MIT Climate Change Conversation Report

Thank You

The MIT Climate Change Conversation Committee would like to thank the hundreds of students, faculty, staff, and MIT community members who shared their input during the year long conversation on how MIT can play a role in addressing the climate challenge.  The Committee submitted a report of final recommendations to MIT senior leadership in June 2015.  Archived materials from the conversation can be found on the website.

Over the summer months of 2015 the Conversation Leadership - Marty Schmidt, Provost, Vice President for Research Maria Zuber, MITEI Director Bob Armstrong, and Environmental Solutions Initiative Interim Director Susan Solomon – will review the report. A final set of recommendations will be presented to President Reif, who will announce a plan for community-wide MIT action on climate change in Fall 2015.

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Submitted June 2015

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Kerry Emanuel and Susan Solomon rebut Koonin's Wall Street Journal op-ed

by Dr. Kerry Emanuel and Dr. Susan Solomon, (Professors, Massachusetts Institute of Technology, Cambridge, MA), The Union of Concerned Scientists, October 16, 2014

Stephen Koonin’s recent Wall Street Journal op‐ed illustrates the importance of distinguishing scientific fundamentals from numerical details, and keeping the distinction between science and values clear in discussions of risk.  

Koonin notes several key scientific fundamentals. He does not deny that climate is changing, that human activities are at least partly responsible for it, or that policy formulation should take climate change into account. But the headline statement—that not enough is known about climate to warrant significant action given the risks—is a statement of values and does not follow from the scientific substance of the essay. The phrase in the essay’s title, “Settled Science,” repeated elsewhere, is often used by journalists and environmentalists, but we have yet to hear it used by an actual climate scientist. Although the first sentence refers to its use in “popular and policy discussions,” later in the essay Koonin argues that uncertainty “should not be confined to hushed sidebar conversations at academic conferences.”

This claim amazed us, because uncertainty is a major and perhaps the major focus of scientific research on climate change and on attempts to formulate sensible policy. In the Summary for Policymakers of the latest IPCC Assessment Report, the word uncertain or uncertainty appears 36 times, and graphs pertaining to climate projections have hefty uncertainty limits and error bars. It is hard to claim that uncertainty is being hushed up. “Settled Science” is a red herring when it comes to the actual practice and publication of climate science.

We are used to hearing that “climate is always changing” as a means of downplaying current climate change; rather like a murder defendant telling the judge that “people are always dying.” Climate changes on many time scales, and if that were not the case, there would be little basis for worrying about our own influence, because the evidence would point to a large intrinsic stability of the climate system. There is no significant doubt that the earth’s past climate has responded dramatically to relatively small changes in Earth’s energy balance in the past, such as changes in sunlight and its distribution with latitude, as well as to changes in atmospheric composition. This is hardly comforting. Koonin gets it wrong when he states that the impact of human activity appears comparable to natural intrinsic variability; in point of fact, many studies using independent data sets have demonstrated that human signals have clearly emerged from the noise on global and regional scales over the past fifty years. What is at issue here is not just the total global temperature change, but the rate at which we are changing the energy balance of our planet, which over the last half century has been far in excess of anything evident in paleo climate data for many thousands of years, at least.

Elsewhere, Koonin falls prey to some of the most common misconceptions about climate science. One of the most widely held is the idea that predictions of climate change rest solely on highly complex computer models. This is far from the case; basic physics and very simple models all show that increasing greenhouse gas concentrations lead to nontrivial warming. In 1906, the Swedish chemist Svante Arrhenius estimated that doubling CO₂concentrations would increase average global surface temperature by around 4 ^oC; his calculations were done with paper and pencil. If the computer had never been developed, climate science would still have identified the substantial risk incurred by changing by hundreds of percent the concentrations of long-lived greenhouse gases.  That is what we are on track to do within this century if current rates of growth of human greenhouse gas emissions continue.

Koonin states that the human impact on the greenhouse effect is a small percentage of the total greenhouse effect. While strictly correct, Koonin’s use of this information in his essay is deeply misleading. While the most important greenhouse gas in the atmosphere is water vapor, the residence time of a water molecule in the atmosphere is about two weeks. Global water vapor concentration therefore responds to changes in global temperature rather than forcing them. The water vapor greenhouse effect is a fast feedback driven by other changes in the system, as is universally recognized (going back at least to Arrhenius), and as Koonin acknowledges later in his essay. By contrast, a portion of the human addition of CO₂ to our atmosphere lasts hundreds to thousands of years; thus on such time scales it is properly considered a forcing. Despite a nominally small contribution to the total planetary greenhouse effect, it is well established that eliminating all atmospheric CO₂ would drop the Earth’s mean surface temperature to below freezing, demonstrating its key role; doubling its concentration can similarly be expected to influence our climate.

The hiatus in the upward trend of surface temperature is a fascinating and important puzzle for climate science, and is not entirely consistent with our present understanding of natural variability. Uncertainties in forcing by changes in atmospheric pollution and volcanic particles may also play an important role. Whole workshops are devoted to this issue. In dealing with it, one must be conscious of the fact that roughly 90% of the planetary energy imbalance caused by upward trends in long-lived greenhouse gases is used to heat the oceans, rather than the atmosphere, and the best available measurements show that ocean heat content has continued its inexorable climb even while the atmospheric temperature has leveled off. It does not take much heat exchange between the oceans and atmosphere to cause large swings in the temperature of the latter. We do not fully understand the natural causes of such exchanges.

Finally we come to what we regard as the most egregious part of Koonin’s essay; namely, his implication that scientific uncertainties dictate that we do nothing. Outside the radical environmental movement and lesser media outlets, no one is claiming that uncertainty in climate projections is small. In spite of their flaws, projections based partially on the ensemble of complex climate models run by many groups internationally is well grounded in basic physics going back to the time of Arrhenius, and represent civilization’s current best shot at the problem; anything else is mere conjecture. These projections portray time-evolving probability distributions of climate variables such as precipitation and global mean surface temperature, which experts in risk analysis convert to probability distributions of various kinds of risk. These risk analyses are taken very seriously by business enterprises (e.g., the reinsurance industry) and many government organizations (e.g., the Department of Defense; the city of New York) and are used constructively in planning.

While it is challenging, many citizens are beginning to understand how to think about risk and uncertainties in climate change too. The median CO₂-doubling temperature increase of about 2.5 ^oC already poses serious risks, while the not-so-improbable higher tail of the distribution would likely be very serious, even catastrophic, for civilization. And if nothing is done to curb emissions, we are on our way to tripling CO₂ by the end of this century, and quadrupling it not long after. Even low-end estimates of the climate response to such forcing entail very serious risk. Barring major improvements in technology for extracting CO₂ from the atmosphere and sequestering it, decisions on whether and how much to reduce emissions cannot be postponed owing to the very long residence time of anthropogenic CO₂ in the atmosphere.

Koonin’s point that decisions on how to deal with this important problem should be made democratically seems obvious to us, but the events of the last decade or so show that the main threat to democratic decision making is not overweening climate scientists (yes, there are some!) but rather wealthy interests vested in the status quo, that seem to exercise undue influence in today’s politics. The rising oligarchy naturally tries, as a means of diversion, to alarm the public with the specter of a technocracy.

Reasonable people may disagree about the best course of action given an uncertain but potentially very serious threat. It should be up to citizens to decide how much to spend now to mitigate such a threat. But ignoring or slanting the risks does a disservice to science and the public.

About the authors: 

Dr. Kerry Emanuel is the Cecil and Ida Green professor of atmospheric science at the Massachusetts Institute of Technology, where he has been on the faculty since 1981, after spending three years on the faculty of UCLA. He is a co-director of MIT’s Lorenz Center, a climate think tank devoted to basic, curiosity-driven climate research. 

Dr. Susan Solomon is the Ellen Swallow Richards Professor of atmospheric chemistry and climate science at the Massachusetts Institute of Technology and the Founding Director of the MIT Environmental Solutions Initiative. Prior to that, she was a scientist at NOAA in Boulder, Colorado, from 1981-2011, and an adjunct professor at the University of Colorado.

http://blog.ucsusa.org/a-response-to-stephen-koonins-call-to-inaction-685

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.

Benjamin D. Santer et al., "Separating signal and noise in atmospheric temperature changes: The importance of timescale," J. Geophys. Res., 2011, in press

Journal of Geophysical Research, in press; doi: 10.1029/2011JD016263

Separating signal and noise in atmospheric temperature changes: The importance of timescale

Benjamin D. Santer, Carl A. Mears, C. Doutriaux, Peter Martin Caldwell, Peter J. Gleckler, Tom M.L. Wigley, Susan Solomon, Nathan Gillett, Detelina P. Ivanova, Thomas R. Karl, John R. Lanzante, Gerald A. Meehl, Peter A. Stott, Karl E. Taylor, Peter Thorne, Michael F. Wehner and Frank J. Wentz

Abstract

We compare global-scale changes in satellite estimates of the temperature of the lower troposphere (TLT) with model simulations of forced and unforced TLT changes. While previous work has focused on a single period of record, we select analysis timescales ranging from 10 to 32 years, and then compare all possible observed TLT trends on each timescale with corresponding multi-model distributions of forced and unforced trends. We use observed estimates of the signal component of TLT changes and model estimates of climate noise to calculate timescale-dependent signal-to-noise ratios (S/N). These ratios are small (less than 1) on the 10-year timescale, increasing to more than 3.9 for 32-year trends. This large change in S/N is primarily due to a decrease in the amplitude of internally generated variability with increasing trend length. Because of the pronounced effect of interannual noise on decadal trends, a multi-model ensemble of anthropogenically-forced simulations displays many 10-year periods with little warming. A single decade of observational TLT data is therefore inadequate for identifying a slowly evolving anthropogenic warming signal. Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature. 

Key points:

• Models run with human forcing can produce 10-year periods with little warming
• S/N ratios for tropospheric temp. are ~1 for 10-yr trends, ~4 for 32-yr trends
• Trends >17 yrs are required for identifying human effects on tropospheric temp.

Received 19 May 2011; accepted 21 August 2011. 

Citation: Santer, B. D., et al. (2011), Separating Signal and Noise in Atmospheric Temperature Changes: The Importance of Timescale, J. Geophys. Res., doi:10.1029/2011JD016263, in press.

http://www.agu.org/pubs/crossref/pip/2011JD016263.shtml

"Early onset of significant local warming in low latitude countries," I. Mahlstein, R. Knutti, S. Solomon & R. W. Portmann, Environmental Research Letters, 6 (2011) 034009; doi: 10.1088/1748-9326/6/3/034009

Environmental Research Letters, 6 (2011) 034009; doi: 10.1088/1748-9326/6/3/034009

Early onset of significant local warming in low latitude countries

I. Mahlstein^1,3, R. Knutti¹, S. Solomon² and R. W. Portmann²

Show affiliations

Abstract

The Earth is warming on average, and most of the global warming of the past half-century can very likely be attributed to human influence. But the climate in particular locations is much more variable, raising the question of where and when local changes could become perceptible enough to be obvious to people in the form of local warming that exceeds interannual variability; indeed only a few studies have addressed the significance of local signals relative to variability. It is well known that the largest total warming is expected to occur in high latitudes, but high latitudes are also subject to the largest variability, delaying the emergence of significant changes there. Here we show that due to the small temperature variability from one year to another, the earliest emergence of significant warming occurs in the summer season in low latitude countries (≈25° S – 25° N). We also show that a local warming signal that exceeds past variability is emerging at present, or will likely emerge in the next two decades, in many tropical countries. Further, for most countries worldwide, a mean global warming of 1 °C is sufficient for a significant temperature change, which is less than the total warming projected for any economically plausible emission scenario. The most strongly affected countries emit small amounts of CO₂ per capita and have therefore contributed little to the changes in climate that they are beginning to experience.

http://iopscience.iop.org/1748-9326/6/3/034009

Real Climate: The Wisdom of Solomon

The wisdom of Solomon

Filed under:  Climate Science — gavin @ 29 January 2010 

 

A quick post for commentary on the new Solomon et al paper in Science Express. We’ll try and get around to discussing this over the weekend, but in the meantime I’ve moved some comments over. There is some commentary on this at DotEarth, and some media reports on the story – some good, some not so good. It seems like a topic that is ripe for confusion, and so here are a few quick clarifications that are worth making.
First of all, this is a paper about internal variability of the climate system in the last decade, not on additional factors that drive climate. Second, this is a discussion about stratospheric water vapour (10–15 km above the surface), not water vapour in general. Stratospheric water vapour comes from two sources – the uplift of tropospheric water through the very cold tropical tropopause (both as vapour and as condensate), and the oxidation of methane in the upper stratosphere (CH4+2O2 –> CO2 + 2H2O; NB: this is just a schematic, the actual chemical pathways are more complicated). There isn’t very much of it (between 3 and 6 ppmv), and so small changes (~0.5 ppmv) are noticeable.

The decreases seen in this study are in the lower stratosphere and are likely dominated by a change in the flux of water through the tropopause. A change in stratospheric water vapour because of the increase in methane over the industrial period would be a forcing of the climate (and is one of the indirect effects of methane we discussed last year), but a change in the tropopause flux is a response to other factors in the climate system. These might include El Nino–La Nina events, increases in Asian aerosols, or solar impacts on near-tropopause ozone – but this is not addressed in the paper and will take a little more work to figure out.

The study includes an estimate of the effect of the observed stratospheric water decadal decrease by calculating the radiation flux with and without the change, and comparing this to the increase in CO2 forcing over the same period. This implicitly assumes that the change can be regarded as a forcing. However, whether that is an appropriate calculation or not needs some careful consideration. Finally, no-one has yet looked at whether climate models (which have plenty of decadal variability too) have phenomena that resemble these observations that might provide some insight into the causes.

Link: http://www.realclimate.org/index.php/archives/2010/01/the-wisdom-of-solomon/

Susan Solomon: Water vapor caused one-third of global warming in 1990s

Water vapour caused one-third of global warming in 1990s, study reveals

Experts say their research does not undermine the scientific consensus on man-made climate change, but call for 'closer examination' of the way computer models consider water vapour

• by David Adam, environment correspondent, The Guardian, Friday 29 January 2010

A 10% drop in water vapour, 10 miles up has had an effect on global warming over the last 10 years, scientists say. Photograph: Getty

Scientists have underestimated the role that water vapour plays in determining global temperature changes, according to a new study that could fuel further attacks on the science of climate change.

The research, led by one of the world's top climate scientists, suggests that almost one-third of the global warming recorded during the 1990s was due to an increase in water vapour in the high atmosphere, not human emissions of greenhouse gases. A subsequent decline in water vapour after 2000 could explain a recent slowdown in global temperature rise, the scientists add.

The experts say their research does not undermine the scientific consensus that emissions of greenhouse gases from human activity drive global warming, but they call for "closer examination" of the way climate computer models consider water vapour.

The new research comes at a difficult time for climate scientists, who have been forced to defend their predictions in the face of an embarrassing mistake in the 2007 report of the Intergovernmental Panel on Climate Change (IPCC), which included false claims that Himalayan glaciers could melt away by 2035. There has also been heavy criticism over the way climate scientists at the University of East Anglia apparently tried to prevent the release of data requested under Freedom of Information laws.

The new research, led by Susan Solomon, at the US National Oceanic and Atmospheric Administration, who co-chaired the 2007 IPCC report on the science of global warming, is published today in the journal Science, one of the most respected in the world.

Solomon said the new finding does not challenge the conclusion that human activity drives climate change. "Not to my mind it doesn't," she said. "It shows that we shouldn't over-interpret the results from a few years one way or another."

She would not comment on the mistake in the IPCC report -- which was published in a separate section on likely impacts -- or on calls for Rajendra Pachauri, the IPCC chairman, to step down.

"What I will say, is that this [new study] shows there are climate scientists round the world who are trying very hard to understand and to explain to people openly and honestly what has happened over the last decade."

The new study analysed water vapour in the stratosphere, about 10 miles up, where it acts as a potent greenhouse gas and traps heat at the Earth's surface.

Satellite measurements were used to show that water vapour levels in the stratosphere have dropped about 10% since 2000. When the scientists fed this change into a climate model, they found it could have reduced, by about 25% over the last decade, the amount of warming expected to be caused by carbon dioxide and other greenhouse gases.

They conclude: "The decline in stratospheric water vapour after 2000 should be expected to have significantly contributed to the flattening of the global warming trend in the last decade."

Solomon said: "We call this the 10, 10, 10 problem. A 10% drop in water vapour, 10 miles up has had an effect on global warming over the last 10 years." Until now, scientists have struggled to explain the temperature slowdown in the years since 2000, a problem climate sceptics have exploited.

The scientists also looked at the earlier period, from 1980 to 2000, though cautioned this was based on observations of the atmosphere made by a single weather balloon. They found likely increases in water vapour in the stratosphere, enough to enhance the rate of global warming by about 30% above what would have been expected.

"These findings show that stratospheric water vapour represents an important driver of decadal global surface climate change," the scientists say. They say it should lead to a "closer examination of the representation of stratospheric water vapour changes in climate models."

Solomon said it was not clear why the water vapour levels had swung up and down, but suggested it could be down to changes in sea surface temperature, which drives convection currents and can move air around in the high atmosphere.

She said it was not clear if the water vapour decrease after 2000 reflects a natural shift, or if it was a consequence of a warming world. If the latter is true, then more warming could see greater decreases in water vapour, acting as a negative feedback to apply the brakes on future temperature rise.

Link:  http://www.guardian.co.uk/environment/2010/jan/29/water-vapour-climate-change

S. Solomon et al., 10% decrease in water vapor in the stratosphere over the last 10 years has slowed Earth’s warming trends, researchers say

Ten percent decrease water vapor in the stratosphere slows Earth’s warming trends, researchers say

by Sindya N. Bhandoo, New York Times, January 28, 2010 

A decrease in water vapor concentrations in parts of the middle atmosphere has contributed to a slowing of Earth’s warming, researchers are reporting. The finding, they said, offers part of the explanation for a string of years with relatively stable global surface temperatures.

Despite the decrease in water vapor, the study’s authors said, the overall trend is still toward a warming climate, primarily caused by a buildup in emissions of carbon dioxide and other heat-trapping gases from human sources.

“This doesn’t alter the fundamental conclusion that the world has warmed and that most of that warming has to do with greenhouse gas emissions caused by man," said Susan Solomon, a climate scientist at the National Oceanic and Atmospheric Administration and the lead author of the report, which appears in the January 29, 2010, issue of the journal Science.

Water vapor, a potent heat-trapping gas, absorbs sunlight and re-emits heat into Earth’s atmosphere. Its concentrations in the stratosphere, the second of three layers in the atmosphere, appear to have decreased in the last 10 years, according to the study.

This has slowed the rate of Earth’s warming by about 25 percent, Dr. Solomon said.

“We use the 10-10-10 to describe it,” she said. “That is, a 10 percent change in water vapor, 10 miles above our head, over the past 10 years.”

The study also found that from 1980 to 2000, an increase in water vapor sped the rate of warming — the result of an increase in emissions of methane, another greenhouse gas, during the industrial period. Methane, when oxidized, produces water vapor. Why a decrease in water vapor has occurred in the last 10 years is still unknown.

Dr. Solomon emphasized that the study focused on the atmosphere’s middle layer, not to be confused with the troposphere, Earth’s first layer. It has been known for years that water vapor in the troposphere amplifies the effect of greenhouse gas emissions.

Some climate skeptics have claimed that a spate of years with relatively stable temperatures indicates that the threat of global warming has been overblown.

Last week, the National Aeronautics and Space Administration released figures indicating that the decade ending in 2009 was the warmest on record.

Link:  http://www.nytimes.com/2010/01/29/science/earth/29vapor.html

S. Solomon et al., Science, Contributions of stratospheric water vapor to decadal changes in the rate of global warming

Science, published online January 28, 2010; DOI: 10.1126/science.1182488

Contributions of stratospheric water vapor to decadal changes in the rate of global warming

Susan Solomon,¹ Karen Rosenlof,¹ Robert Portmann,¹ John Daniel,¹ Sean Davis,^1,2 Todd Sanford,^1,2 and Gian-Kasper Plattner<sup>3

1</sup> NOAA Earth System Research Laboratory, Chemical Sciences Division, Boulder, CO, U.S.A.
² Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, U.S.A.
³ Climate and Environmental Physics, Physics Institute, University of Bern, Sidlerstrasse 5, 3012 Bern, Switzerland.  


Abstract

Stratospheric water vapor concentrations decreased by about 10% after the year 2000. Here, we show that this acted to slow the rate of increase in global surface temperature over 2000-2009 by about 25% compared to that which would have occurred due only to carbon dioxide and other greenhouse gases. More limited data suggest that stratospheric water vapor probably increased between 1980 and 2000, which would have enhanced the decadal rate of surface warming during the 1990s by about 30% compared to estimates neglecting this change. These findings show that stratospheric water vapor represents an important driver of decadal global surface climate change.

Link:  http://www.sciencemag.org/cgi/content/abstract/science.1182488