Abstract
Climate models range in complexity from very simple to very complex. General Circulation Models are the most complex and most require time on a supercomputer in order to utilize all the required data. Box models, Energy Balance models, Radiative-Convective models, and General Circulation models are all used to allow scientists to vary input and ask “what if” questions about the climate system. Validation of models is necessary in order to have confidence in modeling and for individual models. History matching (or hindcasting) is an integral part of the modeling process. The validation process allows scientists to have greater confidence in model results.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsAdditional Readings
Archer, D. (2011). Global warming: Understanding the forecast (2nd ed.). Hoboken: Wiley. ISBN-10: 0470943416; ISBN-13: 978-0470943410.
Archer, D., & Pierrehumbert, R. T. (Eds.). (2011). The warming papers: The scientific foundation for the climate change forecast. Hoboken: Wiley-Blackwell.
Bolin, B. (2007). A history of the science and politics of climate change. The role of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.
Houghton, J. (2009). Global warming: The complete briefing (4th ed.). Cambridge: Cambridge University Press.
IPCC, in IPCC TAR SYR. (2001). In Watson, R. T., The Core Writing Team (Eds.), Climate change 2001: Synthesis report. Contribution of working groups I, II, and III to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, ISBN 0-521-80770-0 (pb: 0-521-01507-3).
Jin, M., & Liang, S. (2006). An improved land surface emissivity parameter for land surface models using global remote sensing observations. Journal of Climate, 19(12), 2867–2881. doi:10.1175/JCLI3720.1.
Meehl, G. A., et al. Climate change 2007 Chapter 10: Global climate projections, in IPCC AR4 WG1 (2007). Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., et al. (Eds.). Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, ISBN 978-0-521-88009-1 (pb: 978-0-521-70596-7).
Pierrehumbert, R. T. (2011). Principles of planetary climate. Cambridge: Cambridge University Press.
Soden, B. J., & Held, I. M. (2006). An assessment of climate feedbacks in coupled ocean–atmosphere models. Journal of Climate, 19, 3354–3360. doi:10.1175/JCLI3799.1.
Sokolov, A. P., et al. (2009). Probabilistic forecast for 21st century climate based on uncertainties in emissions (without policy) and climate parameters. Journal of Climate, 22(19), 5175–5204. doi:10.1175/2009JCLI2863.1.
Wang, W. C., & Stone, P. H. (1980). Effect of ice-albedo feedback on global sensitivity in a one-dimensional radiative-convective climate model. Journal of the Atmospheric Sciences, 37(3), 545–552. doi:10.1175/1520-0469(1980)037<0545:EOIAFO>2.0.CO;2. Bibcode 1980JAtS…37..545W.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Farmer, G.T., Cook, J. (2013). Types of Models. In: Climate Change Science: A Modern Synthesis. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5757-8_18
Download citation
DOI: https://doi.org/10.1007/978-94-007-5757-8_18
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-5756-1
Online ISBN: 978-94-007-5757-8
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)