Surface Weather Station v1.1 turns the first Compositional Defiguration framework into an operational research instrument.
The version locks all five signals to a reproducible ordinal scale and supplies decision rules for Visibility, Anchor Alignment, Figural Integrity, Compositional Lift, and Redundant Substrate Breadth. It formalizes substrate breadth as an effective independence score, ensuring that twenty pages under one authority do not masquerade as twenty independent witnesses.
The calibration adds Occlusion as a state distinct from visible distortion, makes the Scale Drift Index symmetric, expands the query battery to five forms, fixes the object set at twelve canonical objects, and specifies observation-environment metadata. It also creates a governance layer: Green, Yellow, and Red surface states connected to repair actions.
A major innovation is cross-substrate replication. The same corpus can be observed through different AI systems and retrieval stacks, and divergence among those observations becomes evidence about the public composition layer itself. The instrument therefore measures not only whether a corpus is visible, but how visibility changes depending on the machine through which the public encounters it.
Version 1.1 also links surface visibility to persistent-identifier analysis, creating a unified diagnostic for works whose meaning survives while anchors fail, whose addresses survive while composition ignores them, or whose figure disappears entirely.
It is the moment the weather station becomes runnable: a sovereign method for producing dated, citable evidence about how knowledge is represented, selected, displaced, or forgotten.