General circulation model
A general circulation model (GCM) is a type of climate model. It employs a mathematical model of the general circulation of a planetary atmosphere or ocean. It uses the Navier–Stokes equations on a rotating sphere with thermodynamic terms for various energy sources (radiation, latent heat). These equations are the basis for computer programs used to simulate the Earth's atmosphere or oceans. Atmospheric and oceanic GCMs (AGCM and OGCM) are key components along with sea ice and land-surface components.
GCMs and global climate models are used for weather forecasting, understanding the climate, and forecasting climate change.
Atmospheric GCMs (AGCMs) model the atmosphere and impose
Versions designed for decade to century time scale climate applications were originally created by Syukuro Manabe and Kirk Bryan at the Geophysical Fluid Dynamics Laboratory (GFDL) in Princeton, New Jersey.[1] These models are based on the integration of a variety of fluid dynamical, chemical and sometimes biological equations.
Terminology
The acronym GCM originally stood for General Circulation Model. Recently, a second meaning came into use, namely Global Climate Model. While these do not refer to the same thing, General Circulation Models are typically the tools used for modelling climate, and hence the two terms are sometimes used interchangeably. However, the term "global climate model" is ambiguous and may refer to an integrated framework that incorporates multiple components including a general circulation model, or may refer to the general class of climate models that use a variety of means to represent the climate mathematically.
Atmospheric and oceanic models
Atmospheric (AGCMs) and oceanic GCMs (OGCMs) can be coupled to form an atmosphere-ocean coupled general circulation model (CGCM or AOGCM). With the addition of submodels such as a sea ice model or a model for evapotranspiration over land, AOGCMs become the basis for a full climate model.[4]
Structure
General Circulation Models (GCMs) discretise the equations for fluid motion and energy transfer and integrate these over time. Unlike simpler models, GCMs divide the atmosphere and/or oceans into grids of discrete "cells", which represent computational units. Unlike simpler models which make mixing assumptions, processes internal to a cell—such as convection—that occur on scales too small to be resolved directly are parameterised at the cell level, while other functions govern the interface between cells.
Three-dimensional (more properly four-dimensional) GCMs apply discrete equations for fluid motion and integrate these forward in time. They contain parameterisations for processes such as convection that occur on scales too small to be resolved directly.
A simple general circulation model (SGCM) consists of a dynamic core that relates properties such as temperature to others such as pressure and velocity. Examples are programs that solve the primitive equations, given energy input and energy dissipation in the form of scale-dependent friction, so that atmospheric waves with the highest wavenumbers are most attenuated. Such models may be used to study atmospheric processes, but are not suitable for climate projections.
Atmospheric GCMs (AGCMs) model the atmosphere (and typically contain a land-surface model as well) using imposed sea surface temperatures (SSTs).[5] They may include atmospheric chemistry.
AGCMs consist of a dynamical core which integrates the equations of fluid motion, typically for:
- surface pressure
- horizontal components of velocity in layers
- temperature and water vapor in layers
- radiation, split into solar/short wave and terrestrial/infrared/long wave
- parametersfor:
- convection
- land surface processes
- albedo
- hydrology
- cloud cover
A GCM contains
OGCMs model the ocean (with fluxes from the atmosphere imposed) and may contain a sea ice model. For example, the standard resolution of HadOM3 is 1.25 degrees in latitude and longitude, with 20 vertical levels, leading to approximately 1,500,000 variables.
AOGCMs (e.g.
Grid
The fluid equations for AGCMs are made discrete using either the
For a standard finite difference model, uniform gridlines converge towards the poles. This would lead to computational instabilities (see CFL condition) and so the model variables must be filtered along lines of latitude close to the poles. Ocean models suffer from this problem too, unless a rotated grid is used in which the North Pole is shifted onto a nearby landmass. Spectral models do not suffer from this problem. Some experiments use geodesic grids[10] and icosahedral grids, which (being more uniform) do not have pole-problems. Another approach to solving the grid spacing problem is to deform a Cartesian cube such that it covers the surface of a sphere.[11]
Flux buffering
Some early versions of AOGCMs required an ad hoc process of "flux correction" to achieve a stable climate. This resulted from separately prepared ocean and atmospheric models that each used an implicit flux from the other component different than that component could produce. Such a model failed to match observations. However, if the fluxes were 'corrected', the factors that led to these unrealistic fluxes might be unrecognised, which could affect model sensitivity. As a result, the vast majority of models used in the current round of IPCC reports do not use them. The model improvements that now make flux corrections unnecessary include improved ocean physics, improved resolution in both atmosphere and ocean, and more physically consistent coupling between atmosphere and ocean submodels. Improved models now maintain stable, multi-century simulations of surface climate that are considered to be of sufficient quality to allow their use for climate projections.[12]
Convection
Moist convection releases latent heat and is important to the Earth's energy budget. Convection occurs on too small a scale to be resolved by climate models, and hence it must be handled via parameters. This has been done since the 1950s. Akio Arakawa did much of the early work, and variants of his scheme are still used,[13] although a variety of different schemes are now in use.[14][15][16] Clouds are also typically handled with a parameter, for a similar lack of scale. Limited understanding of clouds has limited the success of this strategy, but not due to some inherent shortcoming of the method.[17]
Software
Most models include software to diagnose a wide range of variables for comparison with observations or study of atmospheric processes. An example is the 2-metre temperature, which is the standard height for near-surface observations of air temperature. This temperature is not directly predicted from the model but is deduced from surface and lowest-model-layer temperatures. Other software is used for creating plots and animations.
Projections
Coupled AOGCMs use transient climate simulations to project/predict climate changes under various scenarios. These can be idealised scenarios (most commonly, CO2 emissions increasing at 1%/yr) or based on recent history (usually the "IS92a" or more recently the SRES scenarios). Which scenarios are most realistic remains uncertain.
The 2001 IPCC Third Assessment Report Figure 9.3 shows the global mean response of 19 different coupled models to an idealised experiment in which emissions increased at 1% per year.[19] Figure 9.5 shows the response of a smaller number of models to more recent trends. For the 7 climate models shown there, the temperature change to 2100 varies from 2 to 4.5 °C with a median of about 3 °C.
Future scenarios do not include unknown events – for example, volcanic eruptions or changes in solar forcing. These effects are believed to be small in comparison to greenhouse gas (GHG) forcing in the long term, but large volcanic eruptions, for example, can exert a substantial temporary cooling effect.
Human GHG emissions are a model input, although it is possible to include an economic/technological submodel to provide these as well. Atmospheric GHG levels are usually supplied as an input, though it is possible to include a carbon cycle model that reflects vegetation and oceanic processes to calculate such levels.
Emissions scenarios
For the six SRES marker scenarios, IPCC (2007:7–8) gave a "best estimate" of global mean temperature increase (2090–2099 relative to the period 1980–1999) of 1.8 °C to 4.0 °C.[20] Over the same time period, the "likely" range (greater than 66% probability, based on expert judgement) for these scenarios was for a global mean temperature increase of 1.1 to 6.4 °C.[20]
In 2008 a study made climate projections using several emission scenarios.[21] In a scenario where global emissions start to decrease by 2010 and then declined at a sustained rate of 3% per year, the likely global average temperature increase was predicted to be 1.7 °C above pre-industrial levels by 2050, rising to around 2 °C by 2100. In a projection designed to simulate a future where no efforts are made to reduce global emissions, the likely rise in global average temperature was predicted to be 5.5 °C by 2100. A rise as high as 7 °C was thought possible, although less likely.
Another no-reduction scenario resulted in a median warming over land (2090–99 relative to the period 1980–99) of 5.1 °C. Under the same emissions scenario but with a different model, the predicted median warming was 4.1 °C.[22]
Model accuracy
This section needs to be updated.(August 2015) |
AOGCMs internalise as many processes as are sufficiently understood. However, they are still under development and significant uncertainties remain. They may be coupled to models of other processes in
Imperfect models may nevertheless produce useful results. GCMs are capable of reproducing the general features of the observed global temperature over the past century.[23]
A debate over how to reconcile climate model predictions that upper air (tropospheric) warming should be greater than observed surface warming, some of which appeared to show otherwise,[26] was resolved in favour of the models, following data revisions.
Climate researchers around the world use climate models to understand the climate system. Thousands of papers have been published about model-based studies. Part of this research is to improve the models.
In 2000, a comparison between measurements and dozens of GCM simulations of
The precise magnitude of future changes in climate is still uncertain;[31] for the end of the 21st century (2071 to 2100), for SRES scenario A2, the change of global average SAT change from AOGCMs compared with 1961 to 1990 is +3.0 °C (5.4 °F) and the range is +1.3 to +4.5 °C (+2.3 to 8.1 °F).
The IPCC's
Relation to weather forecasting
The global climate models used for climate projections are similar in structure to (and often share computer code with) numerical models for weather prediction, but are nonetheless logically distinct.
Most
Computations
Climate models use
All climate models take account of incoming energy 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.
The most talked-about models of recent years relate temperature to
Three (or more properly, four since time is also considered) dimensional GCM's discretise the equations for fluid motion and energy transfer and integrate these over time. They also contain parametrisations for processes such as convection that occur on scales too small to be resolved directly.
Atmospheric GCMs (AGCMs) model the atmosphere and impose sea surface temperatures as boundary conditions. Coupled atmosphere-ocean GCMs (AOGCMs, e.g. HadCM3, EdGCM, GFDL CM2.X, ARPEGE-Climat[37]) combine the two models.
Models range in complexity:
- A simple radiant heattransfer model 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 discretise and solve the full equations for mass and energy transfer and radiant exchange.
- Box models treat flows across and within ocean basins.
Other submodels can be interlinked, such as land use, allowing researchers to predict the interaction between climate and ecosystems.
Comparison with other climate models
Earth-system models of intermediate complexity (EMICs)
The Climber-3 model uses a 2.5-dimensional statistical-dynamical model with 7.5° × 22.5° resolution and time step of 1/2 a day. An oceanic submodel is MOM-3 (Modular Ocean Model) with a 3.75° × 3.75° grid and 24 vertical levels.[38]
Radiative-convective models (RCM)
One-dimensional, radiative-convective models were used to verify basic climate assumptions in the 1980s and 1990s.[39]
Earth system models
GCMs can form part of
History
In 1956,
See also
- Atmospheric Model Intercomparison Project (AMIP)
- Atmospheric Radiation Measurement(ARM) (in the US)
- Earth Simulator
- Global Environmental Multiscale Model
- Ice-sheet model
- Intermediate General Circulation Model
- NCAR
- Prognostic variable
References
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- ^ "Pubs.GISS: Sun and Hansen 2003: Climate simulations for 1951-2050 with a coupled atmosphere-ocean model". pubs.giss.nasa.gov. 2003. Retrieved 25 August 2015.
- ^ "Atmospheric Model Intercomparison Project". The Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory. Retrieved 21 April 2010.
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(help) See also Jablonowski, Christiane. "Adaptive Mesh Refinement (AMR) for Weather and Climate Models". Archived - ^ NCAR Command Language documentation: Non-uniform grids that NCL can contour Archived 3 March 2016 at the Wayback Machine (Retrieved 24 July 2010)
- ^ "High Resolution Global Environmental Modelling (HiGEM) home page". Natural Environment Research Council and Met Office. 18 May 2004.
- ^ "Mesoscale modelling". Archived from the original on 29 December 2010. Retrieved 5 October 2010.
- ^ "Climate Model Will Be First To Use A Geodesic Grid". Daly University Science News. 24 September 2001.
- ^ "Gridding the sphere". MIT GCM. Retrieved 9 September 2010.
- ^ "IPCC Third Assessment Report - Climate Change 2001 - Complete online versions". IPCC. Archived from the original on 12 January 2014. Retrieved 12 January 2014.
- ^ "Arakawa's Computation Device". Aip.org. Retrieved 18 February 2012.
- ^ "COLA Report 27". Grads.iges.org. 1 July 1996. Archived from the original on 6 February 2012. Retrieved 18 February 2012.
- ^ "Table 2-10". Pcmdi.llnl.gov. Retrieved 18 February 2012.
- ^ "Table of Rudimentary CMIP Model Features". Rainbow.llnl.gov. 2 December 2004. Retrieved 18 February 2012.
- ^ "General Circulation Models of the Atmosphere". Aip.org. Archived from the original on 30 July 2012. Retrieved 18 February 2012.
- ^ a b NOAA Geophysical Fluid Dynamics Laboratory (GFDL) (9 October 2012), NOAA GFDL Climate Research Highlights Image Gallery: Patterns of Greenhouse Warming, NOAA GFDL
- ^ "Climate Change 2001: The Scientific Basis". Grida.no. Archived from the original on 18 February 2012. Retrieved 18 February 2012.
- ^ a b "Chapter 3: Projected climate change and its impacts". IPCC Fourth Assessment Report: Climate Change 2007: Synthesis Report: Synthesis Report Summary for Policymakers. Archived from the original on 9 March 2013. Retrieved 3 December 2013., in IPCC AR4 SYR 2007
- ^ Pope, V. (2008). "Met Office: The scientific evidence for early action on climate change". Met Office website. Archived from the original on 29 December 2010.
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- ^ The National Academies Press website press release, 12 Jan. 2000: Reconciling Observations of Global Temperature Change.
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Further reading
- Ian Roulstone & John Norbury (2013). Invisible in the Storm: the role of mathematics in understanding weather. Princeton University Press. ISBN 978-0691152721.
External links
- IPCC AR5, Evaluation of Climate Models
- "High Resolution Climate Modeling". – with media including videos, animations, podcasts and transcripts on climate models
- "Flexible Modeling System (FMS)". Geophysical Fluid Dynamics Laboratory. – GFDL's Flexible Modeling System containing code for the climate models
- Program for climate model diagnosis and intercomparison (PCMDI/CMIP)
- National Operational Model Archive and Distribution System (NOMADS) Archived 30 January 2016 at the Wayback Machine
- Hadley Centre for Climate Prediction and Research – model info
- NCAR/UCAR Community Climate System Model (CESM)
- Climate prediction, community modeling
- NASA/GISS, primary research GCM model
- EDGCM/NASA: Educational Global Climate Modeling Archived 23 March 2015 at the Wayback Machine
- NOAA/GFDL
- MAOAM: Martian Atmosphere Observation and Modeling / MPI & MIPT