Advancements in Weather Prediction: From Manual Analysis to Cutting-Edge Models

The United States’ National Oceanic and Atmospheric Administration (NOAA) estimates that the cost of weather and climate-related disasters in the country over the past seven years exceeds one trillion dollars. On a global scale, the World Bank suggests that improvements in early warning systems and disaster prediction technologies, along with saving tens of thousands of lives, could bring annual economic benefits of up to $162 billion.

In the early days of establishing meteorological and seismic centers, scientists had to manually analyze large amounts of data to discover major weather trends. However, in the early 1950s, these centers began using computer models to produce weather predictions based on complex mathematical equations describing the daily evolution of the atmosphere. Since then, two prominent models, or one might say schools of thought, have emerged to interpret this data: the “American model” and the “European model.”

Despite advancements in computer systems from that period until today, the volume of data received by these centers has increased exponentially, requiring massive processing power to operate these models. Upgrading them is a costly and time-consuming process that can take years to complete. Meanwhile, new supercomputers, such as the one purchased by the UK’s Met Office from Microsoft in 2021, can cost over a billion dollars.

The accuracy of traditional weather prediction models has improved by approximately one day per decade, and today’s models can forecast weather for seven days compared to three days in the 1980s. For example, data from the National Hurricane Center shows a substantial increase in the accuracy of hurricane path predictions with a decrease in the average error. In the 1980s, predicting the path of a hurricane from a distance of 100 miles was possible three days before its arrival. Today, the path can be predicted from a distance of 300 miles seven days in advance.

Nevertheless, predicting sudden and severe weather fluctuations, such as powerful hurricanes, floods, cold snaps, winter storms, heatwaves, and droughts, remains challenging. This involves small-scale data details or issuing the necessary advance notice for people to prepare effectively.