MAESTRO
E239147
MAESTRO is a Canadian satellite instrument designed to measure atmospheric trace gases and ozone-related chemistry from orbit.
All labels observed (1)
| Label | Occurrences |
|---|---|
| MAESTRO canonical | 1 |
Statements (43)
| Predicate | Object |
|---|---|
| instanceOf |
atmospheric sounding instrument
ⓘ
satellite instrument ⓘ |
| acronymFor |
Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation
ⓘ
surface form:
Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation
|
| altitudeRangeObserved |
stratosphere
ⓘ
troposphere ⓘ |
| contributesTo |
assessment of atmospheric pollution
ⓘ
global monitoring of ozone layer ⓘ |
| countryOfOrigin | Canada ⓘ |
| dataProduct | vertical profiles of atmospheric constituents ⓘ |
| dataUse |
climate research
ⓘ
ozone trend analysis ⓘ validation of atmospheric models ⓘ validation of other satellite instruments ⓘ |
| developedBy |
Environment and Climate Change Canada
ⓘ
surface form:
Environment Canada
University of Toronto ⓘ |
| developedInCollaborationWith | Canadian Space Agency ⓘ |
| hostedOn |
SCISAT-1
ⓘ
surface form:
SCISAT mission
|
| launchDate | 2003-08-12 ⓘ |
| launchSite |
Vandenberg Space Force Base
ⓘ
surface form:
Vandenberg Air Force Base
|
| launchVehicle | Pegasus XL ⓘ |
| measurementTechnique |
limb viewing
ⓘ
solar occultation ⓘ |
| measures |
aerosol extinction
ⓘ
atmospheric trace gases ⓘ nitrogen dioxide ⓘ ozone ⓘ water vapour ⓘ |
| missionType |
Earth observation
ⓘ
atmospheric science ⓘ |
| operator | Canadian Space Agency ⓘ |
| orbits | Earth ⓘ |
| orbitsWith | SCISAT-1 ⓘ |
| orbitType | low Earth orbit ⓘ |
| primaryMission |
measure atmospheric trace gases
ⓘ
study ozone-related chemistry ⓘ |
| scientificObjective |
improve understanding of stratospheric chemistry
ⓘ
monitor tropospheric composition ⓘ study ozone layer depletion ⓘ |
| spacecraft | SCISAT-1 ⓘ |
| spectralRange |
near-infrared
ⓘ
ultraviolet ⓘ visible ⓘ |
| status | operational (for many years after launch) ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: MAESTRO Description of subject: MAESTRO is a Canadian satellite instrument designed to measure atmospheric trace gases and ozone-related chemistry from orbit.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.