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ZENODO
Software . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
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Dew-Point Anchor Hypothesis (DPAH) Markovian Stochastic Modelling of the Venus Atmosphere: Inverse Paradigm Anchored at Sulfuric Acid LCL Cloud Deck

Authors: Mulholland, Philip;

Dew-Point Anchor Hypothesis (DPAH) Markovian Stochastic Modelling of the Venus Atmosphere: Inverse Paradigm Anchored at Sulfuric Acid LCL Cloud Deck

Abstract

Abstract: The Dew-Point Anchor Hypothesis (DPAH) treats the lifting condensation level (LCL) of sulfuric acid — the dominant condensing volatile on Venus — as the primary independent physical anchor in the atmosphere. Using a Markovian matrix stochastic forward-modelling approach, we construct linked bipolar Hadley cell regimes (equatorial ascent to the cloud deck versus polar vortex descent) and integrate downward from the observable cloud layer using hydrostatic equilibrium and adiabatic processes tailored to Venus’s high-pressure CO₂-dominated environment. Key emergent results (anchored at ~45 kPa cloud-deck pressure) include a planetary surface temperature of ~736 K in the polar descent branch, spontaneous super-rotation (positive zonal momentum) in the upper ascent regime, minimal day-night contrast at cloud-top levels, and a polar vortex atmospheric window effect. The model reproduces post-Venera 7 canonical observations without prescribing surface temperature as an input. This inverse paradigm demonstrates that Venus’s extreme surface conditions can emerge probabilistically from internal thermodynamic constraints and observable cloud physics, offering a complementary perspective to traditional top-down radiative-convective models. Benefits of the DPAH Approach for Venus DPAH provides a robust inverse modelling framework that anchors simulations at a directly observable feature — the sulfuric acid cloud deck LCL. This avoids the circularity of prescribing surface temperature and instead lets it emerge naturally. The stochastic Markovian method efficiently explores probabilistic stationary states under bipolar Hadley circulation, reproducing: Realistic surface pressure (~92 bar) and temperature (~736 K). Spontaneous super-rotation via momentum bias in the ascent branch. Polar surface temperature modulation via vortex-induced clarity (atmospheric window). The approach is computationally efficient on modest hardware and offers clear physical interpretability. Impact on Canonical Radiative Greenhouse Narrative Carl Sagan’s 1961 paper and subsequent radiative-convective models positioned CO₂-driven infrared trapping as the dominant explanation for Venus’s runaway-like surface heat. While CO₂ opacity is important, the DPAH results indicate that this narrative is incomplete. By anchoring at the cloud deck and allowing surface conditions to emerge from adiabatic descent and stochastic circulation, the model achieves canonical temperatures without relying on extreme radiative forcing as the sole mechanism. This supports the view that massive atmospheric thermal inertia, compressional heating in slow-rotator Hadley cells, and phase-change boundaries play central mechanistic roles. It invites a more balanced perspective: radiative transfer operates within a thermodynamically constrained convective envelope rather than dictating it from above.

Keywords

Venus Express, polar vortex window, inverse modelling, Markovian stochastic modelling,, bipolar Hadley cells, DPAH, sulfuric acid clouds, Venera 7, Venus atmosphere, Dew-Point Anchor Hypothesis, LCL anchor, atmospheric super-rotation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average