When attempting to predict how radiation will influence a complex system,

it's often useful to assume that the system in question is a uniform,

fully understood, fully mapped, and predictable object. Rather than trying to understand the full

complexity of the Amazon rainforest then, when trying to make predictions about how deforestation

of the region will influence biodiversity outcomes, it may be trying to make predictions about how deforestation of the region will influence biodiversity

outcomes, it may be useful to make broad-based average assumptions about a portion of the region,

and then scale those assumptions up to encompass all of the forest. This is often productive

because, first, we don't and arguably can't map the holistic totality

of such a system using current methods and technologies, and second, because it dramatically

simplifies the math that must be done to sort out how changed variables will impact

the forest on average, which is generally

what we're aiming for anyway.

Said another way, although we could theoretically figure out how to make exacting predictions

about complex systems, it's often more practical to simplify those systems in a variety

of ways to ensure we can get the predictions done sooner

rather than later, and because the simplified average assumptions we make will be useful enough,

will give us a starting point for assumptions about that larger system, and with sufficient

rapidity that we might actually be able to act on that information before the state of things changes.

When it comes to assessing the bogglingly complex system of Earth, and more specifically, the temperature of the whole planet,

one of the simplifying techniques we use is measuring for what's called the planetary equilibrium

temperature, which is a theoretical temperature that a planet would have across its entire expanse

if it were a perfect absorber of the energy being emitted from its star, and if that energy

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