How the climate changes in the future depends on how much energy remains trapped in the atmosphere: trap more heat and the planet will warm, trap less heat and the planet will cool. One of the main factors that determines how much heat is trapped is the CO2 concentration (the most important of many greenhouse gases). If CO2 concentration increases then more heat is trapped and temperatures will rise (the greenhouse effect). So by estimating how CO2 concentrations will change in the future we can make an educated guess about how the climate will look in the future (in fact we make lots of different CO2 estimates based on various different assumptions: climate scenarios — the SSPs you can choose in the app).
Carbonator is a simple climate model. Unlike a full climate model that can tell us how climate variables evolve at different locations, Carbonator can only tell us how a subset of variables change on a global scale (e.g. globally averaged temperature). Carbonator uses only a few hundred lines of computer code and takes a few seconds to simulate centuries of climate system evolution on your computer.
Carbonator is based on the same laws of physics that underpin state-of-the-art climate models (in particular the conservation of energy) and for a limited number of variables will produce very similar results to those models. As such, it is a powerful tool that can be used to explore how the climate system is affected by different factors (like CO2 emissions, volcanoes or changes in the power output of the sun) and how our decisions are likely to affect the climate system in the future. You can check this for yourself: in the app, overlay observed temperatures (HadCRUT5, Berkeley Earth, GISTEMP) and CMIP6 climate model ranges on top of the Carbonator run.
A climate model is a simulation of the climate system: the atmosphere, ocean, land surface and cryosphere (ice areas), run on a computer. It allows you to tell how important climate variables like temperature, sea level or rainfall change over time at different locations.
Everyone has heard of weather forecast models. Climate models are very similar but, while weather forecast models are used to predict how the atmosphere will change over the timescale of a few days, climate models tell us how the climate system is likely to change over decades or centuries. Climate and weather models are usually run on powerful computers; they generate simulations of important climate variables like temperature, sea level or rainfall change over time at different locations.
State-of-the-art climate models (there are dozens of them built by different research centres around the world) are made up of thousands of lines of computer code. They require hundreds of people-years to build and take weeks or months to simulate a few decades of climate system evolution on powerful supercomputers (equivalent to 100s or 1000s of personal computers).
Here are some YouTube links to some climate model output:
NOAA SOS: GFDL Global Sea Surface Temperature Model
NOAA Research: Improving the global weather forecast model
Stop And Think: NASA's Perpetual Ocean, Animation of Surface Ocean Currents
The Shared Socioeconomic Pathways (SSPs) are the standard future scenarios used in the IPCC Sixth Assessment Report. Each combines a storyline of how society might develop with a resulting pathway of emissions and radiative forcing. Carbonator 2 includes SSP1-1.9 (very strong mitigation), SSP1-2.6 (strong mitigation), SSP2-4.5 (an intermediate pathway) and SSP5-8.5 (a high, fossil-fuel-intensive pathway). They replace the older RCP scenarios used in the original Carbonator.
Not quickly — and this surprises most people. Try the Eliminate All Emissions experiment: three things happen. First, temperatures briefly jump up, because the cooling haze of aerosol pollution washes out of the sky within days while the greenhouse gases stay. Second, methane fades over a couple of decades, giving some cooling back. But third, CO₂ hangs around for centuries, so the temperature mostly stays near its peak rather than returning to pre-industrial levels. Warming is largely irreversible on human timescales — which is why the timing of emission cuts matters so much.
Climate sensitivity is the single most important number in climate science: how much the planet eventually warms if the amount of CO₂ in the air doubles. Scientists estimate it is most likely about 3 °C, and very likely between 2.5 and 4 °C. The uncertainty comes mainly from clouds — nobody is quite sure whether they will amplify or dampen the warming. In this app you can change the sensitivity yourself in Advanced mode (Edit parameters) and watch how much difference it makes to the year-2100 forecast. (This app uses 3.0 °C by default.)
Aerosols are tiny particles made mostly from the sulphur in coal smoke and ship exhaust. They reflect sunlight back to space and make clouds brighter, so they cool the planet — currently hiding roughly half a degree of the warming our greenhouse gases would otherwise cause. The catch: these particles are also air pollution that damages people's health, so we are cleaning them up — and every clean-up "unmasks" some hidden warming. You can see this in the app: turn the aerosol input off and watch the temperature jump. It is one of the reasons warming has accelerated even as air quality improved.
Real thermometer records wobble from year to year even when nothing about greenhouse gases changes, because the climate system contains its own randomness — chiefly the ocean stirring heat between its warm surface and cold depths (El Niño years run warm, La Niña years run cool), plus random fluctuations in cloudiness. A smooth model curve is showing you the forced change with the randomness removed. Switch on Natural Variability in the inputs and the model grows the same kind of wiggles as the observations — and every run gives a different wiggle pattern, just as rerunning history would. The trend underneath, though, stays the same: that is the difference between climate and weather.
Carbonator works out one number per year: the average temperature change of the whole planet. But warming is not shared out evenly — land warms faster than the ocean, and the Arctic warms fastest of all. To estimate change where you live, the app uses a trick called pattern scaling:
local change = global warming × the map value at your location
The map is the pattern. On the temperature map, a value of 2 means that place warms twice as fast as the global average, while 0.8 means it lags behind (like the oceans around Australia). The rainfall map shows the percentage change in precipitation for every degree of global warming — some regions get wetter, others (like the Mediterranean) get drier. The sea-level map shows how much the local rise differs from the global average: winds and ocean currents pile water up more in some places than others, so some coasts get extra sea-level rise on top of the global amount.
Where does the map come from? We compared the end of this century (2071–2100, under a high-emission scenario) with the pre-industrial climate (1850–1900) in twelve of the world's full climate models (the CMIP6 ensemble), divided each model's local change by its own global warming, and took the middle value of the twelve at every point on a 1°×1° grid. Because you can see the continents appear on the map purely from the land–ocean warming contrast, this is also a nice demonstration that the pattern is real physics, not drawn by hand.
Keep in mind it is an approximation: it works well for steady greenhouse-gas-driven warming, but real regional change also depends on things that do not simply scale with global temperature (such as aerosol pollution and shifting ocean currents), and natural year-to-year variability is not included.
