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How Climate Models Work

Climate models are some of the most important tools used to understand Earth’s climate system. At their core, they are mathematical models that simulate how energy moves between the atmosphere, oceans, land surface, and ice. That may sound abstract, but the basic idea is surprisingly intuitive: if scientists can represent how heat and energy flow through the planet, they can study how climate behaved in the past, how it works in the present, and how it may change in the future.

These models are used for more than one timescale or purpose. They help researchers investigate the dynamics of weather and climate, and they are also used to make projections about future climate conditions. In other words, climate models are not just about forecasting tomorrow’s weather. They are designed to examine the longer-term patterns and variability that define climate itself.

Climate is bigger than weather

To understand climate models, it helps to first understand what climate means. Climate is the long-term weather pattern in a region, typically averaged over 30 years. More rigorously, it includes both the mean and the variability of meteorological variables over periods ranging from months to thousands or even millions of years.

Those variables often include temperature, precipitation, wind, humidity, and atmospheric pressure. In a broader sense, climate also includes the condition of the full climate system: the atmosphere, hydrosphere, cryosphere, lithosphere, and biosphere, plus the interactions among them.

A few of those terms are worth unpacking:

The climate system models try to represent

The atmosphere is the layer of gases surrounding Earth. The hydrosphere refers to Earth’s water, including oceans and other bodies of water. The cryosphere is the frozen part of the planet, such as ice and snow. The lithosphere is the solid outer part of Earth, including land. The biosphere includes living things.

Climate models aim to simulate interactions across these connected parts of the planet. That matters because climate is not controlled by one single factor. It is shaped by latitude, longitude, terrain, altitude, land use, and nearby water bodies and their currents. Ocean circulation can redistribute heat, vegetation can affect how much solar energy is absorbed, and greenhouse gases can influence how much energy the planet retains.

A climate model tries to capture these linked processes in a quantitative way.

The central idea: Earth’s energy balance

Everything in climate modeling revolves around energy balance. Climate models balance, or very nearly balance, incoming energy from the Sun with outgoing energy leaving Earth.

The incoming energy is described as short wave electromagnetic radiation, including visible light. The outgoing energy is long wave electromagnetic radiation, which is infrared radiation emitted by Earth.

If those two flows are in balance, the planet’s average temperature stays relatively stable. If there is an imbalance, average temperature changes. This is why energy balance is so central to climate science: even a persistent mismatch between incoming and outgoing energy can shift the climate.

Scientists have identified Earth’s Energy Imbalance, or EEI, as a fundamental metric of the status of global change. In simple terms, it is a measure of whether the planet is gaining more energy than it loses, or vice versa.

How climate models are built

Climate models use quantitative methods and a series of physics equations to simulate how radiative energy is transferred and how the atmosphere, oceans, land surface, and ice interact. Rather than treating climate as a vague pattern, they turn the system into something that can be calculated.

Some models are relatively simple. For example, a simple radiant heat transfer model can treat Earth as a single point and average the outgoing energy. From there, models can be expanded vertically, as in radiative-convective models, or horizontally.

The most complex models go much further. Coupled atmosphere–ocean–sea ice global climate models divide the planet into many pieces and solve full equations for mass transfer, energy transfer, and radiant exchange. The word coupled is important: it means the atmosphere, ocean, and ice are not modeled as isolated parts, but as interacting systems.

That interaction is essential because climate depends on constant exchanges between these components. Oceans store and move heat, ice changes how much sunlight is reflected, and the land surface influences temperature and moisture.

Resolution: from global view to local detail

Not all climate models operate at the same scale. Climate models exist at different resolutions, ranging from more than 100 kilometers to around 1 kilometer. Resolution describes the level of detail in the model.

A lower-resolution global model covers the entire planet but represents it in larger chunks. That makes it useful for studying worldwide patterns, but less precise for local impacts. A higher-resolution model can capture more detailed regional features, but it requires much greater computational resources.

Because very high resolution global climate models are so demanding, only a few global datasets exist at that level. To bridge the gap between global patterns and local consequences, scientists use downscaling.

Downscaling means taking information from a larger-scale global climate model and adjusting it to provide more local detail. Global climate models can be dynamically downscaled or statistically downscaled into regional climate models. This is especially useful for analyzing how climate change may affect a specific area rather than the planet as a whole.

Why greenhouse gases matter so much in these models

The most talked-about use of climate models in recent years has been to infer the consequences of increasing greenhouse gases in the atmosphere, especially carbon dioxide.

Greenhouse gases affect the amount of solar energy retained by the planet. Changes in the quantity of atmospheric greenhouse gases, particularly carbon dioxide and methane, can lead to global warming or global cooling by altering how much energy remains in the climate system.

When models simulate rising greenhouse gas concentrations, they predict an upward trend in global mean surface temperature. The most rapid increase in temperature is projected for the higher latitudes of the Northern Hemisphere.

This use of models matters because climate change can unfold across many timescales, from decades to millions of years. While climate can shift because of internal Earth processes, external forces such as changes in sunlight intensity, or human activities, recent warming is discussed in terms of global warming tied to greenhouse gas emissions.

Models help connect past, present, and future

Climate models are not only about future projections. They are also part of the broader effort to understand climate over time.

The study of ancient climates is called paleoclimatology. Because there were very few direct observations before the 19th century, earlier climates are inferred using proxy variables. These include non-biotic evidence such as sediments in lake beds and ice cores, and biotic evidence such as tree rings and coral.

Modern climate records, by contrast, come from direct measurements using instruments such as thermometers, barometers, and anemometers. Since the 1960s, satellites have allowed records to be gathered on a global scale, including in remote places like the Arctic region and oceans.

Climate models help make sense of all this evidence. They provide a framework for studying how climate behaved under different conditions and how different parts of the climate system interact.

Climate variability versus climate change

Another reason climate models are important is that climate is not static. Climate variability refers to variations in the mean state and other characteristics of climate across spatial and temporal scales beyond individual weather events.

Some variability is random, sometimes called noise. Other variability is more periodic and appears in recurring climate patterns or modes of variability. There are also correlations between climate oscillations and astronomical factors, as well as modes of heat distribution in the ocean-atmosphere climate system.

Climate change, meanwhile, refers to variation in global or regional climates over time. It reflects changes in the average state or variability of the atmosphere over periods ranging from decades to millions of years. In recent usage, especially in environmental policy, the term often refers to changes in modern climate, including the rise in average surface temperature known as global warming.

Climate models are valuable because they help distinguish between background variability and longer-term shifts in the climate system.

Why these models matter

Climate is influenced by many interacting factors, and those interactions are complex. Yet the broad outlines of the system are sufficiently understood to be represented mathematically. That is what makes climate models so powerful.

They are tools for testing ideas about how the climate system works. They simulate the movement of energy through atmosphere, ocean, land, and ice. They show why energy balance matters. They allow global patterns to be translated into regional detail through downscaling. And they are central to understanding the effects of increasing greenhouse gases.

In short, climate models are planet simulators built from physics equations and observations, designed to help us understand one of the most complex systems on Earth.