Lesson 5.4.3

5.4.3 Predictions, models and their limitations Quiz: Pearson Edexcel Biology A (Salters-Nuffield), Unit 5

20 questions

Written by Revision Ninja · Last reviewed 11 October 2026

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Lesson 5.4.3, Predictions, models and their limitations: 20 multiple choice questions for the Pearson Edexcel Biology A (Salters-Nuffield) (9BI0), Unit 5: On the Wild Side, written with Revision Ninja.

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The 20 questions

  1. What is meant by extrapolation of climate data?

    • Measuring the same data again in exactly the same way
    • Extending a data trend beyond the measured range
    • Ignoring the trend in the data entirely
    • Averaging all the data into a single value

  2. Why are models used to predict future climate change?

    • They combine physical processes and data to test scenarios
    • They produce exact certainty about the future climate
    • They replace the need for any measurement of climate
    • They show the past climate with no uncertainty

  3. Which is a limitation of climate models?

    • They ignore all physical processes in the atmosphere
    • They can give exact predictions for every region with certainty
    • They rely on assumptions and uncertain feedbacks
    • They cannot be run on computers at all

  4. Why is it hard to predict the behaviour of clouds in a climate model?

    • Clouds can be measured perfectly at every point on Earth
    • Clouds are always identical across the globe
    • Clouds have no effect on the climate at all
    • Cloud processes are small-scale and complex

  5. Which statement about future scenarios in climate models is correct?

    • Scenarios predict exactly one future that will certainly happen
    • Scenarios test different assumed emission levels
    • Scenarios are only used for past climate
    • Scenarios are not based on any data at all

  6. A model predicts a temperature rise under one emissions scenario and a smaller rise under a lower-emissions scenario. What does this show?

    • The predicted temperature is always the same under every scenario
    • Emissions have no effect on temperature
    • The models are useless because they disagree
    • Predictions depend on assumed emissions, so action matters

  7. Why might climate predictions be more reliable for global averages than for local weather?

    • Global averages cannot be predicted at all
    • Local weather is always easier to predict than global averages
    • Local weather is unaffected by the climate system
    • Global averages smooth out local variability, so trends are easier to predict

  8. A model is tested by comparing its predictions with data from past decades. Why is this done?

    • To check the model reproduces observed changes
    • To remove the need for future predictions
    • To prove the model is always right in the future
    • To change the data so that it fits the model

  9. Which factor is a source of uncertainty in climate predictions?

    • The colour of the models' computer screens
    • The number of trees in a single garden
    • The age of the researchers running the model
    • Future human decisions about emissions and land use

  10. A student says climate models are useless because they cannot predict exact temperatures for next year. What is the best evaluation?

    • Models suit long-term trends more than exact yearly values
    • Models are perfect and have no uncertainty at all
    • The student is correct because models never predict anything correctly
    • The student is correct because models only use past data

  11. Which statement about conclusions on controversial climate issues is supported by the specification?

    • No conclusions on climate can ever be drawn from evidence
    • Conclusions on climate are always objective whoever reaches them
    • Only one group of scientists is allowed to draw conclusions
    • Some controversial conclusions depend on who reaches them

  12. Why does a model need to include feedback mechanisms to give reliable predictions?

    • Feedbacks always cancel out all changes in climate
    • Feedbacks make models impossible to run
    • Feedbacks are only relevant to ocean currents and nothing else
    • Feedbacks can amplify or reduce the original change

  13. Which example illustrates a positive feedback in the climate system?

    • Cooler temperatures causing more sunlight to be absorbed
    • Melting ice reducing reflectivity so more sunlight is absorbed, causing further melting
    • Increased rainfall cooling the surface and reducing warming
    • Trees growing faster and absorbing more CO2 indefinitely with no limit

  14. A model's projected warming differs from an observed value. What is the best first step for scientists?

    • Stop comparing the model with observations
    • Check assumptions and data, then refine the model
    • Discard all data that does not fit the model
    • Assume the observed value must be wrong without checking

  15. Why are predictions presented as ranges with uncertainty in climate reports?

    • To guarantee that the lower bound will happen
    • Because ranges are not used in any scientific field
    • To show likely outcomes given model limits
    • To hide the fact that the models are uncertain

  16. Data are extrapolated to predict future values. Which is a risk of extrapolation?

    • Extrapolation can only be used on past data with no trend
    • The trend may change beyond the measured range
    • Extrapolation always gives exact future values
    • Extrapolation removes all uncertainty from the data

  17. Which is a benefit of using models rather than only observing the climate?

    • Models make the climate easier to measure directly
    • Models prove climate change has no cause
    • Models replace the need for any observations
    • Models let scientists test possible futures and actions

  18. What should a student consider when judging a climate model's prediction?

    • Only the colour of the graph used to show the prediction
    • Only whether the prediction matches the student's expectations
    • Only the number of pages in the report
    • Assumptions, input data quality and past performance

  19. A thermostat switches off a heater when a room warms above a set point. What type of feedback is this?

    • Random feedback, with no effect on temperature
    • Positive feedback, which amplifies the original change
    • No feedback, because the heater is not connected to the room
    • Negative feedback, which reduces the original change

  20. Why is it important for climate models to be open to peer review?

    • So that the model stops changing once it is published
    • So others can check assumptions and results
    • So that the model's predictions become certain
    • So that models can avoid being tested against data

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