Old geometry helps LANL team refine next-gen climate models
Posted September 18, 2012
A snapshot of North Atlantic ocean circulation. Click image to enlarge
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People want to know how climate will change in their back yards. But current climate predictions are based on global models, which are limited by their coarse resolution and by difficulties in capturing detailed climate processes. Improving model and process resolution and figuring out how to use global data to project regional effects will become crucial for predicting agricultural yields, water supplies and other climate-dependent factors.
As computing approaches the exascale – the capacity to do a million trillion calculations per second – it begins to be feasible to model regional climate effects using historic data combined with new satellite and weather station information. But to glean realistic results, climate modelers will need a new, efficient approach to bring the key data into focus while minimizing less important components. In other words, climate modeling needs to view earth through a new lens.
Enter Todd Ringler and his colleagues in the Climate, Ocean and Sea Ice Modeling (COSIM) group at the Department of Energy’s Los Alamos National Laboratory. Ringler’s work combines atmospheric science, numerical modeling and more than a passing acquaintance with an historic mathematician named Georgy Voronoi. (See sidebar, “Why honeycombs are hexagonal.”) The Los Alamos group’s task is to find a mathematically simple way to partition the planet uniformly while conforming to its spherical shape.
For historical reasons, global climate modeling has traditionally divided the earth along latitude and longitude. That works fine for navigation but isn’t ideal if the goal is a uniform grid on which to overlay a climate model. “As we all know, longitude lines meet at the poles,” Ringler says. That irregularity can cause problems if a climate forecaster wants to treat each terrestrial unit identically.