Climate Modeling
The numerical simulation of the climate system, from radiative-convective columns to coupled Earth system models, used to understand climate and project its future.
Definition
Climate modeling is the representation of the climate system through mathematical equations solved numerically on computers, ranging from idealized models that isolate single processes to coupled Earth system models that simulate the whole system and project its future.
Scope
This area covers the construction, use, and evaluation of numerical climate models. It treats the hierarchy of models from simple energy-balance and radiative-convective formulations to comprehensive general circulation and Earth system models, the parameterization of unresolved processes, the emission scenarios that drive projections, the downscaling of coarse output to regional scales, and the systematic evaluation and intercomparison of models against observations.
Sub-topics
Core questions
- How are the physical laws governing climate turned into a solvable numerical model?
- How are processes too small to resolve represented through parameterization?
- How are emission scenarios used to project future climate?
- How are models evaluated and their uncertainties characterized?
Key theories
- Hierarchy of climate models
- Models span a hierarchy from simple energy-balance and radiative-convective formulations that build understanding to comprehensive coupled models that simulate the full system, each suited to different questions.
- Parameterization of subgrid processes
- Processes smaller than the model grid, such as clouds, convection, and turbulence, are represented by parameterizations whose formulation strongly affects model behavior and is a key source of uncertainty.
Mechanisms
Climate models divide the atmosphere, ocean, and land into a three-dimensional grid and integrate the equations of motion, thermodynamics, and radiation forward in time, coupling the components so they exchange energy, water, and momentum. Processes finer than the grid are parameterized; the models are driven by prescribed forcings or emission scenarios, evaluated against observations and the historical record, and compared in coordinated intercomparison projects to gauge robustness and spread.
Clinical relevance
Climate models are the primary tools for projecting future climate under different emission pathways and for attributing observed change, making them the scientific foundation for climate policy, adaptation planning, and risk assessment.
Evidence & guidelines
The IPCC Sixth Assessment Report draws heavily on coordinated model intercomparisons to project future change, assesses that models reproduce many features of observed climate, and uses observational constraints to narrow the projected ranges.
History
Climate modeling grew from the first numerical weather forecasts and from Manabe and Wetherald's 1967 radiative-convective model, expanding through the 1970s and 1980s into coupled atmosphere-ocean general circulation models and, more recently, into Earth system models that include the carbon cycle and biogeochemistry.
Debates
- Treatment of clouds and model spread
- Differences in how models parameterize clouds and convection drive much of the spread in their climate sensitivity and projections, raising debate over how best to constrain and reduce it.
Key figures
- Syukuro Manabe
- Warren Washington
- Ann Henderson-Sellers
- Klaus Hasselmann
Related topics
Seminal works
- manabewetherald1967
- mcguffie2014
Frequently asked questions
- How does a climate model work?
- It divides the Earth into a grid and steps the physical equations for the atmosphere, ocean, and land forward in time, representing small-scale processes such as clouds through parameterizations.
- Can climate models be trusted?
- They reproduce many observed features of past and present climate and agree on the broad response to greenhouse gases, though uncertainties remain, especially in clouds and regional detail.