Actually, they are historical weather forecasts, but assembled to a continuous time-series.
Storing each weather forecast individually to a performance evaluation for "how good a forecast in 5 days is", would require a lot of storage. Some local weather models update every 6 hours.
But even with a continuous time-series, you can already tell how good or bad a forecast compared to measurements are. Assuming, your measurements are correct ;-)
This would still be a remarkable dataset for learning. And worth the storage. Though it might need other inputs as well (like pressure zone etc.) to escape potential biases.
Storing each weather forecast individually to a performance evaluation for "how good a forecast in 5 days is", would require a lot of storage. Some local weather models update every 6 hours.
But even with a continuous time-series, you can already tell how good or bad a forecast compared to measurements are. Assuming, your measurements are correct ;-)