It is well known that most weather APIs just download data from NOAA and "repackage" them to JSON format. This means you will get data only for the nearest grid point which might be a few kilometers away and at a different altitude than your actual location.

Meteosource combines more models (GFS, ECMW, UKMO, GEM,...). It compares individual models' performance to historical data and uses machine learning to create a single output. This approach minimises inaccuracies of individual models and feeds a proprietary hyper-local model that computes weather exactly for the specified location.

The historical data API is based on actual measurements (not forecasts as usual) and there is a free developer plan available.

I greatly appreciate any feedback and thoughts!