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duanem | 3 years ago
I find global models like GFS are great for understanding the large scale weather systems. The regional high-resolution models, which are usually nested in a global model, give better definition of local weather phenomena like wind shadows or cooler temperatures in valleys.
Dues to averaging, weather simulations usually have a bias error in temperature predictions. These errors are corrected using statistics (look up Model-Output-Statistics) but is hyper-local, i.e., you loose the big picture. This is probably what you're looking at with Meteoblue.
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