Air Mass Source Region Classifier

Measured thermodynamic/moisture and independently trajectory-confirmed source-region evidence. Independently declared positive evidence requirements; overlapping/unknown classes retained. Caller independently establishes matching units, evidence, method edition and applicability; output is not compliance, diagnosis, work-safety approval, geological identity or validated hazard prediction.

Description

Air-mass source classifications depend on independently established source-region and thermodynamic evidence.

Air-mass source classifications depend on independently established source-region and thermodynamic evidence.^[1]

Candidate labels require an explicit classification scheme. The tool compares your observed and known flags with your declared positive requirements, retaining unresolved candidates.

When to use Air Mass Source Region Classifier

Use this tool to calculate or review the supplied observations under the stated rules. Establish the observation method, units, averaging period and applicable reference or calibration.

How to use Air Mass Source Region Classifier and understand its results

Establish the observation method, units, averaging period and applicable reference or calibration.
Enter callerAirMassSourceClassIds, callerAirMassSourceRequiredEvidence, observedAirMassSourceEvidence, knownAirMassSourceEvidenceFlags, using the field meanings and rules below, then run the tool.
Read compatibleCallerClasses, fullyWitnessedCallerClasses, using the output meanings and calculation rules below. Distinguish compatible candidates from fully witnessed classes; compatibility can retain unknown required evidence.
Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.

Input field	Meaning	Value type	Requirement
callerAirMassSourceClassIds	Caller air mass source class ids	list of string	Required
callerAirMassSourceRequiredEvidence	Caller air mass source required evidence	numeric matrix	Required
observedAirMassSourceEvidence	Observed air mass source evidence	list of number	Required
knownAirMassSourceEvidenceFlags	Known air mass source evidence flags; binary 1 means the matched observation is known, 0 means unknown	list of number	Required

Use unique nonblank class IDs and a nonempty binary requirement matrix aligned by class and evidence column. Every class must require at least one positive feature. A one requires presence; zero ignores the feature and does not require absence. Supply binary observed evidence and known flags. A known required zero excludes a class; an unknown required feature retains compatibility but prevents full witnessing. Return all compatible classes and the subset with every required feature known and present. Classes may overlap.

compatible_c=∀j(requirement_cj=0 or known_j=0 or evidence_j=1); witnessed_c=∀j(requirement_cj=0 or (known_j=1 and evidence_j=1))

Use the matching field units and the exact boundary, ordering and reference rules above.

Output field	Meaning	Value type
compatibleCallerClasses	Compatible caller classes	list of string
fullyWitnessedCallerClasses	Fully witnessed caller classes	list of string

json

{
  "input": {
    "callerAirMassSourceClassIds": [
      "a",
      "b"
    ],
    "callerAirMassSourceRequiredEvidence": [
      [
        1,
        0
      ],
      [
        0,
        1
      ]
    ],
    "observedAirMassSourceEvidence": [
      1,
      0
    ],
    "knownAirMassSourceEvidenceFlags": [
      1,
      0
    ]
  },
  "output": {
    "compatibleCallerClasses": [
      "a",
      "b"
    ],
    "fullyWitnessedCallerClasses": [
      "a"
    ]
  }
}

Limitations and assumptions

The observations and reference conditions must be independently established. This result does not supply missing measurements, uncertainty or an official warning. Compatible classes with unknown evidence are not positive identifications. Fully witnessed classes satisfy only the declared positive requirements.

Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries; ordinary string lists allow at most 128 strings of 128 UTF-16 units each; numeric matrices allow at most 128 rows and 128 columns, subject to narrower requirements above.

Alternative or Complementary methods

For a related step, use Advection Fog Sea Delta Checker: Air dewpoint above sea-surface temperature indicates a potential condensation margin under sufficient cooling. For a complementary comparison, use Harmattan Dust Season Lookup: Harmattan season descriptions concern regional dry and dusty airflow in a particular place and period.

References

Air Mass Source Region Classifier — tool.io

Similar or alternative tools

Advection Fog Sea Delta Checker
Air dewpoint above sea-surface temperature indicates a potential condensation margin under sufficient cooling.
Harmattan Dust Season Lookup
Harmattan season descriptions concern regional dry and dusty airflow in a particular place and period.