 At the complex end of the spectrum, coupled ocean-atmosphere general circulation models (GCMs) simulate atmospheric and oceanic motions in three spatial dimensions, often at as high a resolution as available supercomputing power allows. They also incorporate representations of the land surface and sea ice, and they attempt to account for important interactions among all of these components. GCMs evolved from atmosphere-only general circulation models, which in turn were inspired by early weather forecasting models (Edwards 2000; Weart 2010). The latest generation of climate models, earth system models (ESMs), extend GCMs by incorporating additional model components related to atmospheric chemistry, aerosols and/or ocean biogeochemistry (Flato et al. 2013: 747). In both GCMs and ESMs, numerical methods are used to estimate solutions to discretized versions of fluid dynamical equations at a set of points on a three-dimensional  grid.[2]  With increased computing power in recent decades, the horizontal spacing of these grid points for the atmosphere has reduced from several hundred kilometres to ~100 km, and the number of vertical layers has increased from ~10 to ~50, with a time step of 10–30 minutes (McGuffie &amp; Henderson-Sellers 2014: 282). Despite this increased resolution, many important processes—including the formation of clouds and precipitation, the transfer of radiation, and chemical reactions—still occur at sub-grid scales; accounting for the effects of these processes is a major challenge, as discussed in the next section.