Science & Education

, Volume 24, Issue 3, pp 299–318 | Cite as

Climate Consensus and ‘Misinformation’: A Rejoinder to Agnotology, Scientific Consensus, and the Teaching and Learning of Climate Change

  • David R. Legates
  • Willie Soon
  • William M. Briggs
  • Christopher Monckton of Brenchley
Article

Abstract

Agnotology is the study of how ignorance arises via circulation of misinformation calculated to mislead. Legates et al. (Sci Educ 22:2007–2017, 2013) had questioned the applicability of agnotology to politically-charged debates. In their reply, Bedford and Cook (Sci Educ 22:2019–2030, 2013), seeking to apply agnotology to climate science, asserted that fossil-fuel interests had promoted doubt about a climate consensus. Their definition of climate ‘misinformation’ was contingent upon the post-modernist assumptions that scientific truth is discernible by measuring a consensus among experts, and that a near unanimous consensus exists. However, inspection of a claim by Cook et al. (Environ Res Lett 8:024024, 2013) of 97.1 % consensus, heavily relied upon by Bedford and Cook, shows just 0.3 % endorsement of the standard definition of consensus: that most warming since 1950 is anthropogenic. Agnotology, then, is a two-edged sword since either side in a debate may claim that general ignorance arises from misinformation allegedly circulated by the other. Significant questions about anthropogenic influences on climate remain. Therefore, Legates et al. appropriately asserted that partisan presentations of controversies stifle debate and have no place in education.

References

  1. Akasofu, S.-I. (2010). On the recovery from the little ice age. Natural Science, 2, 1211–1224.CrossRefGoogle Scholar
  2. Alley, R. B. (2007). Wally was right: Predictive ability of the North Atlantic ‘conveyor belt’ hypothesis for abrupt climate change. Annual Review of Earth and Planetary Science, 35, 241–272.CrossRefGoogle Scholar
  3. Amstrup, S. C., Marcot, B. G., & Douglas, D. C. (2007). Forecasting the range wide status of polar bears at selected times in the 21st century. Anchorage, Alaska: USGS Alaska Science Center.Google Scholar
  4. Anagnostopoulos, G. G., Koutsoyiannis, D. K., Christofides, A., Efstratiadis, A., & Mamassis, N. (2010). A comparison of local and aggregated climate model outputs with observed data. Hydrological Sciences Journal, 55, 1094–1110.CrossRefGoogle Scholar
  5. Anderegg, W. R. L., Prall, J. W., Harold, J., & Schneider, S. H. (2010). Expert credibility in climate change. Proceedings of the National Academy of Science, 107, 12107–12109.CrossRefGoogle Scholar
  6. Armstrong, J. S., Green, K. C., & Soon, W. (2008). Polar bear population forecasts: A public-policy forecasting audit. Interfaces, 38, 382–405.CrossRefGoogle Scholar
  7. Bedford, D. (2010). Agnotology as a teaching tool: Learning climate science by studying misinformation. Journal of Geography, 109, 159–165.CrossRefGoogle Scholar
  8. Bedford, D., & Cook, J. (2013). Agnotology, scientific consensus, and the teaching and learning of climate change: A response to Legates, Soon and Briggs. Science & Education, 22, 2019–2030.CrossRefGoogle Scholar
  9. Brindley, H., & Allan, R. P. (2003). Simulations of the effects of interannual and decadal variability on the clear-sky outgoing long-wave radiation spectrum. Quarterly Journal of the Royal Meteorological Society, 129, 2971–2988.CrossRefGoogle Scholar
  10. Choi, Y.-S. (2011). How sensitive is the Earth’s climate to a runaway carbon dioxide? Journal of Korean Earth Science Society, 32, 239–247.CrossRefGoogle Scholar
  11. Cook, J., Nuccitelli, D., Green, S. A., Richardson, M., Winkler, B., Painting, R., et al. (2013). Quantifying the consensus on anthropogenic global warming in the scientific literature. Environmental Research Letters, 8, 024024.CrossRefGoogle Scholar
  12. David, L., & Gordon, C. (2007). The down-to-earth guide to global warming. London, UK: Orchard Books.Google Scholar
  13. Ding, D., Maibach, E. W., Zhao, X., Roser-Renouf, C., & Leiserowitz, A. (2011). Support for climate policy and societal action are linked to perceptions about scientific agreement. Nature Climate Change, 1, 462–465.CrossRefGoogle Scholar
  14. Doran, P., & Zimmerman, M. (2009). Examining the scientific consensus on climate change. EOS. Transactions of the American Geophysical Union, 99, 22–23.CrossRefGoogle Scholar
  15. Essex, C. (1986). Trace gases and the problem of false invariants in climate models—a comment. Climatological Bulletin, 20, 19–25.Google Scholar
  16. Essex, C. (1991). What do climate models tell us about global warming? Pure and Applied Geophysics, 135, 125–133.CrossRefGoogle Scholar
  17. Essex, C., Ilie, S., & Corless, R. M. (2007). Broken symmetry and long-term forecasting. Journal of Geophysical Research, 112, D24S17. doi:10.1029/2007JD008563.CrossRefGoogle Scholar
  18. Feynman, R. P. (1969). What is science? The Physics Teacher, 7, 313–320.CrossRefGoogle Scholar
  19. Fischer, H., Wahlen, M., Smith, J., Mastroianni, D., & Deck, B. (1999). Ice core records of atmospheric CO2 around the last three glacial terminations. Science, 283, 1712–1714.CrossRefGoogle Scholar
  20. Funtowicz, S. O., & Ravetz, J. R. (1993). Science for the post-normal age. Futures, 25, 739–755.CrossRefGoogle Scholar
  21. Ghil, M., Chekroun, M. D., & Simonnet, E. (2008). Climate dynamics and fluid dynamics: Natural variability and related uncertainties. Physica D: Nonlinear Phenomena, 237, 2111–2126.CrossRefGoogle Scholar
  22. Green, K. C., Armstrong, J. S., & Soon, W. (2009). Validity of climate change forecasting for public policy decision making. International Journal of Forecasting, 25, 826–832.CrossRefGoogle Scholar
  23. Hollander, P. (2013). Peer review, political correctness, and human nature. Academic Questions, 26, 148–156.CrossRefGoogle Scholar
  24. Huang, Y. (2013). A simulated climatology of spectrally decomposed atmospheric infrared radiation. Journal of Climate, 26, 1702–1715.CrossRefGoogle Scholar
  25. Huang, Y., & Ramaswamy, V. (2008). Observed and simulated seasonal co-variations of outgoing longwave radiation spectrum and surface temperature. Geophysical Research Letters, 35, L17803. doi:10.1029/2008GL034859.CrossRefGoogle Scholar
  26. Huang, Y., Ramaswamy, V., Huang, X., Fu, Q., & Bardeen, C. (2007). A strict test in climate modeling with spectrally resolved radiances: GCM simulation versus AIRS observations. Geophysical Research Letters, 34. doi:10.1029/2007GL031409.
  27. Hunter, C. M., Caswell, H., Runge, M. C., Amstrup, S. C., Regehr, E. V., & Stirling, I. (2007). Polar bears in the Southern Beaufort Sea II: Demography and population growth in relation to sea ice conditions. Anchorage, Alaska: USGS Alaska Science Center.Google Scholar
  28. Huntingford, C., Jones, P. D., Livina, V. N., Lenton, T. M., & Cox, P. M. (2013). No increase in global temperature variability despite changing regional patterns. Nature, forthcoming. doi:10.1038/nature12310.
  29. Huxley, T. H. (1866). On the advisableness of improving natural knowledge. Fortnightly Review. Google Scholar
  30. Kennedy, D. (2006). Acts of god. Science, 311, 303.CrossRefGoogle Scholar
  31. Knight, J. R., et al. (2009). Do global temperature trends over the last decade falsify climate predictions? Bulletin of the American Meteorological Society, 90, S22–S23.Google Scholar
  32. Koutsoyiannis, D. (2010). A random walk on water. Hydrology & Earth System Science, 14, 585–601.CrossRefGoogle Scholar
  33. Koutsoyiannis, D. K., Efstratiadis, A., Mamassis, N., & Christofides, A. (2008). On the credibility of climate projections. Hydrological Sciences Journal, 53, 671–684.CrossRefGoogle Scholar
  34. Koutsoyiannis, D. K., Montanari, A., Lins, H. F., & Cohn, T. A. (2009). Climate, hydrology and freshwater: Towards an interactive incorporation of hydrological experience into climate research. Hydrological Sciences Journal, 54, 394–405.CrossRefGoogle Scholar
  35. Kukla, G., & Gavin, J. (2004). Milankovitch climate reinforcements. Global and Planetary Change, 40, 27–48.CrossRefGoogle Scholar
  36. Kukla, G., & Gavin, J. (2005). Did glacials start with global warming? Quaternary Science Reviews, 24, 1547–1557.CrossRefGoogle Scholar
  37. Landsberg, H. E., & Oliver, J. E. (2005). Climatology. In J. E. Oliver (Ed.), Encyclopedia of world climatology (pp. 272–283). Dordrecht, The Netherlands: Springer Encyclopedia of Earth Sciences Series.CrossRefGoogle Scholar
  38. Lefsrud, L. M., & Meyer, R. E. (2012). Science or science fiction? Professionals’ discursive construction of climate change. Organization Studies, 33, 1477–1506.CrossRefGoogle Scholar
  39. Legates, D. R. (2007). An Inconvenient Truth: A focus on its portrayal of the hydrologic cycle. GeoJournal, 70, 15–19.CrossRefGoogle Scholar
  40. Legates, D. R., Soon, W., & Briggs, W. M. (2013). Learning and teaching climate science: The perils of consensus knowledge using agnotology. Science & Education, 22, 2007–2017.CrossRefGoogle Scholar
  41. Lenzer, J. (2013). Why we can’t trust clinical guidelines. British Medical Journal, 346, f3830.CrossRefGoogle Scholar
  42. Lewandowsky, S., Gilles, G., & Vaughan, S. (2012). The pivotal role of perceived scientific consensus in acceptance of science. Nature Climate Change, 3, 399–404.CrossRefGoogle Scholar
  43. Lindzen, R. S. (2007). Taking greenhouse warming seriously. Energy & Environment, 18, 937–950.CrossRefGoogle Scholar
  44. Lindzen, R. S., & Choi, Y.-S. (2011). On the observational determination of climate sensitivity and its implications. Asia-Pacific Journal of Atmospheric Sciences, 47, 377–390.CrossRefGoogle Scholar
  45. Liu, J., Wang, B., Ding, Q., Kuang, X., Soon, W., & Zorita, E. (2009). Centennial variations of the global monsoon precipitation in the last millennium: Results from ECHO-G model. Journal of Climate, 22, 2356–2371.CrossRefGoogle Scholar
  46. Mahmood, R., et al. (2010). Impacts of land use/land cover change on climate and future research priorities. Bulletin of the American Meteorological Society, 91, 37–46.CrossRefGoogle Scholar
  47. Maue, R. N. (2009). Northern Hemisphere tropical cyclone activity. Geophysical Research Letters, 36, L05805. doi:10.1029/2008GL035946.CrossRefGoogle Scholar
  48. Maue, R. N. (2011). Recent historically low global tropical cyclone activity. Geophysical Research Letters, 38, L14803. doi:10.1029/2011GL047711.CrossRefGoogle Scholar
  49. National Oceanographic and Atmospheric Administration (NOAA). (2013). Monthly mean CO2 concentration at Mauna Loa, HI. ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_mm_mlo.txt.
  50. Oreskes, N. (2004). The scientific consensus on climate change. Science, 306, 1686 (and Erratum, 21 January 2005).Google Scholar
  51. Pielke, R, Sr. et al. (2009). Climate change: The need to consider human forcings besides greenhouse gases. EOS. Transactions of the American Geophysical Union, 90, 413.CrossRefGoogle Scholar
  52. Popper, K. R. (1934). Logik der Forchung, Vienna. Reprinted in 1959 as The Logic of Scientific Discovery, London: Hutchinson & Co., p. 480.Google Scholar
  53. Proctor, R. N. (2008). Agnotology: A missing term to describe the cultural production of ignorance (and its study). In R. N. Proctor & L. Schiebinger (Eds.), Agnotology: The making and unmaking of ignorance (pp. 1–33). Stanford, CA: Stanford University Press.Google Scholar
  54. Saloranta, T. M. (2001). Post-normal science and the global climate change issue. Climatic Change, 50, 395–404.CrossRefGoogle Scholar
  55. Santer, B. D., et al. (2011). Separating signal and noise in atmospheric temperature changes: The importance of timescale. Journal of Geophysical Research, 116, D22105. doi:10.1029/2011JD016263.CrossRefGoogle Scholar
  56. Soon, W. (2007). Implications of the secondary role of carbon dioxide and methane forcing in climate change: Past, present, and future. Physical Geography, 28, 97–125.CrossRefGoogle Scholar
  57. Soon, W. (2009). Solar Arctic-mediated climate variation on multidecadal to centennial timescales: Empirical evidence, mechanistic explanation, and testable consequences. Physical Geography, 30, 144–184.CrossRefGoogle Scholar
  58. Soon, W., Baliunas, S., Idso, C., Idso, S., & Legates, D. R. (2003). Reconstructing climatic and environmental changes of the past 1000 years: A reappraisal. Energy & Environment, 14, 233–296.CrossRefGoogle Scholar
  59. Soon, W., Baliunas, S., Idso, S. B., Kondratyev, K. Y., & Posmentier, E. S. (2001). Modeling climatic effects of anthropogenic carbon dioxide emissions: Unknowns and uncertainties. Climate Research, 18, 259–275.CrossRefGoogle Scholar
  60. Soon, W., Dutta, K., Legates, D. R., Velasco, V., & Zhang, W. (2011). Variation in surface air temperatures of China during the 20th century. Journal of Atmospheric and Solar-Terrestrial Physics, 73, 2331–2344.CrossRefGoogle Scholar
  61. Steffensen, J. P., et al. (2008). High-resolution Greenland ice core data show abrupt climate change happens in few years. Science, 321, 680–684.CrossRefGoogle Scholar
  62. Walsh, J. E., Chapman, W. L., & Portis, D. H. (2009). Arctic cloud fraction and radiative fluxes in atmospheric reanalyses. Journal of Climate, 22, 2316–2334.CrossRefGoogle Scholar
  63. Weiss, K. M. (2012). Agnotology: How can we handle what we don’t know in a knowing way? Evolutionary Anthropology, 21, 96–100.CrossRefGoogle Scholar
  64. Weissberg, R. (2013). The hidden costs of journal peer review. Academic Questions, 26, 157–165.CrossRefGoogle Scholar
  65. Wunsch, C. (2002). Ocean observations and the climate forecast problem. In R. P. Pearce (Ed.), Meteorology at the Millennium (pp. 233–245). London, United Kingdom: Academic Press.CrossRefGoogle Scholar
  66. Wunsch, C. (2010). Towards understanding the Paleocean. Quaternary Science Reviews, 29, 1960–1967.CrossRefGoogle Scholar
  67. Zhu, P., Hack, J. J., Kiehl, J. T., & Bretherton, C. S. (2007). Climate sensitivity of tropical and subtropical marine low clouds amount to ENSO and global warming due to doubled CO2. Journal of Geophysical Research, 112, D17108. doi:10.1029/2006JD008174.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • David R. Legates
    • 1
  • Willie Soon
    • 2
  • William M. Briggs
    • 3
  • Christopher Monckton of Brenchley
    • 4
  1. 1.Department of GeographyUniversity of DelawareNewarkUSA
  2. 2.Harvard-Smithsonian Center for AstrophysicsCambridgeUSA
  3. 3.New YorkUSA
  4. 4.EdinburghScotland, UK

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