Digital modeling is relatively new. However, humans have been using analog modeling since the dawn of time; the sundial, Stonehenge, mechanical clocks, the abacus, mechanical calculators and the Antikythera mechanism are examples.
And so we can and have had the ability to predict the future for thousands of years.
Early computer models of the climate were able to show the direction of the change and some hints at the magnitude, and supported earlier theoretical predictions. Later models confirmed the trend and narrowed the range of uncertainty. Surely models are imperfect and are constantly improving, but this is not the point.
As different investigators approach the problem with different computational methods, the different models all show the same trends and general outcomes. As greenhouse gasses increase, average temperature increases. Warming will be greater at the poles and at night. As atmospheric moisture increases due to the ability of warmer air to hold more moisture, precipitation events will become more intense. These effects are occurring now exactly as the models predicted.
Digital modeling is not some sort of alchemy. Theoretical science is based on mathematics. Mathematics is internally consistent and irrefutable. A theoretician uses mathematics to prove that his theory is internally consistent. The theory may have no practical application at this point, but it is a valid framework for further study and application. Newton remains a giant because the calculus he invented has endless applications.
Empirical scientists design experiments to test the theory. After the theory and the mathematics have been proven to be correct by direct measurement through experimentation, the same mathematics from the theory is used to design the model.
Models are used to design nuclear weapons, chart spaceflight, model astrophysical phenomena like star and galaxy lifecycles, model particle interactions in nuclear physics, model biochemical reactions for the design and efficacy of drugs, model population growth, model economic systems, model thermodynamic systems for combustion and engine design, model material behavior for structural design, and more I haven’t thought of.
The point being that the models aren’t “twisted, fudged, and manipulated in order to get the results desired”. They are used every day around the world by scientists and engineers to make things that work.
Computer modeling has opened a new chapter in science. Empirical scientists were once limited by that which they could construct and observe. Now we can take models, which are proven to be internally consistent because they arrive at the same results obtained from direct measurement, and drive them beyond the directly obtainable. We can drive them into the future, into the past, speed them up, slow them down, enter parameters that would be unrealistic or uneconomic or impossible for a researcher with practical constraints. Sometimes the models produce nonsense. Sometimes they produce results that the researchers are unable to explain, and thus open a new field of inquiry. It is a new frontier.
It amuses me that people use weather models as proof they are no good. “We can’t predict the weather next week, who is to say what will happen in 100 years?” The point is we can predict the weather next week with some accuracy. We can predict the weather tomorrow within a degree or two of temperature and an hour or two of when the precipitation will arrive. That is an incredible achievement.