Quantitative Comparison of a Hierarchy of Commonly Used Planetary Climate Energy Balance Models

Authors

  • Mihir Dasgupta Greenwood High International School, Bangalore, Karnataka, India
  • Joy Merwin Monteiro Indian Institute of Science Education and Research, Pune, Maharashtra, India

DOI:

https://doi.org/10.47611/jsrhs.v10i4.2174

Keywords:

Climate Modeling, Energy Balance Model, Radiative Equilibrium, Radiative-Convective Equilibrium, 1-D Model, 0-D Model, RRTM-G

Abstract

The objective of this paper is to examine the effect of the various simplifications inherent in commonly-used planetary energy balance climate models (EBMs). Specifically, we look at the zero-dimensional (0-d) radiative equilibrium model, the 1-d radiative equilibrium model, and the 1-d radiative-convective equilibrium (RCE) model. Each of these models make fundamental steps towards a well-represented Earth system model, and make different simplifications and assumptions in the process. We seek to evaluate the effects these assumptions have on key thermal quantities of the system (OLR / outgoing longwave radiation, surface temperature, etc.). These evaluations lead us to identify contexts for each model wherein it remains a valid option to accurately replicate a system. The 0-d model fails to account for the greenhouse effect’s impact on energetics, thus predicting an erroneously-low surface temperature and low OLR. It instead requires an emissivity coefficient ~ 0.619 to balance OLR and temperature and model the Earth system. The 1-d radiative equilibrium model is a significant improvement on its predecessor, creating a stratospheric thermal profile reasonably similar to that of the Earth. The strong low-altitude temperature lapse rate and convective instability near the surface, however, slightly diminishes the validity of the low-level thermal profile – a drawback the RCE model appears to resolve with the addition of convective and boundary layer components. We conclude that the 0-d radiative equilibrium is best suited to isothermal atmospheres, the 1-d radiative equilibrium model to non-isothermal atmospheres where convection is suppressed, and the 1-d RCE model to convectively-active atmospheres.

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Author Biographies

Mihir Dasgupta, Greenwood High International School, Bangalore, Karnataka, India

Student, IB-DP 1

Joy Merwin Monteiro, Indian Institute of Science Education and Research, Pune, Maharashtra, India

Department: Earth And Climate Science

Rank: Assistant Professor

Research Interests: Tropical Climate, Climate Modelling, Geophysical Fluid Dynamics, Extremes in the Climate System  

Faculty Website Profile: https://www.iiserpune.ac.in/people/faculty-details/200  

  Google Scholar Profile: https://scholar.google.com/citations?user=bMU4QficRmcC&hl=en        

References or Bibliography

Monteiro, J. M., McGibbon, J., & Caballero, R. (2018). sympl (v. 0.4. 0) and climt (v. 0.15. 3)–towards a flexible framework for building model hierarchies in Python. Geoscientific Model Development, 11(9), 3781-3794. https://do i.org/10.5194/gmd-11-3781-2018

Durran, D. R. (1991). The third-order Adams-Bashforth method: An attractive alternative to leapfrog time differencing. Monthly weather review, 119(3), 702-720. https://doi.org/10.1175/1520-0493(1991)119%3C0702: TTOABM%3E2.0.CO;2

Dasgupta, M. (2021). Mihir-DG/earth-EBMs. https://github.com/Mihir-DG/earth-EBMs

McNaught, A. D. (1997). Compendium of chemical terminology (Vol. 1669). Oxford: Blackwell Science. http://

www.old.iupac.org/publications/books/author/mcnaught.html

Manabe, S., & Wetherald, R. T. (1967). Thermal equilibrium of the atmosphere with a given distribution of relative humidity. https://doi.org/10.1175/1520-0469(1967)024%3C0241:TEOTAW%3E2.0.CO;2

Stephens, G. L., O'Brien, D., Webster, P. J., Pilewski, P., Kato, S., & Li, J. L. (2015). The albedo of Earth. Reviews of geophysics, 53(1), 141-163. https://doi.org/10.1002/2014RG000449

Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee III, R. B., Smith, G. L., & Cooper, J. E. (1996). Clouds and the Earth's Radiant Energy System (CERES): An earth observing system experiment. Bulletin of the American Meteorological Society, 77(5), 853-868. https://doi.org/10.1175/1520-0477(1996)077%3C0853:CATERE%3E2.0. CO;2

Jacobowitz, H., & Tighe, R. J. (1984). The earth radiation budget derived from the NIMBUS 7 ERB experiment. Journal of Geophysical Research: Atmospheres, 89(D4), 4997-5010. https://doi.org/10.1029/JD089iD04p04997

Greene, T., Jacobs, P., NASA Release 21-005, 2021. 2020 Tied for Warmest Year on Record, NASA Analysis Shows. https://www.giss.nasa.gov/research/news/20210114/

Hansen, J., Ruedy, R., Sato, M., & Lo, K. (2010). Global surface temperature change. Reviews of Geophysics, 48(4). https://doi.org/10.1029/2010RG000345

Lenssen, N. J., Schmidt, G. A., Hansen, J. E., Menne, M. J., Persin, A., Ruedy, R., & Zyss, D. (2019). Improvements in the GISTEMP uncertainty model. Journal of Geophysical Research: Atmospheres, 124(12), 6307-6326. https://doi.org/10.1029/2018JD029522

Liebmann, B., & Smith, C. A. (1996). Description of a complete (interpolated) outgoing longwave radiation dataset. Bulletin of the American Meteorological Society, 77(6), 1275-1277. https://psl.noaa.gov/data/gridded/data. interp_OLR.html

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., ... & Thépaut, J. N. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999-2049. https:// doi.org/10.1002/qj.3803

Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., ... & Takahashi, K. (2015). The JRA-55 reanalysis: General specifications and basic characteristics. Journal of the Meteorological Society of Japan. Ser. II, 93(1), 5-48. https://doi.org/10.2151/jmsj.2015-001

Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., ... & Zhao, B. (2017). The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Journal of climate, 30(14), 5419-5454. https://doi.org/10.1175/JCLI-D-16-0758.1

Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., ... & Joseph, D. (1996). The NCEP/NCAR 40-year reanalysis project. Bulletin of the American meteorological Society, 77(3), 437-472. https:// doi.org /10.1175/1520-0477(1996)077%3C0437:TNYRP%3E2.0.CO;2

Ernst, W. G., Sleep, N. H., & Tsujimori, T. (2016). Plate-tectonic evolution of the Earth: bottom-up and top-down mantle circulation. Canadian Journal of Earth Sciences, 53(11), 1103-1120. https://doi.org/10.1139/cjes-2015-0126

Camuffo, D. (2001). Lunar influences on climate. In Earth-Moon Relationships (pp. 99-113). Springer, Dordrecht. ht tp://dx.doi.org/10.1023/A:1017099427908

Lenardic, A., Moresi, L. N., Jellinek, A. M., & Manga, M. (2005). Continental insulation, mantle cooling, and the surface area of oceans and continents. Earth and Planetary Science Letters, 234(3-4), 317-333. https://doi.org/10 .1016/j.epsl.2005.01.038

Johnson, F. S. (1954). The solar constant. Journal of Atmospheric Sciences, 11(6), 431-439. https://doi.org/10.1175 /1520-0469(1954)011%3C0431:TSC%3E2.0.CO;2

Meador, W. E., & Weaver, W. R. (1980). Two-stream approximations to radiative transfer in planetary atmospheres: A unified description of existing methods and a new improvement. Journal of Atmospheric Sciences, 37(3), 630-643. https://doi.org/10.1175/1520-0469(1980)037%3C0630:TSATRT%3E2.0.CO;2

Catling, D. C., & Zahnle, K. J. (2009). The planetary air leak. Scientific American, 300(5), 36-43 http://faculty.was hington.edu/dcatling/Catling2009_SciAm.pdf

Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., & Clough, S. A. (1997). Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated‐k model for the longwave. Journal of Geophysical Research: Atmospheres, 102(D14), 16663-16682. https://doi.org/10.1029/97JD00237

Emanuel, K. A., & Živković-Rothman, M. (1999). Development and evaluation of a convection scheme for use in climate models. Journal of the Atmospheric Sciences, 56(11), 1766-1782. https://doi.org/10.1175/1520-0469(1999)

%3C1766:DAEOAC%3E2.0.CO;2

May, R. M., Arms, S. C., Marsh, P., Bruning, E., Leeman, J. R., Goebbert, K., Thielen, J. E., Bruick, Z., and Camron, M. D., 2021: MetPy: A Python Package for Meteorological Data. Unidata. https://github.com/

Unidata/MetPy, https://doi.org/10.5065/D6WW7G29.

Published

06-10-2022

How to Cite

Dasgupta, M., & Monteiro, J. M. (2022). Quantitative Comparison of a Hierarchy of Commonly Used Planetary Climate Energy Balance Models. Journal of Student Research, 10(4). https://doi.org/10.47611/jsrhs.v10i4.2174

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Section

HS Research Articles