PTEM Labs

PTEM — Phase Transition & Emergent Modulation

PTEM is a governed structural measurement instrument for tropical cyclone risk.

It measures how internally organized storms become — providing structural evidence that complements catastrophe models and intensity forecasts.

Purpose-built for reinsurers, model validation teams, and public programs that need governed structural proof alongside their existing hazard stack.

Validated on the frozen Atlantic v1.2 structural spine (1851–2024), aligned to a 6-hour cadence that spans more than 170 years of tropical cyclone observations.

Frozen, forward-only computation delivers immutable manifests, scorecards, and audit-ready hashes instead of forecast feeds.

The same governance discipline ports the multi-century Atlantic spine into EPAC under identical operating constraints.

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Licensed only to institutional risk owners, reinsurers, and public programs that require governed audit trails.

Canonical Atlantic structural spine freeze stamp: freeze-2026-01-27.

Validation surfaces

Governed infrastructure, two horizons

Every tier ships with audit-shaped artifacts so partners can reproduce PTEM scoring and inspect provenance.

Frozen Atlantic structural spine with manifests and receipts
Forward-only, audit-ready artifacts
Two horizons (event activations + year-level SRI)
SDK delivery surface
Cross-basin transfer diagnostics (EPAC) under identical freeze discipline

Two structural horizons

PTEM operates across two complementary horizons: event-scale structural dynamics and basin-scale structural climatology.

Event scale

Activation episodes, lead distributions, lifecycle regime transitions

Forward-only activation episodes recorded at a 6-hour cadence
Per-advisory manifests, validation receipts, and operational behavior summaries
Episode stability, morphology, and gating notes preserved as immutable artifacts

Climatology scale

Structural Regime Index (SRI): regime density, drift, clustering

Canonical SRI freeze with pre-declared percentile and baseline parameters (year-level only)
Robustness metadata (percentile depth × baseline memory) embedded in validation receipts
Immutable manifest bundle with hashes; no storm-level structural exposure

What PTEM adds alongside CAT models

Traditional catastrophe tools measure outcomes.

Intensity trajectories
Hazard footprints
Loss distributions

PTEM measures structural organization.

Regime tightening
Persistence and decay
Structural clustering across basins

Non-stationarity and climate drift monitoring
Tail-regime density and persistence tracking
Independent challenge layer for model assumptions
Second axis of evidence alongside intensity guidance

Credibility & Governance

PTEM operates under a freeze-controlled governance model: forward-only scoring on the frozen Atlantic v1.2 spine, hash-locked manifests, and receipts ensure reproducibility across basins.

Frozen Atlantic structural spine v1.2 (1851–2024) replayed at a 6-hour cadence under a single freeze.
Forward-only computation with no look-ahead or retroactive edits; pre-declared Structural Regime Index thresholds filed before release.
Hash-locked manifests and receipts accompany every activation and climatology drop.
Cross-basin portability — EPAC runs issued under the same governance contract.

Why PTEM?

PTEM augments hazard and loss models with a governed structural perspective, capturing how rare high-organization regimes emerge and persist and preserving those observations as immutable artifacts for institutional review.

Every canonical run inherits the frozen Atlantic v1.2 spine, forward-only rules, and documented gating choices so model-risk teams can replay PTEM scoring from manifests and receipts.

Catastrophe models remain the outcome layer; PTEM supplies the structural layer for drift audits, seasonal context, and interrogation of assumptions. Lead-time, survival, and illustrative precision/recall characteristics live on /validation so they are read in the correct mechanism-based lens rather than as headline metrics.

Snapshot

A compact view of the PTEM hurricane engine

A frozen structural dataset, a reproducible engine, and a narrow surface area for integration.

Scorecards

Versioned scorecards and per-storm summaries that partners use to validate and audit engine behavior.

Structural snapshots

Compact structural snapshots at a 6-hour cadence so teams can integrate PTEM signals without exposing internal model fits.

Governed access

Access tiers that separate evaluation/research from production-grade enterprise integrations with governance and audit support.

How PTEM works

A structural engine on a frozen, auditable dataset

PTEM runs on a frozen, multi-season tropical cyclone dataset. The engine produces governed structural signals that can be audited, compared against baselines, and blended into existing risk workflows.

Step 1

Frozen dataset

PTEM is anchored to a multi-season dataset so partners can reproduce scoring and compare model snapshots fairly.

Step 2

Structural engine & governance

PTEM extracts structural signals, applies governance layers, and delivers versioned outputs for audit and integration.

Step 3

Integration & validation

Partners start with evaluation materials and can progress to enterprise integrations supported by validation packs and governance processes.

SDK integration

PTEM is delivered through a governed SDK that fronts the structural engine. Risk teams pull structural metrics and readiness channels through that single surface and wire them into existing hazard workflows, internal tools, or research environments.

Integration surface: illustrative SDK structural snapshot for downstream risk workflows using ops-safe structural channels.

{
  "storm_id": "al152025",
  "dtg": "2025-09-29T18:00:00Z",
  "hc_struct": 0.81,
  "fme_struct": 0.72,
  "pl_struct": 0.67,
  "dc_struct": 0.03,
  "ppi_live_norm": 0.92
}

Illustrative structural channel names; the SDK output is ops-safe by default and versioned.

This example shows a single structural snapshot for a hypothetical storm: a normalized structural coherence score, energy-like change metrics, phase alignment, structural trend, and an aggregate readiness measure. The actual schema is versioned and documented in the SDK.

PTEM operates as a managed, trade-secret-protected system. The SDK carries version tags for both dataset and model revisions so downstream systems always know what they are consuming.

See validation details →

Key features

Structural Coherence Engine

Captures changes in a storm’s internal organization using a governed set of structural metrics. Designed to complement—not replace—existing hazard models.

Governed readiness channels

Composite structural readiness channels derived from storm organization, symmetry, and burst patterns. Highlight periods where storms may be structurally receptive to rapid changes.

Enterprise SDK

Python SDK client for seamless integration into insurance, reinsurance, or research modeling workflows.

Frozen Validation Harness

A forward-only, 6-hour aligned evaluation harness executed across the full frozen Atlantic structural spine (1851–2024), enabling reproducible scoring, sensitivity analysis, and audit-safe validation.

Who uses PTEM

Built for institutional risk owners

PTEM is designed for reinsurers, carriers, public programs, and modeling teams that need structural visibility into storm evolution.

Reinsurers & carriers

Use structural signals to stress-test portfolios, examine alternative scenarios, and compare PTEM behaviour against existing cat models.

Public agencies & programs

Support planning and communications with a structural view on storm organisation, without replacing official forecasts.

Research & modeling teams

Use the frozen dataset and structural outputs as a benchmark for new models, or as a complementary signal inside broader risk experiments.