Depends, the "optimal" forecast can be very sensitive to the scoring metrics used.
E.g. Darwin in Australia's tropics - persistence forecasting (as you describe above, just predicting the weather the day before) does very well on a metric like 'mean absolute error'. But has no practical skill at forecasting a severe tropical cyclone (aka hurricane/typhoon)! Many are willing to accept some level of false positives and a higher mean absolute error, because the cost of a surprise cyclone is so devestating.
E.g. Darwin in Australia's tropics - persistence forecasting (as you describe above, just predicting the weather the day before) does very well on a metric like 'mean absolute error'. But has no practical skill at forecasting a severe tropical cyclone (aka hurricane/typhoon)! Many are willing to accept some level of false positives and a higher mean absolute error, because the cost of a surprise cyclone is so devestating.