Climate Science Glossary

Term Lookup

Enter a term in the search box to find its definition.

Settings

Use the controls in the far right panel to increase or decrease the number of terms automatically displayed (or to completely turn that feature off).

Term Lookup

Settings


All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

Home Arguments Software Resources Comments The Consensus Project Translations About Support

Twitter Facebook YouTube Mastodon MeWe

RSS Posts RSS Comments Email Subscribe


Climate's changed before
It's the sun
It's not bad
There is no consensus
It's cooling
Models are unreliable
Temp record is unreliable
Animals and plants can adapt
It hasn't warmed since 1998
Antarctica is gaining ice
View All Arguments...



Username
Password
New? Register here
Forgot your password?

Latest Posts

Archives

Empirically observed fingerprints of anthropogenic global warming

Posted on 4 September 2010 by dana1981

Fundamental physics and global climate models both make testable predictions as to how the global climate should change in response to anthropogenic warming. Almost universally, empirical observations confirm that these 'fingerprints' of anthropogenic global warming are present.

Surface Temperature Change

Back in 1988, NASA's James Hansen made some of the first projections of future global warming with a global climate model (Hansen 1988). He created 3 scenarios which he called Scenarios A, B, and C which used various possible future greenhouse gas emissions levels. Scenario A used a model with accelerating greenhouse gas emissions, Scenario B had linearly increasing emissions, and Scenario C had emissions leveling off after the year 2000. None of these models ended up matching greenhouse gas emissions exactly right, but the radiative forcing (energy imbalance) in Scenario B was closest, too high by about 10% as of 2009. Additionally, the climate sensitivity in Hansen's 1988 model (4.2°C global warming for a doubling of atmospheric CO2) was a bit higher than today's best estimate (3°C warming for CO2 doubling).

Hansen's Scenario B projected a global warming trend from 1984-2009 of 0.26°C per decade. The actual trend as measured by surface temperature stations over that period was about 0.2°C per decade. When corrected for the 10% smaller radiative forcing than Scenario B and the higher climate sensitivity in Hansen's models, his study projected the global warming over the ensuing 25 years almost perfectly.

Meehl et al. (2004) took a different approach. Instead of projecting future surface temperature change, they used climate models to attempt to attribute past temperature changes in a method known as 'hindcasting' (as opposed to forecasting). In their study, Meehl et al. show that natural forcings cannot account for the increase in global temperatures in the second half of the 20th century, and that models using both natural and anthropogenic forcings model the temperature change over the 20th century most accurately.

"The late-twentieth-century warming can only be reproduced in the model with anthropogenic forcing (mainly GHGs), while the early twentieth-century warming is mainly caused by natural forcing in the model (mainly solar)."

Meehl 2004 figure

Figure 1: Anthropogenic plus natural vs. just natural radiative forcing temperature change vs. observed global surface temperature increase (Meehl 2004)

Stott et al. (2003) took yet another approach, examining surface temperature changes region-by-region across the planet and comparing them to how climate models predicted they should have changed. Stott found that regional temperature changes could also be traced back to anthropogenic global warming.

"The causes of twentieth century temperature change in six separate land areas of the Earth have been determined by carrying out a series of optimal detection analyses. The warming effects of increasing greenhouse gas concentrations have been detected in all the regions examined, including North America and Europe….Our results show significant anthropogenic warming trends in all the continental regions analyzed. In all these regions, greenhouse gases are estimated to have caused generally increasing warming as the century progressed, balanced to a greater or lesser degree, depending on the region, by cooling from sulfate aerosols in the middle of the century."

Stott 2003.jpg

More warming at night than day

Climate models predict that as a consequence of anthropogenic global warming, the planet should warm more at night than during the day. This is also known as a decreasing diurnal temperature range (DTR – the difference between minimum and maximum daily temperature). Braganza et al. (2004) investigated the changes in DTR over the past 50 years and concluded as follows:

"Observed DTR over land shows a large negative trend of ~0.4°C over the last 50 years that is very unlikely to have occurred due to internal variability. This trend is due to larger increases in minimum temperatures (~0.9°C) than maximum temperatures (~0.6°C) over the same period. Analysis of trends in DTR over the last century from five coupled climate models shows that simulated trends in DTR due to anthropogenic forcing are much smaller than observed. This difference is attributable to larger than observed changes in maximum temperatures in four of the five models analysed here, a result consistent with previous modelling studies."

Essentially Braganza et al. found that that while DTR is decreasing as expected by climate models, it’s decreasing more than they predicted because daytime temperatures are increasing less than they predict, possibly because the models omit changes in the Earth’s reflectivity from factors like cloudcover and land use change. Here you can see the observed changes in maximum, minimum, mean global temperature, and DTR vs. predictions by the four climate models used in the study.

Braganza.jpg

Figure 3: Observed vs. modeled temperature trends (Braganza 2004)

Stratospheric Temperature Change

As the lower atmosphere warms due to an enhanced greenhouse effect, the upper atmosphere is expected to cool as a consequence. The simple way to think about this is that greenhouse gases are trapping heat in the lower atmosphere. Since less heat is released into the upper atmosphere (starting with the stratosphere), it cools.

Jones et al. (2003) investigated the changes in temperature over the past 4 decades at both the near surface (troposphere) and stratosphere layers, and compare them to changes predicted by a coupled atmosphere/ocean general circulation model, HadCM3. They concluded as follows.

"Our results strengthen the case for an anthropogenic influence on climate. Unlike previous studies we attribute observed decadal-mean temperature changes both to anthropogenic emissions, and changes in stratospheric volcanic aerosols. The temperature response to change in solar irradiance is also detected but with a lower confidence than the other forcings."

Tropopause Height

The tropopause is the atmospheric boundary between the troposphere and the stratosphere. Observations indicate that the tropopause height has increased several hundred meters over the past 3 decades. Santer et al. (2003) investigated the causes of this change and concluded as follows.

"Comparable increases are evident in climate model experiments. The latter show that human-induced changes in ozone and well-mixed greenhouse gases account for ~80% of the simulated rise in tropopause height over 1979–1999. Their primary contributions are through cooling of the stratosphere (caused by ozone) and warming of the troposphere (caused by well-mixed greenhouse gases). A model predicted fingerprint of tropopause height changes is statistically detectable in two different observational (“reanalysis”) data sets. This positive detection result allows us to attribute overall tropopause height changes to a combination of anthropogenic and natural external forcings, with the anthropogenic component predominating."

Santer 2003.jpg

Figure 4: Changes in temperature and tropopause height in response to various radiative forcings (Santer 2003)

Upper Atmosphere Temperature Change

The layers above the stratosphere are expected to cool as a result of global warming as well, for similar reasons (less heat reaching higher levels as it’s trapped in the lower atmosphere). Jarvis et al. (1998) investigated changes in the thermosphere and ionosphere in 1998 and concluded as follows.

"The estimated long-term decrease in altitude is of a similar order of magnitude to that which has been predicted to result in the thermosphere from anthropogenic change related to greenhouse gases."

Laštovi?ka et al. (2006) arrived at a similar conclusion.

"The upper atmosphere is generally cooling and contracting, and related changes in chemical composition are affecting the ionosphere. The dominant driver of these trends is increasing greenhouse forcing, although there may be contributions from anthropogenic changes of the ozone layer and long-term increase of geomagnetic activity throughout the 20th century. Thus, the anthropogenic emissions of greenhouse gases influence the atmosphere at nearly all altitudes between ground and space, affecting not only life on the surface but also the space-based technological systems on which we increasingly rely."

Laštovi?ka 2006.gif

Figure 5: Atmospheric temperature and Ionospheric electron density vs. Altitude (Laštovi?ka 2006)

Ocean Heat Content

Ocean heat content has increased significantly over the past 40 years. In fact, approximately 84% of the total heating of the Earth system over that period has gone into warming the oceans. Barnett et al. (2005) investigated the cause of this warming signal, and concluded as follows.

"[the increase in ocean heat content] cannot be explained by natural internal climate variability or solar and volcanic forcing, but is well simulated by two anthropogenically forced climate models. We conclude that it is of human origin, a conclusion robust to observational sampling and model differences. Changes in advection combine with surface forcing to give the overall warming pattern. The implications of this study suggest that society needs to seriously consider model predictions of future climate change."

Barnett 2007.gif

Figure 6: Modeled vs. Observed Ocean Temperature Changes

Sea Level Pressure

Gillett et al. (2003) compared observed changes in sea level pressure with those predicted by four coupled ocean–atmosphere climate models and concluded as follows.

"Here we detect an influence of anthropogenic greenhouse gases and sulphate aerosols in observations of winter sea-level pressure (December to February), using combined simulations from four climate models. We find increases in sea-level pressure over the subtropical North Atlantic Ocean, southern Europe and North Africa, and decreases in the polar regions and the North Pacific Ocean, in response to human influence….Overall, we find that anthropogenic greenhouse gases and sulphate aerosols have had a detectable influence on sea-level pressure over the second half of the twentieth century: this represents evidence of human influence on climate independent of measurements of temperature change."

Precipitation

Zhang et al. (2007) showed that models using natural + anthropogenic forcings do a much better job of matching observed precipitation trends than either natural or anthropogenic alone. The correlation with natural forcings alone is extremely weak - only 0.02. With anthropogenic alone is 0.69, and with both combined is 0.83 over the past 75 years.

"We show that anthropogenic forcing has had a detectable influence on observed changes in average precipitation within latitudinal bands, and that these changes cannot be explained by internal climate variability or natural forcing. We estimate that anthropogenic forcing contributed significantly to observed increases in precipitation in the Northern Hemisphere mid-latitudes, drying in the Northern Hemisphere subtropics and tropics, and moistening in the Southern Hemisphere subtropics and deep tropics. The observed changes, which are larger than estimated from model simulations, may have already had significant effects on ecosystems, agriculture and human health in regions that are sensitive to changes in precipitation"

Infrared Radiation

Increase in downward longwave radiation

Anthropogenic global warming is caused by an increase in the amount of downward longwave infrared radiation coming from greenhouse gases in the atmosphere. Philipona et al. (2004) measured the changes and trends of radiative fluxes at the surface and their relation to greenhouse gas increases and temperature and humidity changes measured from 1995 to 2002 at eight stations of the Alpine Surface Radiation Budget (ASRB) network. They concluded as follows.

"The resulting uniform increase of longwave downward radiation manifests radiative forcing that is induced by greenhouse gas concentrations and water vapor feedback, and proves the "theory" of greenhouse warming with direct observations."

Evans et al. (2006) took it a step further, performing an analysis of high resolution specral data which allowed them to quantitatively attribute the increase in downward radiation to each of several greenhouse gases. The study went as far as to conclude,

"This experimental data should effectively end the argument by skeptics that no experimental evidence exists for the connection between greenhouse gas increases in the atmosphere and global warming."

Decrease in upward longwave radiation

As the concentration of greenhouse gases in the atmosphere increases, we expect to see less infrared radiation escaping at the top of the atmosphere. Satellite observations have confirmed that the decrease in upward longwave radiation matches well with model predictions, including in Harries 2001, Griggs 2004, and Chen 2007, the latter of which concluded:

"Changing spectral signatures in CH4, CO2, and H2O are observed, with the difference signal in the CO2 matching well between observations and modelled spectra."

Increased greenhouse effect -  models vs observations
Figure 7: Increased greenhouse effect from 1970 to 2006. Black line is satellite observations. Red line is modeled results (Chen 2007)

Increased top of the atmosphere energy imbalance

This increase in downward and decrease in upward infrared radiation is expected to create an energy imbalance. Trenberth et al. (2009) used satellite data to measure the Earth's energy balance at the top of the atmosphere (TOA) and found that the net imbalance was 0.9 Watts per square meter. (Wm-2) This figure is consistent with the calculations in Hansen et al. 2005 using ocean heat data.

"The predicted energy imbalance due to increasing greenhouse gases has grown to 0.85 ± 0.15 W/m2"

Hansen 2005.jpg

Figure 8: TOA Radiation (Hansen 2005)

Murphy et al. (2009) obtained a similar result.

"About 20% of the integrated positive forcing by greenhouse gases and solar radiation since 1950 has been radiated to space. Only about 10% of the positive forcing (about 1/3 of the net forcing) has gone into heating the Earth, almost all into the oceans. About 20% of the positive forcing has been balanced by volcanic aerosols, and the remaining 50% is mainly attributable to tropospheric aerosols. After accounting for the measured terms, the residual forcing between 1970 and 2000 due to direct and indirect forcing by aerosols as well as semidirect forcing from greenhouse gases and any unknown mechanism can be estimated as 1.1 ± 0.4 Wm-2."

Murphy 2009

Figure 8: Cumulative energy budget for the Earth since 1950 (Murphy 2009)

This is an impressively wide variety of global and regional climate change observations strongly matching the changes predicted by climate models and providing clear fingerprints of human-caused climate change.

 NOTE: This post is the Advanced version (written by dana1981) of the skeptic argument "It's not us". This means there are now 3 levels of rebuttals addressing the skeptic argument "humans aren't causing global warming":



If other climate bloggers are interested in allowing their existing articles to be used as advanced rebuttals to skeptic arguments, please contact me.

0 0

Printable Version  |  Link to this page

Comments

Comments 1 to 13:

  1. Was the similarity between the symbols used to delineate the level of the rebuttal and the standard symbols for ski trail difficulty deliberate? Good post, by the way. Even at this level, the site does a good job of making things clear for the non-scientist (such as, say, myself).
    0 0
  2. link to Zhang et al. (2007) has an extra space at the end.
    0 0
  3. Composer - thanks and yes, it was deliberate. apeescape - thanks, I fixed the link.
    0 0
  4. Great post, thanks! How about carbon isotope ratios showing that the increased carbon is anthropogenic?
    0 0
  5. Thanks Rick. That's covered in the human CO2 emissions rebuttal. It's a cause of the anthropogenic warming as opposed to a consequence of it.
    0 0
  6. forget the model simulations... are there any direct experimental evidence for 'greenhouse theory'?
    0 0
  7. Gnbatt @ 6 - How do we know more CO2 is causing warming? and On the Absorption and Radiation of Heat by Gases and Vapours, and on the Physical Connection of Radiation, Absorption, and Conduction
    0 0
  8. If by 'greenhouse theory' you mean anthropogenic global warming, that was the entire point of this post. The empirical observational data is matching what's predicted by the models. That's experimental evidence.
    0 0
  9. Dana, Good job. This is a nice and useful post in general, though I would be careful (for this and future posts that Skeptical Science does) not to oversell some of these points and equate ‘consistency’ with a ‘fingerprint.’ Consistencies do not always lead to any explanatory or predictive power, and this could very well be the case with the simulations of the time evolution of global mean temperature anomalies. The solid agreement between model simulations of temperature change (e.g., the Meehl graph) and observations is curious given the strong uncertainties in radiative forcing which ranges from ~0.6 to 2.4 W/m2) (see AR4 Figure 2.20), feedbacks, ocean heat content uptake, and the model ensemble members themselves (e.g., Schwartz et al 2007 Nature commentary; Knutti 2008, GRL). Indeed, the models probably do not sample the full range of uncertainty which is in part owing to the neglect of aerosol indirect effects or possible anti-correlations across the models between forcing and sensitivity, and more detailed inclusion of aerosol physics could very well lead to inconsistencies in model-observations. This should not be surprising or problematic, since formal attribution is about spatio-temporal patterns rather than the agreement in model-observation time series of temperature change. This can be done even after subtracting off the global mean temperature anomaly or ‘tuning’ the amplitudes of a perturbation (since we don’t know the sensitivity). For instance, we would generally expect the response to a volcanic eruption to occur after the eruption. In space, we might expect the response to short-lived aerosols to be focused over areas with large changes in sulphate emissions. These patterns should be pretty robust because they are very strongly constrained by the basic characteristics of the forcings and the climate system. As another example, the increase in downward infrared radiation to the surface is not necessarily unique to increased greenhouse gases, nor is it necessarily inevitable that more CO2 should directly make the atmosphere a better emitter to the surface. This would be the case if the boundary layer was moist enough to already radiate close to a black body at its temperature, which is nearly the case in the tropics. The CO2 still makes it warmer by reducing the outgoing flow of radiation and the increased temperature of the troposphere increases all the energy fluxes into the surface (the sun could do this too), not just the radiative fluxes. Water vapor really complicates getting a clean CO2 spectrum of downwelling radiation, and the best place to do this would probably be a clear night in the Antarctic winter, but this is not too relevant to the enhanced greenhouse effect anyway. I don’t see how Philipona et al (2004) really understood this at the time. Chris
    0 0
  10. Fair point Chris. I started out writing about correct climate model predictions, but most of them turned out to be anthropogenic signals, so I switched gears. But you're right that several of these are *consistent with* AGW rather than "fingerprints". I'll adjust the rebuttal accordingly.
    0 0
  11. gnbatt @6 There is something you and all commentators on science and epistemology are going to have to learn about computer simulations and math modeling. And that is that it is ONLY abstract models that can determine cause and effect - NOT experience. And this is a fact for ALL phenomena, not just climate change. Whether those models are written explicitly in a computer simulation or we merely keep them in our heads, ALL experience requires an interpretation for us to be able to say "this caused that". If we were discussing, for example, the hypothesis of whether non-human aliens are the best explanation for many UFOs and USOs, or whether Bigfoot is the best CAUSE for the observed effects of large footprints found in forests and loud screams heard and for many spontaneous sightings by hunters and motorists, you can sure bet there'd be those who totally ignore the value of direct experimental observed evidence. They'd steer the entire conversation off into the direction of debating the abstract interpretation of these events. It is not, and never has been, "direct experimental or experiential" evidence that proves anything, especially cause and effect. Because the entire concept of PROOF, itself, is abstract. Direct experience is merely sets of atoms. The difference between lazy mindless speculation about cause-and-effect versus the difficult task of writing down one's model mathematically and encoding it into a computer is that the computer simulations and mathematical modeling actually require hard work and discipline, and are INFINITELY better at coming up with theories of cause-and-effect that are LOGICALLY CONSISTENT, not just internally, with themselves, but with all other cause-and-effect theories on events outside climate theory. Example: One CAN say that a human, dressed up in a gorilla suit and placed herself in the middle of a forest in the dead of winter so that a random traveller or hunter would catch sight of them, is the cause of a Bigfoot sighting. For this theory of cause-and-effect to be true, one would have to be consistent accept the theory that every event caught on security surveillance camera is just a staged event, because it is "too outrageous" to believe that anyone could commit a crime and risk arrest. To be completely objective on interpreting events, we would need artificial-intelligent robots, with vision and hearing capabilities, interpret events. We all know how difficult and expensive THAT is. It has taken YEARS of research and BILLIONS of dollars to get robots to categorize all those millions of pixels as separate objects. Since we don't have the money and means to pay robots with AI to interpret outside reality for us, we will have to rely on humans as the interface. In the case of the climate, that means climate scientists. But, just like it would be the robot brain that does the abstract work of turning all those pixels it sees and soundwaves it senses into a theory of cause and effect (if I walk here, that will cause me to bump into this object), the climate scientists and programmers HAVE to do the next best thing by mathematicallly modeling events and fitting it to data in a manner that is logically consistent with the way we model all other events we observe. Deniers are simply too <-snipped-> even to acknowledge that they are doing abstract modeling whenever they hypothesize an alternative cause for current global warming.
    0 0
    Moderator Response: Please refrain from overt insults. And please do not use all caps for emphasis. Use italic or bold.
  12. Link to Meehl, 2004 paper (source of graphic) is now broken.  I briefly looked for it on the CSIRO site without success.  

    http://cawcr.gov.au/bmrc/clfor/cfstaff/jma/meehl_additivity.pdf

    0 0
  13. https://journals.ametsoc.org/doi/10.1175/1520-0442%282004%29017%3C3721%3ACONAAF%3E2.0.CO%3B2#

    0 0
    Moderator Response:

    [DB] Thanks for that.  I rebuilt the links and images and all should work now.

You need to be logged in to post a comment. Login via the left margin or if you're new, register here.



The Consensus Project Website

THE ESCALATOR

(free to republish)


© Copyright 2024 John Cook
Home | Translations | About Us | Privacy | Contact Us