Climate model
- This article is about the theories and mathematics of climate modeling. For computer-driven prediction of Earth's climate, see Global climate model.

Climate models use quantitative methods to simulate the interactions of the atmosphere, oceans, land surface, and ice. They are used for a variety of purposes from study of the dynamics of the climate system to projections of future climate. The most talked-about use of climate models in recent years has been to project temperature changes resulting from increases in atmospheric concentrations of greenhouse gases.
All climate models take account of incoming energy from the sun as short wave electromagnetic radiation, chiefly visible and short-wave (near) infrared, as well as outgoing energy as long wave (far) infrared electromagnetic radiation from the earth. Any imbalance results in a change in temperature.
Models can range from relatively simple to quite complex:
- A simple radiant heat transfer model that treats the earth as a single point and averages outgoing energy
- this can be expanded vertically (radiative-convective models), or horizontally
- finally, (coupled) atmosphere–ocean–sea ice global climate models include the full equations for mass and energy transfer and radiant exchange.
- EMICs include land use changes, thus allows researchers to predict the interaction between climate and ecosystems.
Climate models
Climate models include IGCM, HadCM3, HadGEM1, GFDL CM, CGCM, CCSM, CFS, and ECHAM. Types of climate models include, Atmospheric model, Atmospheric dispersion modeling, Numerical weather prediction, Tropical cyclone forecast model, Chemical transport model, Ensemble forecasting, Model output statistics, or Meteorological reanalysis.
When studying climate change, climate scientists use the standard protocol Coupled Model Intercomparison Project (CMIP).[1] Since Earth's radiation balance plays a key role as climate driver, it is crucial when modeling the climate system. especially for regional climate.[2]
Earth-system models of intermediate complexity (EMICs)
Earth system models of intermediate complexity, include changes in forcing from solar luminosity (or solar constant), and the related Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. EMICs where used in the IPCC AR5 report, and calculated significant land-use emissions over the pre-industrial period. This suggests, that land-use emissions are important to understand estimates in Earth past climate–carbon feedbacks.[3]
General circulation models (GCMs)
A General Circulation Model (or Global Climate Model), includes the physics of the atmosphere, and can be coupled with other parts of the climate system, often the ocean, sea ice and land surface as well.[4]
The first general circulation climate model that combined both oceanic and atmospheric processes was developed in the late 1960s at the NOAA Geophysical Fluid Dynamics Laboratory.[5] Models may be coupled to models of other processes, such as the carbon cycle, to better understand feedback effects. Such integrated multi-system models are sometimes referred to as either "earth system models" or "global climate models."
Radiative-convective models (RCM)
One-dimensional, radiative-convective models were used to verify basic climate assumptions in the '80s and '90s.[6]
Research and development
There are three major types of institution where climate models are developed, implemented and used:
- National meteorological services. Most national weather services have a climatology section.
- Universities. Relevant departments include atmospheric sciences, meteorology, climatology, and geography.
- National and international research laboratories. Examples include the National Center for Atmospheric Research (NCAR, in Boulder, Colorado, USA), the Geophysical Fluid Dynamics Laboratory (GFDL, in Princeton, New Jersey, USA), the Hadley Centre for Climate Prediction and Research (in Exeter, UK), the Max Planck Institute for Meteorology in Hamburg, Germany, or the Laboratoire des Sciences du Climat et de l'Environnement (LSCE), France, to name but a few.
The World Climate Research Programme (WCRP), hosted by the World Meteorological Organization (WMO), coordinates research activities on climate modelling worldwide.
A 2012 U.S. National Research Council report discussed how the large and diverse U.S. climate modeling enterprise could evolve to become more unified.[7] Efficiencies could be gained by developing a common software infrastructure shared by all U.S. climate researchers, and holding an annual climate modeling forum, the report found.[8]
Climate models on the web
- CMIP: Coupled Model Intercomparison Project
- NCAR/CESM: Community Climate System Model (CCSM)
- NASA/GISS: NASA Goddard Institute for Space Studies
- EDGCM/NASA: Educational Global Climate Modeling
- climateprediction.net, community climate prediction
See also
Notes and references
- ^ Lawrence Livermore National Laboratory. "CMIP5 - Coupled Model Intercomparison Project Phase 5 - Overview".
- ^ Chiacchio, Marc; Solmon, Fabien; Giorgi, Filippo; Stackhouse, Paul, Jr. (April 2013). The global energy budget with a regional climate model over Europe. Copernicus. Bibcode:2013EGUGA..15.6581C.
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: CS1 maint: multiple names: authors list (link) - ^ European Geosciences Union (2013). "Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity". doi:10.5194/cp-9-1111-2013.
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(help)CS1 maint: unflagged free DOI (link) - ^ RealClimate. "FAQ on climate models".
- ^ NOAA: The First Climate Model
- ^ Wang, W.C.; P.H. Stone (1980). "Effect of ice-albedo feedback on global sensitivity in a one-dimensional radiative-convective climate model". J. Atmos. Sci. 37: 545–52. Bibcode:1980JAtS...37..545W. doi:10.1175/1520-0469(1980)037<0545:EOIAFO>2.0.CO;2. Retrieved 2010-04-22.
- ^ "U.S. National Research Council Report, A National Strategy for Advancing Climate Modeling".
- ^ "U.S. National Research Council Report-in-Brief, A National Strategy for Advancing Climate Modeling".
Bibliography
- Ian Roulstone and John Norbury (2013). Invisible in the Storm: the role of mathematics in understanding weather. Princeton University Press.