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feat(stories): content update #618

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Sep 14, 2020
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3 changes: 2 additions & 1 deletion i18n/en.json
Original file line number Diff line number Diff line change
Expand Up @@ -59,5 +59,6 @@
"tags.satellite-orbits": "Satellite Orbits",
"tags.sensors": "Sensors",
"tags.electromagnetic-spectrum": "Electromagnetic Spectrum",
"tags.climate-modelling": "Climate Modelling"
"tags.climate-modelling": "Climate Modelling",
"tags.geostationary-satellite": "Geostationary Satellite"
}
3 changes: 2 additions & 1 deletion i18n/es.json
Original file line number Diff line number Diff line change
Expand Up @@ -59,5 +59,6 @@
"tags.satellite-orbits": "Órbitas satelitales",
"tags.sensors": "Sensores",
"tags.electromagnetic-spectrum": "Espectro electromagnético",
"tags.climate-modelling": "Modelos climáticos"
"tags.climate-modelling": "Modelos climáticos",
"tags.geostationary-satellite": "Satélite geoestacionario"
}
3 changes: 2 additions & 1 deletion i18n/fr.json
Original file line number Diff line number Diff line change
Expand Up @@ -59,5 +59,6 @@
"tags.satellite-orbits": "Orbites des satellites",
"tags.sensors": "Détecteurs",
"tags.electromagnetic-spectrum": "Spectre électromagnétique",
"tags.climate-modelling": "Modélisation climatique"
"tags.climate-modelling": "Modélisation climatique",
"tags.geostationary-satellite": "Satellite géostationnaire"
}
3 changes: 2 additions & 1 deletion i18n/nl.json
Original file line number Diff line number Diff line change
Expand Up @@ -59,5 +59,6 @@
"tags.satellite-orbits": "Satellietbanen",
"tags.sensors": "Sensoren",
"tags.electromagnetic-spectrum": "Elektromagnetisch Spectrum",
"tags.climate-modelling": "Klimaatmodellering"
"tags.climate-modelling": "Klimaatmodellering",
"tags.geostationary-satellite": "Geostationaire Satelliet"
}
6 changes: 3 additions & 3 deletions storage/layers/layers-de.json
Original file line number Diff line number Diff line change
Expand Up @@ -23,9 +23,9 @@
{
"id": "oc.chlor_a",
"type": "Ocean Biogeochemistry",
"name": "Ocean Color – Chlorophyll-a Concentration",
"shortName": "Ocean Color",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2018 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.0 \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/eef36ac7c892491aa862097e79827f68)"
"name": "Ocean Colour – Chlorophyll-a Concentration",
"shortName": "Ocean Colour",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2019 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.2 \n**DOI:** \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/5400de38636d43de9808bfc0b500e863)"
},
{
"id": "aerosol.AOD550_mean",
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6 changes: 3 additions & 3 deletions storage/layers/layers-en.json
Original file line number Diff line number Diff line change
Expand Up @@ -23,9 +23,9 @@
{
"id": "oc.chlor_a",
"type": "Ocean Biogeochemistry",
"name": "Ocean Color – Chlorophyll-a Concentration",
"shortName": "Ocean Color",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2018 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.0 \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/eef36ac7c892491aa862097e79827f68)"
"name": "Ocean Colour – Chlorophyll-a Concentration",
"shortName": "Ocean Colour",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2019 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.2 \n**DOI:** \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/5400de38636d43de9808bfc0b500e863)"
},
{
"id": "aerosol.AOD550_mean",
Expand Down
6 changes: 3 additions & 3 deletions storage/layers/layers-es.json
Original file line number Diff line number Diff line change
Expand Up @@ -23,9 +23,9 @@
{
"id": "oc.chlor_a",
"type": "Ocean Biogeochemistry",
"name": "Ocean Color – Chlorophyll-a Concentration",
"shortName": "Ocean Color",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2018 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.0 \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/eef36ac7c892491aa862097e79827f68)"
"name": "Ocean Colour – Chlorophyll-a Concentration",
"shortName": "Ocean Colour",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2019 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.2 \n**DOI:** \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/5400de38636d43de9808bfc0b500e863)"
},
{
"id": "aerosol.AOD550_mean",
Expand Down
6 changes: 3 additions & 3 deletions storage/layers/layers-fr.json
Original file line number Diff line number Diff line change
Expand Up @@ -23,9 +23,9 @@
{
"id": "oc.chlor_a",
"type": "Ocean Biogeochemistry",
"name": "Ocean Color – Chlorophyll-a Concentration",
"shortName": "Ocean Color",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2018 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.0 \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/eef36ac7c892491aa862097e79827f68)"
"name": "Ocean Colour – Chlorophyll-a Concentration",
"shortName": "Ocean Colour",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2019 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.2 \n**DOI:** \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/5400de38636d43de9808bfc0b500e863)"
},
{
"id": "aerosol.AOD550_mean",
Expand Down
6 changes: 3 additions & 3 deletions storage/layers/layers-nl.json
Original file line number Diff line number Diff line change
Expand Up @@ -23,9 +23,9 @@
{
"id": "oc.chlor_a",
"type": "Ocean Biogeochemistry",
"name": "Ocean Color – Chlorophyll-a Concentration",
"shortName": "Ocean Color",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2018 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.0 \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/eef36ac7c892491aa862097e79827f68)"
"name": "Ocean Colour – Chlorophyll-a Concentration",
"shortName": "Ocean Colour",
"description": "Chlorophyll-a is the primary pigment in many plants, including the phytoplankton in the ocean. It absorbs light, allowing plants to photosynthesise and so generate energy to grow. Ocean colour remote sensing uses this light absorption to quantify the amount of Chlorophyll-a in the surface ocean, the depth to which the light penetrates, and so quantify the amount of phytoplankton. Phytoplankton are essential because they are the foundation of the marine food chain, playing a role in carbon fixation that potentially reduces human-induced carbon dioxide in the atmosphere, but can also increase ocean acidification.\n\nThe Ocean Colour CCI project has created a consistent time-series by merging data from multiple ocean colour satellites, including ESA’s MERIS dataset and NASA’s SeaWiFS, MODIS-Aqua and VIIRS datasets. The project is also in the process of adding the Copernicus/ESA OLCI dataset. Further details can be found online at [climate.esa.int/projects/ocean-colour](https://climate.esa.int/en/projects/ocean-colour/)\n\n**Variable Shown:** Chlorophyll-a concentration in seawater in Milligram/m3 \n**Time Span:** September 1997 – December 2019 \n**Temporal Resolution:** monthly \n**Geographic Extent:** global \n**Spatial Resolution:** 4 km \n**Version:** 4.2 \n**DOI:** \n\n[ESA CCI Ocean Color ECV Project website](https://esa-oceancolour-cci.org/) \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/5400de38636d43de9808bfc0b500e863)"
},
{
"id": "aerosol.AOD550_mean",
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2 changes: 1 addition & 1 deletion storage/stories/stories-de.json
Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,6 @@
"title": "Den Puls des Planeten messen",
"description": "",
"image": "assets/soilmoisture_large_14.jpg",
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling"]
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling", "geostationary-satellite"]
}
]
2 changes: 1 addition & 1 deletion storage/stories/stories-en.json
Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,7 @@
"title": "Taking the Pulse of the Planet",
"description": "",
"image": "assets/soilmoisture_large_14.jpg",
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling"],
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling", "geostationary-satellite"],
"position": [40, -25]
}
]
2 changes: 1 addition & 1 deletion storage/stories/stories-es.json
Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,7 @@
"title": "Taking the Pulse of the Planet",
"description": "",
"image": "assets/soilmoisture_large_14.jpg",
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling"],
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling", "geostationary-satellite"],
"position": [40, -25]
}
]
2 changes: 1 addition & 1 deletion storage/stories/stories-fr.json
Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,6 @@
"title": "Taking the Pulse of the Planet",
"description": "",
"image": "assets/soilmoisture_large_14.jpg",
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling"]
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling", "geostationary-satellite"]
}
]
2 changes: 1 addition & 1 deletion storage/stories/stories-nl.json
Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,6 @@
"title": "Taking the Pulse of the Planet",
"description": "",
"image": "assets/soilmoisture_large_14.jpg",
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling"]
"tags": ["satellite-orbits", "sensors", "electromagnetic-spectrum", "climate-modelling", "geostationary-satellite"]
}
]
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