Study finds evidence for a climate-change regime shift in the 1980s

Climate study finds evidence of global shift in the 1980s

Anthropogenic warming, volcanic eruption sparked biggest change in 1,000 years

from ScienceDaily, November 24, 2015

Summary:  Planet Earth experienced a global climate shift in the late 1980s on an unprecedented scale, fueled by anthropogenic warming and a volcanic eruption, according to new research. Scientists say that a major step change, or 'regime shift,' in Earth's biophysical systems, from the upper atmosphere to the depths of the ocean and from the Arctic to Antarctica, was centered around 1987, and was sparked by the El Chichón volcanic eruption in Mexico five years earlier.

Volcano (stock image). Human-made warming and volcanic eruption in the 1980s fuelled the biggest change in 1,000 years, say scientists.

Credit: © beppulos / Fotolia

Planet Earth experienced a global climate shift in the late 1980s on an unprecedented scale, fuelled by anthropogenic warming and a volcanic eruption, according to new research published this week.

Scientists say that a major step change, or 'regime shift,' in Earth's biophysical systems, from the upper atmosphere to the depths of the ocean and from the Arctic to Antarctica, was centred around 1987, and was sparked by the El Chichón volcanic eruption in Mexico five years earlier.

Their study, published in Global Change Biology, documents a range of associated events caused by the shift, from a 60% increase in winter river flow into the Baltic Sea to a 400% increase in the average duration of wildfires in the Western United States. It also suggests that climate change is not a gradual process, but one subject to sudden increases, with the 1980s' shift representing the largest in an estimated 1,000 years.

Philip C. Reid, Professor of Oceanography at Plymouth University's Marine Institute, and Senior Research Fellow at the Sir Alister Hardy Foundation for Ocean Science (SAHFOS), is the lead author of the report, Global impacts of the 1980s' regime shift.

"We demonstrate, based on 72 long time-series, that a major change took place in the world, centred on 1987, that involved a step change and move to a new regime in a wide range of Earth systems," said Professor Reid.

"Our work contradicts the perceived view that major volcanic eruptions just lead to a cooling of the world. In the case of the regime shift it looks as if global warming has reached a tipping point where the cooling that follows such eruptions rebounds with a rapid rise in temperature in a very short time. The speed of this change has had a pronounced effect on many biological, physical and chemical systems throughout the world, but is especially evident in the Northern temperate zone and Arctic."

Over the course of three years, the scientists -- drawing upon a range of climate models, using data from nearly 6,500 meteorological stations, and consulting innumerable scientists and their studies round the world -- found evidence of the shift across a wide range of biophysical indicators, such as the temperature and salinity of the oceans, the pH level of rivers, the timing of land events, including the behaviour of plants and birds, the amount of ice and snow in the cryosphere (the frozen world), and wind speed changes.

They detected a marked decline in the growth rate of CO2 in the atmosphere after the regime shift, coinciding with a sudden growth in land and ocean carbon sinks -- such as new vegetation spreading into polar areas previously under ice and snow. And they found that the annual timing of the regime shift appeared to have moved regionally around the world from west to east, starting with South America in 1984, North America (1985), North Atlantic (1986), Europe (1987), and Asia (1988).

These dates coincide with significant shifts to an earlier flowering date for cherry trees around Earth in Washington, DC, Switzerland, and Japan and coincided with the first evidence of the extinction of amphibians linked to global warming, such as the harlequin frog and golden toad in Central and South America.

Second author Renata E. Hari, Eawag, Dübendorf, Switzerland, said: "The 1980s regime shift may be the beginning of the acceleration of the warming shown by the IPCC. It is an example of the unforeseen compounding effects that may occur if unavoidable natural events like major volcanic eruptions interact with anthropogenic warming."

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Story Source:

The above post is reprinted from materials provided by University of Plymouth. The original item was written by Andrew Merrington. Note: Materials may be edited for content and length.

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Journal Reference:

1. Philip C. Reid, Renata E. Hari, Grégory Beaugrand, David M. Livingstone, Christoph Marty, Dietmar Straile, Jonathan Barichivich, Eric Goberville, Rita Adrian, Yasuyuki Aono, Ross Brown, James Foster, Pavel Groisman, Pierre Hélaouët, Huang-Hsiung Hsu, Richard Kirby, Jeff Knight, Alexandra Kraberg, Jianping Li, Tzu-Ting Lo, Ranga B. Myneni, Ryan P. North, J. Alan Pounds, Tim Sparks, René Stübi, Yongjun Tian, Karen H. Wiltshire, Dong Xiao, Zaichun Zhu. Global impacts of the 1980s regime shift. Global Change Biology, 2015; DOI: 10.1111/gcb.13106

http://www.sciencedaily.com/releases/2015/11/151124081517.htm

Greg Laden: Volcanoes, Tree Rings, and Climate Models: This is how science works.

by Greg Laden, "Greg Laden's Blog," Science Blogs, July 30, 2014

Mark Your Cosmic Calendar: 775/775

One wonders if anyone felt it. Did Charlemagne feel it as he led his forces across Pagan Saxon Westphalia, knocking down Irminsuls and making everyone pretend to be Christian or else? Did the people of Baghdad, just becoming the world’s largest city, notice anything aside from their own metro-bigness? Did the Abbasid Caliph Muhammad ibn Mansur al-Mahdi have the impression something cosmic was going on that year, other than his own ascendancy to power? Or was it mainly some of the nitrogen molecules in the upper atmosphere that were changed, not forever but for an average of 5,730 years, by the event?

The bent tree like object is said by some to be the, or a, Irminsul, the “pagan” sacred object, destroyed by Charlemagne, much as one might destroy a hypothesis, either with, or about, trees.

A long time ago, probably in our galaxy but kind of far away, a cosmic event happened that caused the Earth to be bathed in gamma rays in AD 774 or 775. No one seems to have noticed. There is a mention, in 774, of an apparition in the sky that could be related, but talk of apparitions in the sky were more common back then, before they had certified astronomers to check things out. There is chemical and physical evidence, though, of the gamma ray burst. The best evidence is the large scale conversion of stable nitrogen isotopes into unstable carbon-14 isotopes in the upper atmosphere. As you know, radioactive (meaning "unstable") carbon-14 is created continuously but at a somewhat variable rate in the upper atmosphere. Some of that carbon is incorporated, along with regular stable carbon, into living tissues. After the living tissue is created and further biological activity that might retrofit some of the carbon atoms ends (i.e., the thing dies) the ratio of radioactive carbon to stable carbon slowly changes as the radioactive carbon changes back into nitrogen. By measuring the ratio now, we can estimate how many years ago, plus or minus, the originally living thing lived and died.

But it does vary. Solar activity, nuclear testing, other things, can change the amount of carbon-14 that gets produced. And, a cosmic event that happened in 774/775 caused the production of enough carbon-14 to throw off the chronology by hundreds of years. This is seen in the close examination of carbon in the tissue of trees placed in a tree ring chronology. For example:

Original caption: High-resolution radiocarbon ages, superimposed on annually resolved radiocarbon measurements from Japan and Europe (grey lines and crosses) as well as the IntCal calibration curve based on decadal samples (blue shading), re-sampled at 5-year intervals (light blue crosses). Radiocarbon ages (that is, using 14C, 13C and 12C isotopes) were determined at ETHZ with the MICADAS system.

See the inverted spike there? That is, apparently, gamma rays messing up the radiocarbon chronology. Hold that thought.

Climate Change Is Hard

When volcanoes erupt, they typically spew crap into the air. Some of this material stays in the atmosphere for a while (called aerosols, but not your under-arm deodorant exactly), which will in turn reflect sunlight back out into space prematurely. This causes cooling. It is essential to know how much cooling of the atmosphere happens from aerosols because this is a potentially important factor in global warming. The effect of aerosols caused by volcanoes or industrial activity is an important term in the big giant equation that puts all the different factors together to produce global warming (or cooling). It is important that climate models be able to accurately and realistically incorporate the effects of aerosols. If the science isn’t right on aerosols, climate models may not run true when aerosols are included.

Caldera of Mount Tambora. When Tambora erupted in 1816, we experienced a year without a summer. Tambora was small compared to many earlier volcanoes which may have produced a few summer-less years in a row.

And indeed there is an apparent problem. When climate models are run and include aerosols, and the results are compared with real life data where we have good proxy-indicators of past climate, the model predictions and the real life measurements don’t line up when aerosols are involved at any significant level. A big volcano goes off, but the proxy record consisting mainly of things like tree rings doesn’t show the level of cooling models predict. This has titillated denialists, as you might imagine, because it shows how the science has it all wrong and the only way to truly understand the climate change is to spend hours in the basement with your spreadsheet and a good internet connection, like Galileo would have done.

In fact, this was an interesting problem that needed to be addressed. The modeling methods had to be wrong, or the paleodata had to be wrong, or something had to be wrong.

In 2012 Michael Mann, Jose Fuentes and Scott Rutherford published a paper in Nature Geoscience proposing a hypothesis to explain this discrepancy. The problem was that when a known volcano went off, the tree ring record in particular tended to show only an anemic result. Volcanoes that were thought to totally mess up the weather seemed to have little effect on trees. This even applied to volcanoes which were very directly observed in recent times, when we know there was an effect because people were putting on sweaters and measuring things with actual thermometers.

Mann et al. proposed that rather than having little effect on tree growth, the volcanoes had a huge effect on tree growth. What was being seen by the dendrochronologists (tree daters, like tree huggers but more serious) as a normal, average growth ring at the time of a volcanic eruption was actually the ring for the next year in line; they were missing, understandably, one or more growth rings. The volcano goes off, the trees don’t grow at all. (The masquerading ring would typically be the year before the missing ring since dendrochronology is done backwards, since we know what year it is now.)

You don’t have to imagine a year in which no tree grows ever anywhere to accept this idea. The trees being used as temperature proxies are more the sensitive type. They respond to temperature changes by growing more or less (warmer vs. cooler). Trees that don’t do this are not chosen for study. This has to do with the species and the setting the tree grows in, combining to make temperature the key limiting factor most years, so that growth ring width reflects temperature more than any other factor. So yeah, when it gets very cool because of a big-ass volcanic eruption, one of those “year with out a summer” deals, the very sensitive trees respond by not growing at all that year. They may have a growth period of a few weeks, but trees don’t simply lay down wood every day they are biologically active. They usually start with leaves, then many move on to reproduction, and once they have finished reproducing, have a cigarette, wash up, whatever, they may lay down wood or roots. (Different species have different patterns.) So, a very short growing season can mean no ring at all. If a really bad nuclear-winter-esque volcano happens, this may go on for a few years. This leads to the growth ring corresponding to the year of the volcano simply not being noticed by the dendrochronologists, with a different year standing in. Over time the record can be thrown off by several years, if there are a few volcanoes and one or more of them affects growth for more than one year.

So two things happen. Years with a very strong cold signal are lost entirely, and the record is quasi-randomly offset by a few years in some but not all tree records (because some will be thrown off, while others are not), so the collective record gets out of alignment. A strong uptick in the signal (the zero growth year) does not contribute to the paleoclimate squiggle of temperature at all, and the other possibly contributing years (after the worst is over) are moved around in relation to each other and average in with less cold years. It’s a mess.

Consider the following made up numbers representing temperature over time. The top table is the hypothetical raw data of tree ring growth in relation to temperature across a very strong cold anomaly as might be caused by a massive volcanic eruption. Depending on the tree, there is one or more years of zero growth. The lower table is the same set of numbers but with the earlier years (top) shifted down to cover the zeros, because that is what would happen if a dendrochronologist was looking at the rings from more recent (bottom) to oldest; there would just be this void and it would be filled with the next data in line.

Here are the same data graphed showing a clear anomaly in the top chart, but the very clear anomaly utterly disappears because of missing rings and shifting sequences in the lower chart. This is an existential problem for ancient climate events. I squiggle therefore I am.

Mann et al. proposed adjustments to the record of proxy-indicators of temperature that accounted for missing tree rings at the time of major volcanic events. They made a good case, but it was a bit complicated and relied on some fairly complicated modeling.

Since the publication of Mann et al. there has been quite a bit of back and forth between the climate modelers and the dendrochronologists. I’ve assembled a list of publications and blog posts below. I’ll only very briefly summarize here.

The dendrochronologists had a bit of an academic fit over the idea that they had missed rings. Understandably so. As an archaeologist, I’m partly trained in dendrochronology. There was actually a time when I considered making it my specialty, so I had read all the literature on the topic. I can tell you that missing rings was a serious concern, and taken seriously, and seriously addressed. Seriously, there’s no way modern dendrochronologists would totally miss an entire year’s growth rings. They had ways of dealing with missing rings.

The thing is, it is actually possible to miss rings. Here’s why. The assumption in dendrochronology is that rings can be missed (or for that matter, added) for reasons that allow for correction by cross-dating growth-ring sequences with other trees or even other samples in a single tree. A particular part of a tree can be missing a ring while another is not (especially vertically; the lower part of a tree grows last in many species), or some trees in an area may be missing a ring, but others have that growth ring. This assumption is probably almost always valid; missing rings can be adjusted for by cross-checking across samples. But, if all of the trees of a given species and sampling area have one or more missing rings because of a major volcanic event, that won’t work. But this is not something dendrochronologists are used to.

2 + 2 = 774/775

Eventually Mann and his colleagues put two and two together and realize that the dendrochronologists had a way to test the hypothesis that would not rely on fancy dancy climate-modeling techniques, and that would potentially allow a better calibration of the tree growth-ring record for certain time periods. It was that gamma-ray burst.

That moment in time is a clear marker. Any system involving 14C spanning this time interval should show the spike. Well, what about tree ring records that span both a major volcano and the 774/775 event? If Mann et al. are right, an uncorrected tree-ring record would show a lack of correspondence of any spike at 774/775. But, if missing rings are assumed for sensitive tree records at the time of the volcano, and the tree-ring sequence for those trees shifted, perhaps the records will line up. That would be a test of the hypothesis.

And this is the gist of a letter to Nature from Scott Rutherford and Michael Mann. Very simply put, Mann and his colleagues took this graph, from an earlier paper:

And changed it to this graphic which shows mainly (see caption) the tree ring sequences that span both the 1258 volcanic eruption, which was a big one, and the 774/775 event.

This is a gauntlet, being respectfully thrown down. Mann et al. erected a hypothesis that missing tree rings are virtually universal in large parts of the dendrochronological sample for some events, were not accounted for in the tree-ring chronology, and have thus messed up the tree rings as a proxy-indicator for temperature. Various attempts to knock it down have not worked out. Now, Mann has himself provided an excellent way to assail his own idea. It is now up to the tree ring experts to try to knock this hypothesis down. I suspect Charlemagne might have had an easier time knocking down the Irminsul.

I asked Michael Mann how he felt about this latest development in the ongoing saga of the missing (probably) growth rings. He said, “I’m very pleased that we’ve reached some level of reconciliation with our dendroclimatology colleagues: there’s an objective test that is available to determine if there are indeed missing rings in some of the regional chronologies, as we have speculated to be the case. I look forward to seeing the results of those tests. We proposed a hypothesis, other scientists were skeptical of the hypothesis, and now there is a way forward for testing the hypothesis. In the end, a fair amount of good science will have been done, and we will have learned something. This is the way science is supposed to work.”

http://scienceblogs.com/gregladen/2014/07/30/volcanoes-tree-rings-and-climate-models-this-is-how-science-works/

"Volcanic contribution to decadal changes in tropospheric temperature," by B. D. Santer et al., Nature Geosci., (2014); doi: 10.1038/ngeo2098

Nature Geoscience, (23 February 2014); doi: 10.1038/ngeo2098

Volcanic contribution to decadal changes in tropospheric temperature

• Benjamin D. Santer,
• Céline Bonfils,
• Jeffrey F. Painter,
• Mark D. Zelinka,
• Carl Mears,
• Susan Solomon,
• Gavin A. Schmidt,
• John C. Fyfe,
• Jason N. S. Cole,
• Larissa Nazarenko,
• Karl E. Taylor and
•  Frank J. Wentz

Abstract

Despite continued growth in atmospheric levels of greenhouse gases, global mean surface and tropospheric temperatures have shown slower warming since 1998 than previously^1,2,3, 4,5. Possible explanations for the slow-down include internal climate variability^3,4,6,7, external cooling influences^{1,2,4,8,9,10,11} and observational errors^12,13. Several recent modelling studies have examined the contribution of early twenty-first-century volcanic eruptions^1,2,4,8 to the muted surface warming. Here we present a detailed analysis of the impact of recent volcanic forcing on tropospheric temperature, based on observations as well as climate model simulations. We identify statistically significant correlations between observations of stratospheric aerosol optical depth and satellite-based estimates of both tropospheric temperature and short-wave fluxes at the top of the atmosphere. We show that climate model simulations without the effects of early twenty-first-century volcanic eruptions overestimate the tropospheric warming observed since 1998. In two simulations with more realistic volcanic influences following the 1991 Pinatubo eruption, differences between simulated and observed tropospheric temperature trends over the period 1998 to 2012 are up to 15% smaller, with large uncertainties in the magnitude of the effect. To reduce these uncertainties, better observations of eruption-specific properties of volcanic aerosols are needed, as well as improved representation of these eruption-specific properties in climate model simulations.

Figures at link:  http://www.nature.com/ngeo/journal/vaop/ncurrent/full/ngeo2098.html

Santer et al., Volcanic aerosols account for some of the overestimation of warming by climate models

by reportingclimatescience.com, February 23, 2014

New research suggests that climate models may have overestimated global warming because they do not include the impact of aerosols from volcanic eruptions. The implication is that this may be a partial explanation of the so-called global warming pause since volcanic materials dim the sun and cool the planet -- partially offsetting the warming effect of greenhouse gases. We also include (below) the text of news release issued by MIT.

Click to enlarge. Volcanoes eject material which forms aerosols in the stratosphere which makes the atmosphere more opaque, dims the sun, and cools the planet. The effect is thought to be contributing to the so- called global warming pause. Image courtesy: MIT.

Click to enlarge. Behaviour of overlapping 10-year trends in the ‘ENSO removed’ near-global (82.5 N–70 S) TLT data. Least-squares linear trends were calculated over 120 months, with overlap by all but one month; that is, the first trend is over January 1979–December 1988, the second trend over February 1979–January 1989, and so on. The last trend is over January 2003–December 2012. Courtesy: Santer et al. and Nature Geoscience.

Volcanic eruptions over the past decade or so have cooled global lower-atmosphere temperatures to a statistically significant degree, concludes an article published online in Nature Geoscience. Incorporating these volcanic influences into climate models reduces the difference between observed and computer-simulated surface temperature trends between 1998 and 2012 by up to 15%.

Benjamin Santer and colleagues analysed satellite data to show that volcanic aerosols released from several eruptions since 2000 had a discernable cooling effect on the lower layers of the atmosphere. The authors go on to estimate the magnitude of the effect in climate model simulations, and conclude that the lack of volcanic influences in model simulations of twenty-first-century climate can explain some of the overestimation of warming in these simulations of global mean surface temperatures, compared with observations.

The volcanic aerosols dim the sun and so reduce solar warming of the planet.

The authors state: “We identify statistically significant correlations between observations of stratospheric aerosol optical depth and satellite-based estimates of both tropospheric temperature and short-wave fluxes at the top of the atmosphere. We show that climate model simulations without the effects of early twenty-first-century volcanic eruptions overestimate the tropospheric warming observed since 1998.”

By removing the effects of the El Nino Southern Oscillation (ENSO), the agreement between the observed and the model average temperature responses to major volcanic eruptions was improved, the authors report.

“When both ENSO and volcano influences are subtracted, the model and observed temperature residuals have very similar low-frequency changes up to the end of the twentieth century. After 1999, however, a 'warming hiatus' is still apparent in the observed residual TLT (temperature of the lower troposphere) time series, but the lower troposphere continues to warm in the CMIP-5 multi-model average,” they state.

The authors study the impact of the eruptions of El Chichón and Pinatubo and challenge the suggestion that the recent divergence between modelled and observed temperature changes provides evidence that climate models are on average two or three times too sensitive to human-caused changes in greenhouse gases.

“If this claim is correct, there is a serious error in present model-based estimates of the transient climate response (TCR) to greenhouse gas forcing. As both TCR and the volcanic signal decay time are related to the rate of ocean heat uptake, a large model error in ocean heat uptake would yield errors in the simulated temperature response to El Chichón and Pinatubo. The close agreement we find between the observed and model average TLT (temperature of the lower troposphere) responses to El Chichón and Pinatubo does not support the claim of a fundamental model error in climate sensitivity,” state the authors.

Prof Piers Forster, Professor of Climate Change at the University of Leeds, said: "This is a good paper and confirms the Intergovernmental Panel for Climate Change position that recent volcanoes contribute to the slowdown but cannot be the only cause.  Volcanoes give us only a temporary respite from the relentless warming pressure of continued increases in CO2."

http://www.reportingclimatescience.com/news-stories/article/models-overestimate-warming-because-they-ignore-volcanoes.html

"Small influence of solar variability on climate over the past millennium, by A.P. Schurer, S.F.B. Tett & G.C. Hegerl, Nature Geosci. (2013); doi: 10.1038/ngeo2040

Nature Geoscience, (22 December 2013); doi: 10.1038/ngeo2040

Small influence of solar variability on climate over the past millennium

• Andrew P. Schurer,
• Simon F. B. Tett and
•  Gabriele C. Hegerl

Abstract

The climate of the past millennium was marked by substantial decadal and centennial scale variability in the Northern Hemisphere¹. Low solar activity has been linked to cooling during the Little Ice Age (AD 1450–1850; ref.  1) and there may have been solar forcing of regional warmth during the Medieval Climate Anomaly^{2, 3, 4, 5} (AD 950–1250; ref. 1). The amplitude of the associated changes is, however, poorly constrained^5, 6, with estimates of solar forcing spanning almost an order of magnitude^7, 8, 9. Numerical simulations tentatively indicate that a small amplitude best agrees with available temperature reconstructions^{10, 11, 12, 13}. Here we compare the climatic fingerprints of high and low solar forcing derived from model simulations with an ensemble of surface-air-temperature reconstructions¹⁴ for the past millennium. Our methodology¹⁵ also accounts for internal climate variability and other external drivers such as volcanic eruptions, as well as uncertainties in the proxy reconstructions and model output. We find that neither a high magnitude of solar forcing nor a strong climate effect of that forcing agree with the temperature reconstructions. We instead conclude that solar forcing probably had a minor effect on Northern Hemisphere climate over the past 1,000 years, while, volcanic eruptions and changes in greenhouse gas concentrations seem to be the most important influence over this period.

Link:  http://www.nature.com/ngeo/journal/vaop/ncurrent/full/ngeo2040.html

Benjamin Santer et al., “Human and natural influences on the changing thermal structure of the atmosphere”

Fact sheet for “Human and natural influences on the changing thermal structure of the atmosphere” [1] [Sorry, this is screwed up -- had to copy from a pdf file, and some things did not make it.  Anyone wanting the pdf should send an email to me at apaixonada.por.rio@gmail.com ]
 
by Benjamin D. Santer, Jeffrey F. Painter, Céline Bonfils, Carl A. Mears, Susan Solomon, Tom M.L. Wigley, Peter J. Gleckler, Gavin A. Schmidt, Charles Doutriaux, Nathan P. Gillett, Karl E. Taylor, Peter W. Thorne, and Frank J. Wentz

To be published in Proceedings of the U.S. National Academy of Sciences, Online Early Edition,
Embargoed until September 16, 2013, 3:00 p.m., U.S. Eastern Time

Summary: Observational satellite data and the computer model response to human influence have a common pattern of changes in the thermal structure of the atmosphere. The key features of this pattern are global-scale tropospheric warming and stratospheric cooling over the 34-year satellite temperature record. We show that current climate models are highly unlikely to produce this distinctive signal pattern by internal variability alone, or in response to naturally forced changes in solar output and volcanic aerosol loadings. We detect a “human influence” signal in all cases, even if we test against natural variability estimates with much larger fluctuations in solar and volcanic influences than those we have observed since 1979. Our results highlight the very unusual
nature of observed changes in atmospheric temperature. [2]

Signal-to-noise analysis: A brief primer

Our PNAS paper describes results from a climate change detection and attribution study, in which we investigate the causes of temperature changes in Earth’s atmosphere. The focus of our study is on the vertical structure of atmospheric temperature change – in other words, on patterns of change that vary with latitude and with altitude. These patterns provide information about temperature changes in the troposphere and the stratosphere (see below):

Figure 1: This figure is from Synthesis and Assessment Product 1.1 of the U.S. Climate Change Science Program (Karl et al., 2006 1). It shows the approximate pressure and altitude boundaries of the troposphere and the stratosphere. The multi-colored line indicates the average dependence of temperature on altitude.

We rely on estimates of atmospheric temperature change from satellites and from computer models of the climate system (“climate models”). The satellite observations are made available by two different research groups; the simulation output is from as many as 20 of the models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP-5).

In the real world, many factors – both human and natural – are simultaneously acting on the climate system. We do not have a “control Earth,” on which there are no human-caused changes in atmospheric levels of greenhouse gases.

With climate models, however, it is possible to perform such controlled simulations. For example, we run climate models with our best estimates of the purely natural changes in volcanic activity and the Sun’s energy output over the last 1,000 years [2]. We can then ask whether these computer model estimates of the “world without us” produce climate-change patterns similar to the ones we have actually observed since 1979 [3]. The availability of “world without us” results allows us to examine – and to test – persistent claims that observed changes in climate are primarily due to natural causes, like an increase in solar irradiance, or the “recovery” of atmospheric temperature after large volcanic eruptions.

Our paper also considers simulations in which only human influences act on the climate system, and there are no changes in solar or volcanic influences. Examples of human influences include changes in atmospheric levels of greenhouse gases and particulate pollution. Such “human effects only” simulations are used to estimate the climate-change signal (also called the “fingerprint”) that we expect to see as a result of human activities [4].

Finally, the model simulation output gives us estimates of the year-to-year and decade-to-decade “noise” of internal climate variability, arising from such natural phenomena as the El Niño/Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). This internal variability (which we refer to as VINT) is unrelated to changes in the Sun, or to changes in volcanic activity.

We use a standard fingerprint method [5] to search for the model “human effects only” signal pattern [6] in the satellite observations. First, we quantify the changing strength of the signal pattern in observations. We then estimate the changes in signal strength that are caused by purely natural changes in climate.

Our signal detection method allows us to calculate so-called signal-to-noise (S/N) ratios. If the observed patterns of atmospheric temperature change are becoming increasingly similar to the model “human influence” fingerprint, and if the natural variability patterns are dissimilar to the fingerprint pattern, the S/N ratios will be large. S/N ratios larger than 3 show that there is highly significant correspondence between the model fingerprint and satellite data, and that natural climate variability is unlikely to explain this pattern match.

Our S/N ratios depend on the length of the temperature record. We focus on S/N ratios calculated over the full, 34-year period of the satellite data (1979 to 2012). Looking at long, multi-decade periods of record helps to reduce the impact of large, year-to-year natural variability, and more clearly reveals any underlying signal of human influences on climate. [4]

Question 1: What’s new about this research?

Two aspects are novel.

First, virtually all detection and attribution studies to date use computer model estimates of VINT (natural internal variability; see definition in the “primer”) to determine whether a human-caused climate change signal can be detected in observations. Here, we look at the signal detection issue in several different ways. We try to detect a human influence signal not only against the background noise of internal climate variability, but also against the natural variability information from the CMIP-5 “world without us” simulations. These simulations [7] give us estimates of the “total” natural variability of the climate system, VTOT, which arises from the combined effects of internal variability, fluctuations in the Sun’s energy output, and changes in the levels of volcanic particulates in the atmosphere. 

Second, most previous detection and attribution studies with temperature changes in a “slice” through the atmosphere [8] used results from only one or two climate models, and from a single observational temperature data set. We consider results from up to 20 climate models, and from two different observational data sets [9]. This enables us to determine whether previous claims of the positive detection of a human fingerprint in satellite temperature records are sensitive to current uncertainties in models and observations. We find that prior “positive detection” claims [10] are robust to the model and observational uncertainties considered here.

Question 2: What are your key findings?

In the satellite data, we’ve observed a pattern of large-scale warming of the lower atmosphere (the troposphere) and cooling of the stratosphere. Computer model estimates of the “human influence” fingerprint are broadly similar to the observed pattern (see Fig. 2). In sharp contrast, model simulations of internal and total natural variability cannot produce the same sustained, large-scale warming of the troposphere and cooling of the stratosphere. So in current climate models, natural causes alone are extremely unlikely to explain the observed changes in the thermal structure of the atmosphere.

This is true even if our signal detection approach uses total natural variability estimates from before the period of satellite temperature observations [11]. The “world without us” simulations sample changes in 5 volcanic and solar activity over the last 150 to 1,000 years. Many of these eruptions and solar irradiance changes are much larger [12] than the volcanic and solar changes we have observed since 1979. A remarkable aspect of our results is that even in this “worst case” signal detection situation, when we make signal identification difficult by using very large estimates of total natural variability, we still obtain consistent detection of a “human influence” fingerprint. [12] Examples include the major eruptions of Krakatoa in 1883 and Kuwae in 1452, and the large estimated changes in solar irradiance around the time of the Maunder Minimum (from roughly 1645 to 1715).
 
Satellite observations (Remote Sensing Systems)

Climate models (average of “human influence” simulations)

Figure 2: The vertical structure of changes in atmospheric temperature in satellite observations (top panel) and in computer model simulations performed as part of phase 5 of the Coupled Model Intercomparison Project (CMIP-5; bottom panel). As described in the PNAS paper, both panels provide a vertically smoothed picture of atmospheric temperature change. Information from only three atmospheric temperature layers – the lower stratosphere (TLS), the mid- to upper troposphere (TMT), and the lower troposphere (TLT) was used in generating the two plots. We show temperature changes in this “vertically smoothed” space because satellite-based estimates of atmospheric temperature change are available for TLS, TMT, and TLT, and because our signal detection study is performed with the zonally-averaged temperature changes for these three layers. All temperature changes are in the form of linear trends (in degrees Celsius) over the 408-month period from

Question 3: Is there evidence that the models you’ve used here systematically underestimate the total natural variability of atmospheric temperature?

If the CMIP-5 models analyzed here systematically underestimated the size of observed “total” natural variability, our S/N ratios would be spuriously inflated. In our previous work [13], we found no evidence that this is the case. To test the fidelity with which models simulate observed total natural variability, we compared modeled and observed temperature fluctuations on decadal timescales [14]. On average, the CMIP-5 models substantially overestimate the size of observed tropospheric temperature variability, suggesting that our S/N ratios are probably too conservative [15]. 

Question 4: Are there remaining problems?

Yes. Although we found a “pattern match” between the modeled and observed vertical structure of atmospheric temperature changes, most models have problems capturing the size of the observed changes. On average, the CMIP-5 models underestimate the observed cooling of the lower stratosphere, and overestimate the warming of the troposphere [16]. Some scientists have claimed that there is only one possible interpretation of such differences – that models are too sensitive to greenhouse gas increases. Such claims are incorrect. There are multiple interpretations of differences between modeled and observed temperature changes. Other possible explanations include: (A) residual errors in the observations; (B) an unusual sequence of natural climate fluctuations in the observations; and (C) the neglect or inaccurate specification of key “forcings” in model simulations of historical climate change. 

Results presented in our PNAS paper and elsewhere suggest that forcing errors make an important
contribution to the biases in model temperature trends [17].

References




1 Karl, T.R., S.J. Hassol, C.D. Miller, and W.L. Murray (eds.), 2006: Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. National Oceanic and Atmospheric Administration, National Climatic Data Center, Asheville, NC, USA, 164 pp.  

2 Such simulations lack any human-caused changes in greenhouse gases or particulate pollution.

3 The period over which we have been monitoring atmospheric temperature from space.

4 Like the burning of fossil fuels.

5 Our fingerprint method has been successfully employed for the identification of human effects on surface and atmospheric temperature, upper ocean heat content, the height of the tropopause (the boundary between the troposphere and stratosphere), and atmospheric moisture over oceans.

6 As noted above, the signal is the latitude/altitude pattern of atmospheric temperature change.  

6 January 1979 to December 2012. The model results are an average of “human influence” simulations performed with 8 different CMIP-5 models. The y-axis shows atmospheric pressure (in hectoPascals).  

7 Which are referred to as “NAT” and “P1000” in our paper.

8 In other words, at the pattern of temperature change with latitude and altitude.

9 One of the two observational groups (Remote Sensing Systems in Santa Rosa) explored uncertainties in the
processing steps used to create the observations, and developed a set of four hundred plausible estimates of
observed atmospheric temperature change. We used this “ensemble of observations” in our detection study.

10 See, e.g., Santer, B.D., K.E. Taylor, T.M.L. Wigley, T.C. Johns, P.D. Jones, D.J. Karoly, J.F.B. Mitchell, A.H. Oort, J.E. Penner, V. Ramaswamy, M.D. Schwarzkopf, R.J. Stouffer, and S. Tett, 1996: A search for human influences on the thermal structure of the atmosphere. Nature, 382, 39-46.

11 The last 34 years. 

13 Santer, B.D., J.F. Painter, C.A. Mears, C. Doutriaux, P. Caldwell, J.M. Arblaster, P.J. Cameron-Smith, N.P. Gillett, P.J. Gleckler, J. Lanzante, J. Perlwitz, S. Solomon, P.A. Stott, K.E. Taylor, L. Terray, P.W. Thorne, M.F. Wehner, F.J. Wentz, T.M.L. Wigley, L.J. Wilcox, and C.-Z. Zou, 2013: Identifying human influences on atmospheric temperature. Proceedings of the National Academy of Sciences, 110, 26-33, doi: 10.1073/pnas.1210514109.

14 This analysis used digitally-filtered temperature data; the filtering highlighted temperature variability on timescales ranging from 5 to 20 years.

15 In the lower stratosphere, the size of modeled and observed decadal variability is (on average) very similar.

16 Particularly in tropics and Southern Hemisphere (see Fig. 2).

17 Note that these biases have relatively small impact on the S/N results presented here. This is because the searched-for fingerprint patterns are normalized – thus reducing the effect of biases in the size of modeled temperature changes.

MORE MUST READ TIDBITS: Kevin Trenberth on ocean heat content, changing trade winds, mechanism for heat to be carried down deeper in the ocean

Global warming is here to stay, whichever way you look at it

by Kevin Trenberth, University Corporation for Atmospheric Research, The Conversation, May 22, 2013

Has global warming stalled? This question is increasingly being asked because the local weather seems cool and wet, or because the global mean temperature is not increasing at its earlier rate or the long-term rate expected from climate model projections.

The answer depends a lot on what one means by “global warming.” For some it is equated to the “global mean temperature.” That keeps going up but also has ups and downs from year to year. More on that shortly.

Why should it go up? Well, because the planet is warming as a result of human activities. With increasing carbon dioxide and other heat-trapping greenhouse gases in the atmosphere, there is an imbalance in energy flows in and out of the top of the atmosphere: the greenhouse gases increasingly trap more radiation and hence create warming. “Warming” really means heating, and this can exhibit itself in many ways.

Rising surface temperatures are just one manifestation. Melting Arctic sea ice is another. So is melting of glaciers and other land ice that contribute to rising sea levels. Increasing the water cycle and invigorating storms is yet another. But most (more than 90%) of the energy imbalance goes into the ocean, and several analyses have now shown this. But even there, how much warms the upper layers of the ocean, as opposed to how much penetrates deeper into the ocean where it may not have much immediate influence, is a key issue.

The ups and downs of global temperature

My colleagues and I have just published a new analysis showing that in the past decade about 30% of the heat has been dumped at levels below 700 meters, where most previous analyses stop.

The first point is that this is fairly new; it is not there throughout the record. The cause of the shift is a particular change in winds, especially in the Pacific Ocean where the subtropical trade winds have become noticeably stronger, changing ocean currents and providing a mechanism for heat to be carried down into the ocean. This is associated with weather patterns in the Pacific, which are in turn related to the La Niña phase of the El Niño phenomenon.

The second point is that we have found distinctive variations in global warming with El Niño. A mini global warming, in the sense of a global temperature increase, occurs in the latter stages of an El Niño event, as heat comes out of the ocean and warms the atmosphere. The ocean’s temperature is also affected by volcanic eruptions, which also affect the perceptions of global warming.

Normal weather also interferes by generating clouds that reflect the sunshine, and there are fluctuations in the global energy imbalance from month to month. But these average out over a year or so.

Another prominent source of natural variability in the Earth’s energy imbalance is changes in the sun itself, seen most clearly as the sunspot cycle. From 2005 to 2010 the sun went into a quiet phase and the warming energy imbalance is estimated to have dropped by about 10 to 15%.

Some of the penetration of heat into the depths of the ocean is reversible, as it comes back in the next El Niño [whenever that is -- no signs of one for the rest of this year]. But a lot is not; instead it contributes to the overall warming of the deep ocean. This means less short-term warming at the surface, but at the expense of greater long-term warming, and faster sea level rise. So this has consequences.

Global warming is here to stay

Coming back to the global temperature record, one thing is clear. The past decade is by far the warmest on record. Human-induced global warming really kicked in during the 1970s, and warming has been pretty steady since then.

While the overall warming is about 0.16 °C per decade, there are three 10-year periods where there was a hiatus in warming, as the graph above shows, from 1977 to 1986, from 1987 to 1996, and from 2001 to 2012. But at each end of these periods there were big jumps. We find exactly the same sort of flat periods in climate model projections, lasting easily up to 15 years in length.

Focusing on the wiggles and ignoring the bigger picture of unabated warming is foolhardy, but an approach promoted by climate change deniers. Global sea level keeps marching up at a rate of more than 30 cm per century since 1992 (when global measurements via altimetry on satellites were made possible), and that is perhaps a better indicator that global warming continues unabated. Sea level rise comes from both the melting of land ice, thus adding more water to the ocean, plus the warming and thus expanding ocean itself.

Global warming is manifested in a number of ways, and there is a continuing radiative imbalance at the top of atmosphere. The current hiatus in surface warming is temporary, and global warming has not gone away.

Kevin Trenberth does not work for, consult to, own shares in or receive funding from any company or organisation that would benefit from this article, and has no relevant affiliations.


This article was originally published at The Conversation. Read the original article.

http://theconversation.com/global-warming-is-here-to-stay-whichever-way-you-look-at-it-14532