Models

Written by: Alistair Marjot

Reviewed by: Bridgette Barrett

A model is a simplified version of reality
A model is often used to represent a system
- The model can then be analysed or tested to learn more about how the system works and to predict how the system might respond to change
- For example, weather models are used to predict how our weather systems change over time, allowing us to create weather forecasts

Some models can be very simple, such as a child’s model car, whilst other models can be highly complex and require the power of supercomputers, such as the computer models that are currently being used to predict how our climate will change in the future
- To some extent, due to their very nature, all models involve some level of approximation or simplification, and therefore some loss of accuracy (even the very powerful and complex models)

Strengths and Limitations of Models

Strengths	Limitations
Models simplify complex systems	Models can be oversimplified and inaccurate
Models allow predictions to be made about how systems will react in response to change	Results from models depend on the quality of the data inputs going into them
System inputs can be changed to observe effects and outputs, without the need to wait for real-life events to occur	Results from models become more uncertain the further they predict into the future
Models are easier to understand than the real system	Different models can show vastly different outputs even if they are given the same data inputs
Results from models can be shared between scientists, engineers, companies and communicated to the public	Results from models can be interpreted by different people in different ways
Results from models can warn us about future environmental issues and how to avoid them or minimise their impact	Environmental systems are often incredibly complex, with many interacting factors - it is impossible to take all possible variables into account

Last updated: 27 September 2024

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