Machine learning technology boosts analog weather forecasting

Machine learning technology that can recognize human faces may also help to improve weather forecasts, according to a team of scientists.

UNIVERSITY PARK, Pa. — Machine learning technology that can recognize human faces may also help to improve weather forecasts, according to a team of scientists.

“The idea behind this work comes from Google’s FaceNet, but instead of comparing your picture to images of faces in a database, we are comparing weather to historical forecasts,” said Weiming Hu, a machine learning scientist at the University of San Diego and a former doctoral student at Penn State.

The scientists applied a deep learning algorithm to analog weather forecasting, which uses past weather conditions to make future forecasts. They found that analyzing surface wind speed and solar irradiance forecasts in Pennsylvania from 2017 to 2019 using machine learning improved analog forecasting accuracy in this case study.

Read the full story at Penn State News