Climate models have been remarkably effective at projecting global warming trends, but they still fail to fully capture some crucial processes that could dramatically accelerate climate change, according to experts at UNSW.
Most climate change models look similar, with temperatures slowly rising year by year. But history shows Earth's climate doesn't always follow a linear path - it lurches and jumps, says Professor Katrin Meissner , Director of the UNSW Climate Change Research Centre.
Prof. Meissner studies abrupt climate shifts and the thresholds and feedback loops that drive them. While today's climate models have proven remarkably accurate, she warns they overlook key processes that could lead to more rapid, unpredictable warming in the future.
The challenge of improving climate models is immense. But Prof. Meissner says the science already gives us a strong mandate for action.
How climate models work
Climate models use equations based on physical laws to simulate future warming. These models incorporate forcings - elements that drive climate, such as greenhouse gases and solar radiation.
Since their inception in the 1970s, climate models have grown more complex. Early models included representations of the atmosphere, oceans, land surfaces, and sea ice. Over time, scientists have added aerosols, the carbon cycle, vegetation, atmospheric chemistry, and land ice.
"Our current models do a good job of simulating today's climate and have been fairly accurate predicting recent decades of warming, but they struggle as temperatures get higher," Prof. Meissner says.
"This is because many complex processes, which interact, are not fully represented in existing models."
One key constraint is computational power. Climate models divide the Earth into 3D grid boxes across space and time.
Horizontal resolution and time steps are closely linked in atmospheric models. Since elements like wind can't 'skip' over grid boxes, smaller grid sizes require correspondingly smaller time steps to maintain accuracy and stability.
Doubling the resolution of models increases the number of grid boxes at least eightfold, and time steps twofold, requiring roughly 16 times more computing power.
Clouds, carbon, and chaos
Clouds present a major modelling challenge, says UNSW Professor Steven Sherwood , whose work has focused on their impact.
Clouds can both cool and warm the planet, depending on their type, altitude, and location. But the turbulent processes that drive their formation are still not fully understood or modelled, making them a major source of uncertainty.
Recent research indicates that Earth is absorbing significantly more heat than climate models have predicted, with changes in cloud cover identified as a possible contributing factor, says Prof. Sherwood.
