arXiv · 2409.18305
Algorithmic Forecasting of Extreme Heat Waves
Abstract
This paper provides some foundations for valid forecasting of rare and extreme heat waves through a better understanding of the similarities and differences between several consecutive hot days under normal circumstances and rare, extreme heat waves. We analyze AIRS data from the American Pacific Northwest and AIRS data from the Phoenix, Arizona region. A genetic algorithm is used to help determine the most promising predictors. Classification accuracy with supervised learning is excellent for the Pacific Northwest and is replicated for Phoenix. Conformal prediction sets are considered as a way to represent forecasting uncertainty. Complications caused by endogenous sampling are discussed.
Explore related subjects
Keep this discovery
Richard A. Berk, Amy Braverman, Arun Kumar Kuchibhotla. 2024-09-26. Algorithmic Forecasting of Extreme Heat Waves. https://arxiv.org/abs/2409.18305
Cite the original work for its findings. Save a collection to share your selection of sources.