Predicting climate change: extrapolation and models

Energy Flow, Ecosystems and the Environment · Climate change · note 4 of 7

Spec 5.19

A Level only

A Level only: only in the full A Level, not the AS Level. AS Level students can skip it. What the labels mean

Download all Climate change notes (PDF)Download all notes (PDF)9 pages

Predicting climate change: extrapolation and modelsSpec 5.19

In short

Extrapolation extends a trend in existing data beyond the range measured to make predictions, and these predictions are built into mathematical models of future climate change. Models have limitations: the climate is a complex system with many interacting factors and feedback loops, data are incomplete, and predictions depend on assumptions about future emissions.

Extrapolation means extending a line or curve beyond the measured data to predict what might happen in the future. Predictions are used in models of future climate change, which use data on greenhouse gas concentrations, temperature, ice cover and ocean currents to estimate how much warming might occur under different assumptions (for example scenarios of high or low emissions).

Graph of atmospheric CO2 concentration against year: a solid line of measured data to 2020 and dashed extrapolated lines to 2100 for high, intermediate and low emission scenarios, each with a shaded range of uncertainty. — Extrapolating measured CO₂ data to 2100 under different emission scenarios (values illustrative).

Limitations of models

The climate is a complex system with many interacting factors (oceans, clouds, ice, vegetation, volcanic activity), and it is not possible to include them all accurately.
Models contain feedback loops, which are hard to represent. Positive feedback increases the change: for example, melting ice exposes darker surfaces that absorb more heat; warming thaws permafrost and releases methane. Negative feedback reduces change: for example, more CO₂ may increase plant growth.
Data may be incomplete or unreliable, especially for the past and for remote areas, and small errors in the data are amplified in the predictions.
Extrapolation assumes that the trend continues as it has done, which may not be true. Predictions depend on assumptions about future human behaviour, such as emissions and population growth, which cannot be known.
Different models give different predictions, so there is uncertainty. A model can be tested by checking whether it reproduces known past climates.

Exam tip:

A 'limitation' needs a reason. Write 'the model may not predict accurately because it cannot include all the variables, such as feedback from melting ice' rather than just 'models are not accurate'.

Written and checked against the Edexcel International A Level Biology (YBI11) specification · Updated October 2026

Frequently asked questions

What evidence is there for climate change?

Evidence includes direct records of atmospheric carbon dioxide and global temperature, and indirect evidence such as pollen preserved in peat bogs and tree ring widths (dendrochronology). Together these show past and present changes, and the correlation between carbon dioxide and temperature is supported by the greenhouse effect mechanism.

How do greenhouse gases cause global warming?

Greenhouse gases such as carbon dioxide and methane absorb infra-red radiation emitted by Earth’s warmed surface and re-radiate it, some back to the surface. Higher concentrations from human activities trap more heat, so the lower atmosphere warms. This is the enhanced greenhouse effect.

How can the carbon cycle be used to reduce atmospheric carbon dioxide?

Methods increase removal or reduce release. Planting trees raises photosynthesis, protecting forests and peat bogs keeps carbon stored, and replacing fossil fuels with renewable energy or biofuels reduces combustion. Each method acts on a specific stage of the carbon cycle.

All 5 questions on Climate change