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Service Description: Argo is a global network of more than 3000 free-drifting robots that measure temperature and salinity of the upper 2000 m of the ocean. This allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being sent to satellites passing overhead and then made publicly available within hours after collection.
Main Benefits:
- Improve Ocean and Climate forecasting
- Understand ocean-atmosphere interactions
- Predict seasonal to decadal climate variability
Argo improves maps of the distribution of the heat energy in the ocean and, as a consequence, improves forecasting of the development (track and intensity) of sever weather systems. Sever weather systems are driven by convection and the transfer of water vapour from the ocean to the atmosphere. Hurricanes (e.g. Katrina, Gulf of Mexico) gain strength when passing over positive temperature anomaly areas and decay over low temperature anomaly regions. Argo, an old dream of oceanographers, is becoming the ocean's climate warning system for the benefits of humankind.
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Description: Argo is a global network of more than 3000 free-drifting robots that measure temperature and salinity of the upper 2000 m of the ocean. This allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being sent to satellites passing overhead and then made publicly available within hours after collection.Main Benefits: - Improve Ocean and Climate forecasting - Understand ocean-atmosphere interactions - Predict seasonal to decadal climate variabilityArgo improves maps of the distribution of the heat energy in the ocean and, as a consequence, improves forecasting of the development (track and intensity) of sever weather systems. Sever weather systems are driven by convection and the transfer of water vapour from the ocean to the atmosphere. Hurricanes (e.g. Katrina, Gulf of Mexico) gain strength when passing over positive temperature anomaly areas and decay over low temperature anomaly regions. Argo, an old dream of oceanographers, is becoming the ocean's climate warning system for the benefits of humankind.
Copyright Text: OceanOPS
Spatial Reference:
4326
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Initial Extent:
XMin: -193.85948643679544
YMin: -119.91114295555275
XMax: 190.93975737804416
YMax: 146.1905973187496
Spatial Reference: 4326
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Full Extent:
XMin: -180
YMin: -90
XMax: 180
YMax: 90
Spatial Reference: 4326
(4326)
Units: esriDecimalDegrees
Document Info:
Title: Argo Network Real Time Locations
Author:
Comments: Argo is a global network of more than 3000 free-drifting robots that measure temperature and salinity of the upper 2000 m of the ocean. This allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being sent to satellites passing overhead and then made publicly available within hours after collection.Main Benefits: - Improve Ocean and Climate forecasting - Understand ocean-atmosphere interactions - Predict seasonal to decadal climate variabilityArgo improves maps of the distribution of the heat energy in the ocean and, as a consequence, improves forecasting of the development (track and intensity) of sever weather systems. Sever weather systems are driven by convection and the transfer of water vapour from the ocean to the atmosphere. Hurricanes (e.g. Katrina, Gulf of Mexico) gain strength when passing over positive temperature anomaly areas and decay over low temperature anomaly regions. Argo, an old dream of oceanographers, is becoming the ocean's climate warning system for the benefits of humankind.
Subject: Argo floats' latest and deployment locations: one layer to represent deployment location of the floats, the second one contains the latest location of each float, according to the data transmitted to the Global Data Assembly Centres (GDAC).
Category:
Keywords: goos,oceanops,integrated,weather,ocean,meteorology,oceanography,observation,wmo,ioc,argo
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Supports Return Service Edits Option : false
Supports Dynamic Layers: false
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