In the future, weather forecasts that provide storm warnings and help us plan our daily lives could reach up to five days before we reach the limits of numerical weather prediction, the scientists said.
"The obvious question that has been raised from the beginning of our entire field is what is the maximum limit at which we can predict the day-to-day weather in the future," said Fuqing Zhang, distinguished professor of meteorology and atmospheric science. Director of the Center for Advanced Data Assimilation and Prediction Techniques at Penn State. "We think we've found that limit and, on average, that it's about two weeks."
Now it is possible to make reliable forecasts of nine to 10 days for the daily climate in the middle latitudes, where the majority of the Earth's population lives. According to research published online on the website, the new technology could add another four to five days in the coming decades. Journal of Atmospheric Sciences.
The research confirms a long-term predictability limit for weather prediction, first proposed in the 1960s by Edward Lorenz, a Massachusetts Institute of Technology mathematician, meteorologist and pioneer of chaos theory, the scientists said.
"Edward Lorenz showed that you can not predict the weather beyond a time horizon, even in principle," said Kerry Emanuel, a professor of atmospheric science at MIT and co-author of the study. "Our research shows that this horizon of predictability of time is around two weeks, very close to Lorenz's estimate."
According to scientists, unpredictability in the way climate is developed means that, even with perfect models and understanding of initial conditions, there is a limit to the anticipation of accurate forecasts.
"We use cutting-edge models to answer this fundamental question," said Zhang, lead author of the study. "I think in the future we will refine this response, but our study conclusively shows that there is a limit, although we still have a lot of room to improve the forecast before reaching the limit."
To test the limit, Zhang and his team used the world's two most advanced numerical weather prediction modeling systems: the European Center for Medium-Range Weather Predictions and the next-generation global prediction system in the United States.
They provided an almost perfect picture of the initial conditions and proved how the models could recreate two real-world weather phenomena, a cold wave in northern Europe and rains that cause flooding in China. According to the scientists, the simulations could predict the weather patterns with reasonable accuracy up to approximately two weeks.
Improvements in day-to-day weather forecasting have implications for things like storm evacuations, energy supply, agriculture and forest fires.
"We have made significant progress in weather forecasting over the past few decades, and now we can predict the climate five days in advance with great confidence," Zhang said. "If in the future we can predict additional days with high confidence, we would have a huge economic and social benefit."
The researchers said that better data collection, algorithms to integrate data into models and improved computing power are needed to run experiments to further improve our understanding of baseline conditions.
"Reaching this additional predictability limit will require coordinated efforts by the entire community to design better numerical climate models, improve observations and make better use of observations with advanced data assimilation and computation techniques," said Zhang.
Close the gap between meteorology / hydrology / radar engineering and weather prediction
Fuqing Zhang et al, What is the predictability limit of mid-latitude climate? Journal of Atmospheric Sciences (2019). DOI: 10.1175 / JAS-D-18-0269.1
Predictability limit: scientists find the limits of weather prediction (2019, April 15)
retrieved on April 16, 2019
This document is subject to copyright. Apart from any fair treatment for private research or study purposes, no
Part can be reproduced without written permission. The content is provided for informational purposes only.