Merge pull request #130 from NASA-IMPACT/bugfix/develop

Fastforward develop to track HEAD of main

overrides/components/visit-ghg.tsx

@@ -85,12 +85,12 @@ export default function VisitGHG({
                 radius="square"
                 variation="primary-fill"
               >
-                Visit the U.S. GHG Center website
+                Visit the US GHG Center website
               </Button>
             </div>
           </InfoImageContent>
         </BottomContent>
       </FoldBody>
     </Fold>
   )
-};
+};

stories/locfeature.HYPER/carousel_content.json

@@ -37,7 +37,7 @@
         "caption":"This 3-D view of our atmosphere shows the rise of carbon dioxide levels from 2020 to 2021. The world’s vegetation and oceans absorb about half of human carbon dioxide emissions. However data stretching as far back as the 1950s, taken from sensors on the ground, show a steady upward march in carbon dioxide concentrations."
     },{
         "src":"https://www.youtube.com/embed/d-bFeE4YZ6s",
-        "title":"Net Ecosystem CO2 Exchange",
+        "title":"Net Ecosystem CO₂ Exchange",
         "caption":"In colors of green and purple, this map shows ecosystems emitting and absorbing carbon dioxide from 2003 to 2017. Green shows plants absorbing the carbon dioxide, with more absorption during the spring and summer growing seasons. Purples shows plants releasing much of this carbon dioxide back to the atmosphere during the fall and winter. "
     },{
         "src":"https://www.youtube.com/embed/35QjTwIG-eg",

stories/theme.AG_.introduction_agriculture/carousel_content.json

@@ -19,5 +19,9 @@
         "src":"https://www.youtube.com/embed/SPHtB88ra6c",
         "title":"Relative Wetness Root Zone Versus Groundwater Comparison",
         "caption":"These maps combine satellite and ground-based measurements to model the relative amount of water stored at two different depths: plant root level and underground. The brown regions represent dry conditions. The blue regions represent wet areas. The maps do not attempt to represent human consumption of water; but rather, they show changes in water storage related to weather, climate, and seasonal patterns. NASA researchers developed these maps with data incorporated data from the joint NASA-German Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions in partnership with the National Drought Mitigation Center."
+    },{
+        "src":"https://www.youtube.com/embed/6z58cOh_1TA",
+        "title":"Increasingly Dangerous Climate for Agricultural Workers",
+        "caption":"A warming climate will create challenges for agricultural workers as well as the crops which they grow. This visualization shows the increased number of days per year that are expected to have a NOAA Heat Index greater than 103 degrees Fahrenheit, a threshold that NOAA labels \u2018dangerous\u2019 given that people struggle to regulate their body temperatures at this level of heat and humidity. These results are from an ensemble of 22 global climate models from the Sixth Coupled Model Intercomparison Project (CMIP6) bias-adjusted by the NASA Earth Exchange (NEX GDDP). Two projections are visualized, one for a moderate emissions climate scenerio (SSP2-4.5) and one for a high emmissions climate scenerio (SSP5-8.5).\nVisualizations by: Mark SubbaRao, Scientific consulting by: Alex C. Ruane\nFor more information or to download this public domain video, go to https://svs.gsfc.nasa.gov/4972"
     }
-]
+]

stories/theme.AG_.mdx

@@ -30,12 +30,24 @@ import contentArray from './theme.AG_.introduction_agriculture/carousel_content.
 
 <Block>
   <Prose>
-    ## Info
-    Producing food has always been challenging, and in the 21st century, human-caused climate change is already affecting food security through increasing temperatures, increased frequency of extreme events, and changing precipitation patterns.
+  ## Info
+  Producing food has always been challenging, and in the 21st century, human-caused climate change is already affecting food security through increasing temperatures, increased frequency of extreme events and changing precipitation patterns.
 
-    Earth data has increasingly become part of the food farming process.
-    Observations from satellites, aircraft, ground sensors, and surveys, combined with high-end computer modeling are used by scientists working with federal agencies who collaborate with farmers, ranchers, fishermen, and decision-makers to share their understanding of the relationship between the Earth system and the environments that provide food across the globe.
+  Earth data have increasingly become part of the food farming process.
+  Observations from satellites, aircraft, ground sensors and surveys, combined with high-end computer modeling are used by scientists working with Federal agencies who collaborate with farmers, ranchers, fishermen and decision-makers to share their understanding of the relationship between the Earth system and the environments that provide food across the globe.
   </Prose>
+    <Figure>
+          <Image
+            src={new URL('./theme.AG_.introduction_agriculture/elnino_crops.jpg', import.meta.url).href}
+            alt='a chloropleth map demonstrating the forecasted impact of elnino on crop yields. The colorbar spans from negative (orange) to positive (purple). Positive impacts are located in the northern and southern tips of Africa, India, China, and the southern parts of Australia. Negative impacts are concentrated in the United States, southern parts of South America, and Central Asia.'
+          />
+        <Caption
+          attrAuthor='The NASA Scientific Visualization Studio'
+          attrUrl='https://svs.gsfc.nasa.gov/31278'
+        >
+            A global map forecasting the impact of El Niño on crop yields. Areas colored in shades of orange indicate regions expected to experience negative impacts on crop yields, while areas in shades of purple are expected to see positive impacts. The map highlights significant regional variations, with negative impacts forecasted for parts of South America, Southern Africa, Southeast Asia, and Australia. Conversely, positive impacts are anticipated in certain regions of North and South America, Europe, and Southwest Asia. This visualization underscores the varied effects of El Niño on agricultural productivity across different global regions.
+        </Caption>
+    </Figure>
 </Block>
 
 <Block type="wide">
@@ -51,16 +63,6 @@ import contentArray from './theme.AG_.introduction_agriculture/carousel_content.
   </Figure>
 </Block>
 
-<Block type="wide">
-  <Prose>
-  ## Agriculture
-  Producing food has always been challenging, and in the 21st century, human-caused climate change is already affecting food security through increasing temperatures, increased frequency of extreme events and changing precipitation patterns.
-
-  Earth data have increasingly become part of the food farming process.
-  Observations from satellites, aircraft, ground sensors and surveys, combined with high-end computer modeling are used by scientists working with Federal agencies who collaborate with farmers, ranchers, fishermen and decision-makers to share their understanding of the relationship between the Earth system and the environments that provide food across the globe.
-  </Prose>
-</Block>
-
 <Block type='wide'>
   <Figure>
     <Carousel items={contentArray} />

stories/theme.AQ_.introduction_air_quality/carousel_content.json

@@ -26,10 +26,26 @@
     },{
         "src":"https://www.youtube.com/embed/aHBDHTXRzxY",
         "title":"Active Fires As Observed by VIIRS, January-September 2021",
-        "caption":"This view of fires around the world from Jan. 1 to Sep. 24, 2021, is thanks to data from  the Visible Infrared Imaging Radiometer Suite, or  (VIIRS), aboard NASA’s Suomi-NPP satellite and the National Oceanic and Atmospheric Administration's NOAA-20 satellite. "
+        "caption":"This view of fires around the world from Jan. 1 to Sep. 24, 2021, is thanks to data from  the Visible Infrared Imaging Radiometer Suite, or  (VIIRS), aboard NASA's Suomi-NPP satellite and the National Oceanic and Atmospheric Administration's NOAA-20 satellite. "
     },{
         "src":"https://www.youtube.com/embed/miTwo0oKMB4",
         "title":"Spread of the Dixie Fire",
-        "caption":"The largest fire in California’s recorded history was the 2021 Dixie Fire. Combining active fire detections via NASA’s Suomi-NPP satellite with computer models, Earth scientists could update the size of the fire and estimate where it would spread. The data from Suomi-NPP provided updated data every 12 hours. In this visualization, yellow lines show the fire front lines based on the active fire data (red points) every 12 hours. In total, the Dixie fire burned for more than 100 days, including more than a month of fire activity after the perimeter was contained in mid-September."
+        "caption":"The largest fire in California's recorded history was the 2021 Dixie Fire. Combining active fire detections via NASA's Suomi-NPP satellite with computer models, Earth scientists could update the size of the fire and estimate where it would spread. The data from Suomi-NPP provided updated data every 12 hours. In this visualization, yellow lines show the fire front lines based on the active fire data (red points) every 12 hours. In total, the Dixie fire burned for more than 100 days, including more than a month of fire activity after the perimeter was contained in mid-September."
+    },{
+        "src":"https://www.youtube.com/embed/gQ5HJdKaTKY",
+        "title":"Predicting Air Pollution with Computer Models: Nitrogen Oxides",
+        "caption":"Soot. Exhaust. Ghosting smog. Air pollutants can travel in wind and wildfire smoke, brew by day, and change by the hour.\n\nPredictions of air pollution are created using complex models that combine information about weather and the emissions, transformation, and transport of chemical species and particles. The Goddard Earth Observing System Composition Forecasting (GEOS-CF) system is a research model maintained by NASA\u2019s Global Modeling and Assimilation Office to help scientists understand the causes and impact of air pollution. It is one of the highest resolution and most detailed models of its kind in the world, made possible through ongoing collaborations between NASA and university scientists. GEOS-CF tracks the concentrations of hundreds of gas phase chemical species and dozens of types of particles characterized by their composition and size.\n\n It is used by a wide variety of stakeholders around the world to develop new methods for improving local predictions, understanding the impact of pollution on human health, and improving the quality of NASA satellite datasets.\n\nFor more information or to download this public domain video, go to https://svs.gsfc.nasa.gov/14439"
+    },{
+        "src":"https://www.youtube.com/embed/f6ErmXRAFjw",
+        "title":"Predicting Air Pollution with Computer Models: PM2.5",
+        "caption":"Soot. Exhaust. Ghosting smog. Air pollutants can travel in wind and wildfire smoke, brew by day, and change by the hour.\n\nPredictions of air pollution are created using complex models that combine information about weather and the emissions, transformation, and transport of chemical species and particles. The Goddard Earth Observing System Composition Forecasting (GEOS-CF) system is a research model maintained by NASA\u2019s Global Modeling and Assimilation Office to help scientists understand the causes and impact of air pollution. It is one of the highest resolution and most detailed models of its kind in the world, made possible through ongoing collaborations between NASA and university scientists. GEOS-CF tracks the concentrations of hundreds of gas phase chemical species and dozens of types of particles characterized by their composition and size.\n\n It is used by a wide variety of stakeholders around the world to develop new methods for improving local predictions, understanding the impact of pollution on human health, and improving the quality of NASA satellite datasets.\n\nFor more information or to download this public domain video, go to https://svs.gsfc.nasa.gov/14439"
+    },{
+        "src":"https://www.youtube.com/embed/A9V518Zpzeg",
+        "title":"Predicting Air Pollution with Computer Models: Near Surface Ozone",
+        "caption":"Soot. Exhaust. Ghosting smog. Air pollutants can travel in wind and wildfire smoke, brew by day, and change by the hour.\n\nPredictions of air pollution are created using complex models that combine information about weather and the emissions, transformation, and transport of chemical species and particles. The Goddard Earth Observing System Composition Forecasting (GEOS-CF) system is a research model maintained by NASA\u2019s Global Modeling and Assimilation Office to help scientists understand the causes and impact of air pollution. It is one of the highest resolution and most detailed models of its kind in the world, made possible through ongoing collaborations between NASA and university scientists. GEOS-CF tracks the concentrations of hundreds of gas phase chemical species and dozens of types of particles characterized by their composition and size.\n\n It is used by a wide variety of stakeholders around the world to develop new methods for improving local predictions, understanding the impact of pollution on human health, and improving the quality of NASA satellite datasets.\n\nFor more information or to download this public domain video, go to https://svs.gsfc.nasa.gov/14439"
+    },{
+        "src":"https://www.youtube.com/embed/KnZsVY1mO00",
+        "title":"Predicting Air Pollution with Computer Models: Carbon Monoxide",
+        "caption":"Soot. Exhaust. Ghosting smog. Air pollutants can travel in wind and wildfire smoke, brew by day, and change by the hour.\n\nPredictions of air pollution are created using complex models that combine information about weather and the emissions, transformation, and transport of chemical species and particles. The Goddard Earth Observing System Composition Forecasting (GEOS-CF) system is a research model maintained by NASA\u2019s Global Modeling and Assimilation Office to help scientists understand the causes and impact of air pollution. It is one of the highest resolution and most detailed models of its kind in the world, made possible through ongoing collaborations between NASA and university scientists. GEOS-CF tracks the concentrations of hundreds of gas phase chemical species and dozens of types of particles characterized by their composition and size.\n\n It is used by a wide variety of stakeholders around the world to develop new methods for improving local predictions, understanding the impact of pollution on human health, and improving the quality of NASA satellite datasets.\n\nFor more information or to download this public domain video, go to https://svs.gsfc.nasa.gov/14439"
     }
 ]

stories/theme.AQ_.mdx

@@ -61,26 +61,10 @@ import contentArray from './theme.AQ_.introduction_air_quality/carousel_content.
   </Figure>
 </Block>
 
-<Block type="wide">
-  <Prose>
-  ## Air Quality
-    Air pollution is a global hazard, so it takes a combination of airborne, ground and satellite-based tools to better understand the origins and movement of pollutants, as well as the impacts on air quality.
-    The causes of air pollution vary from human activities, such as coal-fired power plants, to natural events, like wildfires and dust storms.
-
-  Ground-based measurements are also used to assess air quality and the concentrations of different types of atmospheric pollution. Satellite data help fill the gaps between ground-based monitors, so there is global coverage over all neighborhoods.
-
-  Satellite-acquired data have many health and air-quality applications, including:
-  * Monitoring the movement of wildfire smoke and dust plumes.
-  * Tracking the path of ash from volcanic eruptions.
-  * Identifying concentrations of nitrogen dioxide, sulfur dioxide and other pollutants near cities, suburbs and major transportation systems.
-  * Understanding how concentrations of these pollutants are changing over time.
-  </Prose>
-</Block>
-
 <Block>
     <Prose>
       ### DID YOU KNOW?
-      The ozone hole is primarily caused by human-produced chemicals like chlorofluorocarbons (CFCs), which were banned by an international treaty in 1989 to protect our natural sunscreen. Modern global warming is driven by greenhouse gases like carbon dioxide (CO2) and is primarily linked to the burning of fossil fuels. 
+      The ozone hole is primarily caused by human-produced chemicals like chlorofluorocarbons (CFCs), which were banned by an international treaty in 1989 to protect our natural sunscreen. Modern global warming is driven by greenhouse gases like carbon dioxide (CO₂) and is primarily linked to the burning of fossil fuels. 
     </Prose> 
     <Figure>
       <Image

stories/theme.BIO.introduction_biodiversity.mdx

@@ -24,23 +24,4 @@ taxonomy:
   - name: Theme Page
     values:
       - biodiversity
----
-
-import CardGallery from "./components/card_gallery";
-import { biodiversityStoryIds } from "../overrides/common/story-data";
-
-<Block type='wide'>
-  <Prose>
-    ## Info
-
-    Planetary change includes more than understanding the physical components of our planet, it also includes understanding how diversity of life on Earth is changing too.
-    Biodiversity refers to the variety, or diversity, of all life on Earth.
-    However, changes in temperature, precipitation and land cover directly impact the ability of species to survive and the habitats where they are found.
-    Researchers in local habitats work on the ground, directly monitoring vegetation and wildlife, while researchers using remote sensing techniques study biodiversity from space-based and airborne missions.
-    Both approaches provide critical information on species richness and distribution across the globe.
-    Additionally, modeling can be used to forecast how species and their habitat may change in the future.
-    This information is also used across multiple scales of research and government to inform management practices.
-  </Prose>
-</Block>
-
-<CardGallery title={"Biodiversity Stories"} storyIds={biodiversityStoryIds} />
+---