Following is a list of Images, Animations or Movies that ARC has either created or downloaded from the source and pre-formatted for display on our OmniGlobe spherical display system. Almost all of the items below come pre-loaded on the OmniGlobe but a few of the items like our Paleo-Animation and our Real-Time Weather service have an additional charge. All Content would be pre-loaded on your OmniGlobe before delivery so you would be up and running on day 1.

 

ARC’s own Face-of-the-Earth Image with simulated cloud cover. Included with every OmniGlobe.

Cloudy Earth


 

ARC’s own cloudless Face-of-the-Earth Image. Included with every OmniGlobe.

Cloudless Earth


 

ARC’s own rotating Diurnal Earth animation with city lights. Available as an animation or a movie.

ARCDiurnalEarth


 

Global IR cloud composite overlayed on ARC’s seasonaly adjusted Natural Earth background with date and time stamps on each side of the planet. Updates can be downloaded from the ARC server every 3 hours. The global IR Cloud data is provided by SSEC. This product is sold as an annual subscription service.

ARCRealTimeClouds


 

Composite Animation created by ARC Science using NASA & NOAA data showing seasonal changes on the Earth including vegetation, sea ice and snow cover.

Seasonal Earth


 

Simulation of the Landsat 7 Satellite orbiting the cloudless, diurnal Earth. The Landsat 7 satellite was launched in 1999 and was inserted into a plar, sun-synchonous orbit ofthe Earth. The mission of the Landsat Program is to provide repetitive acquisition of high resolution multispectral data of the Earth’s surface on a global basis. Landsat represents the only source of global, calibrated, high spatial resolution measurements of the Earth’s surface that can be compared to previous data recoreds. The data from the Landsat spacecraft constitutes teh longest record of the Earth’s continental surfaces as seen from space. Is is a record unmatched in quality, detail, coverage, and value. The spacecraft orbits at a nominal altitude of 705km and completes 14.5 orbits per day, covering the entire Earth every 16 days. Circling the Earth at 7.5km/sec, each orbit takes nearly 99 minutes. Landsat 7 crosses the Equator from North to South on a descending orbital node between 10:00AM – 10:15AM on each pass. Source of Simulation: ARC Science Simulations.

Landsat7Sim


 

This animation shows plate tectonics over the last 300 Million Years. It is a time-elapsed frame set of approximately 2000 high-resolution images with original artwork visualizing the evolution of the Earth’s surface due to plate tectonics over the past 600 million years. The 600 million year dateset shows the large southern landmass called Pannotia, which began to break apart into several small pieces as well as Gondwana 550 million years ago, which eventually became the cores of North America, Northern Europe, and Siberia. The smaller pieces from the break up of Pannotia drifted together to form Laurasia. Gondwana and Laurasia drifted for more than 200 million years, and then came back together again, pushing up a great mountain range of which the Appalachian Mountains are one remnant. Source of Data: Ron Blakey, Department of Geology, Northern Arizona University/ARC Science Simulations.

paleo300


 

This animation shows plate tectonics over the last 600 Million Years. It is a time-elapsed frame set of approximately 4000 high-resolution images with original artwork visualizing the evolution of the Earth’s surface due to plate tectonics over the past 600 million years. The 600 million year dateset shows the large southern landmass called Pannotia, which began to break apart into several small pieces as well as Gondwana 550 million years ago, which eventually became the cores of North America, Northern Europe, and Siberia. The smaller pieces from the break up of Pannotia drifted together to form Laurasia. Gondwana and Laurasia drifted for more than 200 million years, and then came back together again, pushing up a great mountain range of which the Appalachian Mountains are one remnant. Source of Data: Ron Blakey, Department of Geology, Northern Arizona University/ARC Science Simulations.

paleo600


Geophysical Content

SSEC Sample data set from 2006 showing One Week of Earthquakes by location and magnitude.

SSECEarthquakes


 

Animation showing cumulative earthquakes occuring between 1980-1995. Only earthquakes with a magnetude greater than 4.2 were plotted. A yellow dot represents 1 or 2 earthquakes, an orange dot represents about 10 earthquakes and a red dot represents 50-200 earthquakes. The red lines are convergent boundaries, the green lines are divergent boundaries, the blue dashed lines are diffuse boundaries and the purple lines are transform boundaries. Source of data: The National Earthquake Center of the United States Geological Survey.

CumEarthquakes


 

Image showing the plate boundaries and the age of the sea floor. Source of data: School of Geosciences, University of Sydney, Australia via NOAA’s National Geophysical Data Center.

AgeOfSeaFloor


 

Animation of the Indian Ocean Tsunami. This dataset is a Model put together by the Pacific Marine EnvironmentalLaboratory that Simulates the waves of the December 26, 2004 tsunami the first 36hours after it occurred. A color bar is included showing color ranges from light blue for troughs 50cm below sea level and yellow for ridges 50cm above sea level. This Tsunami was the result of a massive earthquake that occurred when the India tectonic plate subducted beneath the Burma plate, causing an earthquake with a magnitude of at least 9.0 on the Richter scale which displaced a huge amount of water. Out in the depths of the ocean, the wave heights do not increase dramatically. But as the waves travel inland, the depth of the ocean gets shallower causing the waves to build up. Waves with heights of 35.5 feet were reported during the Sumatra Tsunami. Source of Data: Pacific Marine Environmental Laboratory/NOAA Center for Tsunami Research.

2004-Tsunami-Animation


 

Image showing the location of Volcanoes world wide.

WorldVolcanoes


 

ARC’s Face of the Earth Image with Topographic shading.

TopoARC4000


 

Animation showing changing magnetic lines from 1590-2010. The first dataset shows the magnetic filed lines at the surface of the Earth. The magnetic poles are indicated by stars. The blue lines show where the magnetic filed dips into the Earth and the red lines show where the magnetic field emerges fromthe Earth. Where the filed lines are horizontal to the Earth, between the red and blue lines, is the magnetic equator shaded yellow. Source of Data: NOAA National Geophysical Data Center.

MagLines


 

Animation showing changes in global magnetism from 1590-2010. The second dataset shows the compass pointingdirections around the world. The black lines (meridians) indicate the direction of Ture North. The angle between the compass pointing direction and True North is called magnetic declination. Source of Data: NOAA National Geophysical Data Center.

Magnetism


 

Animation showing changing Magnetic Declination from 1590-2010. The third dataset shows lines of equal magnetic declination measured in degress east (positive) or west (negative) of True North. The black line is where the declination equals zero and the direction of True North and Magnetic North are equal. The magnetic North and South Poles are indicated by the black stars. Source of Data: NOAA National Geophyscial Data Center.

MagDeclination


 

Animation of Japan Tsunami of March 2011 showing a Model run of predicted tsunami wave heights from the Center for Tsunami Research at the NOAA Pacific Marine Environmental Laboratory. It shows the predicted wave heights of the tsunami as it travels across the Pacific basin. The largest wave heights are near the earthquake epicenter, off Japan. The wave decreases in height as it travels across the deep Pacific but grows taller as it encounters shallow waters near coastal areas. In general, the energy of the wave decreases with distance, causing the maximum height of the waves at the coasts to decrease. This explains why coastal Hawaii does not see the heights that were encountered in coastal Japan. Out in the open ocean, areas of low wave height correspond to deeper areas in the ocean.

JapaneseTsunami


 

Image showing the locations of the top ten recorded earthquakes, with additional smaller earthquakes as well. Thetop ten earthquakes are in yellow text, and all the others are in red text. Each bullseye represents an earthquake, with the size of the bullseye proportional to the magnitude of the earthquake. Source of Data: United States Geological Survey.

Biggest Earthquakes


 

Animation created by the Zürich University of Applied Sciences showing a simulation of the changing Earth using past climate data, observations, and computer models. The simulation starts 21,000 years ago and ends 8,000 years in the future, showing the changes in ice concentration, sea level, and vegetation. 19,000BC was chosen as the start date because this was the last glacial maximum.

Earth19K


Human Impact Content

The Anthropic Landscapes map is based on an overlay of the a global land quality map and a global populationdensity map.

Anthland


 

The Global Biomes map is based on a combination of soil moisture regimes and soil temperature regimes.

Biomes


 

The Desertification Vulnerability map is based on a reclassification of the global soil climate map and global soil map.

Desertification


 

The Risk of Human-Induced Desertification is based on an overlay of the global desertification map and a global population density map.

Desertification_Risk


 

The Anthropic System Tension Zones map is based on an overlay of the global land quality map and a global population density map. Biodiversity hotspots are also outlined.

Hotspots


 

The Inherent Land Quality map is based on a reclassification of the global soil climate map and global soil map.

Land_Quality


 

The Major Land Resource Stresses map is based on a reclassification of the global soil climate map and global soil map.

Major_Stresses


 

The Phosphorus Retention Potential map is based on a reclassification of the global soil climate map and global soil map.

Phosphorus


 

Global Population Density.

Population_Density


 

The Soil Inorganic Carbon map is based on a reclassification of the FAO-UNESCO Soil Map of the World combined with a soil climate map. The soil Inorganic carbon map shows the distribution of the soil Inorganic carbon to 1 meter depth.

Soil_Inorganic_Carbon


 

The Global Soil Moisture Regimes map is based on an interpolation of over 20,000 climatic stations that were input into a soil water balance model to estimate soil moisture regimes.

Soil_Moisture


 

The Soil Organic Carbon map is based on a reclassification of the FAO-UNESCO Soil Map of the World combined with a soil climate map. The soil organic carbon map shows the distribution of the soil organic carbon to 1 meter depth.

Soil_Organic


 

The Global Soil Temperature Regimes map is based on an interpolation of over 20,000 climatic stations that were input into a soil water balance model to estimate soil temperature regimes.

Soil_Temperature


 

The Vulnerability to Water Erosion map is based on a reclassification of the global soil climate map and global soil map.

Water_Erosion


 

The Risk of Human-Induced Water Erosion map is based on an overlay of the global Water erosion map and a global population density map.

Water_Erosion_Risk


 

The Available Water Holding Capacity map is based on a reclassification of the global soil climate map and global soil map.

Water_Holding_Capacity


 

The Global wetlands map is based on a reclassification of the FAO-UNESCO Soil Map of the World combined with a soil climate map.

Wetlands


 

The Vulnerability to Wind Erosion map is based on a reclassification of the global soil climate map and global soil map. Four vulnerability classes are defined based on soil climate and soil classification.

Wind_Erosion


 

The Risk of Human-Induced Wind Erosion map is based on an overlay of the global wind erosion map and a global population density map. Four risk classes are defined based on wind erosion vulnerability and population density.

Wind_Erosion_Risk


 

Animation showing fires over the course of a year. Fire data is accumulated over 10 day periods. Over the course of a year, 37 maps are generated. Every fire that occurred over the 10 day period is indicated by a dot. The dots are colored from red to indicate a low fire count through yellow to indicate a high fire count. Source of Data is MODIS Rapid Response System at NASA/GSFC.

Global Fires


Ocean Content

Animation showing Global Sea Currents. In this visualization, a model created by NASA, the color variations denote speed. The lighter green areas are moving faster than the blue areas. Source of Data: Los Alamos National Labs and the Naval Postgraduate School.

NASA Sea Currents


 

Animation showing changes in Global Sea Surface Temperature. While the coldest areas remain at the poles and the warmest area remains at the Equator, many of the seasonal variations linked to the ocean are visible in this dataset generated by a NASA computer model. The warmest water, which is shaded red, can be seen expanding from the equator during the summer. The East Coast of the U.S. warms steadily during the summer months and then cools in the fall and winter. Ocean currents are also visible, such as the Gulf Stream, which transports warm Gulf of Mexico water up the East Coast. Along the edges of many of the currents, ocean eddies (small whirlpools) can be seen mixing and dispersing the temperature gradients. Ocean eddies also appear along coasts, where land is an obstacle in the path of the water. Source of Data: Los Alamos National Labs and the Naval Posgraduate School.

NASA Global Sea Surface Temp


 

Animation showing Sea Surface Temperature Anomaly Data from 1980-1999. Rather than plotting sea surface temperatures, sea surface temperature anomalies have been plotted here to show the dramatic departures from normal that are associates with El nino and L Nina from 1980-1999. The red shading signifies a warming of the ocean by 5-10 degrees F, the green shading is normal and the blue shading is a cooling effect of the ocean by 5-10 degrees F.Source of Data: NCDC.

NCDC SST Anomaly Data 1980-1999


 

Animation showing changing Sea Surface Temperature between April 2005 through October 2006. Source of Data: Fleet Numerical Meteorology and Oceanography Center.

SST Fleet


 

Animation showing changing Sea Surface Temperature between July 2002 through September 2006. Source of Data: MODIS Satellite – NASA Goddard Space Flight Center.

SST MODIS


 

This Image obtained from NOAA is a map that was put together from the data compiled from the report, A Global Map of Human Impact on Marine Ecosystems, which was published in Science Magazine. In addition to finding that 40% of the world’s oceans are heavily impacted by human activities, researchers also concluded that no area is unaffected by human influence. However, there are large areas that have relatively low human impact, especially near the poles. The areas where humans have had the worst impact include the East Cost of North America, North Sea, South and East China Seas, Caribbean Sea, Mediterranean Sea, Red Sea, Persian Gulf, Bering Sea and the western Pacific Ocean. Areas that are shaded red have a high human impact and blue areas have a very low human impact. The study also examined 20 marine ecosystems to determine the impact of the human influences. The ecosystems that are most threatened are coral reefs, seagrass beds, and mangroves. Source of Data: NOAA Environmental Visualization Program.

Extent Harm to Ocean


 

Animation showing the depth of the 26 degree Isotherm in 2005. Scientists often look at the depth of the 26°C isotherm to determine how deep the warm surface layer of the ocean extends. An isotherm is a line of equal temperature and 26°C is equal to 78.8°F. The depth of the 26°C isotherm is estimated from satellite altimeter measurements of the sea surface. The density of sea water decreases with increasing temperature (above 4°C), making the warm water more buoyant than cold water. This means that the warmest water is always at the surface and the coldest water is always at the ocean floor. Where the water is warm through a significant depth, it bulges up (the surface is centimeters higher) compared to the surrounding cooler water. Satellites can measure this bulge, which is statistically correlated, through many ocean temperature measurements, with the depth of the 26°C isotherm. Source of Data: NOAA/AOML.

Depth of the 26 degree Isotherm


 

Animation of the Indian Ocean Tsunami. This dataset is a Model put together by the Pacific Marine Environmental Laboratory that Simulates the waves of the December 26, 2004 tsunami the first 36 hours after it occurred. A color bar is included showing color ranges from light blue for troughs 50cm below sea level and yellow for ridges 50cm above sea level. This Tsunami was the result of a massive earthquake that occurred when the India tectonic plate subducted beneath the Burma plate, causing an earthquake with a magnitude of at least 9.0 on the Richter scale which displaced a huge amount of water. Out in the depths of the ocean, the wave heights do not increase dramatically. But as the waves travel inland, the depth of the ocean gets shallower causing the waves to build up. Waves with heights of 35.5 feet were reported during the Sumatra Tsunami. Source of Data: Pacific Marine Environmental Laboratory/NOAA Center for Tsunami Research.

2004-Tsunami-Animation


 

Image showing DART Buoy locations. After the horrific events of the Indian Ocean Tsunami on December 26, 2004, the need for a tsunami warning system was apparent. As part of the U.S. National Tsunami Hazard Mitigation Program (NTHMP), the Deep Ocean Assessment and Reporting of Tsunamis (DART) Project is an ongoing effort to maintain and improve the capability for the early detection and real-time reporting of tsunamis in the open ocean. Developed by NOAA’s Pacific Marine Environmental Laboratory (PMEL) and operated by NOAA’s National Data Buoy Center (NDBC), DART is essential to fulfilling NOAA’s national responsibility for tsunami hazard mitigation and warnings. The DART Project will consist of 32 DART buoys. Source of Data: SSEC, Space Science and Engineering Center.

SSEC DART Buoy Locations


 

Image showing Worldwide Buoy Locations. Buoys with the ability to collect data are scattered through out the world’s oceans in order to gain a better understanding of how the oceans work and how they are changing. The data is being used for monitoring chemical levels in the oceans, garnering accurate ocean temperatures and change in temperature, and many other endless uses. Each dot on this visualization represents a buoy, and each color indicates the use of the buoy. The buoy network is still expanding past what can be seen on this visualization. The various colors represent buoys from Argo, NOAA, C-MAN, DART and TAO/TRITON. Source of Data: National Oceanographic Data Center, National Data Buoy Center, Pacific Marine Environmental Laboratory.

World Buoy Locations


 

Animation showing the movement of the Argo buoys. Argo is a global array of 3,000 free-drifting profiling floats that measures the 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 relayed and made publicly available within hours after collection. This animation shows the surface movement due to ocean currents over a six-month period during 2005. Each dot in the ocean represents one of the Argo buoys. They are distributed roughly every 185 miles over the oceans. The full network is scheduled to be in place and collecting data by the end of 2006. During the six-month period used for the visualization, many deployments were still taking place. A sudden appearance of a line of dots represents new buoys being deployed off of a research ship. Deployment began in 2000 and by the end of 2005, 75% of the network was in place. Source of Data: National Oceanographic Data Center.

Argo Buoy Tracks


 

Animation showing Argo Buoy movement. In order to measure temperature and salinity of the upper 2000m (over 6500ft) of the ocean, the Argo buoys are designed to be neutrally buoyant at the “parking depth” which is typically 2000m. The buoys drift along at this level for many days, recording data before an external bladder on the buoy causes it to slowly rise to the surface over a six-hour period. During the ascent, measurements are continuously taken. Once at the surface, satellites are used to determine the buoy’s position and to receive the data transmitted by the buoy. After that has been completed, the bladder deflates and the buoy sinks back down to its parking depth. The whole cycle typically takes 10 days. This visualization shows the buoys movement across the oceans, but also their descent and ascent. The lighter buoys are at the sea surface while the darker buoys are below the sea surface. The dataset is referred to as “waterfall” because the data during the ascent of the buoy, when plotted, looks like a waterfall. Source of Data: National Oceanographic Data Center.

Argo Buoy Movement


 

This dataset has both historic and forecasted model-based changes in the ocean’s carbonate chemistry due to increasing CO2 levels, as well as the presence of coral reefs depicted. The coral reefs are represented by black X’s for shallow water species and magenta X’s for deep water species. The ocean acidification levels are based on the median model output of the 13 international ocean carbon models based on the OCMIP-2 Project (Orr et al. 2005). The model outputs are represented on the global map in 5-yr increments from 1765 thru 2100. The future changes in CO2 chemistry were determined based on atmospheric CO2 scenarios presented in The Intergovernmental Panel on Climate Change (IPCC) IS92a ‘continually increasing’ CO2 emissions scenario (788 p.p.m.v. in the year 2100). As atmospheric levels of CO2 increase, the amount of CO2 that is absorbed by the ocean increases as well. This increase of CO2 in the ocean upsets the carbonate chemistry of the ocean and causes the waters to become more corrosive. The images indicate that all of the Southern Ocean surface waters south of 60°S and portions of the North Pacific become undersaturated (corrosive) with respect to aragonite, a form of calcium carbonate. The scale to the left is proportional to the level of aragonite present in the ocean. Source of Data: Pacific Marine Environmental Laboratory/NOAA..

Ocean Acidification


 

Set of 7 images showing the effect of rising sea levels in 1 meter increments. Major population centers are indicated by city lights at night. Graphics created by ARC Science.

SeaLevelRise6m


 

Animation showing changing Sea Ice between 2005-2007 updated every 6 days. Sea ice is simply ocean water that hasfrozen. At least 15% of the ocean is covered by sea ice some part of the year. This means that on average, sea ice covers almost 10 million square miles (about 25 million square kilometers) of the Earth. Sea ice concentrations are monitored closely by scientists because changing sea ice concentrations can have a huge impact on the rest of the globe. Global warming is amplified in polar regions. Because of this, monitoring changes in sea ice can be a good indicator of climate change. The National Snow and Ice Data Center monitors sea ice concentrations using a satellite data record that begins in 1978. The Special Sensor Microwave/Imager (SSM/I) is the current monitoring instrument. The sea ice concentration dataset is on a 25km cell size grid covering both Arctic and Antarctic polar regions. Source of Data: National Snow and Ice Data Center.

Annual Sea Ice Changes


 

Animation showing changing sea ice and snow cover. This dataset nicely shows the seasonal variations in the snow and ice. Source: National Snow and Ice Data Center.

Sea Ice Concentration (2005-2007)


 

Animation showing the changing size of the sea ice between 1987-2007. September was chosen to highlight the change in the Arctic minimum sea ice concentration through time. The decrease in sea ice coverage is apparent in this dataset. Source of Data: National Snow and Ice Data Center.

September Sea Ice 1987-2007


 

Animation showing the changing Sea Surface Height Anomaly from 1992-2008. This dataset illustrates the changing height of the ocean surface as seen from space from 1992 – 2008. The data are sea surface height anomalies from blended TOPEX/Poseidon, Jason-1, ERS 1, ERS 2, GFO and Envisat ocean altimetry satellites. An “anomaly” is the difference between the long-term average for different regions of the ocean and what is actually ‘seen’ by the spacecraft. When oceanographers and climatologists view these “anomalies” they can identify unusual patterns and see where heat is being stored in the ocean, which will influence future global climate events. Source of Data: NASA JPL, AVISO.

SSHeightAnomaly


 

Animation showing changes in Ocean Phytoplankton and Land Vegetation. Subtle changes in ocean color signify various types and quantities of marine phytoplankton (microscopic marine plants), the knowledge of which has both scientific and practical applications. The SeaWiFS Project collects, processes, and distributes data received from an ocean color sensor orbiting the Earth on a satellite. The orbiting sensor can view every square kilometer of cloud-free ocean every 48 hours, providing global information on the oceans. The satellite observations can be used to derive the concentration of microscopic marine plants, phytoplankton, based on the color of the ocean. Greener water signifies an abundance of phytoplankton, while bluer water indicates less. The oceans are shaded based on the chlorophyll (green pigment in plants) concentration as indicated on the color bar below. The lands are shaded to depict the vegetation. Green areas have abundant vegetation, yellow areas have little vegetation, and brown areas have no vegetation. Source of Data: NASA Goddard Space Flight Center.

SeaWiFS


 

Animations showing near-surface wind speed and direction over the oceans. A rougher ocean surface returns a stronger signal because the waves reflect more of the radar energy back toward the scatterometer antenna (backscatter), and a smoother ocean surface returns a weaker signal because less of the energy is reflected. Given the known relationship between the roughness of the surface and the strength of the wind, it is possible to compute the wind speed and direction – the wind vector – from multiple observations of the signal returned from a given area on the ocean surface. Measurements of the global sea-surface wind speed and direction, observed by QuikSCAT, are important to meteorologists and oceanographers in the preparation of marine weather forecasts and the issuance of warnings for the high seas. These include forecasts of the strength and track of hurricanes and winter storms, forecasts that are important to emergency response, offshore oil production and commercial shipping. Wind information is also used in forecasts of waves and ocean currents. Source of Data: SeaWinds on QuikSCAT retrieved by Remote Sensing Systems. Center for Ocean-Atmospheric Prediction Studies, Florida State University.

OceanSVwinds


 

Image depicting the Ocean Conveyer Belt phenomenon. In this dataset the warm, surface waters are the red lines and cold. The ocean is not a still body of water. There is constant motion in the ocean in the form of a global ocean conveyor belt due to thermohaline currents. These currents are density driven, which are affected by both temperature and salinity. Cold, salty water is dense and sinks to the bottom of the ocean while warm water is less dense and rises to the surface. The “start” of the ocean conveyor belt is in the Norwegian Sea. Warm water is transported to the Norwegian Sea by the Gulf Stream. The warm water provides heat for the atmosphere in the northern latitudes that get particularly cold during the winter. This loss of heat to the atmosphere makes the water cooler and denser, causing it to sink to the bottom of the ocean. As more warm water is transported north, the cooler water sinks and moves south to make room for the incoming warm water. This cold bottom water flows south of the equator all the way down to Antarctica. Eventually, the cold bottom waters are able to warm and rise to the surface, continuing the conveyor belt that encircles the global. It takes water almost 1000 years to move through the whole conveyor belt. Source of Data: NASA Conceptual Image Lab, Goddard Space Flight Center.

ConveyerBelt


 

This dataset shows a computer model simulation of surface ocean pH from 1895-2094, with continents and coral reefs marked. Each successive frame shows, in 6-month increments beginning with January 1885 and ending with July 2094. Source of Data: Woods Hole Oceanographic Institute.

OceanAcidification2


 

This dataset shows a computer model simulation of aragonite saturation state from 1895-2094, with continents and coral reefs marked. (aragonite saturation state is commonly used to track ocean acidification because it is a function of carbonate ion concentration.) This dataset shows aragonite saturation state changes over time. Aragonite is one of the more soluble forms of calcium carbonate but it is widely used by marine calcifiers. Each successive frame shows, in 6-month increments beginning with January 1885 and ending with July 2094. Source of Data: Woods Hole Oceanographic Institute.

Ocean Saturation State


 

Animation showing the predictive capability for the ocean’s role in future climate change scenarios, the NASA Modeling, Analysis, and Prediction (MAP) program has created a project called stimating the Circulation and Climate of the Ocean, Phase II (ECCO2): High-Resolution Global-Ocean and Sea-Ice Data Synthesis. ECCO2 produces increasingly accurate syntheses of all available global-scale ocean and sea-ice data at resolutions that start to resolve ocean eddies and other narrow current systems, which transport heat, and other properties within the ocean. ECCO2 data syntheses are created by using the available satellite and in-situ data in the Massachusetts Institute of Technology General Circulation Model (MIT GCM). ECCO2 simulates ocean flows at all depths, but only surface flows are used in this visualization. The global sea surface current flows are colored by corresponding sea surface temperatures. The sea surface temperature data is also from the ECCO2 model.

ECCO2


 

Processes that took place through Earth’s history, such as the weathering of rocks, evaporation of ocean water, and the formation of sea ice, have made the ocean salty. Those are still at work today and are counterbalanced by processes that decrease the salt in the ocean, like freshwater input from rivers, precipitation, and the melting of ice. The result is an ocean surface where the salinity – the concentration of salt – changes and these changes, small as they may be, have large-scale effects on Earth’s water cycle and ocean circulation.


Atmospheric Content

Animation showing the 2004 Hurricane Season in IR. The 2004 hurricane season started on July 31 with Hurricane Alex and continued all the way through to December 2 with Tropical Storm Otto. The season featured 15 tropical storms, 9 of which became hurricanes, and 6 of those were classified as major hurricanes. This over-active hurricane season tallied up a bill of $42 billion in damages, which at the time was record high. Florida took the brunt of the damage with 4 major hurricanes making landfall in the state. Two of the hurricanes, Frances and Jeanne, landed in almost the same location on the east coast of Florida only 3 weeks apart. It is estimated that one in every five homes in Florida was damaged in the 2004 hurricane season. This data set was created using infrared satellites, which measure emitted heat. Where there are clouds, the satellites measure the heat emitted by the cloud rather than the ground below it. Because clouds are so much colder than the ground, they are easy to detect on IR satellite images. Areas that show up in the bright colors are extremely cold and the gray shades are areas that are warmer. The higher the cloud, the colder the cloud top will be and so it shows up vividly on the IR satellite image. Hurricanes and tropical storms are well developed weather systems and therefore have high clouds that are easy to detect in the IR satellite images. Source of Data: NOAA.

2004HS - IR


 

Animation showing the 2005 Hurricane Season in Gray Scale IR. With 28 named storms, 15 hurricanes, seven major hurricanes, and four category 5 hurricanes, the 2005 hurricane season certainly blew the records away. It was also the first season in which four major hurricanes hit the U.S.. The season started early and ended late with two tropical storms in June (which hadn’t happened since 1986) and three tropical storms in November with one that formed in December and dissipated in January. The season also included the most rapid intensification of a hurricane in 24 hours in the Atlantic Ocean, a record held by Wilma. The third and fourth most intense hurricanes ever recorded in the Atlantic basin were Rita and Wilma. Even with all these records, the 2005 hurricane season will arguably be most remembered for Hurricane Katrina, which devastated parts of Mississippi, Louisiana and in particular, New Orleans. Over 1600 people died during the storm and an estimated cost for all the damage, $75 billion, makes Katrina the costliest hurricane ever. This data set is a gray-scale infrared satellite image available from June 1, 2005 through January 3, 2006. IR satellites measure emitted heated. Where there are clouds, the satellites measure the heat emitted by the clouds rather than the ground below it. Because clouds are so much colder than the ground, they are easy to detect on IR satellite images. The brightest white clouds are the highest ones, indicating that they have powerful storms below. Source of Data: MCIDAS/AWC.

2005HS - Gray Scale IR


 

Animation showing the 2005 Hurricane Season as Water Vapor with Sea Surface Temperature. This version of the 2005 Hurricane Season is a water vapor satellite image with sea surface temperatures below it available from June 30, 2005 through October 31, 2005. Because water vapor emits radiation, satellites can be set to detect water vapor in the atmosphere. All clouds contain water vapor, so when the satellite detects an area with a high concentration of water vapor, it is detecting a cloud. The clouds in hurricanes are easy to detect because they are well formed and contain an excess of water vapor. The shading of the ocean indicates the temperature; the orange and red areas are the warmest, and the blue areas are the coolest. One reason the unusually powerful hurricane season of 2005 was the above average temperature of the oceans. Source of Data: Space Science and Engineering Center, University of Wisconsin.

2005HSWater Vapor and SST


 

Animation showing Hurrican Tracks from January 1, 2000 through October 3, 2006 and displays the tracks of all of the hurricanes that occurred during this time period. The hurricanes are depicted by red dots in the dataset. For each day, the hurricane track appears as a series of four red dots. The red dots are spaced out according to how fast the hurricane was moving. When a hurricane moved very little over a 24 hour period, the four red dots appear clustered together. To represent a hurricane that traveled a long distance in one day the four red dots are spaced to cover that distance. The summer and spring are calm seasons. The hurricane activity begins to pick up late each summer and typically lasts through the fall. The unusually long hurricane season of 2005 can be seen in this dataset. Source of Data: National Hurricane Center – NOAA/NGDC.

Hurricane Tracks 2000-2006


 

Image showing cumulative Hurricane tracks from 1950-2005. This dataset shows the paths of all recorded hurricanes worldwide from 1950 – 2005. The dots show the locations of the tropical storms at six hour intervals and are shaded according to the Saffir-Simpson Scale using the provided color bar. Source of Data: National Hurricane Center, Joint Typhoon Warning Center.

Hurricane Tracks Cumulative


 

Image showing cumulative lighting flash rate frequency between 1995-2005. Before scientists had satellites to detect and measure lightning frequency, it was thought that there were globally 100 lightning flashes per second, an estimate that dates back to 1925. With satellites monitoring lightning frequency, it is now accepted that the global lightning flash frequency is on the order of 40 flashes per second. NASA has two different sensors that measuring flash frequency, the Optical Transient Detector, OTD, and the Lightning Imaging Sensor, LIS. Data from the OTD from 1995 – 2000 and the LIS from 1998 – 2005 has been combined and averaged to create an average annual lightning flash rate map. 11 years of data is included to remove any anomalies that might be present in just one year. The color variations in the map display the average annual number of lightning flashes per square kilometer. Source of Data: NASA LIS/OTD Science Team.

AnnualLightning


 

Animation showing historical terrestrial air temperature variations between 1950-1990. The temperature of the air varies dramatically in both time and space. Because the Earth’s rotational axis is at a 23° tilt, the Northern Hemisphere and Southern Hemisphere simultaneously experience opposite seasons. This dataset displays the gridded, monthly, historical terrestrial air temperature from 1950 – 1999. The original data is from the Global Historical Climatology Network, which is part of NOAA’s National Climatic Data Center. The data was interpolated by the Center for Climatic Research at the University of Delaware. This sequence clearly illustrates the annual cycle of climate variability across the world through the seasons. Besides displaying how the hemispheres experience opposite seasons simultaneously, this dataset also reveals the effect of significant elevation changes. The mountainous regions tend to be cooler than the surrounding areas. Temperature responses over land to significant El Nino/La Nina events can also be measured as well as global warming trends in many regions. These responses however, are generally masked by the overwhelming changes in the seasons. Source of Data: NOAA’s NCDC Global Historical Climatology Network.

IDL TIFF file


 

Animation showing the distribution of carbon dioxide in the atmosphere for every day of the year 2004, allowing the large variations in CO2 from day-to-day (often called ‘carbon weather’) to be illustrated along with season-to-season changes. The data set also shows black and white dots at every location and time that NOAA ESRL and collaborators collect samples of air to analyze the contents for CO2 and multiple other gases. These are the locations for which we know the mixing ratios of CO2 exactly. The rest of the globe is filled in by a computer model driven by our best knowledge of the surface sources and sinks (fossil fuel and biomass burning emissions, biospheric and ocean uptake or release) of CO2 that are across the globe. The CO2 plumes can be seen moving across the globe, illustrating the importance of monitoring CO2 globally, not just locally. The large variations in CO2 concentration from season to season are due to the plant life. During the winter season, plants and trees respire CO2 as they shed leaves and stop growing or decay, adding much CO2 to the atmosphere. This process reverses during spring and summer, when they have plenty of access to sunlight and grow leaves and flowers, or increase their size substantially. This time of year is very well visible in the movie: in July the NH shows intense blue colors especially over the mid-latitude regions where forests and crops are soaking up CO2 in great amounts. The large change in CO2 between the seasons caused by plant activity is sometimes referred to as the ‘breathing’ of the planet. In the tropics, intense red areas are visible especially during July, August and September. This is due to the burning of biomass. Some of this is natural, such as dry grasses on the savannas burning, but most of it is man-made as people burn fields to prepare them for another year of production, or burn forests to make way for new agricultural lands. Source of Data: NOAA/ESRL GMD Carbon Cycle Greenhouse Gases group.

NOAAs Carbon Tracker


 

Animation showing Carbon Dioxide in the atmosphere in 2005. The Global Monitoring Division at NOAA diligently monitors carbon dioxide and other trace gases in the atmosphere. One of the methods they use to sample trace gases is collecting flasks of air from around the world that can be tested. They have several other means for collecting samples as well. In this data set, the NOAA GMD sampling network as of 2005 is portrayed. Circles are flask sampling locations, stars are aircraft sites (12 flasks per flight are filled) and ships, which are only visible as they race from Australia and New Zealand to the US west coast or Japan, or from Cape Town to the US east coast. The coloration in the dataset represents the fluxes constructed by the ocean, biosphere, and fossil fuel modules of the NOAA ESRL data assimilation system for CO2 and related trace gases. The data set shows daily average fluxes constructed from 3-hour model output. Source of Data: NOAA/ESRL GMD Carbon Cycle Greenhouse Gases group.

CarbonFlux


 

Animation showing Black Carbon in the atmosphere in 2007. With so many uncertainties attached to climate change, it is important to look at all of the factors. As early as 1896, scientists have been analyzing the presence of black carbon in the atmosphere. This group of three datasets looks at the presence of aerosols in the Earth’s atmosphere. The first dataset contains only black carbon optical thickness, the second has sulfate optical thickness and the third has a combination of both black carbon and sulfate optical thickness. The data is from January 31, 2007 and extends out 120 hours through February 4, 2007. Black carbon is commonly known as soot. It is generated from burning fossil fuels and biomass fuels. Soot is the result of incomplete combustion, especially of coal, diesel fuels, biofuels and other biomass burnings. Source of Data: NASA Global Modeling and Assimilation Office.

BlackCarbon AOT


 

Animation showing Black Carbon & Sulfate in the atmosphere in 2007. Sulfate is the result of sulfur dioxide and sulfur trioxide interacting with other compounds in the atmosphere. Sulfate aerosols in the atmosphere are associated with the combustion of fossil fuels and also the eruption of volcanoes like Mt. Pinatubo. Both black carbon and sulfate affect the global temperature by absorbing sunlight. It is thought that the presence of sulfate lowers the total mean global temperature by reflecting away incoming solar radiation. Black carbon absorbs the sunlight that reaches it, causing the air temperature to rise. This rise in air temperature causes convection and has been proven to change the hydrological cycle. Source of Data: NASA Global Modeling and Assimilation Office.

BlackCarbon and SulfateAOT


 

Animation showing Sulfate in the atmosphere in 2007. Source of Data: NASA Global Modeling and Assimilation Office.

Sulfate AOT


 

Animation showing Carbon Monoxide in the atmosphere in 2000. This dataset tracks the carbon monoxide in ppb at 500mb (about 12,000ft) from March 1, 2000 through December 31, 2000. The measurements were made using MOPITT, Measurements of Pollution in the Troposphere, an instrument on the NASA satellite Terra. The lifespan of carbon monoxide in the atmosphere is several months. This lifespan is shorter than the time it takes the gas to completely mix through the atmosphere, so the carbon monoxide can be seen moving in concentrated masses. Often the carbon monoxide from one continent has an impact on other continents down wind from the first. Carbon monoxide is one of six pollutants regulated in the United States and other countries. It is not a direct greenhouse gas, but it reacts with other chemicals in the atmosphere that would otherwise destroy methane and ozone. Therefore, carbon monoxide indirectly leads to an increase in the greenhouse gases methane and ozone. There is a distinct difference in the concentrations of carbon monoxide in the northern hemisphere versus the southern hemisphere. This is likely due to the fact that many more people live in the northern hemisphere than the southern hemisphere. The carbon monoxide coming from Africa and South America is largely due to agricultural burning. Source of Data: Terra/MOPITT NASA Goddard Space Flight Center.

Carbon Monoxide in 2000


 

Animation showing the movement of the satellites that make up the A-Train. In order to enable coordinated science observations, the Earth Observations System has created the A-Train. When finally completed in 2008, the A-Train will consist of 6 polar-orbiting satellites that travel just minutes apart in a line. Four of the satellites are NASA satellites, one is a French Centre National d’Etudes Spatiales (CNES) satellite, and the other is a joint satellite between NASA and CNES. The satellites have low polar orbits 438 miles (705 km) above Earth at an inclination of 98 degrees. Together, their overlapping science instruments give a comprehensive picture of Earth weather and climate. The “A” in the A-Train is for “afternoon” because the lead satellite, Aqua, crosses the equator at the mean local time of approximately 1:30pm. Five of the satellites are currently in orbit, and the sixth satellite is scheduled to be launched in 2008.This dataset illustrates the movement of 5 of the 6 satellites that will make up the A-Train. The 6th satellite, the Orbiting Carbon Observatory, OCO, is not shown in this dataset because as of 2007, it has not yet been launched. The lead satellite, shaded an aqua color, is NASA’s Aqua satellite. This satellites main mission is to monitor the water and energy cycle. The next satellite, just 30 seconds behind Aqua, is the CloudSat. This white satellite in the dataset is used to study clouds. The next satellite, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) is used to study clouds and aerosols and is colored pink in this dataset. CALIPSO, the joint NASA/CNES satellite, is only 15 seconds behind CloudSat. Behind CALIPSO by one minute is the CNES satellite PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences couple with Observations from a Lidar). PARASOL, which is red in this dataset, is used to study clouds and aerosols. The last satellite currently in place is Aura. This is the yellow satellite that trails behind the rest by 13 minutes. Aura is used to observe atmospheric chemistry. This dataset covers a 24 hour period and the background shows the movement of sunlight over the globe. Source of Data: Rick Kohrs, SSEC, Space, Science, and Engineering Center.

Earth Observing System


 

This visualization animates the tracks of airplanes that are involved in ACARS during a twenty-four hour period. It also includes Aircraft Meteorological Data Relay, AMDAR, data for many European and Asian air carriers. Essentially, the entire United States is covered, as well as many major cities across the world. ACARS, which is managed by Aeronautical Radio, Inc., is used by the involved airlines to transmit a variety of information such as longitude, latitude, time, temperature, wind direction and wind speed. About 140,000 observations from 4000 aircraft are recorded each day, with 100,000 of those over the United States. Not only does this system provide researchers and forecasters with the data they need, it also helps the airlines to determine the best routes to take based on the highly accurate wind measurements that ACARS provides. Source of Data: NOAA/GSD.

ACARS Flight Tracks


 

Animation of the wind measurments provided by ACARS over a 24 hour period. This vizualization displays all of the wind measurements from the surface up to 45,000ft, while the other displays the winds from 30,000ft to 45,000ft. All of the wind measurements are displayed as wind barbs, which indicate direction and speed of the wind. Source of Data: NOAA/GSD.

ACARS Wind


 

Animation showing the proposed Global Unified Profiling System (GUPS) and the tracks of UAV’s. The Global Unified Profiling System is a new, long-term global observing system that would improve weather and climate prediction. Data from locations over the oceans and polar regions is sparse. This proposed new observing network consists of 240 fixed locations over the oceans and polar regions where oceanic and atmospheric profiles would be routinely measured. Each location would be visited by an unmanned aerial vehicle which would cruise the lower stratosphere and descend to near the surface during flight, using dropsondes and on-board, in situ instruments to obtain detailed profiles of state variables, clouds, aerosols, and chemistry. In the ocean, at the same locations where the atmospheric profiles are measured, a new generation of ocean observatories and buoys would be deployed to report surface and subsurface data. This datasets shows the track that the unmanned aerial vehicles would follow. The grid of data points is set up in such a way that they are equally distributed across the oceans and polar regions. Each plane would follow the labeled tracks on the dataset every three days so that new data is available from every location every three days. At each point on the grid the plane drops several dropsondes that stay at specified pressure levels and travel with the wind. Each of the dropsondes is denoted by the colored lines that appear. The length of the line is proportional to the time it has spent in the atmosphere. This would dramatically increase the amount of information that is available about the atmosphere over the oceans and polar regions and provide detailed profiles of important climate parameters such as temperature and moisture. Source of Data: NOAA/GSD.

GUPS


 

Animation showing AIRS Precipitable Water from November 2005 – November 2006 at 100-500mb. The AIRS, Atmospheric Infrared Sounder, on board the Aqua spacecraft was created by NASA’s Jet Propulsion Laboratory in order to provide accurate, detailed atmospheric measurements for weather and climate applications. The sounder provides daily global coverage, even in the presence of clouds. The AIRS instrument measures humidity, temperature, cloud properties, and greenhouse gas concentrations. Source of Data: Atmospheric Infrared Sounder NASA/Jet Propulsion Laboratory.

AIRSWater100-500mb


 

Animation showing AIRS Precipitable Water from November 2005 – November 2006 at 500-700mb. The AIRS, Atmospheric Infrared Sounder, on board the Aqua spacecraft was created by NASA’s Jet Propulsion Laboratory in order to provide accurate, detailed atmospheric measurements for weather and climate applications. The sounder provides daily global coverage, even in the presence of clouds. The AIRS instrument measures humidity, temperature, cloud properties, and greenhouse gas concentrations. Source of Data: Atmospheric Infrared Sounder NASA/Jet Propulsion Laboratory.

AIRSWater500-700mb


 

Animation showing AIRS Precipitable Water from November 2005 – November 2006 at 700-1000mb. The AIRS, Atmospheric Infrared Sounder, on board the Aqua spacecraft was created by NASA’s Jet Propulsion Laboratory in order to provide accurate, detailed atmospheric measurements for weather and climate applications. The sounder provides daily global coverage, even in the presence of clouds. The AIRS instrument measures humidity, temperature, cloud properties, and greenhouse gas concentrations. Source of Data: Atmospheric Infrared Sounder NASA/Jet Propulsion Laboratory.

AIRSWater700-1000mb


 

Animation showing AIRS Temperature data from November 2005 – November 2006 at 300mb. The AIRS, Atmospheric Infrared Sounder, on board the Aqua spacecraft was created by NASA’s Jet Propulsion Laboratory in order to provide accurate, detailed atmospheric measurements for weather and climate applications. The sounder provides daily global coverage, even in the presence of clouds. The AIRS instrument measures humidity, temperature, cloud properties, and greenhouse gas concentrations. Source of Data: Atmospheric Infrared Sounder NASA/Jet Propulsion Laboratory.

AIRSTemp300mb


 

Animation showing AIRS Temperature data from November 2005 – November 2006 at 500mb. The AIRS, AtmosphericInfrared Sounder, on board the Aqua spacecraft was created by NASA’s Jet Propulsion Laboratory in order to provide accurate, detailed atmospheric measurements for weather and climate applications. The sounder provides daily global coverage, even in the presence of clouds. The AIRS instrument measures humidity, temperature, cloud properties, and greenhouse gas concentrations. Source of Data: Atmospheric Infrared Sounder NASA/Jet Propulsion Laboratory.

AIRSTemp500mb


 

Animation showing AIRS Temperature data from November 2005 – November 2006 at 925mb. The AIRS, Atmospheric Infrared Sounder, on board the Aqua spacecraft was created by NASA’s Jet Propulsion Laboratory in order to provide accurate, detailed atmospheric measurements for weather and climate applications. The sounder provides daily global coverage, even in the presence of clouds. The AIRS instrument measures humidity, temperature, cloud properties, and greenhouse gas concentrations. Source of Data: Atmospheric Infrared Sounder NASA/Jet Propulsion Laboratory.

AIRSTemp925mb


 

Animation showing AIRS Carbon Cycle (4 Year Model).  In this animation, NASA instruments show the seasonal cycle of vegetation and the concentration of carbon dioxide in the atmosphere. The animation begins on January 1, when the northern hemisphere is in winter and the southern hemisphere is in summer. At this time of year, the bulk of living vegetation, shown in green, hovers around the equator and below it, in the southern hemisphere.  As the animation plays forward through mid-April, the concentration of carbon dioxide, shown in orange-yellow, in the middle part of Earth’s lowest atmospheric layer, the troposphere, increases and spreads throughout the northern hemisphere, reaching a maximum around May. This blooming effect of carbon dioxide follows the seasonal changes that occur in northern latitude ecosystems, in which deciduous trees lose their leaves, resulting in a net release of carbon dioxide through a process called respiration.

Source of Data: NASA/Goddard Space Flight Center Scientific Visualization Studio, NASA/JPL Atmospheric Infrared Sounder Project 


 

Animation showing Aerosols in the atmosphere. The extinction optical thickness of aerosols from a free running 10-km GEOS-5 Nature-Run including dust (red), sea salt (blue), black and organic carbon (green) and sulphate (white) are depicted from August 2006 through April 2007. GEOS-5 was run with the GOCART model providing feedbacks of the direct radiative effects of aerosols within the model in addition to their advection by the weather within the simulation.  Dust (red), sea salt (blue), organic/black carbon (green), and sulfates (white) displayed by their extinction aerosol optical thickness. This simulation used GEOS-5 and the Goddard Chemistry Aerosol Radiation and Transport (GOCART) Model.

Source of Data: NASA/Goddard Space Flight Center Scientific Visualization Studio


 

Animation showing annual changes in the Carbon Dioxide Concentration in 2006

Models create a dynamic portrait of the Earth through numerical experiments that simulate our current knowledge of the dynamical and physical processes governing weather and climate variability. This new simulation of carbon dioxide in Earth’s atmosphere provides an ultra-high-resolution look at how the key greenhouse gas moves around the globe and fluctuates in volume throughout the year.   The visualization is a product of a NASA computer model called GEOS-5, created by scientists with the Global Modeling and Assimilation Office at NASA’s Goddard Space Flight Center, Greenbelt, Maryland. This particular simulation has about 64 times greater resolution than most global climate models. In particular, the simulation is called a Nature Run. In this kind of simulation, real data on emissions and atmospheric conditions is ingested by the model, which is then left to run on its own to simulate the behavior of Earth’s atmosphere for a two-year period – in this case, May 2005 to June 2007.  The colors represent a range of carbon dioxide concentrations, from 375 (dark blue) to 395 (light purple) parts per million. The red represents about 385 parts per million. White plumes represent carbon monoxide emissions.

Source of Data: NASA/Goddard Space Flight Center


 

Animation showing GEOS-5 Simulation of Surface & Upper Level Winds, May 2005-May 2007.  To study global wind speeds and patterns, researchers from NASA’s Global Modeling and Assimilation Office ran a 10-kilometer global mesoscale simulation. In this simulation, from May 2005 to May 2007, surface wind speeds appear in shades of white, ranging from 0 to 40 meters per second (0 to 89 mph). The colors represent upper-level winds (250 hPa), ranging from 0 to 175 meters per second (0 to 390 mph); the fastest winds appear red. Simulations such as these allow scientists to better understand global surface and upper-air wind patterns and how atmospheric constituents such as aerosols can be transported from the surface to upper-levels.

Source of Data: NASA/Goddard Space Flight Center Scientific Visualization Studio


 

Animation showing Major sources of tropospheric NO2 include industrial emissions, automobile traffic, forest and brush fires, microbiological soil emissions, lightning, and aircraft. More than half of the total NO2 emissions are estimated to be anthropogenic, mainly from the burning of fossil fuels for energy production, transportation, and industrial activities. NO2 has a relatively short lifetime (about a day) and is therefore concentrated near its sources.  This sequence of daily images from September 1, 2009 – August 31, 2010, shows the global perspective of tropospheric nitrogen dioxide (NO2) as measured by the Ozone Measuring Instrument (OMI) flying aboard NASA’s Aura spacecraft.

Data: NASA/Goddard Space Flight Center Scientific Visualization Studio, NASA’s Aura spacecraft.


 

Animation showing the five-year rolling averages that start with (1880 through 1884) and end with (2009 through 2013).  NASA scientists say 2013 tied with 2009 and 2006 for the seventh warmest year since 1880, continuing a long-term trend of rising global temperatures. With the exception of 1998, the 10 warmest years in the 134-year record all have occurred since 2000, with 2010 and 2005 ranking as the warmest years on record.  NASA’s Goddard Institute for Space Studies (GISS) in New York, which analyzes global surface temperatures on an ongoing basis, released an updated report on temperatures around the globe in 2013. The comparison shows how Earth continues to experience temperatures warmer than those measured several decades ago. The average temperature in 2013 was 58.3 degrees Fahrenheit (14.6 degrees Celsius), which is 1.1 °F (0.6 °C) warmer than the mid-20th century baseline. The average global temperature has risen about 1.4 °F (0.8 °C) since 1880, according to the new analysis. Exact rankings for individual years are sensitive to data inputs and analysis methods.

Source of Data: NASA/Goddard Space Flight Center Scientific Visualization Studio


 

Animation showing changing Stratospheric Ozone over 1 year.  Ozone is a gas made of three oxygen atoms, and just like any other gas it circulates in the atmosphere. The stratospheric ozone layer is critical because it protects Earth from harmful ultraviolet solar radiation. Areas with ozone concentrations less than 220 Dobson Units are called “holes” in the layer. The Antarctic ozone hole is formed each year in the Southern Hemisphere spring (September-November) when there is a sharp decline (currently up to 60%) in the total ozone over most of Antarctica. During the cold dark Antarctic winter, stratospheric ice clouds (PSCs, polar stratospheric clouds) form when temperatures drop below -78C. These very cold clouds are responsible for chemical changes that promote production of chemically active chlorine and bromine. When sunlight is combined with the chlorine and bromine in the Antarctic Spring, there is an activation that leads to a rapid ozone loss, which results in the Antarctic ozone hole.   Source of Data:  NOAA Vizualization Lab


IPCC Climate Models Content

Animation of the IPCC Temperature Change GFDL Model. The Intergovernmental Panel on Climate Change (IPCC) was established by WMO and UNEP to assess scientific, technical and socio- economic information relevant for the understanding of climate change, its potential impacts and options for adaptation and mitigation. It is open to all members of the UN and of WMO. In an effort to better visualize the future of climate change, the IPCC releases assessment reports on the current state of the atmosphere and what the future could hold. All three models have similar forcing agents. For the past data they use the 20th Century Model 20C3M, which takes into account the historical record of greenhouse gases, sulfate aerosol concentrations, volcanic aerosol optical depths, and historical solar irradiation. For the future, there are two variations. Each model is available using the Special Report on Emissions Scenarios, SRES, A1B scenario, which assumes: Rapid economic growth, A global population that reaches 9 billion in 2050 and then gradually declines, The quick spread of new and efficient technologies, A convergent world – income and way of life converge between regions, Extensive social and cultural interactions worldwide and a balanced emphasis on all energy sources. Source of Data: Geophysical Fluid Dynamics Laboratory.

IPCC Temp Change-GFDL Sample


 

Animation of the IPCC Temperature Change CCSM Model. The Intergovernmental Panel on Climate Change (IPCC) was established by WMO and UNEP to assess scientific, technical and socio- economic information relevant for the understanding of climate change, its potential impacts and options for adaptation and mitigation. It is open to all members of the UN and of WMO. In an effort to better visualize the future of climate change, the IPCC releases assessment reports on the current state of the atmosphere and what the future could hold. All three models have similar forcing agents. For the past data they use the 20th Century Model 20C3M, which takes into account the historical record of greenhouse gases, sulfate aerosol concentrations, volcanic aerosol optical depths, and historical solar irradiation. For the future, there are two variations. Each model is available using the Special Report on Emissions Scenarios, SRES, A1B scenario, which assumes: Rapid economic growth, A global population that reaches 9 billion in 2050 and then gradually declines, The quick spread of new and efficient technologies, A convergent world – income and way of life converge between regions, Extensive social and cultural interactions worldwide and a balanced emphasis on all energy sources. Source of Data: CCSM/NCAR.

IPCC Temp Change-CCSM model Sample


 

Animation of the IPCC Temperature Change UKMET Model. The Intergovernmental Panel on Climate Change (IPCC) was established by WMO and UNEP to assess scientific, technical and socio- economic information relevant for the understanding of climate change, its potential impacts and options for adaptation and mitigation. It is open to all members of the UN and of WMO. In an effort to better visualize the future of climate change, the IPCC releases assessment reports on the current state of the atmosphere and what the future could hold. All three models have similar forcing agents. For the past data they use the 20th Century Model 20C3M, which takes into account the historical record of greenhouse gases, sulfate aerosol concentrations, volcanic aerosol optical depths, and historical solar irradiation. For the future, there are two variations. Each model is available using the Special Report on Emissions Scenarios, SRES, A1B scenario, which assumes: Rapid economic growth, A global population that reaches 9 billion in 2050 and then gradually declines, The quick spread of new and efficient technologies, A convergent world – income and way of life converge between regions, Extensive social and cultural interactions worldwide and a balanced emphasis on all energy sources. Source of Data: United Kingdom Meteorology Office.

IPCC Temp Change-UKMET model Sample


 

Animation of the IPCC Precipitation Anomaly, GFDL Model. The model for precipitation anomaly that is available was developed by the Geophysical Fluid Dynamics Laboratory. The model uses the same forcing agents as the temperature change model and the sea ice model, but is set to determine precipitation anomalies. For the past data, the 20th Century Model 20C3M is used, which takes into account the historical record of greenhouse gases, sulfate aerosol concentrations, volcanic aerosol optical depth, and historical solar irradiation. For the future, the SRES A1B is used; a scenario which assumes very rapid economic growth with low population growth and the introduction of new and more efficient technology. In this model, CO2 production increases until it reaches 717ppm near the year 2100; then it is cut off. The precipitation anomaly is the difference from what is normal. In this case, normal was defined as the precipitation averages for the year 2000. Red shading is used to signify areas that will receive more rain than in 2000, and the blue shading represents areas that will receive less rain than in 2000. Unlike the temperature models which show a warming trend over almost the entire globe, the precipitation anomaly is varied across the globe with time showing no clear trend. Source of Data: Geophysical Fluid Dynamics Laboratory (GFDL).

IPCC Precip Anomaly GFDL Sample


 

Animation showing changes in sea ice from 1861-2100, GFDL Model. In order to better understand how the climate is changing and the extent of the impact on the Arctic sea ice, scientists create models designed to simulate what has happened and what is likely to happen in the future. The model output for this dataset comes from GFDL’s CM2.1 coupled model. The simulation of past years takes into account the historical record of greenhouse gases, volcanic aerosols, black and organic carbon aerosols, sulfate aerosols, ozone, solar irradiance, and land surface changes. For the future, they use the SRES A1B scenario from the Intergovernmental Panel on Climate Change, which assumes a mid-level increase in 21st century greenhouse gas levels. This simulation shows the change in the average sea ice concentration for August, September, and October. The sea ice in the Arctic is at a minimum during these months. Source of Data: NOAA Geophysical Fluid Dynamics Laboratory.

GFDL Sea Ice 1861-2100


Astronomy Content

The latest image of Mercury from the Messenger spacecraft. Source of Data: NOAA/GSD.


 

Image of Venus from the Magellan spacecraft. Source of Data: NASA Goddard Space Flight Center.

Venus


 

Radar image of Venus from the Magellan spacecraft. Source of Data: NASA Goddard Space Flight Center.

VenusRadar


 

Topographical image of Venus from the Magellan spacecraft. The surface of Venus in geological terms is relatively young, dating about 300 to 500 million years old. Roughly 90% of the surface appears to be solidified basalt lava. More than 1000 volcanoes, with diameters in excess of 12 miles, cover the surface of Venus. This topographic map uses color to represent height, with red for high elevations and blue for low elevations. The intensity of the color is proportional to the radar brightness. Source of Data: NASA Goddard Space Flight Center.

VenusTopo


 

ARC’s Face of the Earth, natural Earth image with simulated clouds.

Cloudy Earth


 

ARC’s Face of the Earth, natural Earth image without clouds.

Cloudless Earth


 

NASA and Japan’s Ministry of Economy, Trade and industry released the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model to the worldwide public on June 29, 2009. The GDEM was created by processing and stereo-correlating the 1.3 million-scene ASTER archive of optical images, covering Earth’s land surface between 83 degrees North and 83 degrees South latitudes. The GDEM is produced with 30-meter (98-feet) postings, and is formatted as 23,000 one-by-one- degree tiles. The GDEM is available for download from NASA’s EOS data archive and Japan’s Ground Data System. In this colorized version, low elevations are purple, medium levations are greens and yellows, and high elevations are orange, red and white. Ocean Bathymetry added by ARC Science.

Earth-Topo-Bath


 

Image of Earth’s Moon from the Clementine spacecraft. Source of Data: NASA Goddard Space Flight Center.

Earths Moon


 

Image of the Moon with the locations of the Apollo and Surveyor landing sites. Surveyor landings are noted by “S”: S1, S3, S5, S6, S7 and Apollo landings are noted by number: 11, 12, 14, 15, 16, 17. Source of Data: NASA Goddard Space Flight Center.

Moon Landings


 

Image of Mars from the Viking spacecraft. Source of Data: NASA Goddard Space Flight Center. Graphic created by ARC Science.

Mars


 

Image of Mars with clouds. Image from the Viking spacecraft. Source of Data: NASA Goddard Space Flight Center. Graphic created by ARC Science.

MarsWithClouds


 

Image showing Mars Magnetic Fields from the Mars Global Surveyor spacecraft. Source of Data: NASA Goddard Space Flight Center.

Mars Magnetic Fields


 

Topographical image of Mars from the Mars Global Surveyor spacecraft. A topographic view of Mars can be telling of the many distinguishing characteristics that it possesses. Mars is known to have several significant topographic features such as Olympus Mons, the highest peak in the solar system, and Valles Marineris, a canyon that easily dwarfs the Grand Canyon. The Mars Orbiter Laser Altimeter, MOLA, an instrument used to determine the altitude, was in orbit, attached to the Mars Global Surveyor spacecraft. Since its launch in 1996, the instruments on the Mars Global Surveyor, such as MOLA, have been providing scientists with valuable information. The altitude is determined by MOLA by transmitting a laser pulse toward the surface of Mars. By recording the flight time of the pulse, the distance between the spacecraft and the surface of Mars can be calculated. These range measurements are then used to create the topographic maps. Areas that are red and brown have higher altitudes while areas that are blue and green have lower altitudes. Source of Data: NASA.

Mars MOLA


 

Image of Jupiter from NASA.

Jupiter


 

Animation of the clouds of Jupiter from the Cassini spacecraft. Source of Data: NASA.

JupiterAnimation


Image of Jupiter’s moon Io from the Voyager and Galileo spacecraft. Source of Data: NASA.

Io


 

Image of Jupiter’s moon Europa from the Voyager and Galileo spacecraft. Source of Data: NASA.

Europa


 

Image of Jupiter’s moon Ganymede from the Voyager and Galileo spacecraft. Source of Data: NASA.

Ganymede


 

Image of Jupiter’s moon Callisto from the Voyager and Galileo spacecraft. Source of Data: NASA.

Callisto


 

Image of Saturn without its rings. Source of Data: NASA.

Saturn


 

Image of Saturn’s moon Mimas from the Cassini and Voyager spacecraft. Source of Data: NASA/JPL.

Mimas


 

Image of Saturn’s moon Enceladus from the Cassini and Voyager spacecraft. Source of Data: NASA/JPL

Enceladus


 

Image of Saturn’s moon Tethys from the Cassini and Voyager spacecraft. Source of Data: NASA/JPL.

Tethys


 

Image of Saturn’s moon Dione from the Cassini and Voyager spacecraft. Source of Data: NASA/JPL.

Dione


 

Image of Saturn’s moon Rhea from the Cassini and Voyager spacecraft. Source of Data: NASA/JPL.

Rhea


 

Image of Saturn’s moon Titan from the Cassini spacecraft. Source of Data: NASA/JPL.

Titan-Color


 

Image of Saturn’s moon Iapetus from the Cassini and Voyager spacecraft. Source of Data: NASA/JPL.

Iapetus


 

Image of Saturn’s moon Phoebe from the Cassini and Voyager spacecraft. Source of Data: NASA/JPL.

Phoebe


 

Image of Uranus. Source of Data: NASA.

Uranus


 

Image of Uranus’s moon Ariel from the Voyager spacecraft. Source of Data: NASA/JPL.

Ariel


 

Image of Uranus’s moon Umbriel from the Voyager spacecraft. Source of Data: NASA/JPL.

Umbriel


 

Image of Uranus’s moon Titania from the Voyager spacecraft. Source of Data: NASA/JPL.

Titania


 

Image of Uranus’s moon Oberon from the Voyager spacecraft. Source of Data: NASA/JPL.

Oberon


 

Image of Uranus’s moon Miranda from the Voyager spacecraft. Source of Data: NASA/JPL.

Miranda


 

Image of Neptune from the Voyager spacecraft. Source of Data: NASA/JPL.

Neptune


 

Image of Neptune’s moon Tritan (improved by ARC Science). Base image from the Voyager spacecraft. Source of Data: NASA/JPL. Graphic created by ARC Science.

Triton


 

Image of the visible Sun. Source of Data: NASA Goddard Space Flight Center.

VizSun


 

Image of the visible Sun with the planets overlayed to show scale. Source of visualization: ARC Science Simulations.

VizSunScale


 

Animation of the Sun from the Solar and Heliospheric Observatory (SOHO) over a 30 day period. Source of Data: NASA Solar and Heliospheric Observatory/Goddard Space Flight Center.

SOHO


 

Animation of the Sun in X-Ray, produced by Dr. Steven Hill of NOAA’s Space Environment Center, is from October 19, 2001 through November 4, 2001. The data for it is from GOES Solar X-Ray Imager, SXI, which is an instrument attached to the GOES 12 satellite. The Space Environment Center receives a stream of the data which it then uses to make space weather alerts and forecast services. The SXI collects one image per minute and varies the exposure settings to allow for three different views to see coronal structures, active regions and solar flares. Source of Data: NASA/NOAA Space Environment Center.

XRAY-Sun


 

Axel Mellinger’s composite image of the full night sky.

MilkyWay


 

Axel Mellinger’s composite image of the full night sky with the constellations indicated.

MilkyWayConstellations


 

Image showing the temperature of the cosmic background radiation over the full sky after the First year. This map of remnant heat from the Big Bang provides answers to fundamental questions about the origin and fate of our universe. Temperature fluctuations displayed here are 13.7 billion years old, from the time when the Big Bang was thought to have occurred. Essentially, it is a detailed, all-sky display of the young universe developed from one year of WMAP data. The blue areas are cooler while the red areas are warmer. The temperature range on this map is ± 200
microKelvin. Source of Data: NASA/WMAP Science Team/Goddard Space Flight Center.

WMAP - First Year


 

Image showing the temperature of the cosmic background radiation over the full sky after three years of data. This map of remnant heat from the Big Bang provides answers to fundamental questions about the origin and fate of our universe. Temperature fluctuations displayed here are 13.7 billion years old, from the time when the Big Bang was thought to have occurred. Essentially, it is a detailed, all-sky display of the young universe developed from three years of WMAP data. The blue areas are cooler while the red areas are warmer. The temperature range on this map is ± 200 microKelvin. Source of Data: NASA/WMAP Science Team/Goddard Space Flight Center.

WMAP - First Year


 

Image showing the temperature of the cosmic background radiation over the full sky after five years of data. This map of remnant heat from the Big Bang provides answers to fundamental questions about the origin and fate of our universe. Temperature fluctuations displayed here are 13.7 billion years old, from the time when the Big Bang was thought to have occurred. Essentially, it is a detailed, all-sky display of the young universe developed from five years of WMAP data. The blue areas are cooler while the red areas are warmer. The temperature range on this map is ± 200 microKelvin. Source of Data: NASA/WMAP Science Team/Goddard Space Flight Center.

WMAP 5th Year


 

Animation showing the 2012 transit of Venus as observed by the Solar Dynamic Observatory satellite in 195 Angstroms.

VenusTransit195


 

Animation showing the 2012 transit of Venus as observed by the Solar Dynamic Observatory satellite in 304 Angstroms.

VenusTransit304


Additional Content

Alternate Physical Earth Image from ArcGIS Online. Courtesy of ESRI.

AGOL_Physical


 

Traditional map showing world political boundaries from ArcGIS Online. Courtesy of ESRI.

AGOL_Political


 

AGOL map showing major world highways from ArcGIS Online. Courtesy of ESRI.

AGOL_Streets


 

Global map showing countries with highest poverty levels.

Human_Suffering


 

Global map showing average level of education by country.

K12Education


 

Global map showing different languages spoken by region.

Languages


 

Alternate Earth Image provided by NASA.

NASA_Base


 

Alternate Cloudy Earth Image provided by NASA.

NASA_Clouds


 

NASA image showing the entire Earth at night with city lights.

NASA_Night_Lights


 

NGS Political Earth map re-formatted for the OmniGlobe.

NGS_MAP


 

Alternate Earth Image with Bathymetry from ArcGIS Online. Courtesy of ESRI.

Physical_Inset_Base


 

Map showing global human population density from ArcGIS Online. Courtesy of ESRI.

Population_Density-23


 

Global Tree Cover – Broadleaf.

Tree_Cover_Broadleaf


 

Global Tree Cover – Deciduous.

Tree_Cover_Deciduous


 

Global Tree Cover – Evergreen.

Tree_Cover_Evergreen


 

Global Tree Cover – Needle Leaf.

Tree_Cover_Needleleaf


 

Percentage of the Earth covered by trees.

Tree_Cover_Percent


 

Image showing global time zones.

GlobalTimeZones


 

Old World Map created by Drake in 1581, cropped and formatted for the OmniGlobe. Source – Library of Congress.

Drake 1581 Old World Map


 

Old World Map created by De Jode in 1589, cropped and formatted for the OmniGlobe. Source – Library of Congress.

De Jode 1589 Old World Map


 

Old World Map created by Moll in 1719, cropped and formatted for the OmniGlobe. Source – Library of Congress.

Moll 1719 Map


 

Old World Map created by Maury in 1848, cropped and formatted for the OmniGlobe. Source – Library of Congress.

Maury 1848 Map


 

Old World Map created by Wilkes in 1856, cropped and formatted for the OmniGlobe. Source – Library of Congress.

Wilkes 1856 Map


 

Global Relief Map provided by the National Geophysical Data Center, National Oceanic and Atmospheric Administration, U.S. Dept. of Commerce.

ETOPO2


 

Global Map showing commonly used shipping routes from Oct. 2004 – Oct. 2005. Provided by The National Center for Ecological Analysis and Synthesis.

ShippingRoutes


 

Global Map showing Facebook connections. This dataset was created by an intern at Facebook who plotted 10 million pairs of friends on Facebook. The result is a stunning map that shows the connections between people and highlights the regions with readily available access to the internet. Source of image: Facebook.

FacebookFriendships


 

Global Map showing how the Ocean conveyor belts work.

ConveyorBelt


 

Global Map showing Hurricane, Cyclone and Typhoon Zones.

HurricaneZones