A downvote is not a vote of confidence in climate science but more of the opposite. I can only assume that there is no proof to be had of earlier predictive suc

A downvote is not a vote of confidence in climate science but more of the opposite. I can only assume that there is no proof to be had of earlier predictive successes and with that the original statement made by transcriptase is strengthened rather than weakened. Assuming that this is not the intended result it would be good to get an actual answer to the request - give some examples of predictions close enough to the mark to matter. You may think this is just a word game but there is more at play. Blind belief in the outcome of flawed models is a bad foundation for good science. Climate models are notorious for their dependency on 'fudge factors', magical constants which need to be introduced to make their outcome match the expected one. It is not clear what those fudge factors actually represent, it can be anything from a simple miscalculation of a given effect of one of the inputs - i.e. something which does not change the predictive power of the model once the factor has been dialled in correctly - to an unknown variable input which has substantial effect on the output. The latter can seriously affect the predictive power of model output since it is by definition unknown whether the fudge factor is related to the output in some way, e.g. cloud cover affecting temperature sensitivity which in turn affects cloud cover leading to uncertainty in the climate sensitivity of simulated inputs. Cloud cover is just an example, there are many other similar factors which can wreak havoc with the predictive capacity of complex and sometimes - often - poorly understood models.