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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.
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.
Vaibhav Chaturvedi, senior fellow at the Delhi-based Council on Energy, Environment and Water (CEEW) told The Indian Express, “With climate models or statistical sciences, the objective is not to achieve accurate or precise outcomes. The objective is to see what trends these models are showing, what insights they are giving, and if they are reliable or not.”
Researchers say that modern climate models are fairly reliable when it comes to capturing large-scale patterns and long-term changes, particularly at the global level, such as sea-level rise and polar ice loss.
One way scientists check the reliability of models is by using past events. If the model correctly predicts past events that scientists know occurred, then it should also be able to reliably predict future events.
That said, current climate models are not perfect, and there is always a degree of uncertainty with their predictions. 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 like a volcanic eruption, or natural phenomena such as El Niño events.
Chaturvedi said, “There will always be uncertainty, for example, when models make projections regarding climate sensitivity [the estimated amount of future global warming for an increase in atmospheric carbon dioxide concentration]. That is because there is a non-linear relationship between the rise in emissions concentration and the increase in temperature.
There is also uncertainty when it comes to projecting climate impacts, as they have a non-linear relationship with temperature increase. There is also a lack of data regarding attributing climate change to specific impacts.”
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).
The most glaring shortcoming of these models is that they tend to be less accurate in the Global South because of inadequate ground data, and complex, poorly represented regional climate patterns, such as the Indian monsoon.
Vidya said, “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.”
Nonetheless, 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. A 2020 study, published in the journal Geophysical Research Letters, looked at 17 climate models which were developed between 1970 and 2007 and found that 14 of them quite accurately projected Earth’s future global average surface temperatures.
Govindasamy Bala, a professor at the Centre for Atmospheric and Oceanic Sciences at the Indian Institute of Science (IISc), told The Indian Express, “Climate models are just like any other tools. And like every tool, they have certain limitations… It is all about asking the right questions… These models are built for giving projections for national & continental spatial scales… Climate, by definition, is the average of weather over 20 or 30-year periods… Therefore, it does not make sense to ask climate modellers to provide accurate climate change information for the next decade.”
