Earth System Models—complex computer models that describe Earth processes and how they interact—are critical for predicting future climate change. By simulating the response of our land, oceans and atmosphere to manmade greenhouse gas emissions, these models form the foundation for predictions of future extreme weather and climate event scenarios, including those issued by the UN Intergovernmental Panel on Climate Change (IPCC). However, climate modelers have long faced a major problem. Because Earth System Models integrate many complicated processes, they cannot immediately run a simulation; they must first ensure that it has reached a stable equilibrium representative of real-world conditions before the industrial revolution. Without this initial settling period—referred to as the "spin-up" phase—the model can "drift," simulating changes that may be erroneously attributed to manmade factors. Unfortunately, this process is extremely slow as it requires running the model for many thousands of model years which, for IPCC simulations, can take as much as two years on some of the world's most powerful supercomputers. However, a study published in Science Advances by a University of Oxford scientist describes a new computer algorithm which can be applied to Earth System Models to drastically reduce spin-up time. ....