Fractal and Volatility Early Warning Signals for Storms

This study is based on the hypothesis that fractal metrics (DFA, Hurst, Lyapunov) signal atmospheric instability. Early findings show That the divergence of precipitable water vapour and longwave outgoing radiation at the top of the atmosphere appears to be a reliable storm precursor, particularly when supported by radiation and atmospheric fractal metrics. That a combination of fractal volatility metrics of solar radiation profile between the top of the atmosphere and the ground is a significant input and may contribute to early warning, and that fractal volatility of water vapour may also contribute to prediction and early warning of large storms (hurricanes, typhoons and cyclones). When combined with a newly defined Storm Propensity Index (SPI), fractal volatility signals improve early warning accuracy for major storm events. Year on year changes show climate transition, and fractal metrics indicate that, particularly in the Atlantic, atmospheric drivers may be approaching global heating tipping points. Gravity changes (largely due to melting ice) also play a seasonal part in weather volatility. A large spike in detrended Fluctuation Analysis (DFA), an anomaly observed at the tail end of 2024, for which there is no apparent explanation.This occurs in both net solar radiation flux profile DFA volatility and precipitable water vapour DFA volatility at the same time. It may indicate a chaos tipping point where the entire weather system is moving to a new attractor pattern. DFA is a metric of longer term structural memory.