Even local weather forecasting, which is rapidly evolving all the time, can stand to benefit from improved forecasting. Take, for example, thunderstorms, where highly accurate and advanced prediction by improved data analysis could minimize the resulting damage, as there could be warning further in advance about potential power outages, and increased preparedness, allowing the local community to restore power faster.3 So, then, how can weather forecasting be improved on both the local and global scale?
Quantum computing has the potential to improve conventional numerical methods to boost tracking and predictions of meteorological conditions by handling huge amounts of data containing many variables efficiently and quickly, by harnessing the computing power of qubits,4 and by using quantum-inspired optimization algorithms.5 Moreover, pattern recognition, crucial for understanding the weather, can be enhanced by means of quantum machine learning.1, 2
Quantum computing will serve to benefit weather forecasting on both the local scale as well as on a grander scale for more-advanced and accurate warning of extreme weather events, potentially saving lives and reducing property damage annually. Beyond weather prediction, to stay informed on the state of quantum computing and its increasing impact on a variety of industries, keep up to date with the 1QBit blog, and follow us on social media.
1 A. V. Frolov, “Can a Quantum Computer be Applied for Numerical Weather Prediction?”, Russian Meteorology and Hydrology 42(9), 545–553 (2017).
2 S. Das, “Top Applications Of Quantum Computing Everyone Should Know About”, Analytics India Magazine, https://analyticsindiamag.com/top-applications-of-quantum-computing-everyone-should-know-about/, (2020).
3 K. Taylor-Smith, “Using Quantum Computing to Tell the Weather”, AZO Quantum, https://www.azoquantum.com/Article.aspx?ArticleID=98#:~:text=Quantum%20Computing%20Improves%20Weather%20Forecasting&text=It%20employs%20IBM’s%20supercomputing%20technology,supercomputers%20are%20unable%20to%20achieve (2018).
4 A. Trabesinger, “Quantum Leaps, Bit by Bit”, Nature 543, S2–S3 (2017).
5 M. C. Cardoso, M. Silva, M. M. B. R. Vellasco, and E. Cataldo, “Quantum-Inspired Features and Parameter Optimization of Spiking Neural Networks for a Case Study from Atmospheric”, Procedia Computer Science 53, 74–81 (2015).
6 A. Al-Heeti, “CES 2019: IBM Unveils Weather Forecasting System, CNET, Commercial Quantum Computer”, https://www.cnet.com/news/ibm-unveils-weather-forecasting-system-commercial-quantum-computing-at-ces/ (2019).