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What is a climate model?

A climate model is a computer simulation of the Earth’s climate system, including the atmosphere, ocean, land and ice. They can be used to recreate the past climate or predict the future climate.

Climate models calculate many different properties of the climate, including atmospheric temperature, pressure, wind, and humidity.  The models calculate these properties for thousands and thousands of different points on a three-dimensional grid. In fact, there are so many mathematical equations involved that a typical climate model includes enough code to fill 18,000 pages of printed text.

By solving the relevant mathematical equations, the climate model is able to calculate how the state of the atmosphere and ocean evolves over time.

Why use climate models?

Climate models help scientists to test their understanding of our climate system, and to predict future changes to our climate.

Scientists use climate models to evaluate their understanding of the climate, and test out their ideas. For example, they could run a simulation of the atmosphere over the UK. Then, they could compare the results to real-world observations of the atmosphere over the UK. This would show them how accurate their computer model is or where it needs improvement. 

Scientists also use climate models to predict the future climate. For example, they can input different scenarios for global warming and see the effects on our climate. This is how we know what the impacts of global warming are likely to be. The Intergovernmental Panel for Climate Change recently investigated the impacts of 1.5°C of warming above pre-industrial temperatures by using climate models.

Are climate models reliable?

Scientists are confident that climate models accurately represent our climate system because they are based on theories that have been understood for many years, they are verified against real world observations, and they make accurate predictions. 

Climate models are based on physical principles that have been understood for many years, such as the conservation of energy. These principles are the foundation of our understanding of climate and weather.

Climate models are also checked by running simulations of past events. We have real-world observations from the past, so we can test if the climate model is accurate or not.

Lastly, climate models have successfully predicted patterns in our climate, such as the El Niño phenomenon.

Like many aspects of science, climate models are constantly improving and there is often a small margin of error on their results.

No climate model is perfect, but scientists work hard to identify any weaknesses in their model, and communicate the reliability of different climate models when they publish results.

Climate models are usually run on large supercomputers, provided by organisations such as the Centre for Environmental Data Analysis

How to improve climate models?

There are many ways to improve climate models. Scientists continually test their models with new observations to assess their reliability, and to identify where improvements are needed. 

One of the big challenges for scientists is creating climate models that display the earth in high-resolution. Higher resolution models will allow scientists to zoom in on certain regions, such as the South of England, and see the effects of climate change on local scales. 

Scientists divide the earth into a three dimensional grid to run climate simulations. Previously, these grid squares were around 200km by 200km. Now, scientists are able to calculate the climate using a grid that is 25km by 25km. This means we can see individual weather systems, like storms.

Scientists are also trying to create climate models that take more aspects of the climate into account. The latest generation of climate models are known as Earth System Models. This is a specific type of model that incorporates chemical and biological processes into the picture. Recently, we helped the UK to develop its first Earth System Model

Often, the biggest problem that scientists face is finding enough computing power to run higher resolution models. Higher resolution models can require supercomputers the size of a tennis court, and take a long time to run.