  In climate science and kindred disciplines, sub-grid modeling is called “parameterization.” This, again, refers to the method of replacing processes—ones that are too small-scale or complex to be physically represented in the model— by a more simple mathematical description. This is as opposed to other processes—e.g., large-scale flow of the atmosphere—that are calculated at the grid level in accordance with the basic theory. It is called “parameterization” because various non-physical parameters are needed to drive the highly approximative algorithms that compute the sub-grid values. Examples of parameterization in climate simulations include the descent rate of raindrops, the rate of atmospheric radiative transfer, and the rate of cloud formation. For example, the average cloudiness over a 100 km2 grid box is not cleanly related to the average humidity over the box. Nonetheless, as the average humidity increases, average cloudiness will also increase—hence there could be a parameter linking average cloudiness to average humidity inside a grid box. Even though modern-day parameterizations of cloud formation are more sophisticated than this, the basic idea is well illustrated by the example. The use of sub-grid modeling methods in simulation has important consequences for understanding the structure of the epistemology of simulation. This will be discussed in greater detail in section 4.