The objective of the present experiment is to compare the performance of the two different model architectures
- XGBoost decision tree ensemble, PyTorch Transformer -
for predicting three weather variables
- temperature, cloud cover, wind speed -
at six time horizons
- 1hr, 2hr, 3hr, 4hr, 5hr, 6hr -
for five cities in the USA
- Los Angeles, Miami, Boston, Seattle, Denver -
The forecasts are based on the weather data for a 300x300 km grid surrounding each city, from the Openmeteo open-source weather API and are compared to the forecasts from the NOAA GFS.
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