Published June 11, 2026 | Version v1
Software Open

Dew-Point Anchor Hypothesis (DPAH): Application to Atlantic Hurricanes – Master Workflow, Rapid Intensification, and Radial Structure Analysis of 2018 Hurricane Michael

  • 1. Independent Researcher

Description

The Dew-Point Anchor Hypothesis (DPAH) posits that the lifting condensation level (LCL) anchored by surface dewpoint is the primary thermodynamic control for convective organization. This deposit extends DPAH to Atlantic tropical cyclones, with a detailed case study of 2018 Hurricane Michael.

Key Components:

  • Vertical thermodynamic profiles (eye vs eyewall) with stratospheric subsidence in the eye
  • Intensity sensitivity and Rapid Intensification (RI) modeling
  • Time-track analysis across three distinct surface environments: Gulf of Mexico → Florida Land → Atlantic Ocean
  • Radial Markov chain model (Eye ↔ Eyewall ↔ Rainbands) coupled with LCL profiles
  • Full consolidated master script (RunMaster_Hurricane.pv)

The modelling reproduces observed behaviour: very low LCL and high eyewall probability during RI over warm Gulf waters, sharp LCL rise and eyewall suppression at landfall, and partial recovery over the Atlantic.

This work complements the earlier Monsoon/Thar Desert deposit and demonstrates DPAH’s versatility across dry sensible-heat and moist latent-heat driven systems.

All code is MIT-licensed and executable with standard scientific Python libraries (numpy, matplotlib, pandas).

Files

01_PythonCode.zip

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Additional details

Software

Programming language
Python

References

  • Beven, J.L., Berg, R. and Hagen, A., 2019. National hurricane center tropical cyclone report: Hurricane Michael (AL142018). US National Oceanic and Atmospheric Administration (NOAA), National Hurricane Center, Miami, FL. https://www.nhc.noaa.gov/data/tcr/AL142018_Michael.pdf
  • Mulholland, P. (2026). Dew-Point Anchor Hypothesis (DPAH): Application to the Indian Summer Monsoon and Thar Desert Heat Low – Thermodynamic Modelling, Sounding Validation, and Hurricane-Eye Analogy (Python Runs 4001–Master). Zenodo. https://doi.org/10.5281/zenodo.20637607