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Home›Geophysics›General Circulation Model
Process / pipelineClimate simulation and modeling

General Circulation Model

Also known as: GCM, Global Climate Model

A General Circulation Model (GCM), also called a Global Climate Model, is a three-dimensional numerical representation of the Earth's atmosphere, oceans, ice, and land surface that simulates physical processes governing weather and climate. Pioneered by Manabe and Wetherald in 1975, GCMs are the primary tools for understanding past climate, projecting future climate change, and investigating climate sensitivity to greenhouse gases and other forcings.

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General Circulation Model
NDVIOcean-Atmosphere Coupled…Standardized Precipitati…Aerosol Optical DepthStandardized Precipitati…SWAT Model

When to use it

Use GCMs to project long-term climate change (decadal to century-scale), understand the response to emissions scenarios, and assess regional climate impacts. Combine GCM projections with downscaling methods (statistical or dynamical) for local applications. GCMs are essential for policy-relevant climate assessments. For short-term weather prediction (1–2 weeks), use numerical weather prediction models, not GCMs.

Strengths & limitations

Strengths
  • Physically based representation of atmosphere-ocean-land interactions, respecting fundamental conservation laws
  • Enables exploration of climate change under different socioeconomic and emissions scenarios
  • Provides spatially continuous fields of multiple variables (temperature, precipitation, wind), useful for regional impact assessment
  • Ensemble capability allows quantification of uncertainty and identification of robust signals
Limitations
  • High computational cost limits spatial resolution (typically 50–250 km); regional details require downscaling
  • Uncertainty in representation of clouds, convection, and ice sheets introduces systematic biases in climate projections
  • Equilibrium climate sensitivity (warming per doubling of CO2) varies significantly among GCMs, leading to uncertainty in magnitude of future change
  • Long spin-up time (decades to millennia) required to reach equilibrium, making coupled simulations computationally expensive

Frequently asked

How accurate are GCM projections?

GCMs skillfully simulate observed climate variability on seasonal to decadal timescales, with correlation coefficients of 0.8+ for regional temperature patterns. However, uncertainty increases with projection timescale and at regional scales. By 2100, ensemble spread (range among different GCMs) is often comparable to the forced signal, meaning we can be confident in the direction and broad magnitude of change but uncertain about precise values.

What is the difference between GCMs and Earth System Models?

GCMs simulate physical climate (atmosphere, ocean, ice, land) driven by prescribed external forcings (greenhouse gases, aerosols). Earth System Models add interactive modules for the carbon cycle, atmospheric chemistry, and ecosystem dynamics. ESMs are more complex but provide coupled feedbacks; GCMs are simpler and computationally cheaper for ensemble projections.

Why do different GCMs give different climate projections?

GCMs differ in spatial resolution, parameterization of subgrid processes (clouds, convection), land-surface schemes, ocean mixing, and parameter choices. These differences lead to different climate feedbacks, particularly cloud feedback, which varies among models. Using multiple GCMs (ensemble multi-model approach) is essential to characterize uncertainty.

Can GCMs predict weather weeks or months in advance?

GCMs are not designed for weather prediction; they lack the initialization and data assimilation procedures used in weather models. GCMs can sometimes provide seasonal forecast skill (e.g., El Niño forcing can predict temperature/precipitation anomalies 3–6 months ahead), but this is not their primary purpose. Weather prediction uses specialized models (e.g., ECMWF, NOAA GEFS) updated daily with observations.

Sources

  1. Manabe, S., & Wetherald, R. T. (1975). The effects of doubling the CO2 concentration on the climate of a general circulation model. Journal of the Atmospheric Sciences, 32(1), 3-15. DOI: 10.1175/1520-0469(1975)032<0003:TEODTC>2.0.CO;2 ↗
  2. IPCC (2021). Climate Change 2021: The Physical Science Basis. Sixth Assessment Report. link ↗

How to cite this page

ScholarGate. (2026, June 3). General Circulation Model. ScholarGate. https://scholargate.app/en/geophysics/general-circulation-model

Related methods

NDVIOcean-Atmosphere Coupled ModelStandardized Precipitation Index

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

  • NDVIGeophysics↔ compare
  • Ocean-Atmosphere Coupled ModelGeophysics↔ compare
  • Standardized Precipitation IndexGeophysics↔ compare
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Referenced by

Aerosol Optical DepthNDVIOcean-Atmosphere Coupled ModelStandardized Precipitation Evapotranspiration IndexStandardized Precipitation IndexSWAT Model

Similar methods

Ocean-Atmosphere Coupled ModelWRF ModelCrop Simulation ModelingCrop Growth ModelStorm Surge ModelingCrop Growth SimulationSpectral Bin MicrophysicsSWAT Model

Related reference concepts

General Circulation and Earth System ModelsClimate ModelingNumerical Weather PredictionEmission Scenarios and Climate ProjectionsWeather ForecastingClimate System and Energy Balance

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — General Circulation Model (General Circulation Model). Retrieved 2026-07-21 from https://scholargate.app/en/geophysics/general-circulation-model · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Syukuro Manabe and Richard Wetherald
Subfamily
Climate simulation and modeling
Year
1975
Type
Deterministic coupled atmosphere-ocean simulation
Related methods
NDVIOcean-Atmosphere Coupled ModelStandardized Precipitation Index
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