- This is part two of a two-part post. Read part one here.
When Princeton University’s Syukuro Manabe first studied global warming with general circulation models (GCMs), few other researchers approved. It was the 1970s, computing power was scarce, and the GCMs had grown out of mathematical weather forecasting to become the most complex models available. “Most people thought that it was premature to use a GCM,” ‘Suki’ Manabe told interviewer Paul Edwards in 1998. But over following decades Suki would exploit GCMs widely to examine climate changes ancient and modern, helping make them the vital research tool they are today.
In the 1970s, the world’s weather and climate scientists were building international research links, meeting up to share the latest knowledge and plan their next experiments. Suki’s computer modelling work at Princeton’s Geophysical Fluid Dynamics Laboratory (GFDL) had made his mark on this community, including two notably big steps. He had used dramatically simplified GCMs to simulate the greenhouse effect for the first time, and developed the first such models linking the atmosphere and ocean. And when pioneering climate research organiser Bert Bolin invited Suki to a meeting in Stockholm, Sweden, in 1974, he had already brought these successes together.
Suki and his GFDL teammate Richard Weatherald had worked out how to push their global warming study onto whole world-scale ocean-coupled GCMs. They could now consider geographical differences and indirect effects, for example those due to changes of the distribution of snow and sea ice. Though the oceans in the world they simulated resembled a swamp, shallow and unmoving, they got a reasonably realistic picture of the difference between land and sea temperatures. Their model predicted the Earth’s surface would warm 2.9°C if the amount of CO2 in the air doubled, a figure known as climate sensitivity. That’s right in the middle of today’s very latest 1.5-4.5°C range estimate.
At the time no-one else had the computer facilities to run this GCM, and so they focussed on simpler models, and fine details within them. Scientists model climate by splitting Earth’s surface into 3D, grids reaching up into the air. They can then calculate what happens inside each cube and how it affects the surrounding cubes. But some processes are too complex or happen on scales that are too small to simulate completely, and must be replaced by ‘parameterisations’ based on measured data. To get his GCMs to work Suki had made some very simple parameterisations, and that was another worry for other scientists. Read the rest of this entry »