|
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Tight) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a narrow view of the US. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Tight) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a narrow view of the US. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Tight) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a narrow view of the US. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Tight) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a narrow view of the US. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Tight) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a narrow view of the US. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Tight) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a narrow view of the US. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
True Color MODIS Albedo imag
…
| Title |
True Color MODIS Albedo image improves Climate Modeling |
| Abstract |
The MODIS instrument, flying aboard NASA's Terra and Aqua satellites, measures how much solar radiation is reflected by the Earth's surface almost every day over the entire planet. Zooming in on Africa's Sahara Desert and the Arabian Peninsula, MODIS observed considerable variability in reflectance across the region-from the darkest volcanic terrains to the brightest sand. This matches specific soil groups and rock types to MODIS-derived albedo measurements. This correlation is important because most current weather forecast models treat this region as if the surface is uniform and therefore reflects the same amount of light all across its wide expanse. However, the terrain across the Sahara Desert and Arabian Peninsula is actually quite varied. Darker surface features (like rocks and plant canopies) absorb more light than lighter surfaces (like sand) and therefore get hotter in the afternoon. Over the course of a day, these heating differences can set up atmospheric motions that influence global clouds and rain. |
| Completed |
2002-07-01 |
|
True Color MODIS Albedo imag
…
| Title |
True Color MODIS Albedo image improves Climate Modeling |
| Abstract |
The MODIS instrument, flying aboard NASA's Terra and Aqua satellites, measures how much solar radiation is reflected by the Earth's surface almost every day over the entire planet. Zooming in on Africa's Sahara Desert and the Arabian Peninsula, MODIS observed considerable variability in reflectance across the region-from the darkest volcanic terrains to the brightest sand. This matches specific soil groups and rock types to MODIS-derived albedo measurements. This correlation is important because most current weather forecast models treat this region as if the surface is uniform and therefore reflects the same amount of light all across its wide expanse. However, the terrain across the Sahara Desert and Arabian Peninsula is actually quite varied. Darker surface features (like rocks and plant canopies) absorb more light than lighter surfaces (like sand) and therefore get hotter in the afternoon. Over the course of a day, these heating differences can set up atmospheric motions that influence global clouds and rain. |
| Completed |
2002-07-01 |
|
True Color MODIS Albedo imag
…
| Title |
True Color MODIS Albedo image improves Climate Modeling |
| Abstract |
The MODIS instrument, flying aboard NASA's Terra and Aqua satellites, measures how much solar radiation is reflected by the Earth's surface almost every day over the entire planet. Zooming in on Africa's Sahara Desert and the Arabian Peninsula, MODIS observed considerable variability in reflectance across the region-from the darkest volcanic terrains to the brightest sand. This matches specific soil groups and rock types to MODIS-derived albedo measurements. This correlation is important because most current weather forecast models treat this region as if the surface is uniform and therefore reflects the same amount of light all across its wide expanse. However, the terrain across the Sahara Desert and Arabian Peninsula is actually quite varied. Darker surface features (like rocks and plant canopies) absorb more light than lighter surfaces (like sand) and therefore get hotter in the afternoon. Over the course of a day, these heating differences can set up atmospheric motions that influence global clouds and rain. |
| Completed |
2002-07-01 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Wide) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a wide area of the United States. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Wide) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a wide area of the United States. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Wide) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a wide area of the United States. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Wide) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a wide area of the United States. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Wide) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a wide area of the United States. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
MODIS Data May Aid EPA Air Q
…
| Title |
MODIS Data May Aid EPA Air Quality Predictions (Wide) |
| Abstract |
This visualization shows how MODIS data from NASA's Terra and Aqua spacecraft may be able to help EPA in producing air quality index forcasts. Currently, most air quality forcasts are generated from gound based measuring stations, however, these stations generally only exist in heavily populated areas. MODIS data may help EPA provide air quality forcasts over much wider areas and with higher accuracy. In this visualization, the EPA air quality data shows as the thin colored boxes sticking out from the surface. The MODIS data is represented by the colored overlay. An event that began over the northwestern US in September 2003 is shown propagating across the US and into the midwest. Notice that the movement of the air mass is evident only from the MODIS data. This version of the animation shows a wide area of the United States. This animation was inspired by a similar animation created at the Langley Research Center. |
| Completed |
2004-06-14 |
|
Creating the Tamarisk Habita
…
| Title |
Creating the Tamarisk Habitat Suitability Map (for General Use) |
| Abstract |
The spread of invasive species is one of the most daunting environmental, economic, and human-health problems facing the United States and the World today. It is one of several grand challenge environmental problems being addressed by NASA's Science Mission Directorate through a national application partnership with the US Geological Survey. NASA and USGS are working together to develop a National Invasive Species Forecasting System (ISFS) for the management and control of invasive species on Department of Interior and adjacent lands. The system provides a framework for using USGS's early detection and monitoring protocols and predictive models to process MODIS, ETM+, ASTER and commercial remote sensing data. It can also be used to create on-demand, regional-scale assessments of invasive species patterns and vulnerable habitats. The first step in this process is to collect relevant satellite data which can then be used to derive a Tamarisk Habitat Suitability Map. By combining satellite observed annual vegetation cycles with landcover classification data the likely habitat for Tamarisk can be derived. |
| Completed |
2006-01-25 |
|
Creating the Tamarisk Habita
…
| Title |
Creating the Tamarisk Habitat Suitability Map (for General Use) |
| Abstract |
The spread of invasive species is one of the most daunting environmental, economic, and human-health problems facing the United States and the World today. It is one of several grand challenge environmental problems being addressed by NASA's Science Mission Directorate through a national application partnership with the US Geological Survey. NASA and USGS are working together to develop a National Invasive Species Forecasting System (ISFS) for the management and control of invasive species on Department of Interior and adjacent lands. The system provides a framework for using USGS's early detection and monitoring protocols and predictive models to process MODIS, ETM+, ASTER and commercial remote sensing data. It can also be used to create on-demand, regional-scale assessments of invasive species patterns and vulnerable habitats. The first step in this process is to collect relevant satellite data which can then be used to derive a Tamarisk Habitat Suitability Map. By combining satellite observed annual vegetation cycles with landcover classification data the likely habitat for Tamarisk can be derived. |
| Completed |
2006-01-25 |
|
Creating the Tamarisk Habita
…
| Title |
Creating the Tamarisk Habitat Suitability Map (for General Use) |
| Abstract |
The spread of invasive species is one of the most daunting environmental, economic, and human-health problems facing the United States and the World today. It is one of several grand challenge environmental problems being addressed by NASA's Science Mission Directorate through a national application partnership with the US Geological Survey. NASA and USGS are working together to develop a National Invasive Species Forecasting System (ISFS) for the management and control of invasive species on Department of Interior and adjacent lands. The system provides a framework for using USGS's early detection and monitoring protocols and predictive models to process MODIS, ETM+, ASTER and commercial remote sensing data. It can also be used to create on-demand, regional-scale assessments of invasive species patterns and vulnerable habitats. The first step in this process is to collect relevant satellite data which can then be used to derive a Tamarisk Habitat Suitability Map. By combining satellite observed annual vegetation cycles with landcover classification data the likely habitat for Tamarisk can be derived. |
| Completed |
2006-01-25 |
|
Creating the Tamarisk Habita
…
| Title |
Creating the Tamarisk Habitat Suitability Map (for General Use) |
| Abstract |
The spread of invasive species is one of the most daunting environmental, economic, and human-health problems facing the United States and the World today. It is one of several grand challenge environmental problems being addressed by NASA's Science Mission Directorate through a national application partnership with the US Geological Survey. NASA and USGS are working together to develop a National Invasive Species Forecasting System (ISFS) for the management and control of invasive species on Department of Interior and adjacent lands. The system provides a framework for using USGS's early detection and monitoring protocols and predictive models to process MODIS, ETM+, ASTER and commercial remote sensing data. It can also be used to create on-demand, regional-scale assessments of invasive species patterns and vulnerable habitats. The first step in this process is to collect relevant satellite data which can then be used to derive a Tamarisk Habitat Suitability Map. By combining satellite observed annual vegetation cycles with landcover classification data the likely habitat for Tamarisk can be derived. |
| Completed |
2006-01-25 |
|
Progression of Hurricane Jea
…
| Title |
Progression of Hurricane Jeanne, 2004 (WMS) |
| Abstract |
Hurricane Jeanne was the fourth hurricane to hit Florida during the 2004 hurricane season. This set of images shows the progression of the hurricane as it approached Florida from the Atlantic Ocean and the Caribbean Sea. When it hit the Florida coast on September 26, Jeanne was a Category 3 storm with sustained winds near 115 miles per hour. |
| Completed |
2004-10-22 |
|
Progression of Hurricane Jea
…
| Title |
Progression of Hurricane Jeanne, 2004 (WMS) |
| Abstract |
Hurricane Jeanne was the fourth hurricane to hit Florida during the 2004 hurricane season. This set of images shows the progression of the hurricane as it approached Florida from the Atlantic Ocean and the Caribbean Sea. When it hit the Florida coast on September 26, Jeanne was a Category 3 storm with sustained winds near 115 miles per hour. |
| Completed |
2004-10-22 |
|
Progression of Hurricane Jea
…
| Title |
Progression of Hurricane Jeanne, 2004 (WMS) |
| Abstract |
Hurricane Jeanne was the fourth hurricane to hit Florida during the 2004 hurricane season. This set of images shows the progression of the hurricane as it approached Florida from the Atlantic Ocean and the Caribbean Sea. When it hit the Florida coast on September 26, Jeanne was a Category 3 storm with sustained winds near 115 miles per hour. |
| Completed |
2004-10-22 |
|
Progression of Hurricane Jea
…
| Title |
Progression of Hurricane Jeanne, 2004 (WMS) |
| Abstract |
Hurricane Jeanne was the fourth hurricane to hit Florida during the 2004 hurricane season. This set of images shows the progression of the hurricane as it approached Florida from the Atlantic Ocean and the Caribbean Sea. When it hit the Florida coast on September 26, Jeanne was a Category 3 storm with sustained winds near 115 miles per hour. |
| Completed |
2004-10-22 |
|
Progression of Hurricane Jea
…
| Title |
Progression of Hurricane Jeanne, 2004 (WMS) |
| Abstract |
Hurricane Jeanne was the fourth hurricane to hit Florida during the 2004 hurricane season. This set of images shows the progression of the hurricane as it approached Florida from the Atlantic Ocean and the Caribbean Sea. When it hit the Florida coast on September 26, Jeanne was a Category 3 storm with sustained winds near 115 miles per hour. |
| Completed |
2004-10-22 |
|
Progression of Hurricane Jea
…
| Title |
Progression of Hurricane Jeanne, 2004 (WMS) |
| Abstract |
Hurricane Jeanne was the fourth hurricane to hit Florida during the 2004 hurricane season. This set of images shows the progression of the hurricane as it approached Florida from the Atlantic Ocean and the Caribbean Sea. When it hit the Florida coast on September 26, Jeanne was a Category 3 storm with sustained winds near 115 miles per hour. |
| Completed |
2004-10-22 |
|
Progression of Hurricane Jea
…
| Title |
Progression of Hurricane Jeanne, 2004 (WMS) |
| Abstract |
Hurricane Jeanne was the fourth hurricane to hit Florida during the 2004 hurricane season. This set of images shows the progression of the hurricane as it approached Florida from the Atlantic Ocean and the Caribbean Sea. When it hit the Florida coast on September 26, Jeanne was a Category 3 storm with sustained winds near 115 miles per hour. |
| Completed |
2004-10-22 |
|
Habitat Suitability for Tama
…
| Title |
Habitat Suitability for Tamarisk Invasion in the State of Arizona |
| Abstract |
The Invasive Species Forecasting System (ISFS) is a partnership between NASA and The US Geological Survey (USGS). The ISFS combines NASA Earth observations and statistical models to enhance USGS capabilities to map, monitor and predict the spread of significant invasive plant species. This video shows the habitat suitability for a Tamarisk invasion in the state of Arizona. Tamarisk spreads quickly along riverbeds and when it sheds it's leaves, this foliage secretes salt on the soil, which hinders other plant growth. Red indicates areas that are highly suitable. Yellow indicates areas which are less suitable, and grey are areas which are not suitable. |
| Completed |
2005-10-18 |
|
Habitat Suitability for Tama
…
| Title |
Habitat Suitability for Tamarisk Invasion in the State of Arizona |
| Abstract |
The Invasive Species Forecasting System (ISFS) is a partnership between NASA and The US Geological Survey (USGS). The ISFS combines NASA Earth observations and statistical models to enhance USGS capabilities to map, monitor and predict the spread of significant invasive plant species. This video shows the habitat suitability for a Tamarisk invasion in the state of Arizona. Tamarisk spreads quickly along riverbeds and when it sheds it's leaves, this foliage secretes salt on the soil, which hinders other plant growth. Red indicates areas that are highly suitable. Yellow indicates areas which are less suitable, and grey are areas which are not suitable. |
| Completed |
2005-10-18 |
|
Progression of Hurricane Emi
…
| Title |
Progression of Hurricane Emily, 2005 (WMS) |
| Abstract |
Emily was a record-setting storm for many reasons. When it formed on July 11, Emily became the earliest fifth named storm on record. As it moved through the Caribbean, Emily intensified into a powerful Category 4 storm with winds over 250 kilometers per hour (150 mph) and gusts as high as 300 kilometers per hour (184 mph), making it the most powerful storm to form before August. The previous record was set by Hurricane Dennis, which ripped through the Caribbean during the first week of July 2005. Emily's Category 4 status also made 2005 the only year to produce two Category 4 storms before the end of July. |
| Completed |
2005-07-26 |
|
Progression of Hurricane Emi
…
| Title |
Progression of Hurricane Emily, 2005 (WMS) |
| Abstract |
Emily was a record-setting storm for many reasons. When it formed on July 11, Emily became the earliest fifth named storm on record. As it moved through the Caribbean, Emily intensified into a powerful Category 4 storm with winds over 250 kilometers per hour (150 mph) and gusts as high as 300 kilometers per hour (184 mph), making it the most powerful storm to form before August. The previous record was set by Hurricane Dennis, which ripped through the Caribbean during the first week of July 2005. Emily's Category 4 status also made 2005 the only year to produce two Category 4 storms before the end of July. |
| Completed |
2005-07-26 |
|
Progression of Hurricane Emi
…
| Title |
Progression of Hurricane Emily, 2005 (WMS) |
| Abstract |
Emily was a record-setting storm for many reasons. When it formed on July 11, Emily became the earliest fifth named storm on record. As it moved through the Caribbean, Emily intensified into a powerful Category 4 storm with winds over 250 kilometers per hour (150 mph) and gusts as high as 300 kilometers per hour (184 mph), making it the most powerful storm to form before August. The previous record was set by Hurricane Dennis, which ripped through the Caribbean during the first week of July 2005. Emily's Category 4 status also made 2005 the only year to produce two Category 4 storms before the end of July. |
| Completed |
2005-07-26 |
|
Progression of Hurricane Emi
…
| Title |
Progression of Hurricane Emily, 2005 (WMS) |
| Abstract |
Emily was a record-setting storm for many reasons. When it formed on July 11, Emily became the earliest fifth named storm on record. As it moved through the Caribbean, Emily intensified into a powerful Category 4 storm with winds over 250 kilometers per hour (150 mph) and gusts as high as 300 kilometers per hour (184 mph), making it the most powerful storm to form before August. The previous record was set by Hurricane Dennis, which ripped through the Caribbean during the first week of July 2005. Emily's Category 4 status also made 2005 the only year to produce two Category 4 storms before the end of July. |
| Completed |
2005-07-26 |
|
Progression of Hurricane Emi
…
| Title |
Progression of Hurricane Emily, 2005 (WMS) |
| Abstract |
Emily was a record-setting storm for many reasons. When it formed on July 11, Emily became the earliest fifth named storm on record. As it moved through the Caribbean, Emily intensified into a powerful Category 4 storm with winds over 250 kilometers per hour (150 mph) and gusts as high as 300 kilometers per hour (184 mph), making it the most powerful storm to form before August. The previous record was set by Hurricane Dennis, which ripped through the Caribbean during the first week of July 2005. Emily's Category 4 status also made 2005 the only year to produce two Category 4 storms before the end of July. |
| Completed |
2005-07-26 |
|
Progression of Hurricane Emi
…
| Title |
Progression of Hurricane Emily, 2005 (WMS) |
| Abstract |
Emily was a record-setting storm for many reasons. When it formed on July 11, Emily became the earliest fifth named storm on record. As it moved through the Caribbean, Emily intensified into a powerful Category 4 storm with winds over 250 kilometers per hour (150 mph) and gusts as high as 300 kilometers per hour (184 mph), making it the most powerful storm to form before August. The previous record was set by Hurricane Dennis, which ripped through the Caribbean during the first week of July 2005. Emily's Category 4 status also made 2005 the only year to produce two Category 4 storms before the end of July. |
| Completed |
2005-07-26 |
|
Giant Iceberg in McMurdo Sou
…
| Title |
Giant Iceberg in McMurdo Sound (WMS) |
| Abstract |
Iceberg B-15A, in Antarctica's McMurdo Sound, is as large as Long Island, NY (3,000 square kilometers or 1,200 square miles) and is the largest fragment of a much larger iceberg that broke away from the Ross Ice Shelf in March 2000. Iceberg B-15A has trapped sea ice in McMurdo Sound, and the ice build-up presents significant problems for Antarctic penguins, which must now swim great distances to reach open waters and food. These images were taken by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on NASA's Aqua and Terra satellites between 2004-11-09 and 2005-01-17. |
| Completed |
2005-01-02 |
|
MODIS Sea Surface Temperatur
…
| Title |
MODIS Sea Surface Temperature around the Australian Continent |
| Abstract |
The earliest technique for measuring Sea Surface Temperature (SST) was dipping a thermometer into a bucket of water. The first automated technique for determining SST was accomplished by measuring the temperature of water in the intake port of large ships. A large network of coastal buoys in U.S. waters is maintained by the National Data Buoy Center (NDBC). Since about 1990, there has also been an extensive array of moored buoys maintained across the equatorial Pacific Ocean designed to help monitor and predict the El Niño phenomenon. Since the 1980s satellites have been increasingly utilized to measure SST and have provided an enormous leap in our ability to view the spatial and temporal variation in SST. The satellite measured SST provides both a synoptic view of the ocean and a high frequency of repeat views, allowing the examination of basin-wide upper ocean dynamics not possible with ships or buoys. For example, a ship traveling at 10 knots (20 km/h) would require 10 years to cover the same area a satellite covers in two minutes. This animation uses SST data taken at nighttime from the MODIS/Aqua and MODIS/Terra satellites. This data has many important applications that permit scientists to use ocean temperatures to observe ocean circulation and locate major ocean currents. Ocean current analysis can facilitate ocean transportation. Additionally, by using SST, scientists can monitor changes in ocean temperatures and relate these to weather and climate changes like coral bleaching around the Great Barrier Reef. Finally, the SST changes have many important biological implications for hospitable/inhospitable conditions for many organisms including species of plankton, seagrasses, shellfish, fish, coral, and mammals. |
| Completed |
2005-02-28 |
|
MODIS Sea Surface Temperatur
…
| Title |
MODIS Sea Surface Temperature around the Australian Continent |
| Abstract |
The earliest technique for measuring Sea Surface Temperature (SST) was dipping a thermometer into a bucket of water. The first automated technique for determining SST was accomplished by measuring the temperature of water in the intake port of large ships. A large network of coastal buoys in U.S. waters is maintained by the National Data Buoy Center (NDBC). Since about 1990, there has also been an extensive array of moored buoys maintained across the equatorial Pacific Ocean designed to help monitor and predict the El Niño phenomenon. Since the 1980s satellites have been increasingly utilized to measure SST and have provided an enormous leap in our ability to view the spatial and temporal variation in SST. The satellite measured SST provides both a synoptic view of the ocean and a high frequency of repeat views, allowing the examination of basin-wide upper ocean dynamics not possible with ships or buoys. For example, a ship traveling at 10 knots (20 km/h) would require 10 years to cover the same area a satellite covers in two minutes. This animation uses SST data taken at nighttime from the MODIS/Aqua and MODIS/Terra satellites. This data has many important applications that permit scientists to use ocean temperatures to observe ocean circulation and locate major ocean currents. Ocean current analysis can facilitate ocean transportation. Additionally, by using SST, scientists can monitor changes in ocean temperatures and relate these to weather and climate changes like coral bleaching around the Great Barrier Reef. Finally, the SST changes have many important biological implications for hospitable/inhospitable conditions for many organisms including species of plankton, seagrasses, shellfish, fish, coral, and mammals. |
| Completed |
2005-02-28 |
|
MODIS Sea Surface Temperatur
…
| Title |
MODIS Sea Surface Temperature around the Australian Continent |
| Abstract |
The earliest technique for measuring Sea Surface Temperature (SST) was dipping a thermometer into a bucket of water. The first automated technique for determining SST was accomplished by measuring the temperature of water in the intake port of large ships. A large network of coastal buoys in U.S. waters is maintained by the National Data Buoy Center (NDBC). Since about 1990, there has also been an extensive array of moored buoys maintained across the equatorial Pacific Ocean designed to help monitor and predict the El Niño phenomenon. Since the 1980s satellites have been increasingly utilized to measure SST and have provided an enormous leap in our ability to view the spatial and temporal variation in SST. The satellite measured SST provides both a synoptic view of the ocean and a high frequency of repeat views, allowing the examination of basin-wide upper ocean dynamics not possible with ships or buoys. For example, a ship traveling at 10 knots (20 km/h) would require 10 years to cover the same area a satellite covers in two minutes. This animation uses SST data taken at nighttime from the MODIS/Aqua and MODIS/Terra satellites. This data has many important applications that permit scientists to use ocean temperatures to observe ocean circulation and locate major ocean currents. Ocean current analysis can facilitate ocean transportation. Additionally, by using SST, scientists can monitor changes in ocean temperatures and relate these to weather and climate changes like coral bleaching around the Great Barrier Reef. Finally, the SST changes have many important biological implications for hospitable/inhospitable conditions for many organisms including species of plankton, seagrasses, shellfish, fish, coral, and mammals. |
| Completed |
2005-02-28 |
|
MODIS Sea Surface Temperatur
…
| Title |
MODIS Sea Surface Temperature around the Australian Continent |
| Abstract |
The earliest technique for measuring Sea Surface Temperature (SST) was dipping a thermometer into a bucket of water. The first automated technique for determining SST was accomplished by measuring the temperature of water in the intake port of large ships. A large network of coastal buoys in U.S. waters is maintained by the National Data Buoy Center (NDBC). Since about 1990, there has also been an extensive array of moored buoys maintained across the equatorial Pacific Ocean designed to help monitor and predict the El Niño phenomenon. Since the 1980s satellites have been increasingly utilized to measure SST and have provided an enormous leap in our ability to view the spatial and temporal variation in SST. The satellite measured SST provides both a synoptic view of the ocean and a high frequency of repeat views, allowing the examination of basin-wide upper ocean dynamics not possible with ships or buoys. For example, a ship traveling at 10 knots (20 km/h) would require 10 years to cover the same area a satellite covers in two minutes. This animation uses SST data taken at nighttime from the MODIS/Aqua and MODIS/Terra satellites. This data has many important applications that permit scientists to use ocean temperatures to observe ocean circulation and locate major ocean currents. Ocean current analysis can facilitate ocean transportation. Additionally, by using SST, scientists can monitor changes in ocean temperatures and relate these to weather and climate changes like coral bleaching around the Great Barrier Reef. Finally, the SST changes have many important biological implications for hospitable/inhospitable conditions for many organisms including species of plankton, seagrasses, shellfish, fish, coral, and mammals. |
| Completed |
2005-02-28 |
|
NASA's Orbiting Earth Observ
…
| Title |
NASA's Orbiting Earth Observing Fleet (includes Aura in orange) |
| Abstract |
NASA's Earth Observing fleet of vehicles constitutes a major milestone in the history of Earth science, facilitating the kinds of wide scale and synergistic research endeavors that until the last decade have been impossible to even consider. Many of the techniques being employed around Earth are a direct offshoot of technological and scientific techniques developed on missions to other worlds. NASA's continued commitment to primary research about our home remains a top priority not only to the agency, but to the nation, and the world as a whole. This visualization shows the spacecraft in NASA's Earth Observing fleet. The relative altitudes, speeds, and sun position are correct for 12-01-2003 starting at 5:00 UTC. Aura was added as it would appear in orbit (if it were in orbit at this time). |
| Completed |
2004-05-13 |
|
Super Typhoon Nida
| Title |
Super Typhoon Nida |
| Abstract |
The MODIS instrument onboard NASA's Aqua and Terra satellites captured this sequence of true-color images of Super Typhoon Nida churning through the Philippine Islands. Packing winds up tof 100 mph and gusts of 122 mph, and caused floods and landslides. Nida has been responsible for at least six deaths in the Philippines and has displaced thousands as it skirted the eastern part of the country before moving towards southern Japan. |
| Completed |
2004-05-18 |
|
Super Typhoon Nida
| Title |
Super Typhoon Nida |
| Abstract |
The MODIS instrument onboard NASA's Aqua and Terra satellites captured this sequence of true-color images of Super Typhoon Nida churning through the Philippine Islands. Packing winds up tof 100 mph and gusts of 122 mph, and caused floods and landslides. Nida has been responsible for at least six deaths in the Philippines and has displaced thousands as it skirted the eastern part of the country before moving towards southern Japan. |
| Completed |
2004-05-18 |
|
Super Typhoon Nida
| Title |
Super Typhoon Nida |
| Abstract |
The MODIS instrument onboard NASA's Aqua and Terra satellites captured this sequence of true-color images of Super Typhoon Nida churning through the Philippine Islands. Packing winds up tof 100 mph and gusts of 122 mph, and caused floods and landslides. Nida has been responsible for at least six deaths in the Philippines and has displaced thousands as it skirted the eastern part of the country before moving towards southern Japan. |
| Completed |
2004-05-18 |
|
Super Typhoon Nida
| Title |
Super Typhoon Nida |
| Abstract |
The MODIS instrument onboard NASA's Aqua and Terra satellites captured this sequence of true-color images of Super Typhoon Nida churning through the Philippine Islands. Packing winds up tof 100 mph and gusts of 122 mph, and caused floods and landslides. Nida has been responsible for at least six deaths in the Philippines and has displaced thousands as it skirted the eastern part of the country before moving towards southern Japan. |
| Completed |
2004-05-18 |
|
Progression of Hurricane Fab
…
| Title |
Progression of Hurricane Fabian, 2003 (WMS) |
| Abstract |
Hurricane Fabian threatened the Eastern Coast of the United States before it turned northward and hit the island of Bermuda instead. Fabian came within 50 miles to the west of Bermuda on September 5th, 2003, with sustained winds of 117 miles per hour and with gusts of up to 130 miles per hour. |
| Completed |
2005-05-18 |
|
Progression of Hurricane Fab
…
| Title |
Progression of Hurricane Fabian, 2003 (WMS) |
| Abstract |
Hurricane Fabian threatened the Eastern Coast of the United States before it turned northward and hit the island of Bermuda instead. Fabian came within 50 miles to the west of Bermuda on September 5th, 2003, with sustained winds of 117 miles per hour and with gusts of up to 130 miles per hour. |
| Completed |
2005-05-18 |
|
Progression of Hurricane Fab
…
| Title |
Progression of Hurricane Fabian, 2003 (WMS) |
| Abstract |
Hurricane Fabian threatened the Eastern Coast of the United States before it turned northward and hit the island of Bermuda instead. Fabian came within 50 miles to the west of Bermuda on September 5th, 2003, with sustained winds of 117 miles per hour and with gusts of up to 130 miles per hour. |
| Completed |
2005-05-18 |
|
Progression of Hurricane Fab
…
| Title |
Progression of Hurricane Fabian, 2003 (WMS) |
| Abstract |
Hurricane Fabian threatened the Eastern Coast of the United States before it turned northward and hit the island of Bermuda instead. Fabian came within 50 miles to the west of Bermuda on September 5th, 2003, with sustained winds of 117 miles per hour and with gusts of up to 130 miles per hour. |
| Completed |
2005-05-18 |
|
Progression of Hurricane Fab
…
| Title |
Progression of Hurricane Fabian, 2003 (WMS) |
| Abstract |
Hurricane Fabian threatened the Eastern Coast of the United States before it turned northward and hit the island of Bermuda instead. Fabian came within 50 miles to the west of Bermuda on September 5th, 2003, with sustained winds of 117 miles per hour and with gusts of up to 130 miles per hour. |
| Completed |
2005-05-18 |
|
Progression of Hurricane Fab
…
| Title |
Progression of Hurricane Fabian, 2003 (WMS) |
| Abstract |
Hurricane Fabian threatened the Eastern Coast of the United States before it turned northward and hit the island of Bermuda instead. Fabian came within 50 miles to the west of Bermuda on September 5th, 2003, with sustained winds of 117 miles per hour and with gusts of up to 130 miles per hour. |
| Completed |
2005-05-18 |
|
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