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Journalism of Courage
US President Donald Trump, in his speech at the United Nations General Assembly on September 23, said that climate change was the greatest “con job” ever.
“All of these predictions made by the United Nations and many others, often for bad reasons, were wrong. They were made by stupid people that have cost their countries fortunes and given those same countries no chance for success,” he said.
The predictions that Trump alluded to in his speech are usually made using climate models. These computer programs are at the heart of climate research: they help scientists understand how the climate changed in the past, how it is changing now, and how it might change in the future.
But how do climate models work? What are the different types of climate models? How accurate are they?
A climate model is a computer simulation that uses mathematical formulae and algorithms to replicate how the Earth’s climate system — including the atmosphere, ocean, land and ice — works.
Vidya S, senior associate at the Centre of Science, Technology and Policy (CSTEP), a Bengaluru-based think tank, told The Indian Express over email, “These models are built on the principles of physics, chemistry, and biology, and are designed to simulate or mimic the interactions between the atmosphere, oceans, land surface, and ice.”
Climate models can forecast how variables such as temperature and humidity will change over time under different scenarios, like increased greenhouse gas emissions or changes in land use. Simply put, they allow scientists to test hypotheses and draw conclusions on past and future climate systems.
This also helps them to determine if abnormal weather events like extreme heavy rainfall are a result of changes in climate or just part of routine climate variation.
Note that climate models are different from weather models. While weather models make predictions over specific areas and short time spans, climate models are broader and analyse long-term patterns.
A modern climate model first divides the Earth into a three-dimensional grid, with cells extending across the planet’s surface, up into the atmosphere, and down into the ocean. Each cell is represented by mathematical equations that describe the materials — land, air, and ice — within it, and the way energy moves through it.
Scientists then feed input data from observations, for example, of greenhouse gases or ocean conditions, and have the model solve equations to determine how the weather will change within each cell, what impacts those changes will have on adjacent cells, and what changes those adjacent cells will have on others. This allows scientists to gain an understanding of the effects on a particular region or the entire planet.
The output from the model can include “projected changes in temperature and precipitation patterns, sea-level rise, ocean circulation, frequency and intensity of extreme weather events (such as heatwaves, droughts, and storms), and shifts in snow and ice cover,” Vidya said.
* The earliest form of climate models, known as the Energy Balance Models (EBMs), emerged in the 1960s. These only determine surface temperature by considering the balance between the energy entering the Earth’s atmosphere from the Sun, and the heat released back out to space.
* Then came Radiative Convective Models (RCMs), which are more complex and simulate the transfer of energy through the height of the atmosphere. They estimate both surface temperature and the temperature variation with elevation.
* Subsequently, General Circulation Models (GCMs), also called Global Climate Models, emerged. They are the most sophisticated and precise models for understanding climate systems and predicting climate change. GCMs simulate Earth’s atmosphere, oceans, land, and ice to represent large-scale climate processes over time, including the movement of energy and matter.
* There are also Regional Climate Models (RCMs) that do a similar job as GCMs, but offer more precise local forecasts and concentrate on smaller regions, such as a country or a continent.
Researchers say that modern climate models are fairly accurate when it comes to capturing large-scale patterns and long-term changes, particularly at the global level.
“Over the past few decades, they have been successful in forecasting several important phenomena, like sea-level rise and polar ice loss. When averaged over wide regions and time periods, models also do a good job of simulating general patterns of temperature, precipitation, and ocean circulation,” said Vidya.
One way scientists check the accuracy of models is by using past events. If the model accurately predicts past events that scientists know took place, then it should also be able to accurately predict future events.
That said, current climate models are not perfect. This is because of imperfect, incomplete, or unavailable data on complex, dynamic processes such as the nature of clouds, the climatic effects of sudden geophysical events such as a volcanic eruption, or natural phenomena such as El Niño events.
Climate models also overlook regional specifics such as intense rain in rural areas, flooding in urban areas, or heat in towns, as they view the Earth in broad sections, typically ranging from 100 to 250 kilometres (the size of each cell of the three-dimensional grid), according to Vidya.
“Moreover, these models frequently oversimplify the interactions between land and air, such as how farms, trees, and soil moisture impact rain and temperature. Climate models might, therefore, overestimate or underestimate extreme occurrences like heat waves or torrential rains,” she said.
The most glaring shortcoming of these models is that they tend to be less accurate in the Global South. This could be because of inadequate ground data, and more complex and poorly represented regional climate patterns, such as the Indian monsoon.
“Most climate models were initially created in North America and Europe… Because the Global North has more accurate and detailed observational records, climate models are frequently calibrated and validated using data from this region,” said Vidya.
These flaws, however, do not mean that climate models are useless. Since they are based on well-founded physical principles of Earth system processes, climate models are still one of the best ways to understand general climate patterns and make policy decisions to mitigate the adverse effects of climate change.
As such, almost all climate models and climate scientists agree on one fundamental fact: that climate change is real, and the rise of the global mean surface temperatures is due to the continuing emission of heat-trapping greenhouse gases.
