Goddard Earth Observing System models
E88904
The Goddard Earth Observing System models are a suite of advanced atmospheric and Earth system models used for global weather, climate, and data assimilation research and forecasting.
All labels observed (16)
How this entity was disambiguated
This entity first appeared as the object of triple T747354 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: Goddard Earth Observing System models Context triple: [Goddard Space Flight Center, manages, Goddard Earth Observing System models]
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A.
Global Data-processing and Forecasting System
The Global Data-processing and Forecasting System is an international meteorological infrastructure that collects, processes, and distributes weather and climate data to support global forecasting and early warning services.
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B.
Global Climate Observing System
The Global Climate Observing System is an international program that coordinates and supports comprehensive, long-term observations of the Earth’s climate system to underpin climate research, services, and policy.
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C.
Deep Space Climate Observatory
The Deep Space Climate Observatory (DSCOVR) is a NOAA and NASA satellite positioned at the Sun–Earth L1 Lagrange point that continuously monitors solar wind conditions and provides real-time space weather and Earth observation data.
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D.
Mars Science Laboratory entry, descent, and landing modeling
Mars Science Laboratory entry, descent, and landing modeling is the suite of analytical and computational tools used to predict and optimize the Curiosity rover’s atmospheric entry, parachute descent, and landing performance on Mars.
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E.
Geostationary Operational Environmental Satellite program
The Geostationary Operational Environmental Satellite (GOES) program is a series of U.S. weather satellites in geostationary orbit that provide continuous monitoring of atmospheric, oceanic, and environmental conditions for forecasting and research.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Goddard Earth Observing System models Target entity description: The Goddard Earth Observing System models are a suite of advanced atmospheric and Earth system models used for global weather, climate, and data assimilation research and forecasting.
-
A.
Global Data-processing and Forecasting System
The Global Data-processing and Forecasting System is an international meteorological infrastructure that collects, processes, and distributes weather and climate data to support global forecasting and early warning services.
-
B.
Global Climate Observing System
The Global Climate Observing System is an international program that coordinates and supports comprehensive, long-term observations of the Earth’s climate system to underpin climate research, services, and policy.
-
C.
Deep Space Climate Observatory
The Deep Space Climate Observatory (DSCOVR) is a NOAA and NASA satellite positioned at the Sun–Earth L1 Lagrange point that continuously monitors solar wind conditions and provides real-time space weather and Earth observation data.
-
D.
Mars Science Laboratory entry, descent, and landing modeling
Mars Science Laboratory entry, descent, and landing modeling is the suite of analytical and computational tools used to predict and optimize the Curiosity rover’s atmospheric entry, parachute descent, and landing performance on Mars.
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E.
Geostationary Operational Environmental Satellite program
The Geostationary Operational Environmental Satellite (GOES) program is a series of U.S. weather satellites in geostationary orbit that provide continuous monitoring of atmospheric, oceanic, and environmental conditions for forecasting and research.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
Earth system model suite
ⓘ
atmospheric general circulation model ⓘ numerical weather prediction model ⓘ |
| basedOn | primitive equations of atmospheric motion ⓘ |
| countryOfOrigin |
United States of America
ⓘ
surface form:
United States
|
| developedBy |
Global Modeling and Assimilation Office
ⓘ
Goddard Space Flight Center ⓘ
surface form:
NASA Goddard Space Flight Center
|
| field |
Earth system science
ⓘ
climate modeling ⓘ numerical weather prediction ⓘ |
| hasComponent |
Goddard Earth Observing System models
self-linksurface differs
ⓘ
surface form:
GEOS aerosol module
Goddard Earth Observing System models self-linksurface differs ⓘ
surface form:
GEOS atmospheric chemistry module
Goddard Earth Observing System models self-linksurface differs ⓘ
surface form:
GEOS atmospheric general circulation model
Goddard Earth Observing System models self-linksurface differs ⓘ
surface form:
GEOS data assimilation system
Goddard Earth Observing System models self-linksurface differs ⓘ
surface form:
GEOS land surface model
GEOS ocean model coupling ⓘ GEOS sea ice model coupling ⓘ |
| hasVersion |
Goddard Earth Observing System models
self-linksurface differs
ⓘ
surface form:
GEOS-5
GEOS-FP ⓘ GEOS-IT ⓘ Goddard Earth Observing System models self-linksurface differs ⓘ
surface form:
GEOS-S2S
MERRA reanalysis system ⓘ MERRA reanalysis system ⓘ
surface form:
MERRA-2 reanalysis system
|
| implements |
data assimilation algorithms
ⓘ
ensemble-based data assimilation ⓘ variational data assimilation ⓘ |
| input |
in situ meteorological observations
ⓘ
land surface observations ⓘ ocean observations ⓘ satellite observations ⓘ |
| operatedBy | Global Modeling and Assimilation Office ⓘ |
| spatialCoverage | global ⓘ |
| supports |
ensemble forecasting
ⓘ
near-real-time forecasting ⓘ retrospective reanalysis ⓘ |
| usedFor |
aerosol forecasting
ⓘ
aerosol–cloud interaction studies ⓘ atmospheric composition modeling ⓘ climate change studies ⓘ climate research ⓘ coupled atmosphere–ocean simulations ⓘ data assimilation ⓘ global weather prediction ⓘ observing system simulation experiments ⓘ reanalysis production ⓘ satellite data assimilation ⓘ seasonal forecasting ⓘ stratospheric chemistry studies ⓘ subseasonal to seasonal prediction ⓘ |
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.
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.
Subject: Goddard Earth Observing System models Description of subject: The Goddard Earth Observing System models are a suite of advanced atmospheric and Earth system models used for global weather, climate, and data assimilation research and forecasting.
Referenced by (21)
Full triples — surface form annotated when it differs from this entity's canonical label.