Why do scientists need models?
What does it mean when the newspaper reports the results of a scientist's most recent climate modelling? Scientists work with models when the system they are interested in studying is too complex, too remote, or too difficult to deal with as a whole. Models are necessary in science, but it must always be remembered that they are models.
Models are Useful Tools
are useful tools in science. Earth’s climate is extremely complex, with many factors that are dependent on one another. Such a system is impossible for scientists to work with as a whole. To deal with such complexity, scientists may create models to represent the system that they are interested in studying.
Scientists must validate their ideas by testing. A model can be manipulated and adjusted far more easily than a real system. Models help scientists understand, analyze, and make predictions about systems that would be impossible to study as a whole. If a scientist wants to understand how rising CO
levels will affect climate, it will be easier to model a smaller portion of that system. For example, he may model how higher levels of CO
affect plant growth and the effect that will have on climate.
Models can be Used to Make Predictions
How can scientists know if a model designed to predict the future is likely to be accurate, since it may not be possible to wait long enough to see if the prediction comes true? One way is to run the model using a time in the past as the starting point see if the model can accurately predict the present. A model that can successfully predict the present is more likely to be accurate when predicting the future.
Many models are created on computers because only computers can handle and manipulate such enormous amounts of data. For example, climate models are very useful for trying to determine what types of changes we can expect as the composition of the atmosphere changes. A reasonably accurate climate model would be impossible on anything other than the most powerful computers.
Models Have Limitations
Since models are simpler than real objects or systems, they have limitations. A model deals with only a portion of a system. It may not predict the behavior of the real system very accurately. But the more computing power that goes into the model and the care with which the scientists construct the model can increase the chances that a model will be accurate.
Types of Models
Physical models are smaller and simpler representations of the thing being studied. A globe or a map is a physical model of a portion or all of Earth.
Conceptual models tie together many ideas to explain a phenomenon or event.
Mathematical models are sets of equations that take into account many factors to represent a phenomenon. Mathematical models are usually done on computers.
A model is a representation of a more complex system. Models can be manipulated far more easily than the system they represent.
Models can be used to make predictions.
Models may be physical, conceptual, or mathematical.
Use this resource to answer the questions that follow.
1. What is a model?
2. How do scientists create models?
3. How are models checked for accuracy?
4. How did Dr. Hansen check his model?
5. What are the challenges associated with modeling?
1. If models have limitations, why do scientists use them?
2. What are some types of scientific models that you can name?
3. Imagine you make a model to predict an earthquake in a particular location. What factors would you need to include? How accurately do you think your model might predict that earthquake?