About Global Climate Models

What is a Global Climate Model?

A Global Climate Model (GCM), also known as a general circulation model, is a mathematical model of the circulation of the Earth's atmosphere and ocean. Atmospheric and oceanic GCMs are key components of global climate models along with sea ice and land-surface components. GCMs and global climate models are widely applied for weather forecasting, understanding the climate, and projecting climate change. The first general circulation climate model that combined both oceanic and atmospheric processes was originally created in the 1960s at the Geophysical Fluid Dynamics Laboratory in Princeton, New Jersey (NOAA, 2012). Scientists were for the first time able to understand how the ocean and atmosphere interacted with each other to influence climate. The model still stands today as a breakthrough of enormous importance for climate science and weather forecasting. Since then additional GCMs have been developed based on the integration of a variety of fluid dynamical, chemical, and sometimes biological equations.

What are Climate Change Scenarios or "Futures"?

Climate change scenarios, also called "futures" and "future scenarios" are plausible climate sequences that might affect California in the next century. They are expressed in spatial datasets providing projected climatic and sometimes other data (such as hydrologic, see the California Basin Characterization Model) created using one or more climate models combined with emissions scenarios in a modeling program formulated to simulate conditions at a future time period by iteratively combining inter-dependent factors. To create climate change scenarios that inform work done at a regional scale such as for California, it is necessary to translate the GCMs to the finer scale via a process of downscaling.

To inform research on climate change in California, Cayan et. al. selected and evaluated GCMs from the IPCC Fourth Assessment from the Parallel Climate Model (PCM1) from NCAR and DOE, and the NOAA Geophysical Fluid Dynamics Laboratory CM2.1 model (GFDL). Temperatures over California warm significantly during the twenty-first century in each simulation, with end-of-century temperature increases from approximately +1.5°C under the lower emissions B1 scenario in the less responsive PCM1 to +4.5°C in the higher emissions A2 scenario within the more responsive GFDL model.

Climate scenarios offer one way to identify and examine the land management challenges posed by climate change. Selecting projections, however, requires careful consideration of the natural resources under study, and where and how they are sensitive to climate. Selection also depends on the robustness of different projections for the resources and geographic area of interest, and possibly on what climate projections are available for a region.

Rather than a misguided attempt to identify the "most accurate" climate scenario, managers are strongly encouraged to explore variability through the use of multiple climate scenarios. Considering a range of possible future climates facilitates the identification of management strategies to help ensure resilience of natural resource systems across a broad set of potential conditions. (Daniels, 2012)

Further Resources

A historical account by Spencer Weart of the development of GCMs is provided here as part of Weart's online treatise on the discovery of global warming. Paul Edwards has an article on the history of atmospheric general circulation modeling available here; also see his excellent book on informatics and the history of climate modeling A Vast Machine.

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