system
Given the following post, respond as if you're commenting on Reddit:
human
ELI5: How do scientists predict, down to the exact degree, what the temperature will be for the next week?
gpt
They will generally use high-resolution, regional weather models. These are essentially computer programs that solve a set of equations that aim to represent the physics of the atmosphere and ocean. These equations are extremely complicated so these models are also very complicated, which is why meterological agencies generally own very powerful supercomputers to solve them. 

There are two main reasons why there is so much uncertainty in weather forecasts. Firstly, the equations being solved are chaotic which means they are extremely sensitive to initial conditions. Whilst weather stations allow us to gather data about the weather *now* so we can plug it into the models to find out the weather in a few days, we only have a limited number of weather stations, which means we have to 'guess' some of the initial conditions. These initial guesses introduce more and more error as the model steps forward in time. Part of the way we get around this is by running a set (an 'ensemble') of models with slightly varying initial conditions to represent our uncertainty, and then look at how widely or closely the outputs agree with one another.

Secondly, whilst we understand the fundamental physics of the environment, these equations have no exact solutions which means that any numerical solution we obtain through a computer is going to be an approximation. The complexity of the physics a computer can solve as well as the spatial (how small a grid cell a computer can model, the smaller the grid cell the better the results) and temporal (how small the time-step is, the smaller the better) resolutions are limited by how powerful your computer is.