Causes of differences in model and satellite tropospheric warming rates

Abstract

In the early twenty-first century, satellite-derived tropospheric warming trends were generally smaller than trends estimated from a large multi-model ensemble. Because observations and coupled model simulations do not have the same phasing of natural internal variability, such decadal differences in simulated and observed warming rates invariably occur. Here we analyse global-mean tropospheric temperatures from satellites and climate model simulations to examine whether warming rate differences over the satellite era can be explained by internal climate variability alone. We find that in the last two decades of the twentieth century, differences between modelled and observed tropospheric temperature trends are broadly consistent with internal variability. Over most of the early twenty-first century, however, model tropospheric warming is substantially larger than observed; warming rate differences are generally outside the range of trends arising from internal variability. The probability that multi-decadal internal variability fully explains the asymmetry between the late twentieth and early twenty-first century results is low (between zero and about 9%). It is also unlikely that this asymmetry is due to the combined effects of internal variability and a model error in climate sensitivity. We conclude that model overestimation of tropospheric warming in the early twenty-first century is partly due to systematic deficiencies in some of the post-2000 external forcings used in the model simulations.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Time series and difference series of simulated and observed tropospheric temperature.
Figure 2: Trends (left column) and trend significance (right column) for TMT difference series.
Figure 3: Asymmetries in the statistical significance of differences between modelled and observed tropospheric temperature trends.
Figure 4: Overall statistical significance of the γ1, γ2 and γ3 asymmetry statistics as a function of the analysis timescale and the satellite data used to compute the ‘MMA minus observed’ difference time series.

References

  1. 1

    IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 29 (Cambridge Univ. Press, 2013).

  2. 2

    Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 741–866 (IPCC, Cambridge Univ. Press, 2013).

    Google Scholar 

  3. 3

    Karl, T. R. et al. Possible artifacts of data biases in the recent global surface warming hiatus. Science 348, 1469–1472 (2015).

    Article  Google Scholar 

  4. 4

    Cowtan, K. et al. Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures. Geophys. Res. Lett. 42, 6526–6534 (2015).

    Article  Google Scholar 

  5. 5

    Hausfather, Z. et al. Assessing recent warming using instrumentally homogeneous sea surface temperature records. Sci. Adv. 3, e1601207 (2017).

    Article  Google Scholar 

  6. 6

    Lewandowsky, S., Risbey, J. S. & Oreskes, N. The “pause” in global warming: Turning a routine fluctuation into a problem for science. Bull. Am. Meteorol. Soc. 97, 723–733 (2016).

    Article  Google Scholar 

  7. 7

    Cahill, N., Rahmstorf, S. & Parnell, A. C. Change points of global temperature. Environ. Res. Lett. 10, 084002 (2015).

    Article  Google Scholar 

  8. 8

    Rajaratnam, B., Romano, J., Tsiang, M. & Diffenbaugh, N. S. Debunking the climate hiatus. Climatic Change 133, 129–140 (2015).

    Article  Google Scholar 

  9. 9

    Rahmstorf, S., Foster, G. & Cahill, N. Global temperature evolution: recent trends and some pitfalls. Environ. Res. Lett. 12, 054001 (2017).

    Article  Google Scholar 

  10. 10

    Kosaka, Y. & Xie, S.-P. Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature 501, 403–407 (2013).

    Article  Google Scholar 

  11. 11

    Meehl, G. A., Teng, H. & Arblaster, J. M. Climate model simulations of the observed early-2000s hiatus of global warming. Nat. Clim. Change 4, 898–902 (2014).

    Article  Google Scholar 

  12. 12

    Risbey, J. S. et al. Well-estimated global surface warming in climate projections selected for ENSO phase. Nat. Clim. Change 4, 835–840 (2014).

    Article  Google Scholar 

  13. 13

    England, M. H. et al. Recent intensification of wind–driven circulation in the Pacific and the ongoing warming hiatus. Nat. Clim. Change 4, 222–227 (2014).

    Article  Google Scholar 

  14. 14

    Steinman, B. A., Mann, M. E. & Miller, S. K. Atlantic and Pacific multidecadal oscillations and Northern Hemisphere temperatures. Science 347, 988–991 (2015).

    Article  Google Scholar 

  15. 15

    Santer, B. D. et al. Volcanic contribution to decadal changes in tropospheric temperature. Nat. Geosci. 7, 185–189 (2014).

    Article  Google Scholar 

  16. 16

    Fyfe, J. C. et al. Making sense of the early-2000s warming slowdown. Nat. Clim. Change 6, 224–228 (2016).

    Article  Google Scholar 

  17. 17

    Schmidt, G. A., Shindell, D. T. & Tsigaridis, K. Reconciling warming trends. Nat. Geosci. 7, 1–3 (2014).

    Article  Google Scholar 

  18. 18

    Gleisner, H., Thejll, P., Christianson, B. & Nielsen, J. K. Recent global warming hiatus dominated by low-latitude temperature trends in surface and troposphere data. Geophys. Res. Lett. 42, 510–517 (2014).

    Article  Google Scholar 

  19. 19

    Medhaug, I., Stolpe, M. B., Fischer, E. M. & Knutti, R. Reconciling controversies about the ‘global warming hiatus’. Nature 545, 41–47 (2017).

    Article  Google Scholar 

  20. 20

    Solomon, S. et al. The persistently variable “background” stratospheric aerosol layer and global climate change. Science 333, 866–870 (2011).

    Article  Google Scholar 

  21. 21

    Vernier, J.-P. Major influence of tropical volcanic eruptions on the stratospheric aerosol layer during the last decade. Geophys. Res. Lett. 38, L12807 (2011).

    Article  Google Scholar 

  22. 22

    Neely, R. R. et al. Recent anthropogenic increases in SO2 from Asia have minimal impact on stratospheric aerosol. Geophys. Res. Lett. 40, 1–6 (2013).

    Article  Google Scholar 

  23. 23

    Ridley, D. A. et al. Total volcanic stratospheric aerosol optical depths and implications for global climate change. Geophys. Res. Lett. 41, 7763–7769 (2014).

    Article  Google Scholar 

  24. 24

    Santer, B. D. et al. Observed multivariable signals of late 20th and early 21st century volcanic activity. Geophys. Res. Lett. 42, 500–509 (2015).

    Article  Google Scholar 

  25. 25

    Kopp, G. & Lean, J. L. A new, lower value of total solar irradiance: evidence and climate significance. Geophys. Res. Lett. 38, L01706 (2011).

    Article  Google Scholar 

  26. 26

    Smith, D. M. et al. Role of volcanic and anthropogenic aerosols in the recent global surface warming slowdown. Nat. Clim. Change 6, 936–940 (2016).

    Article  Google Scholar 

  27. 27

    Solomon, S. et al. Contributions of stratospheric water vapor to decadal changes in the rate of global warming. Science 327, 1219–1223 (2010).

    Article  Google Scholar 

  28. 28

    Christy, J. R. Testimony in Hearing before the U.S. Senate Committee on Commerce, Science, and Transportation, Subcommittee on Space, Science, and Competitiveness (2015); http://www.commerce.senate.gov/public/index.cfm/2015/12/data-or-dogma-promoting-open-inquiry-in-the-debate-over-the-magnitude-of-human-impact-on-earth-s-climate

  29. 29

    Mears, C. & Wentz, F. J. Sensitivity of satellite-derived tropospheric temperature trends to the diurnal cycle adjustment. J. Clim. 29, 3629–3646 (2016).

    Article  Google Scholar 

  30. 30

    Po-Chedley, S., Thorsen, T. J. & Fu, Q. Removing diurnal cycle contamination in satellite-derived tropospheric temperatures: understanding tropical tropospheric trend discrepancies. J. Clim. 28, 2274–2290 (2015).

    Article  Google Scholar 

  31. 31

    Zou, C.-Z. & Wang, W. Inter-satellite calibration of AMSU-A observations for weather and climate applications. J. Geophys. Res. 116, D23113 (2011).

    Google Scholar 

  32. 32

    Cowtan, K. & Way, R. G. Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends. Q. J. R. Meteorol. Soc. 140, 1935–1944 (2014).

    Article  Google Scholar 

  33. 33

    US Senate Data or Dogma? Promoting Open Inquiry in the Debate over the Magnitude of Human Impact on Earth’s Climate (2015); http://go.nature.com/2qQjvNL

  34. 34

    Christy, J. R., Norris, W. B., Spencer, R. W. & Hnilo, J. J. Tropospheric temperature change since 1979 from tropical radiosonde and satellite measurements. J. Geophys. Res. 112, D06102 (2007).

    Article  Google Scholar 

  35. 35

    Bloomfield, P. & Nychka, D. Climate spectra and detecting climate change. Climatic Change 21, 275–287 (1992).

    Article  Google Scholar 

  36. 36

    Brown, P. T., Li, W., Cordero, E. C. & Mauget, S. A. Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise. Sci. Rep. 5, 9957 (2016).

    Article  Google Scholar 

  37. 37

    Allen, M. R. & Tett, S. F. B. Checking for model consistency in optimal fingerprinting. Clim. Dynam. 15, 419–434 (1999).

    Article  Google Scholar 

  38. 38

    Mann, M. E., Rahmstorf, S., Steinman, B. A., Tingley, M. & Miller, S. K. The likelihood of recent warmth. Sci. Rep. 6, 19831 (2016).

    Article  Google Scholar 

  39. 39

    Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

    Article  Google Scholar 

  40. 40

    Fu, Q., Johanson, C. M., Warren, S. G. & Seidel, D. J. Contribution of stratospheric cooling to satellite-inferred tropospheric temperature trends. Nature 429, 55–58 (2004).

    Article  Google Scholar 

  41. 41

    Fu, Q. & Johanson, C. M. Stratospheric influences on MSU-derived tropospheric temperature trends: a direct error analysis. J. Clim. 17, 4636–4640 (2004).

    Article  Google Scholar 

  42. 42

    Fu, Q., Manabe, S. & Johanson, C. M. On the warming in the tropical upper troposphere: models versus observations. Geophys. Res. Lett. 38, L15704 (2011).

    Google Scholar 

  43. 43

    Po-Chedley, S. & Fu, Q. Discrepancies in tropical upper tropospheric warming between atmospheric circulation models and satellites. Environ. Res. Lett. 7, 044018 (2012).

    Article  Google Scholar 

  44. 44

    Santer, B. D. et al. Separating signal and noise in atmospheric temperature changes: the importance of timescale. J. Geophys. Res. 116, D22105 (2011).

    Article  Google Scholar 

  45. 45

    Santer, B. D. et al. Comparing tropospheric warming in climate models and satellite data. J. Clim. 30, 373–392 (2017).

    Article  Google Scholar 

  46. 46

    Wigley, T. M. L., Ammann, C. M., Santer, B. D. & Raper, S. C. B. The effect of climate sensitivity on the response to volcanic forcing. J. Geophys. Res. 110, D09107 (2005).

    Article  Google Scholar 

  47. 47

    Fyfe, J. C., Gillett, N. P. & Zwiers, F. W. Overestimated global warming over the past 20 years. Nat. Clim. Change 3, 767–769 (2013).

    Article  Google Scholar 

  48. 48

    Johansson, D. J. A., O’Neill, B. C., Tebaldi, C. & Häggström, O. Equilibrium climate sensitivity in light of observations over the warming hiatus. Nat. Clim. Change 5, 449–453 (2015).

    Article  Google Scholar 

  49. 49

    Wentz, F. J. & Schabel, M. Effects of orbital decay on satellite-derived lower-tropospheric temperature trends. Nature 394, 661–664 (1998).

    Article  Google Scholar 

  50. 50

    Mears, C. A., Schabel, M. C. & Wentz, F. J. A reanalysis of the MSU channel 2 tropospheric temperature record. J. Clim. 16, 3650–3664 (2003).

    Article  Google Scholar 

  51. 51

    Po-Chedley, S. & Fu, Q. A bias in the mid-tropospheric channel warm target factor on the NOAA-9 Microwave Sounding Unit. J. Atmos. Ocean. Technol. 29, 646–652 (2012).

    Article  Google Scholar 

  52. 52

    Trenberth, K. E. Has there been a hiatus? Science 349, 791–792 (2015).

    Article  Google Scholar 

  53. 53

    Chen, X. & Tung, K. K. Varying planetary heat sink led to global-warming slowdown and acceleration. Science 345, 897–903 (2014).

    Article  Google Scholar 

  54. 54

    Santer, B. D. et al. Identifying human influences on atmospheric temperature. Proc. Nat Acad. Sci. USA 110, 26–33 (2013).

    Article  Google Scholar 

  55. 55

    Imbers, J., Lopez, A., Huntingford, C. & Allen, M. R. Testing the robustness of anthropogenic climate change detection statements using different empirical models. J. Geophys. Res. 118, 3192–3199 (2013).

    Google Scholar 

  56. 56

    Wigley, T. M. L. & Raper, S. C. B. Natural variability of the climate system and detection of the greenhouse effect. Nature 344, 324–327 (1990).

    Article  Google Scholar 

  57. 57

    Henley, B. J. et al. Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation. Environ. Res. Lett. 12, 044011 (2017).

    Article  Google Scholar 

  58. 58

    Mears, C., Wentz, F. J., Thorne, P. & Bernie, D. Assessing uncertainty in estimates of atmospheric temperature changes from MSU and AMSU using a Monte-Carlo technique. J. Geophys. Res. 116, D08112 (2011).

    Article  Google Scholar 

  59. 59

    Zou, C.-Z. et al. Recalibration of microwave sounding unit for climate studies using simultaneous nadir overpasses. J. Geophys. Res. 111, D19114 (2006).

    Article  Google Scholar 

  60. 60

    Zou, C.-Z., Gao, M. & Goldberg, M. Error structure and atmospheric temperature trends in observations from the Microwave Sounding Unit. J. Clim. 22, 1661–1681 (2009).

    Article  Google Scholar 

  61. 61

    Fu, Q. & Johanson, C. M. Satellite-derived vertical dependence of tropical tropospheric temperature trends. Geophys. Res. Lett. 32, L10703 (2005).

    Article  Google Scholar 

  62. 62

    Johanson, C. M. & Fu, Q. Robustness of tropospheric temperature trends from MSU Channels 2 and 4. J. Clim. 19, 4234–4242 (2006).

    Article  Google Scholar 

  63. 63

    Gillett, N. P., Santer, B. D. & Weaver, A. J. Atmospheric science: stratospheric cooling and the troposphere. Nature http://dx.doi.org/10.1038/nature03209 (2004).

  64. 64

    Kiehl, J. T., Caron, J. & Hack, J. J. On using global climate model simulations to assess the accuracy of MSU retrieval methods for tropospheric warming trends. J. Clim. 18, 2533–2539 (2005).

    Article  Google Scholar 

  65. 65

    Andrews, T., Gregory, J. M., Webb, M. J. & Taylor, K. E. Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models. Geophys. Res. Lett. 39, L09712 (2012).

    Google Scholar 

Download references

Acknowledgements

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison (PCMDI) provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank M. Zelinka (PCMDI) for providing CMIP5 climate sensitivity results, S. Solomon (M.I.T.) for helpful discussions, and N. Swart and V. Arora (both CCCma) for constructive comments. The views, opinions, and findings contained in this report are those of the authors and should not be construed as a position, policy, or decision of the US Government, the US Department of Energy, or the National Oceanic and Atmospheric Administration.

Author information

Affiliations

Authors

Contributions

B.D.S., J.C.F., G.P., G.M.F. and E.H. designed the analysis. B.D.S. performed all statistical analyses. J.F.P. calculated synthetic satellite temperatures from model simulation output and provided assistance with processing of observed temperature data. C.M., F.J.W., S.P.-C., Q.F. and C.-Z.Z. provided satellite temperature data. I.C., C.B. and J.F.P. assisted with the processing of the CMIP5 simulations analysed here. All authors contributed to the writing and review of the manuscript.

Corresponding author

Correspondence to Benjamin D. Santer.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Information (PDF 2266 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Santer, B., Fyfe, J., Pallotta, G. et al. Causes of differences in model and satellite tropospheric warming rates. Nature Geosci 10, 478–485 (2017). https://doi.org/10.1038/ngeo2973

Download citation

Further reading