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Fixed anvil temperature hypothesis

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Background and hypothesis

In the tropics, the radiative cooling of the troposphere is balanced by the release of latent heat through condensation of water vapour lofted to high altitudes by convection. The radiative cooling is mostly a consequence of emissions by water vapour and thus becomes ineffective above the 200 hPa pressure level. Congruently, it is at this elevation that thick clouds and anvil clouds - the topmost convective clouds - concentrate.[1]

The "fixed anvil temperature hypothesis" stipulates that owing to energetic and thermodynamic constraints imposed by the Clausius-Clapeyron relationship, the temperature and thus radiative cooling of anvil clouds does not change much with surface temperature.[1] Specifically, cooling decreases below −73 °C (200 K) as the ineffective radiative cooling by CO
2 becomes dominant below that temperature.[2] Instead, the elevation of high clouds rises with surface temperatures.[3]

A related hypothesis is that tropopause temperatures are insensitive to surface warming; however it appears to have distinct mechanisms from the fixed anvil temperature process.[4]

Evidence

Models

The fixed anvil temperature hypothesis was initially formulated by Hartmann and Larson 2002 in the context of the NCAR/PSU MM5 climate model[5] but the stability of top cloud temperatures was already observed in an one-dimensional model by Hansen et al. 1981.[6] It has also been recovered, with limitations, in climate models[7] and in numerous general circulation models[8] although some have recovered a dependence on cloud size.[9] Climate models also simulate an increase in cloud top height.[10]

The fixed anvil temperature hypothesis has also been obtained in simulations of exoplanet climates.[11] At very high CO
2 concentrations approaching a runaway greenhouse however, other physical effects pertaining to cloud opacity may take over and dominate the fixed anvil temperature as surface temperatures reach extreme levels.[12]

Observations

The fixed anvil temperature hypothesis has been backed by observational studies[13] for large clouds. Smaller clouds however have no stable temperature and there are temperature fluctuations of about 9.0 °F (5 K).[14] Xu et al. 2007 found that cloud temperatures are more stable for clouds with sizes exceeding 150 kilometres (93 mi).[15] The ascent of cloud top height with warming is also supported by observations.[10]

Implications

The fixed anvil temperature hypothesis has effects on global climate sensitivity, since anvil clouds are the most important source of outgoing radiation linked to tropical convection[16] and their temperature being stable would render the outgoing radiation non-responsive to surface temperature changes.[17] This creates a positive feedback component of cloud feedback.[18]

Alternative views

An alternative hypothesis is the iris hypothesis, according to which the coverage of anvil clouds declines with warming, thus allowing more radiation to escape into space and resulting in slower warming.[19] The proportionate anvil warming hypothesis by Zelinka and Hartmann 2010 was formulated on the basis of general circulation models and envisages a small increase of anvil temperature with high warming.[20] The latter hypothesis was intended as a modification to the fixed anvil temperature hypothesis.[14] Finally, there is a view that cloud top temperatures could actually decrease with surface warming[21] as convection height rises. This may constitute a non-equilibrium response.[22]

References

  1. ^ a b Hartmann & Larson 2002, p. 1.
  2. ^ Hartmann & Larson 2002, p. 3.
  3. ^ Albern, Nicole; Voigt, Aiko; Pinto, Joaquim G. (2019). "Cloud-Radiative Impact on the Regional Responses of the Midlatitude Jet Streams and Storm Tracks to Global Warming". Journal of Advances in Modeling Earth Systems. 11 (7): 1949. doi:10.1029/2018MS001592. ISSN 1942-2466.
  4. ^ Hu, Shineng; Vallis, Geoffrey K. (2019). "Meridional structure and future changes of tropopause height and temperature". Quarterly Journal of the Royal Meteorological Society. 145 (723): 2709. doi:10.1002/qj.3587. ISSN 1477-870X.
  5. ^ Hartmann & Larson 2002, p. 2.
  6. ^ Del Genio 2016, p. 107.
  7. ^ Igel, Drager & van den Heever 2014, p. 10516.
  8. ^ Maher, Penelope; Gerber, Edwin P.; Medeiros, Brian; Merlis, Timothy M.; Sherwood, Steven; Sheshadri, Aditi; Sobel, Adam H.; Vallis, Geoffrey K.; Voigt, Aiko; Zurita-Gotor, Pablo (2019). "Model Hierarchies for Understanding Atmospheric Circulation". Reviews of Geophysics. 57 (2): 267. doi:10.1029/2018RG000607. ISSN 1944-9208.
  9. ^ Noda et al. 2016, p. 2313.
  10. ^ a b Li, R. L.; Storelvmo, T.; Fedorov, A. V.; Choi, Y.-S. (15 August 2019). "A Positive Iris Feedback: Insights from Climate Simulations with Temperature-Sensitive Cloud–Rain Conversion". Journal of Climate. 32 (16): 5306. doi:10.1175/JCLI-D-18-0845.1. ISSN 0894-8755.
  11. ^ Yang, Jun; Leconte, Jérémy; Wolf, Eric T.; Merlis, Timothy; Koll, Daniel D. B.; Forget, François; Abbot, Dorian S. (April 2019). "Simulations of Water Vapor and Clouds on Rapidly Rotating and Tidally Locked Planets: A 3D Model Intercomparison". The Astrophysical Journal. 875 (1): 11. doi:10.3847/1538-4357/ab09f1. ISSN 0004-637X. {{cite journal}}: More than one of |pages= and |page= specified (help)CS1 maint: unflagged free DOI (link)
  12. ^ Ramirez, Ramses M.; Kopparapu, Ravi Kumar; Lindner, Valerie; Kasting, James F. (August 2014). "Can Increased Atmospheric CO2 Levels Trigger a Runaway Greenhouse?". Astrobiology. 14 (8): 723. doi:10.1089/ast.2014.1153. ISSN 1531-1074.
  13. ^ Asrar, Ghassem R.; Hurrell, James W., eds. (2013). Climate Science for Serving Society. Dordrecht: Springer Netherlands. p. 406. doi:10.1007/978-94-007-6692-1. ISBN 978-94-007-6691-4.
  14. ^ a b Noda et al. 2016, p. 2307.
  15. ^ Noda et al. 2016, p. 2312.
  16. ^ Hartmann & Larson 2002, pp. 1–2.
  17. ^ Hartmann & Larson 2002, p. 4.
  18. ^ Del Genio 2016, p. 116.
  19. ^ Seeley, Jacob T.; Jeevanjee, Nadir; Langhans, Wolfgang; Romps, David M. (2019). "Formation of Tropical Anvil Clouds by Slow Evaporation". Geophysical Research Letters. 46 (1): 492. doi:10.1029/2018GL080747. ISSN 1944-8007.
  20. ^ Zelinka, Mark D.; Hartmann, Dennis L. (16 December 2011). "The observed sensitivity of high clouds to mean surface temperature anomalies in the tropics: TEMPERATURE SENSITIVITY OF HIGH CLOUDS". Journal of Geophysical Research: Atmospheres. 116 (D23): 1. doi:10.1029/2011JD016459.
  21. ^ Igel, Drager & van den Heever 2014, p. 10530.
  22. ^ Igel, Drager & van den Heever 2014, p. 10531.

Sources

  • Del Genio, Anthony D. (22 August 2016). "The Role of Clouds in Climate". Our Warming Planet. 1. World Scientific: 103–130. doi:10.1142/9789813148796_0005.
  • Hartmann, Dennis L.; Larson, Kristin (2002). "An important constraint on tropical cloud - climate feedback". Geophysical Research Letters. 29 (20): 12–1–12-4. doi:10.1029/2002GL015835. ISSN 1944-8007.
  • Igel, Matthew R.; Drager, Aryeh J.; van den Heever, Susan C. (16 September 2014). "A CloudSat cloud object partitioning technique and assessment and integration of deep convective anvil sensitivities to sea surface temperature: CloudSat Objects and Sensitivity to SST". Journal of Geophysical Research: Atmospheres. 119 (17): 10515–10535. doi:10.1002/2014JD021717.
  • Noda, A. T.; Seiki, T.; Satoh, M.; Yamada, Y. (16 March 2016). "High cloud size dependency in the applicability of the fixed anvil temperature hypothesis using global nonhydrostatic simulations: CLOUD SIZE DEPENDENCY OF FAT HYPOTHESIS". Geophysical Research Letters. 43 (5): 2307–2314. doi:10.1002/2016GL067742.


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