What type of models are characterized by being easily solved on a computer?

Computational models are designed to be easily solved using computers, making them particularly effective for complex systems where analytical solutions may be difficult or impossible to derive. These models often utilize numerical methods to approximate solutions, allowing for the simulation of various physical phenomena, including those related to atmospheric dispersion.

Their strength lies in their ability to handle large amounts of data and complex equations that would be cumbersome to solve manually. Computational modeling can also be adapted to incorporate various scenarios and variables, making them versatile tools in research and practical applications.

Other models, such as statistical models or analytical models, might not lend themselves as readily to computer-based solutions because they may rely on different methodologies or assumptions. For instance, analytical models provide closed-form solutions, while empirical models rely on observed data to make predictions but typically don't incorporate the computational power that complex simulations require. Thus, computational models truly stand out for their ease of use in a digital environment, allowing for more complex and accurate representation of real-world scenarios.