original raw data. This graph is based on the data provided by NASA’s Goddard Institute for Space Studies (GISS). All of the different data sets show the same thing, a general increase in global surface temperatures, and the variation over time, the up and down squiggles, is similar for all the data sets. They differ only in details.
It is an important fact that as the line indicating global surface temperature going up across the indicated time span, the amount it goes up varies. There are short periods of time when the temperature value goes up rather quickly then drops a bit, and there are periods of time during which the value goes up and down without much increase over several years running.
When we see a brief period (a few years, or a decade, etc.) where the trend varies from the long term trend, we need to ask why this is happening. Most of the dramatic upward spikes turn out to be El Niño years, when the ocean is adding a lot of stored heat into the atmosphere. Most of the periods where the rise in temperature value is somewhat lackadaisical are periods both lacking an El Niño event and having a number of La Niña events, during which the Pacific Ocean is soaking up more heat than average (that heat comes back out during El Niño periods).
There are also periods when the rise in global temperature is attenuated by additional aerosols in the atmosphere. This may be caused by a high rate of volcanic activity or the explosion of a particularly large volcano. Also, at one point, we see general increase in the upward trend that is probably a combination of a) cleaning up some of the human caused aerosols with the Clean Air Act and similar regulatory changes, and b) an increase in the human output of greenhouse gas pollution.
A significant cause in the variation of this signal over time, related to El Niño and La Niña events, is probably the result of one or more long term oscillations in the relationship between the ocean and the atmosphere. I’ve written about recent research addressing this phenomenon here. These multi-decadal oscillations probably explain most of the waviness in the line.
We have recently moved past a period of a relative slowdown in the increase in global surface temperature and are now experiencing a rapid rise in average global temperature. The way this slowdown is discussed is part of the confusion about global warming. To the average person, the term “slowdown” might sound like “decrease,” but it is not a decrease in surface temperatures, but a reduction in the rate at which surface temperatures are going up for a few years.
Nonetheless, the recent slowdown has been exploited by those who argue that global warming is not real, or is not, somehow, caused the way scientists say it is. It has been termed a “hiatus” or a “pause.” This terminology is problematic. A hiatus is a gap. When we “pause” something (like using a pause button) we stop it. The stop button on your music device stops the music. The pause button also stops it. The difference between stop and pause is what happens after you restart it, or a difference in the internal working mechanism. In the old days, for example, if you stop an audio or video tape, the magnetic head that reads the data is lifted off the tape, but if you hit “pause” the magnetic head stays on the tape so restarting is smoother. (If you pause for too long the magnetic head can damage the data on the tape!) Thus, “pause” and “stop” are functionally the same thing when it comes to whether or not the music or video is playing. A “pause” in global warming would be a stop in global warming. That, however, did not happen.
A hiatus or a pause in global warming is at present physically impossible. Our climate system operates in such a way that increasing the amount of human generated greenhouse gas pollution, all else being equal (or more or less equal), will increase the global heat imbalance and force the surface temperatures upwards. The implication of a “pause” or “hiatus” (stopping, or a gap in, warming) is that global warming is not happening for a period of time, as though the physical process stopped working, and the implication of that is that physics does not work the way climate scientists know it works. This is why “pause” is so beloved a meme in the denier community. If there is a pause, the science must be wrong. But even if there were sufficient aerosols from a huge volcanic eruption to actually lower global surface temperatures significantly for a short time, the greenhouse gasses previously and continuously added by humans would remain and continue to exert an upward effect on temperature. Once the aerosols settle, which does not take long, the added greenhouse gasses will remain for many decades (even centuries) and warming will continue until an equilibrium is reached. That would not be a pause or hiatus, just a bit more wiggling in the line marching ever upward.
Global warming is a process. More greenhouse gasses along with the resulting positive (heat increasing) feedback effects that accompany that increase cause a heat imbalance and the parts of the Earth that can absorb heat from the sun directly or indirectly become warmer. Global warming is also a pattern. It is a pattern we observe in the average global temperature measures such as the surface temperature measurement described above.
If you can show that the pattern as observed is not as expected, that would bring into question the process of greenhouse gas-caused changes in the Earth’s heat, right? Well, no. The answer is no because the way the process works and the way we generally observe the pattern are not the same thing.
Look at these two graphs.
OHC
GMST
The upper graph shows the temperature of the part of the ocean, the upper 700 or 2000 meters, that can be warmed indirectly by increasing greenhouse gas pollution over a period of time. The lower graph shows the same thing for the sea surface and the atmosphere. These graphs are dramatically different in the x-axis. The ocean heat content graph only goes back to the late 1950s, while the surface graph goes back to 1880. This is because of difference in the data that are available.
Now, have a look at this graph:
BUBBLE GRAPH SHOWING DISTRIBUTION OF HEAT IMBALANCE
This graph shows the relative percentage of the overall warming that occurs in the ocean vs. the atmosphere and a few other systems. The ocean heat graph above, which shows no recent period of time during which heat does not go up, represents over 90% of the heat increase due to global warming. The surface represents only a small percentage. In the following graph, I simply cropped each of these two graphs to show only 1960 to the present, then scaled them so the surface graph and the ocean graph are in proper relationship to each other on the vertical axis. This is a bit hokey but it makes the point:
HYBRID GRAPH SHOWING GMST AND OHC SCALED
Wow. When we refer to the process of global warming, we are referring to changes in the Earth’s heat balance, which is a combination of what climate scientists call “forcings” (not my favorite term but it is the one in use) that move heat imbalance either up or down. Human caused greenhouse gas pollution is a positive forcing, which in turn causes a number of other feedbacks, also positive. So the total result of greenhouse gas pollution is an increase in temerature over time until some future point where the forcing stops (because we stop using fossil fuels) and the heat imbalance eventually settles out (far into the future). Aerosols from other human pollution or volcanoes, etc., force in the opposite direction. The net outcome has been, for decades, an increase in temperature. The cobbed together graph above shows that all of the forcing combined has resulted in a steady upward increase in temperature. The graph also demonstrates that even large up or down deviations in the pattern of surface temperature are not especially relevant to the total process of warming.
When we refer to the pattern of global warming, however, we generally do not refer to overall changes in heat balance, but in practice, we refer to changes only in global means surface temperature. Why? Because that is the measure for which we have data over a long period of time. It is like this. Say you want to know if your child has a fever. You may put a thermometer in the child’s mouth, or some other orifice, or put a heat sensitive strip on the child’s forehead, or an ear thermometer in the ear. In so doing, you have measured the child’s temperature, right? Well, no. What you measured is the temperature of the child’s mouth, or distal large intestine, or forehead, or ear drum. You don’t call the nurse hot line and say, “Help, my child’s mouth is 104 F, what do I do?” You use the measurement you took of one tissue or body part to estimate the child’s overall body temperature. Well, actually, you use the measurement you took to see if your child’s temperature-related homeostasis is off. In any event, you used a measurement of a small part of your child’s body to estimate internal temperature.
When climate scientists show you a graph of mean surface temperature and talk about global warming, they are not ignoring the ocean. They are simply measuring the surface as an indicator of an ongoing change in the Earth’s heat imbalance, using data that are available, understood, and cover a long time period. So they are talking about the process of global warming (which involves the oceans, the air, the sea surface, the ground under your feet, ice, etc) but using a readily available and useful tool to track it.
As a result, the term “global warming” to many climate scientists means “overall positive heat imbalance most of which is in the ocean.” To some scientists, “global warming” refers to global mean surface temperature change, and the ocean is viewed as a reservoir where heat is stored, waiting in the pipeline to come out later. That is really the same thing, and both acknowledge the difference between surface temperature measurement and ocean heat content measurement. When you actually look in the published literature, you see no confusion or changes in terminology. You really don’t see the term “global warming” being used very often when referencing measurements. If the measurement being discussed is the heat in the ocean, you see the term “ocean heat content” (OHC). When the measurement being discussed is the surface temperature record, you see a term like “Global mean surface temperature” (GMST). And, you don’t even see these terms used on their own; At some point in the scientific paper, the actual data set used to derive these values is specified.
This does not imply that the difference between ocean heat content and global surface temperature is not important. It is very important. For one thing, we live at the surface. Heat waves are a phenomenon of the atmospheric temperature at the same location it is measured by all those thermometers. Tropical storms form more frequently or grow larger with a higher sea surface temperature. A warmer atmosphere holds more water. Relative changes at different latitudes in surface temperature appear to have changed how weather systems behave, giving us the phenomenon known as “weather whiplash” causing frequent droughts (short or long term) and regional inundation with exceptional rain or snow. The deeper (down to 2000 meters) heat in the ocean does not directly cause those things.
But, the heat in the ocean does contribute when it comes out, like during an El Niño, adding to the surface heat. And, there are other effects of heat in the ocean, causing important ecological changes including ocean acidification. It isn’t really that complex. Both the ocean (down to 2000 meters or so) and the surface (SST and the bottom of the atmosphere over land) are warming. The total amount of heat that the ocean can absorb is huge (because water holds more heat than air). The heat moves back and forth between the sea and the air. Numerous effects occur. The whole shebang together is global warming, but we often represent the phenomenon as changes in surface temperatures because that is an excellent measurement.
Perhaps we should not use the term “global warming” for the pattern of surface temperature changes, because global warming is bigger than that, it includes more stuff. But the surface is where we are at, and just like we say “my child has a fever” because our child’s forehead feels hot and the ear drum is verified as warmer than it should be with an optical thermocouple, we can refer to the GMST and speak of global warming. Because it is.
On several occasions, I have had lengthy discussions with colleagues who are full time well respected climate scientists about this terminology. As far as I can tell, two things are true: 1) left on their own, these scientist would probably sort out into two groups who prefer two different ways of using terms like “global warming” and “surface temperature” and such; and 2) this matters about as much as what color pocket protector they are using to hold their mini-slide rules. It does not matter at all. As discussed above, when doing the science, the systems to which one refers and the data one makes use of are specified unambiguously and differences in the way these terms may bleed out into public (and policy making) space are not important. Outside the science, in that public and policy making space, the terms do become important, but not because they have problems. They become important only because they are being used, exploited, by deniers of science to misdirect and mislead.
And, as I suggested at the beginning of this essay, this is normal. Terminological messiness occurs in all areas of science. I once copied out all of the glossary definitions of major phenomena in population genetics, from a well written textbook produced by a well respected population geneticists, into a handout. Every definition from that glossary contradicted or complexified at least one other definition. It was a mess. But it was also real. Each term had been introduced at a different time by different scientists for different reasons with different problems trying to describe something somewhat different. Had a committee of population geneticists sat down for two years, long after the science had been worked out in some detail, and generated a glossary of terms (like “bottleneck,” “genetic drift” and “founder effect”) there would be no contradictions or ambiguities (though there might be a few black eyes along the way). Even the term “gene” has multiple and often contradictory meaning in use, and that gets worse when dealing with the literature over a couple of decades. This emerged over time as we learned more about what a “gene” actually is. Yet, population geneticists and DNA experts do not have any problem doing the science. These are just quirks that emerge at the interface of the rational pursuit of truth in science and this crazy thing we have called language.
The Earth’s climate is warming. The upper oceans are warming, the sea surface temperatures are elevated, the air in the lower Troposphere, where we live, is warming. This warming is caused almost entirely by the increase in human generated greenhouse gasses and the positive (not positive in a good way) feedbacks caused by that. The effects that increase the global heat imbalance and the effects that decrease it (such as greenhouse gas increase and aerosols — dust — from volcanoes, respectively) vary over time in their effect, which causes some variation in the upward march of global surface and ocean temperatures. Meanwhile heat is going back and forth between the surface (atmosphere and sea surface) and the deeper (but still upper) ocean, which causes either of these parts of the Earth system to wiggle up and down in temperature. There are other effects causing other wiggles.
Every now and then the wiggling results in a seemingly rapid increase in temperature. Every now and then the wiggling results in a seeming slowdown in increase in temperature. When the latter happen, those who wish you to believe that climate change is not real point, jumping up and down, giddy, and say, “See, there is a pause in global warming, therefore global warming is not happening!” They are wrong for the reasons just stated.
Dana Nuccitelli (author of this book), over at the Guardian, has written a blog post that nicely summarizes current scientific thinking on the so-called pause (or so-called hiatus) which has been named by witty climate scientists as the #FauxPause. Because it is faux.
I’m pretty sure Dana and I were looking at the same information recently. While Dana focuses on the #FauxPause, I recently penned this: Global Warming Getting Worse
A paper just published in Science Magazine helps explain variation we see in the long term Carbon-pollution caused upward trend Earth’s surface temperatures. The research also, and rather ominously, suggests that a recent slowdown in that trend is likely to reverse direction in the near future, causing the Earth’s surface temperature to rise dramatically.
The graph shown above represents the ongoing warming of the Earth’s surface owing to the increased atmospheric concentration of human generated greenhouse gas pollution, mainly CO2. But, have a look at the following graph of changes in concentration of CO2 in the Earth’s Atmosphere:
As you can see, the increase in CO2 is very steady, while the changes in Earth’s surface temperature is very squiggly. Why? In particular, the Earth’s surface temperatures seem to undergo a series of rapid increases or decreases, and now and then, seem to squiggle up and down along a slowly ascending plateau, as has been happening recently. Climate science deniers have taken this recent slowing in the increase of temperature as a signal that the link between CO2 concentrations and global surface temperatures is a hoax. But real climate scientists focus instead on actually explaining, rather than making up stories about, this variation.
There are several different factors that may cause the shorter term squiggles that we see superimposed on the longer term warming trend. The sun’s energy varies over decades, and this contributes a small amount to the variation. Aerosols (dust), either from human activities or volcanic activity, can produce a cooling effect, and this effect varies across time. If you look at the graph of temperatures, you’ll see a strong downward trend associated with the vast eruption of Mount Pinatubo in 1991, for example. A third source of variation in the upward march of the Earth’s temperature is not really a source of cooling or heating at all, but rather, a shift in where the heat goes. The graph on the top of this post is of “surface temperature,” which is a combination of land-based thermometers at roughly head-height, located at weather stations around the world, and sea surface temperatures. But well over 90% of the heat added to the Earth’s system by the human-caused greenhouse effect actually ends up in the ocean. A small percentage of variation in how much heat goes into, or comes out of, the ocean can cause a large variation in the “surface temperature.” You can think of the surface temperature measurements as a relatively small tail attached to a rather large dog, where the dog is the ocean and the tail is the land based thermometers and the sea surface. (I’ve developed this analogy here.)
That the behavior of the ocean is important can be understood by noting that while surface temperature increase has slowed in recent years, the temperature in the top couple of kilometers of the world’s oceans has continued to increase apace. You can also look at the relationship between the squiggle of the surface temperature curve and El Niño and La Niña events. The former are periods of time when the Pacific ocean is sending heat out into the atmosphere, and the latter are periods of time when the Pacific is sucking more heat in. The following graphic from Skeptical Science illustrates this nicely.
“ENSO” refers to the El Niño-La Niña cycling. The top line, in red, represents the change over time in surface temperature just during El Niño periods, while the blue line, along the bottom, represents change over time in surface temperature just using La Niña years. As you can see, many of the ups and downs in the long term surface temperature trend seem to represent ENSO variation.
The recent slowdown in global warming has brought into question the reliability of climate model projections of future temperature change and has led to a vigorous debate over whether this slowdown is the result of naturally occurring, internal variability or forcing external to Earth’s climate system. To address these issues, we applied a semi-empirical approach that combines climate observations and model simulations to estimate Atlantic- and Pacific-based internal multidecadal variability (termed “AMO” and “PMO,” respectively). Using this method, the AMO and PMO are found to explain a large proportion of internal variability in Northern Hemisphere mean temperatures. Competition between a modest positive peak in the AMO and a substantially negative-trending PMO are seen to produce a slowdown or “false pause” in warming of the past decade.
The research (also reviewed here by Chris Mooney) combines observational data (temperature records and the indices for the AMO and PMO) with sophisticated modeling techniques to parse out the contributions of the Pacific and Atlantic oceans, the big dogs of climate change (the Pacific being the much bigger dogs) on surface temperature variability. Essentially, they are trying to determine how much of the squiggling, specially the recent slowing down of temperature increase, is accounted for by “internal variability” as opposed to “forcings.” The former includes the interactions of the surface and the ocean. “Forced” variation is, according to Michael Mann, means “… governed by drivers, be they human (increased greenhouse gas concentrations, sulphate pollutants) or natural (volcanoes, solar output changes). The internal variability is what’s left, it is the purely natural oscillations in the system that have no particular cause, just as weather variations on daily timescales have no particular cause, they just happen.”
One of the findings of this paper, important in climate research but perhaps a bit esoteric, is that the Pacific and Atlantic have mostly independent effects as sources of internal variation. This is not really new, but confirmed by this work. More exactly, treating them as independent provided good results.
But the most important finding is summarized in the following figure, taken from Figure 3 and also reproduced in a writeup by author Mann at Real Climate:
This shows the AMO, PMO, and the derived (combining the two) NMO values over time. Assume that the highest and lowest values are close to the maximum and minimum that these measures normally reach. Note that there is something of a periodicity in these values. That there would be makes sense. These values represent the way in which the oceans interact with the air, and we know that although there is not perfect periodicity (regularity) in that relationship, historically, every year the ocean is in a phase of removing heat from the atmosphere there is an increased chance of a reversal in that relationship. Now, step back from the contentious issue of climate change for a moment, and imagine that these are values of a blue chip stock you are thinking of investing in. Remember the cardinal rule of getting rich on the stock market: Buy low, sell high! Now, decide if you want to put your hard earned money ito the AMO or the PMO. Clearly, the PMO is at a minimum. Buy now because it is going to go up soon!
Remembering that the PMO was found to be a much bigger source of internal variability than the AMO, and that it is a major player in determining surface temperatures, this can only mean one thing. Things are going to heat up soon. Study author Michael Mann told me, “The PMO appears to be very close to a turning point, based on the historical pattern. So we don’t expect it to continue to plunge downward. We expect a turning point soon.” In his summary of the work in Real Climate, Mann notes that “the most worrying implication of our study [is] that the “false pause” may simply have been a cause for false complacency, when it comes to averting dangerous climate change”
We just had the warmest calendar year on record. Last month, January 2015, was probably the second warmest January on record. Using a 12 month moving average (like in the graph at the top of this post), the last 12 months were the warmest 12 months on record. I hear rumors that February, the month we are in, is relatively warm. We have been seeing signs of the Pacific belching out more heat lately, with El Niño threatening. This could all be a very short term trend, as we expect to happen frequently with the general upward march of surface temperatures owing to greenhouse gas pollution. But this latest paper indicates that it might not be; it could be the beginning of a longer upward trend. Whatever effects of surface warming you might be concerned with — increased storms, drought, more rapid melting of glacial ice, killer heat waves — expect more over the next decade than we have over the last decade. And we had quite a bit of that over the last decade.
In 2009 someone wrote a blog post about climate change that made all the usual science denialist claims. Hurricanes have reduced therefore global warming is not real. In this case, hurricanes are one of the main threats of climate change (a straw man) and since they are not as common these days in the Atlantic as alarmists claimed the would be (cherry picking) global warming is not a concern. There were stronger storms in the past. Katrina wasn’t really all that bad. Etc. etc.
The Ice Caps (he called sea ice “Ice Caps”) are not really melting that bad and besides we don’t really know what they were doing before 1970 so we can use anecdotal evidence that sea ice was less extensive and ignore anecdotal evidence that sea ice was more extensive in the past.
El Nino was supposed to do somehting rather specific and unusual (that El Nino researchers were never very sure of) and instead did something else rather unusual therefore there is no global warming. Climate models don’t really work, Carbondioxide is a plant food, global temperatures are experiencing a hiatus in increase, it’s really the sun, etc. He called concern over climate change hysteria and called discussion of changes to climate alarmism.
This was Matt Rogers, who at the time, and who is still now, with the Capitol Weather Group. Perhaps Matt was confused five years ago. Perhaps he was a climate change skeptic in the days when it was reasonable to question the mainstream science, before the consensus formed and climate scientists started working more on details. But no, that doesn’t really explain what he was saying then because consensus was already established. He was, in truth, spouting denialist creed. But still, perhaps these days Matt, who is actually a trained meteorologist, has shaken off the denialism.
Maybe. But just the other day he came out with a post that is very much worhy of admonishment, in part because of a graphic it uses. Have a look at the graphic, which is about Global Temperature Change in recent years. Tell me what you think this graph shows?
Decrease, decline, flatness, hiatus. Cooling. Climate getting cooler. Global warming must be wrong.
Nope.
This is a change in the rate of acceleration of the velocity of global temperatures. We’ll get back to that in a moment.
Matt starts his post with:
The recently-released National Climate Assessment (NCA) from the U.S. government offers considerable cause for concern for climate calamity, but downplays the decelerating trend in global surface temperature in the 2000s, which I document here.
No it doesn’t. The NCA addresses the topic in the FAQ and in the body of the report rather prominently.
Matt then notes:
Many climate scientists are currently working to figure out what is causing the slowdown, because if it continues, it would call into question the legitimacy of many climate model projections (and inversely offer some good news for our planet).
This is a misstatement. This verbiage implies that many climate scientists accept the idea of a “slowdown” and are trying to figure it out. This is simply not true. There is secular variation in the commonly used surface temperature measures, which are an incomplete estimate of global temperature and warming/cooling over time, ignoring the largest heat reservoir on the planet (the ocean) and highly dynamic changing effects such as the Arctic. It is like an index, useful but nothing like perfect. Imagine using only one of several indexes of the economy to stand in for all of them? You wouldn’t Actually, these temperatures series are much better measures of global warming than any of those economic indexes are of the economy, but you get the point; it is a good estimate. Emphasis on both “good” and “estimate.” Anyway, most of this variation has been explained in the past. A few studies recently explained more of the variation. But overall the march of global surface temperatures have tracked with expectations and gone up over time. Scientists are not scrambling to explain a thing that is not happening. Matt should know this.
Now about his graph. Matt first tells the people reading his post that they could create their own graph of global temperatures and make one, but no, Mat will do it for you:
You can see the pause (or deceleration in warming) yourself by simply grabbing the freely available data from NASA and NOAA. For the chart below, I took the annual global temperature difference from average (or anomaly) and calculated the change from the prior year.
He’s referring to the chart I show above, but implying in the text that this is a chart of global temperature anomalies (differences above or below a baseline) just like any other temperature change over time chart. He doesn’t exactly lie, but he made a very obscure graph of a very obscure measure with questionable statistical validity or usefulness and seems to do everything he can to pass it off to the unwary as a graph showing global temperature decreases over the last several years.
More subtly, why did he smooth the line? It makes it look like a mathematical function (giving it undue credence?) when it is really multi-cause variation from year to year in a derivative.
Also, by setting the start of the graph at a recent arbitrary point, the graph can not show the long term trend. That would probably be a more or less flat line with short term up and down trends. It would be a very uninteresting graph. Only by focusing on this close up does it look like it is showing something. At the moment I’m writing this blog post from the middle of the Great North Woods so I don’t have access to the data but maybe I’ll make that graph for you and show you at a later time.
The “sign of data validation” he refers to in his post, that both data sets have the same trend, is bogus. They are not two separate data sets. They are two overlapping sets of data measuring the same thing. So, here, “Data Validation” means that no one accidentally inserted their checkbook balancing data into the wrong spreadsheet cells.
Matt notes “…the warm changes have generally been decreasing while cool changes have grown.” This is not a graph of warm or cool changes. It is a graph of the rate at which changes have happened. So by stating it this way, the essence of the graph is lost. This is a graph of change in rate of change.
Then, “To be sure, both sets of data points show an mean annual change of +0.01C during the 2000s. But, if current trends continue for just a few more years, then the mean change for the 2000s will shift to negative.”
Wut?
Nice to admit that the trend is an increasing temperature, but suggesting that this could shift to negative (for more than a brief moment) is insane. This is like looking at the increase in maximum rate of human travel over a century, from horse to car to aircraft to space ship and predicting that at some point we will be going faster than the speed of light. You can’t go faster than the speed of light. You can’t add greenhouse gasses to the atmosphere and cool off the planet short of a very serious negative feedback mechanism which apparently does not exist. Warp drives in the news lately notwithstanding, we will not cool the planet by, effectively, turning up the effects of the sun’s energy.
Then, “The current +.01C mean increase in temperatures is insufficient to verify the climate change projections for major warming (even the low end +1-2C) by mid-to-late century.”
There is not a “current +.01C increase.” There is a poorly made graph combined with an apparently poor understanding of the science possibly made with the intent of minimizing concern over global warming covering only a short period of time being misinterpreted as a valid measurement. This is like cold fusion or faster than light neutrinos invalidating the Standard Model in physics. But less interesting.
The rest of Matt’s post is him tossing softballs at himself in the form of the usual objections people make when someone advocates for the #FausPause. Like that Matt or his friends might be cherry picking. Like they do. Or noting that it is warmer now than ever. Like it is.
In the end, literally, Matt notes that the slow down is not real, is only temporary, and will go away. But this is only after a majorly misleading graphic and a lot of verbiage with an entirely different message. Is this a new kind of denialism and what do we call it?
Just a quick item on the pause in global warming that is said to have happened over the last X number of years. I took NOAA’s instrumental record since the late 19th century and calculated the average deviation for “surface” temperatures from a baseline for the entire period. Surface temperatures refer to the lower part of the atmosphere and sea surfaces. When you look at a graph of “global warming” expressed in temperatures, this is almost always what is meant (this leaves out a lot of things, including the poles, much of Africa, and deeper ocean waters). But it is a standard and a fairly useful one.
If there was a significant pause in the overall upswing of temperatures for any period of time, I reasoned, it would show up as a cluster of negative years … years where the temperature for that year is lower than the previous years. More to the point, “hiatuses” (and I actually don’t like that word because it is being used correctly …. “pause” is a better word) if they happen on a regular basis should show up as a cluster, not necessarily continuous, of negative years.
Look at the graph above. This is simply a graph that shows a point for each year that is cooler than the previous year. There are tests that one could do on this data. For example, a sign test or a run test would tell if there was any clustering of negatives. But I’m not going to bother with this at this point.
It seems to me that negative years are fairly uniformly distributed at the large scale and seem random. There may in fact be some real clusters in here, but if they are, they are not recent.
The weatherologists have more or less stopped saying there might be an El Niño this year. Now they are saying there will be an El Niño, and they are starting to consider how strong it will be. Well, actually, they’ve stopped doing that too and are now talking about whether it will be a mondo-El Niño or a mondo-mondo-El Niño.
Here is a newly released video by Peter Sinclair and the Yale Climate Forum about the coming El Niño:
I have a prediction to make. First a bit of background.
You know about the so-called “hiatus” in global warming, because every Tea Partier with a mouth is yammering about it. (See this for a nice response to Sean Hannity’s most recent yammering.) There is a slowing down of the increase of what we call “surface temperatures” over the last several years. However, there are at least two major categories of cause to consider when thinking about this slowdown. First, “surface temperatures” do not reflect the totality of global warming. Surface temperature is a summary of several important parts of the planet, mainly the lower part of the atmosphere and the very top layer of the ocean. The vast majority of the heat added to the system by increasing CO2 in the atmosphere actually goes somewhere else; it goes into the oceans. I’ve talked about this problem of measurement here and here. So, we expect that actual “global warming” (the total warming of the Earth because of added CO2) to be one thing, and “surface temperatures” to reflect but not perfectly track that. (Having said that the term “Global Warming” usually refers just to surface temperatures, a terminological glitch, in my opinion, that arises from the historic uses of the terms among scientists.)
The second feature of the so called hiatus, aka #FauxPause, is that even within that part of the planetary system that is measured and summarized as “surface temperature” there are biases. Much of interior Africa and huge regions of the poles are not as accurately measured, or are simply not included in the squiggle that we use to represent global warming. Recent analysis, however, has estimated the degree and direction of that bias, and it turns out that the bias is towards the negative — we have been missing heat. When you put that heat back into the squiggle, the so-called hiatus gets less hiatusy.
What does all this have to do with El Niño? And my prediction? Here’s the thing. El Niño is part of a larger ongoing continuous climatological phenomenon referred to as ENSO. This is a cyclic (but not periodic) phenomenon having to do with surface heat being plowed into the deeper ocean for a period of time then coming out later. When the heat comes out, the “surface temperatures” go up. If we have the mondo-, or especially the mondo-mondo- El Niño people are expecting, a whopping pile of heat that has been hiding in the Pacific Ocean is going to spring from the sea and heat up the air. Expect heat.
In Anthropology we have a concept called the “Nature-Nurture Dichotomy.” You know what this is because you have made references to it frequently in day to day life. Nature is learned, enculturated, received behavior or personality or whatever. If you water your plants more or less they grow more or less. If we raise our children to be more or less violent, we may get a society that is more or less violent. That sort of thing. Nature is the built in part. A gene causes men to be more violent than women, or women to be more nurturing than men. The “men are from Mars” and “women are from Venus” thing is a statement — unsupported by science and way oversimplified to the extent of being stupid and useless, I quickly add — about nature. According to the Nature-Nurture dichotomy model, we, our plants, other living things, can be described as the outcome of innate (genetic) causes and external, learned or environmental causes. Indeed, according to this framework, we can characterize a feature of a person or a plant or whatever as X percent nature and Y percent nurture, adding up to 100%.
The nature-nurture dichotomy is a falsehood. It is wrong. It is incorrect. It is not supported by the data. This is not to say that there are not “built in” features of living systems and “environmental” features of living systems. But, the stark distinction between the two, the lack of consideration of interaction between the two, and the simplified partitioning of causality to add up to 100% between the two are all demonstrably wrong. Not only are those things wrong, but Nature-Nurture dichotomy thinking is misleading.
What does this have to do with El Niño and global warming and stuff?
If global warming was not happening, the surface temperature measurements would look like a flat squiggle over time, going up and down but averaging out over just a few years or a decade or two. There are many “natural” features of the climate system that act like this, such as the strength of the sun or the effects on surface temperatures of aerosols (i.e. volcanic dust). ENSO is such a thing, a natural squiggling of effects on surface temperatures.
Human release of Carbon Dioxide into the atmosphere is also a squiggle, potentially varying from year to year, but the effects of CO2 release have been to increase the baseline temperature over time.
The following graph is a made up version of this. The squiggles in the lower part of the graph represent a set of natural factors that influence the final outcome; they vary with their own up and down pattern. Just above that is a single upward tending variable. The line in the topmost part of the graph is the sum of all of these.
When temperatures started to flatten out over the last few years (they did not decrease, and they kept rising, but at a slower rate) climate change denialists made the claim that this was because anthropogenic global warming (represented by that middle, upward trending line in the made up graph) wasn’t real. Climate scientists argued that there were two or three reasons the graph flattened out a bit. One of those reasons is the simple, overarching claim that natural variation (like ENSO) makes the graph squiggle up and down independently of anthropogenic global warming. The climate scientists were correct, the science denialists were wrong, of course.
Now, with ENSO about to produce an El Niño, we are probably going to see the squiggle that is the sum of all squiggles squiggle upward, perhaps rather dramatically. The heat that has been hiding in the ocean will return to the “surface” (lower atmosphere and top layer of the oceans).
I predict that denialists will claim that this is not global warming, but rather, natural variation, so therefore global warming is not real.
The first part of that is sort of true, but if so, it was ALSO TRUE that the flattening out of the overall surface temperature curve, and much or all of the squiggle in that line over many decades, is explained by natural variation.
In other words, denialists will have ended up saying: “The pause is true because AGW is not true. The upward swing in 2014/5 is not real because is is natural.”
Climate scientists will say “The pause was an artifact of the natural process of heat plowing into the ocean and the resurgence of surface temperatures in 2014/5 is due to the natural process of that heat coming back to the surface, all of this playing out on a generally upward trending surface temperature graph.”
See the difference?
I’d like to add, taking the aforementioned anthropological perspective, that the nature-nurture (natural/anthropogenic) dichotomy is actually present in this argument and mucking it up a bit. The resurgence in temperature increase we are likely to see over the next year or so is not a “natural” occurrence in that the actual heat is “natural.” Some of that heat, we humans made. So you can’t really call it natural variation. This is more of a linguistic point than anything else, because the natural variations of which we speak are “variations” more than they are “natural” or “not natural.” And the science of climate is, like science in general, all about variation. In the end, the trend of temperature change over the last half of the 20th century up to the present and for decades to come is an increase (a kind of variation) pretty much all caused by human release of CO2 and related effects. In the end, the squiggly nature of the line that represents that trend will end up being a combination of natural features and changes in the human effect. This has been true for decades, it is true right now, and it will continue to be true for a long time.
It is said that global warming has taken a break over the last decade or so. This is not true. Surface temperatures (air, sea surface, and ice) have increased over this period of time, though less so than previous years. Also, there are various indicators that the coming year or so may be extra warm, depending on what happens in the Pacific Ocean. Perhaps more importantly, deep sea temperatures seem to have gone up, and since most of the effects of anthropogenic global warming are seen in the ocean (over 90% of the extra heat goes there), changes in the rate of global warming at the surface can easily be the result of short term changes in exactly where the heat goes. (I discuss this in detail here: The Ocean is the Dog. Atmospheric Temperature is the Tail and About That Global Warming Hiatus… #Fauxpause.)
Recent research has suggested that part of the recent slow down in global surface warming, and other fluctuations, have resulted from the fact that the Earth’s surface is not as evenly sampled as one would like, and certain areas that have heated up quite a bit lately such as the Arctic and interior Africa are underrepresented in the data.
Some of the variation in surface warming has been attributed by some researchers to a phenomenon known as the Atlantic Multidecadal Oscillation (AMO). “Oscillations” are a common phenomenon in climatology. Generally speaking, this is where a major variable (temperature or air pressure) in a given area or between two areas shifts back and forth around a mean. The AMO in particular has been a bit difficult to figure out, or for that matter, to prove that it really even exists. Part of the problem is that a single oscillation, which involves seas surface temperatures over the Atlantic Ocean, may have a period of forty or even eighty years. For this reason, the high quality record of surface temperature change allows us to only see a couple of full oscillations, and this makes it hard to characterize and even harder to explain causally.
According to Michael Mann, lead author of a paper just out addressing the pause and its relationship to the AMO, “Some researchers have in the past attributed a portion of Northern Hemispheric warming to a warm phase of the AMO. The true AMO signal, instead, appears likely to have been in a cooling phase in recent decades, offsetting some of the anthropogenic warming temporarily.”
One application to understanding recent changes in the rate of warming in the context of the AMO is the so-called “Stadium Wave.” This is an actual Stadium Wave, a phenomenon seen at sporting events:
The climate Stadium Wave idea as proposed by Judith Curry suggests that certain changes in surface conditions related to the AMO result in swings in surface temperature that actually explain the long term “global warming curve” enough to discount or reduce the presumed effects of global warming. Curry’s Stadium Wave is a kind of emergent property of climate, where this and that thing happens and results in a large effect because of compounding variables.
It’s complicated. Here is an abstract from a paper by MG Wyatt and JA Curry explaining it:
A hypothesized low-frequency climate signal propagating across the Northern Hemisphere through a network of synchronized climate indices was identified in previous analyses of instrumental and proxy data. The tempo of signal propagation is rationalized in terms of the … Atlantic Multidecadal Oscillation. Through multivariate statistical analysis of an expanded database, we further investigate this hypothesized signal to elucidate propagation dynamics. The Eurasian Arctic Shelf-Sea Region, where sea ice is uniquely exposed to open ocean in the Northern Hemisphere, emerges as a strong contender for generating and sustaining propagation of the hemispheric signal. Ocean-ice-atmosphere coupling spawns a sequence of positive and negative feedbacks that convey persistence and quasi-oscillatory features to the signal. Further stabilizing the system are anomalies of co-varying Pacific-centered atmospheric circulations. Indirectly related to dynamics in the Eurasian Arctic, these anomalies appear to negatively feed back onto the Atlantic‘s freshwater balance. Earth’s rotational rate and other proxies encode traces of this signal as it makes its way across the Northern Hemisphere.
This led to a number of statements and predictions by Curry, which have been parsed out here.
For the past 15+ years, there has been no increase in global average surface temperature…
The stadium wave hypothesis provides a plausible explanation for the hiatus in warming and helps explain why climate models did not predict this hiatus. Further, the new hypothesis suggests how long the hiatus might last.
The ‘hiatus’ will continue at least another decade
Climate models are too sensitive to external forcing
Hiatus persistence beyond 20 years would support a firm declaration of problems with the climate models
Incorrect accounting for natural internal variability implies: Biased attribution of 20th century warming [and] Climate models are not useful on decadal time scales
So, the Stadium Wave model goes a long way to explain recent surface temperature trends, and seriously calls into question the viability of climate models that show a strong human influence on global warming and that predict future catastrophic warming. For this reason, the Stadium Wave hypothesis brings up key questions, and if there is evidence either supporting it or falsifying it, that would be of utmost importance.
The paper under consideration here, “On Forced Temperature Changes, Internal Variability and the AMO” by Michael Mann, Byron Steinman, and Sonya Miller, addresses the Stadium Wave issue (and other matters). This is a very complicated study and if you really want to understand it I recommend getting at least a Masters Degree in Atmospheric Science then sitting down with it for a long time. The way I got through the paper was asking the lead author a bunch of questions. Here, I mainly want to address the Stadium Wave issue. The short version of the story is this: Curry’s Stadium Wave is an artifact of her methods. A second and probably more important finding is that the AMO, previously thought to have contributed to warming surface temperatures over the last ten years, is now thought, based on this new analysis, to have contributed to a relative flattening out of the warming, and thus may account for the so-called “hiatus” in part.
Previous work, including that done by Curry but also others, treated the AMO as a long term change in sea surface temperature that could be identified by removing other signals using some standard statistical techniques, most notably “detrending.” Detrending is where you have a known (or presumed) signal that imposes a certain pull on the system over time. This is then numerically removed from the signal as a linear adjustment. For example, if I want to know the average heart beat rate of a set of people, I could just hook them up to a monitor and collect data and get an average. But say I don’t want my signal to be messed up by certain factors, such as caffeine intake, aerobic exercise, or watching episodes of exciting TV shows. So, I estimate the effects of these other activities on heart rate using some independent information and come up with a linear fudge factor. Then, I record when my subjects are drinking their Latte, engaged in their Cardio-Kick class, or watching The Walking Dead. For those periods of time I adjust the heart rate data based my numerical model of those effects, and the result is the detrended heart rate.
A more straight forward use is found in climate studies. We know that there is long term global warming caused by the release of fossil Carbon (mainly as Carbon Dioxide) into the atmosphere. So if we want to observe something like the AMO all by itself, we take the long term temperature record of sea surface in the Atlantic, subtract a numerical value representing anthropogenic global warming over time, and what is left should be the AMO.
But there is a problem with that technique.
The relationship between different variables in a complicated system has to be known or assumed to do this kind of adjustment. For example, let’s say that drinking a latte before Cardio-Kick makes the effects of Cardio-Kick five times more intense on the heart rate. If you didn’t know that, than your detrending of heart rate would get messed up. If you knew about this non-linear relationship, you could adjust for it, but if you don’t know about it, or assume it to be not significant and thus ignore it, than your results will be wrong.
Here’s another analogy that may help. Let’s say you know how to drive a car. That includes how to steer the car through a turn. This involves turning the wheel in a certain direction a certain amount as the car goes through the curve, then straightening out the wheel to go straight after the curve. Now, lets say you get a job flying a high performance fighter jet. But, you slept through flight school. Now, you are flying the jet and you want to make a small turn, so you turn the “wheel” of the plane a bit, then straighten it out to continue in a straight line after the turn.
If you did that, you would actually tilt the plane with your first turn of the wheel, and it would stay tilted indefinitely thereafter, continuing with the turn. To properly turn the jet you have to tilt it, let it start flying in the new direction, then untilt it. In other words, if you fly a jet fighter like you drive a car, you will fly it wrong because you made incorrect assumptions about the relationships between the key variables leading to the final outcome (the direction you are going in). I recommend that you don’t do that with fighter planes or climate data.
Mann, Steinman and Miller, in this new paper, tried something interesting. They recreated a set of scenarios in which they could observe the AMO and other climate variables over time, but rather than having the AMO be a variable subject to emergence after other factors are accounted for, they introduced a known AMO. This way they could see the exact effects of the AMO on surface temperatures and other variables and explore the relationship between the variables. They call this the “differenced-AMO approach.” Knowing the true AMO signal they were able to produce a correct climate signal, and when the AMO signal was detrended in this scenario, the final result failed to match known internal variability. In other words, using the previously applied techniques, such as used by Curry, the modeling did not work. More importantly, the detrended AMO signal had an artificially increased amplitude, with lower lows and higher highs, and these peaks occurred at the wrong times.
Go back to the fly vs. drive analogy. Imagine you are now driving something … a car or a plane … with a blindfold. Your job is to drive or fly around for a while then later show your path on a map. You know how to drive a car. You drive around a bit at a regular speed, make four left turns, and when you are done you may be able to draw your path on a map with reasonable accuracy because you have an accurate expectation of what happens when you turn the wheel of a car. Now, do it with the high performance jet fighter but using your car-driving expectations. You think that first turn to the left made your path turn 90 degees to the left but it really sent you into an unending circle. Now you make two more left turns and you think you’d be back to the starting point like you would be in a car, but what you’ve really done is to send the jet into a tighter and tighter turn and while you think you flew in a big square, your actual path is more like something a kid might draw with a Sprograph(TM). That appears to be what Judith Curry did.
The Stadium Wave is alleged to happen when the AMO and other related climate factors peak and wane in sync, but this new paper shows that this is a statistical artifact. According to Mann, “Past studies arguing for a large AMO temperature signal with a substantial contribution to recent warming have assumed that the forced component of climate change (human factors such as greenhouse gases and sulphate aerosols, as well as natural factors such as volcanoes and solar output changes) is a simple straight line, a linear trend. That is the null hypothesis they assume. They subtract off that linear trend and interpret what is left over as an “oscillation”. But the significance of that oscillation rests upon the validity of the null hypothesis of a simple linear forced signal. That null hypothesis is just wrong.”
Driving a jet plane like a car.
“We estimate the forced signal (which includes a cooling component from 1950s–1970s due to human-generated sulphate aerosols) using a variety of climate model results, and show that the residual “internal variability” that results when you subtract off a more valid estimate of the forced climate trend is very different. The AMO signal turns out to be much smaller (and the estimated amplitude is consistent with findings from coupled model simulations that exhibit an AMO oscillation).”
So, the Stadium Wave hypothesis now looks more like this:
As I mention above, another important finding of this work is that the AMO probably accounts for part of the recent decade’s warming being less than previous years. According to Mann, “Rather than contributing to recent warming, the correctly-estimated AMO signal appears to have contributed cooling over the past decade, i.e. it offset some greenhouse warming.”
The previously used detrending also missed the contribution of other factors that probably make the AMO look like something it isn’t. There have been a number of other effects on surface temperatures that are left behind after anthropogenic warming is detrended out of the data, especially the effects of sulfate aerosols, which come from power plants and such. “These aerosols have cooled substantial regions of the Northern Hemisphere continents in recent decades, thus masking some of the warming we otherwise would have seen,” Mann told me. “But aerosols have tailed off in recent decades thanks to the Clean Air Acts, etc. That has allowed the hidden warming to emerge in recent decades. If you subtract off a straight line from the temperature trend, you will appear to have an “oscillation”, but that oscillation is just mostly due to the non-linear nature of the long-term forcing, with a substantial positive forcing (warming through 1950s, then slight warming or even cooling from the 1950s–1970s due to a large sulphate aerosol cooling contribution), followed by the accelerated warming in recent decades as aerosols have tailed off. We show in the paper that subtracting off a simple linear trend when you have this more complicated time history of human forcing of climate, gives rise to a spurious apparent “oscillation”.”
Go back, if you dare, to the abstract from Curry’s paper. Back when I used to teach multi-variate statistics for grad students (co-taught with a brilliant statistician, I quickly add) this is the kind of abstract we would look for to use in class. It demonstrates an all too common error, or at least potentially demonstrates it well enough to examine as an exemplar of what not to do. Climate systems are complex. There are a lot of known variables and accessible data sets, but those variables and data sets have often hidden relationships, or important factors are unknown, either entire variables or relationships between variables. If you take a set of possible causal variables and one or two ideal outcome variables, it is possible to mix and match among the candidate causal variables until you get a model that matches the outcome. Perhaps, in doing so, you’ve figured something out. Or, perhaps you just made up some stuff. One way to know if you’ve really explained a phenomenon is to have a sensible, even expected, physical process that links things together. In other words, you have a logical cause as well as a statistical link. The latter without the former is potentially wrong. A second way to evaluate your finding is to seek internal statistical or numerical relationships that result in apparent meaning but that are actually artifacts of your methods. In this case, Mann et al have done this; as demonstrated in this new paper, Curry’s stadium wave is one possible, but meaningless, outcome from the process of making statistical stone soup. Such is the way many theories of everything, large or small, seem to go.
Mann also told me that some of the other large scale oscillations that make up part of the standard descriptions of Earth climate systems could be subject to similar artifactual effects. It will be interesting to see if further work allows further refinement of our understanding of these systems over coming months or years. The models climate scientists use are pretty good, but this would make them more useful and accurate.
First, there is no hiatus. Climate science skeptics claim that warming stopped in 1998. It didn’t. Stefan Rahmstorf has a nice post placing 2013 in context with the most recent data, HERE. Just click the “translate” button to read it in your favorite language.
Stefan has a bunch of great graphics that you will enjoy. Following his lead I’ve decided to make a graphic or two myself.
First, the data. NASA has this data to which people often refer when discussing global warming. I took that database and fixed it up a bit. I deleted the first year because there’s some missing data and who cares about only one year anyway. Then, I converted all the values to degrees C rather than hundreds of degrees off a baseline. I also calculated a rank for each year in reference to the entire database. You can download the data as a comma delimited file here. Let me know if that link doesn’t work for you, I’ll be happy to send you the file. Please cite the original (linked to above) if you use this.
Using these data I made this handy graphic showing “surface temperatures” (air and sea surface) over time from 1881 to the present.
When people talk about the hiatus in climate change, or the pause in climate change, what this means is that the slope of the temperature curve for a particular period of time is at or near zero, or negative. What actually happens is that the slope of the curve for a given interval, say 10 years, goes up and down over time. If the temperature was varying around a mean, and not going up over time, the sum of those slopes would be zero, but if there is an average increase in temperature the sum of all the different slopes (of a given interval) one can calculate will be positive.
This is actually a slightly strange way of looking at the data, but I think it is constructive, especially given that the so-called-pause is a dead horse and we are hear to beat it. Look at the chart above. Imagine taking any given ten year period and calculating a slope for that period. Then another and another and another, until you’ve measured out a slope for every ten year period … not just every ten years, but every possible interval of ten consecutive years. This would be a “moving slope” and a graph of it would look like this:
What this shows is that for the vast majority of ten year intervals since 1889 (so the first interval is 1880-1889) the slope of the temperature curve is positive, going up, increasing. It also shows what looks like a remarkably periodic increase and decrease in this slope, with only a few dips below zero. That’s presumably due to oscillations such as ENSO or other factors. Also, most of those dips are from fairly far back in time, and this happens rarely in recent years. We are currently in a period of positive change (upward temperature swings) but currently reduced. But if you look at this graph you can see that there are OFTEN periods of time when the upward slope is very high and other periods when it is very low but still above zero almost always. I hope this helps put the “hiatus” into perspective.
I also made this graph of each year’s rank for the entire period represented by the data set.
Again, this is a slightly unusual way of depicting the data, but it may be helpful. All of the highest ranked years … top ten or so … are from very recent time. The graph has grid lines at every 10 ranks. This lets you quickly identify the period of time over which the top 10, or 20, or 30, or whatever, warmest year according to this data set occurred. There are no top ten years prior to about 1998. All of the top 30 warmest years post date the early 1970s. And so on.
OK, so let’s look at the hiatus again. The hiatus is supposed to be a period of no global warming since 1998. Here’s a closeup of the original chart (above) for that period of time:
What we see here, with the trend line included to make it easier to read, is an increase in global temperature, on average, during this so called hiatus period. But, by picking 1998 as a starting point, climate science denialists have managed to flatten the curve out quite a bit. That’s called cherry picking.
Now let’s arbitrarily double the period of interest, to include the entire so-called hiatus and the same amount of time back before the so-called hiatus. What does the graph look like then? Here, I’ve tried to keep all the scales the same so you can see the shorter “hiatus” period as part of this larger graph. You can also see that 1998 was an exceptionally warm year, which is why you’d want to pick it as the beginning of your fake hiatus period if you were a damn liar. Have a look.
Let’s look at those so called hiatus years in yet another way. Here, we have the graph of the temperature by years (with the upward sloping trend line indicating continued warming even though it is supposed to be a “pause”) and at each node I’ve written in the rank order of the year for the instrumental record. Note that tied years share a number. Basically, this period of “hiatus” is a very very warm period indeed, with temperatures trending upward during the entire period, looking only at the earth’s surface. (Elsewhere we’ve discussed how there is also heat going into the oceans. See links below.)
Since the climate science denialists have chosen a period of time of 16 years to describe a so-called “hiatus” which is not really a hiatus, I thought it would be fun to chunk out the data for the entire time period into 16 year intervals, starting with the most recent and going back to 1886. When viewed using these time intervals, we see overall warming with the most recent years seeing accelerated warming. Have a look:
These are all first drafts and if I get reasonable suggestions I may make new versions with corrections, additions, etc.
