The models were chosen to support their beliefs, and conclusion.
That's a problem because a model can be tuned to a desired outcome.
If the opposite had been true, say that model after model had predicted a rise, and then they went out and found the model to be true, there might be more credibility.
As it was, they had a measurements first, they had a belief/hypothesis first (naturally), and they found a model they could make fit. That's not a proof, not conclusive. They should take the model, and see if it tells them something they didn't know/expect, and then try and see if they can find it in nature. Validate the model beyond the very very narrow conclusion you are trying to justify.