As the effects of climate change and global warming escalate, the unpredictability of weather patterns is posing a significant challenge when it comes to energy evaluation of buildings. Current methods for predicting weather conditions don’t fully consider the interconnectedness of weather elements such as solar radiation, air temperature, and absolute humidity, which are crucial for determining energy consumption and efficiency.

In response to this, a team of researchers from the Graduate School of Human Life and Ecology at Osaka Metropolitan University has created a groundbreaking evaluation approach. The research team, consisting of Associate Professor Jihui Yuan, Professor Emeritus Kazuo Emura, Dr. Zhichao Jiao, and Associate Professor Craig Farnham, designed a method that uses a statistical model to encapsulate the interrelation among various weather factors. This enables the creation of more reliable meteorological data.

The scientists predicted the temperature, solar radiation, and humidity levels at noon each day, and then incrementally extended this data to cover a full day and eventually an entire year to generate comprehensive weather data for the year. A noteworthy feature of this model is its consideration of the interconnectedness of weather elements, enhancing the precision of building energy simulations. The team found that their generated data closely mirrored the original data set, thus confirming the accuracy of their method.

“We envision that this method will pave the way for energy-efficient building designs that can adapt to a wide range of weather conditions,” said Professor Yuan.