StormZ Data Signals
StormZ tracks evolving atmospheric structures associated with tropical cyclone formation.
Each day, candidate storm systems are detected, scored, and tracked forward in time to identify risk drift,
persistence, and potential genesis windows.
StormZ combines satellite-derived atmospheric signals with historical storm data to estimate where and when storm development may occur.
The locations at which major storms develop depend partly on the evolving, basin-wide organisation of water vapour.
Daily, statistically significant increases in water vapour accompanied by decreases in outgoing longwave radiation, measured at the top of the atmosphere, are displayed by location. The Storm Propensity Index (SPI) is a z-score measure of this divergence.
Ten years of historical storm data provide the statistical baselines for moving-average risk scores derived from SPI amplitude, fractal characteristics, and residual behaviour.
- Persistent SPI nodes, or spirals, are interpreted as signatures of basin-scale atmospheric organisation rather than local weather systems.
- Relocation of these nodes may reflect changes in the basin-wide atmospheric energy balance.
- SPI nodes over land masses play a different role. Land provides a physical and thermal boundary for water vapour fluctuations. Over ocean, reduced outgoing longwave radiation is an indicator of storm convection.
Over hot, arid regions, reduced outgoing longwave radiation may also reflect land-surface heat storage.
StormZ data sources include NASA MERRA-2, European Centre ERA reanalysis data, and NOAA IBTrACS tropical cyclone records.
What StormZ Shows
The StormZ map displays daily storm-risk drift derived from tracked atmospheric candidate groups.
Each visible spiral represents a persistent atmospheric structure that has shown signals associated with storm development.
Risk structures are detected from divergence patterns between total column water vapour (TQV) and outgoing longwave radiation (OLR) — a known indicator of convective activity.
Clicking a spiral reveals the candidate’s estimated genesis window, persistence history, and associated atmospheric signals.
Core Signals
StormZ combines several atmospheric indicators into interpretable risk signals:
GRI – Global Risk Index:
Composite risk indicator combining atmospheric instability and energy imbalance.
SCI – Storm Coupling Index:
Degree to which atmospheric instability is organizing toward storm formation.
EII – Energy Imbalance Index:
Strength of atmospheric energy divergence available to power storm growth.
REOI – Regional Energy Oscillation Index:
Historical volatility context for the region.
Convection Amplitude:
Strength of divergence between water vapour increase and longwave radiation decrease.
Convection Spike :
Late-stage surge in convective activity often preceding storm formation.
Persistence:
Tracks that appear repeatedly over several days have higher confidence.
Genesis Window:
Estimated time range in which storm formation may occur.
How to Read the Map
Pale Sun Symbol:
Indicates a tracked atmospheric candidate associated with storm risk.
Heat Field:
Represents the regional storm risk anomaly derived from atmospheric volatility.
Centroid Marker:
Approximate center of the detected atmospheric structure.
Spiral Growth:
Spiral size increases as risk approaches its peak.
Imminence Signal:
Risk structures approaching a predicted genesis window become more prominent.
StormZ Reporting Fields
Subscriber reports provide detailed diagnostic fields describing each tracked atmospheric structure.
These include:
⇒ Atmospheric signals
⇒ Water vapour / radiation divergence metrics
⇒ Convection amplitude and spike signals
⇒ Rotational instability measures
⇒ Structural diagnostics
⇒ Persistence of candidate structures
⇒ Centroid drift and spatial extent
⇒ Track continuity and clustering behaviour
⇒ Genesis timing estimates
⇒ Predicted genesis center date
⇒ Early and late bounds of the estimated window
⇒ Confidence and uncertainty measures
⇒ Risk aggregation
⇒ Maximum and mean risk signals across tracked groups
⇒ Composite indices such as SCI, EII, IAI, and GRI
These fields allow analysts to examine how atmospheric structures evolve before storms form, enabling deeper investigation into storm development patterns.