For more information: https://science.nasa.gov/earth-science
Content Contact:
NASA’s (The Clouds and the Earth's Radiant Energy System) CERES and NASA's Total and Spectral solar Irradiance Sensor (TSIS-1), missions play key roles in our continued understanding of Earth’s Energy Budget.
NASA’s TSIS helps scientists keep a close watch on the sun’s energy input to Earth. Various satellites have captured a continuous record of this solar energy input since 1978. TSIS-1 sensors advance previous measurements, enabling scientists to study the sun's natural influence on Earth's ozone layer, atmospheric circulation, clouds, and ecosystems. These observations are essential for a scientific understanding of the effects of solar variability on the Earth system.
TSIS-1 makes two key measurements: total solar irradiance, or TSI, the sun's total energy input into Earth, and solar spectral irradiance (SSI), the distribution of the sun's energy input across ultraviolet, visible, and infrared wavelengths of light. TSI measurements are needed to quantify the solar variations in the total amount of energy input to the Earth. SSI measurements are also vital because different wavelengths of light are absorbed by different parts of the atmosphere.
For more than 20 years, NASA Langley's CERES (System) instruments have measured the solar energy reflected by Earth, the heat the planet emits, and the role of clouds in that process. The final CERES Flight Model, CERES FM6 launched aboard NOAA’s JPSS-1 in Fall 2017.
CERES FM6 contributes to an already extensive CERES dataset that helps scientists validate models that calculate the effect of clouds on planetary heating and cooling. The same data can also be helpful for improving near-term, seasonal forecasts influenced by weather events such as El Niño and La Niña. El Niño and La Niña are weather patterns that develop when ocean temperatures fluctuate between warm and cool phases in the Equatorial Pacific Ocean. Built by Northrop Grumman and managed by Langley, CERES FM6 joins five other CERES instruments orbiting the planet on three other satellites.
NASA Goddard Space Flight Center manages the TSIS-1 project. The University of Colorado's Laboratory for Atmospheric and Space Physics (LASP) built both instruments and provides mission operations. The International Space Station carries TSIS-1. Earth's energy budget is a metaphor for the delicate equilibrium between energy received from the Sun versus energy radiated back out in to space. Research into precise details of Earth's energy budget is vital for understanding how the planet's climate may be changing, as well as variabilities in solar energy output.
NASA’s (The Clouds and the Earth's Radiant Energy System) CERES and NASA's Total and Spectral solar Irradiance Sensor (TSIS-1), missions play key roles in our continued understanding of Earth’s Energy Budget.
NASA’s TSIS helps scientists keep a close watch on the sun’s energy input to Earth. Various satellites have captured a continuous record of this solar energy input since 1978. TSIS-1 sensors advance previous measurements, enabling scientists to study the sun's natural influence on Earth's ozone layer, atmospheric circulation, clouds, and ecosystems. These observations are essential for a scientific understanding of the effects of solar variability on the Earth system.
TSIS-1 makes two key measurements: total solar irradiance, or TSI, the sun's total energy input into Earth, and solar spectral irradiance (SSI), the distribution of the sun's energy input across ultraviolet, visible, and infrared wavelengths of light. TSI measurements are needed to quantify the solar variations in the total amount of energy input to the Earth. SSI measurements are also vital because different wavelengths of light are absorbed by different parts of the atmosphere.
For more than 20 years, NASA Langley's CERES (System) instruments have measured the solar energy reflected by Earth, the heat the planet emits, and the role of clouds in that process. The final CERES Flight Model, CERES FM6 launched aboard NOAA’s JPSS-1 in Fall 2017.
CERES FM6 contributes to an already extensive CERES dataset that helps scientists validate models that calculate the effect of clouds on planetary heating and cooling. The same data can also be helpful for improving near-term, seasonal forecasts influenced by weather events such as El Niño and La Niña. El Niño and La Niña are weather patterns that develop when ocean temperatures fluctuate between warm and cool phases in the Equatorial Pacific Ocean. Built by Northrop Grumman and managed by Langley, CERES FM6 joins five other CERES instruments orbiting the planet on three other satellites.
NASA Goddard Space Flight Center manages the TSIS-1 project. The University of Colorado's Laboratory for Atmospheric and Space Physics (LASP) built both instruments and provides mission operations. The International Space Station carries TSIS-1.
As the visualization shows, carbon dioxide in the atmosphere can be mixed and transported by winds in the blink of an eye. For several decades, scientists have measured carbon dioxide at remote surface locations and occasionally from aircraft. The OCO-2 mission represents an important advance in the ability to observe atmospheric carbon dioxide. OCO-2 collects high-precision, total column measurements of carbon dioxide (from the sensor to Earth’s surface) during daylight conditions. While surface, aircraft, and satellite observations all provide valuable information about carbon dioxide, these measurements do not tell us the amount of carbon dioxide at specific heights throughout the atmosphere or how it is moving across countries and continents. Numerical modeling and data assimilation capabilities allow scientists to combine different types of measurements (e.g., carbon dioxide and wind measurements) from various sources (e.g., satellites, aircraft, and ground-based observation sites) to study how carbon dioxide behaves in the atmosphere and how mountains and weather patterns influence the flow of atmospheric carbon dioxide. Scientists can also use model results to understand and predict where carbon dioxide is being emitted and removed from the atmosphere and how much is from natural processes and human activities.
Carbon dioxide variations are largely controlled by fossil fuel emissions and seasonal fluxes of carbon between the atmosphere and land biosphere. For example, dark red and orange shades represent regions where carbon dioxide concentrations are enhanced by carbon sources. During Northern Hemisphere fall and winter, when trees and plants begin to lose their leaves and decay, carbon dioxide is released in the atmosphere, mixing with emissions from human sources. This, combined with fewer trees and plants removing carbon dioxide from the atmosphere, allows concentrations to climb all winter, reaching a peak by early spring. During Northern Hemisphere spring and summer months, plants absorb a substantial amount of carbon dioxide through photosynthesis, thus removing it from the atmosphere and change the color to blue (low carbon dioxide concentrations). This three-dimensional view also shows the impact of fires in South America and Africa, which occur with a regular seasonal cycle. Carbon dioxide from fires can be transported over large distances, but the path is strongly influenced by large mountain ranges like the Andes. Near the top of the atmosphere, the blue color indicates air that last touched the Earth more than a year before. In this part of the atmosphere, called the stratosphere, carbon dioxide concentrations are lower because they haven’t been influenced by recent increases in emissions.
This set of images shows Singapore and the nearby region on May 29, 2015, when air quality conditions were normal, and on September 25, 2015, when a thick smoky haze covered the nation. Each image reveals a true-color image [top] from the Moderate Resolution Imaging Spectroradiometer (MODIS) and atmospheric cross-section [bottom] from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The CALIPSO image from September 25 reveals the thick layer of smoke (dark orange) in the atmosphere.
This visualization, created using data from the Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite, shows annual, average changes in sulfur dioxide concentrations from 2005 to 2017. Sulfur dioxide concentrations from volcanic (i.e., natural) sources have been removed.
Sulfur dioxide is produced by the combustion of coal, fuel oil, and gasoline (since these fuels contain sulfur), and in the oxidation of naturally occurring sulfur gases, such as in volcanic eruptions. The largest source of sulfur dioxide in the atmosphere is the burning of fossil fuels by power plants and other industrial facilities. National and regional rules to reduce emissions of sulfur dioxide can improve air quality.
This gallery was created for Earth Science Week 2015 and beyond. It includes a quick start guide for educators and first-hand stories (blogs) for learners of all ages by NASA visualizers, scientists and educators. We hope that your understanding and use of NASA's visualizations will only increase as your appreciation grows for the beauty of the science they portray, and the communicative power they hold. Read all the blogs and find educational resources for all ages at: The Earth Science Week 2015 page.
I've always been fascinated by our atmosphere. Think about it: even though we don't see it, above us is a great aerial ocean! Over time my fascination has grown from weather maps and pondering the origins of storms, to learning all about the physics that surround our everyday lives. From as early as grade school I was also very interested in computers: diagnosing errors, developing programming skills and learning all about hardware and operating systems. So you might say my interests naturally led me to a career as a NASA scientist, where I create visualizations to study the underlying factors that drive weather patterns. Visualizations help us to see the world differently and actively.
Many of you have no doubt seen your homes from space using a program called Google Earth™. But did you know you could do a lot more with the right data? In fact I often use it to map atmospheric data in three-dimensions (3-D) around the globe. But one of the challenges I often face is that data comes from many different sources, such as NASA and NOAA satellites or ground-observation stations. This means the data is stored on computer disks all over the country and are named and organized according to different standards, requiring us to customize techniques for producing accurate visualizations in one, 3-D display of the Earth. We do this in order to analyze atmospheric relationships more easily because many weather phenomena arise from physical interactions, both horizontally and vertically, in the global circulation.
A big part of atmospheric research relies on using computer models to simulate what our atmosphere will do under different conditions. A great example of this is the data used to prepare the daily weather forecast. This data originates from weather forecasting models that calculate atmospheric motions using the world’s fastest supercomputers. But how do we know these forecasts are accurate? Researchers can verify a model's performance by visualizing one of the variables such as temperature, humidity, wind speed, wind direction, or air pressure and then using color shading, contour curves, and wind "barbs" to graph that data. Then they overlay the observations from NASA satellites such as cloud-top imagery, cloud-top temperature, and vertical distributions of clouds and aerosols, with the graph (it can be challenging to synchronize the data display as these times usually don't match). After this process, the display confirms the model's accuracy. This method is used to study many atmospheric events, such as timing of a storm system, precipitation, or the direction of dust or smoke transport.
My passion is transforming weather data into rich visualizations that allow us to see things differently or tell us a story. My favorite part is using remotely-sensed NASA data to view clouds over the oceans. This is very important because ground observations are sparse to non-existent for oceans, which cover much of the Earth's surface. Warm oceans are what allow hurricanes to form. Visualization tools can greatly aid the interpretation of data used to understand and forecast hurricanes by integrating multiple datasets into a common display. This helps to communicate to the public the track and intensity of tropical storms, which is absolutely vital for the safety of millions of people around the world, especially those living in coastal communities.
Ultimately, it's how my work impacts understanding of weather and potentially helps the rest of the world that keeps me motivated. I have been very lucky to explore our planet in a new and different way and to continually rediscover my passion for Earth science. It’s been a remarkable journey — challenging, fulfilling and ever-changing — and I hope many of you choose to undertake it!
-- Roman Kowch, Staff Research Scientist (SSAI/NASA Langley Research Center)
CERES products include both solar-reflected and Earth-emitted radiation from the top of the atmosphere to the Earth's surface. Cloud properties are determined using simultaneous measurements by other EOS and NPP instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible and Infrared Sounder (VIRS). Analyses using CERES data, build upon the foundation laid by previous missions such as NASA Earth Radiation Budget Experiment (ERBE), leading to a better understanding of the role of clouds and the energy cycle in global climate change.
The sun's radiant energy is the fuel that drives Earth's climate engine. The Earth-atmosphere system constantly tries to maintain a balance between the energy that reaches the Earth from the sun and the energy that flows from Earth back out to space. Energy received from the sun is mostly in the visible (or shortwave) part of the electromagnetic spectrum. About 30% of the solar energy that comes to Earth is reflected back to space. The ratio of reflected-to-incoming energy is called "albedo" from the Latin word meaning whiteness. The solar radiation absorbed by the Earth causes the planet to heat up until it is radiating (or emitting) as much energy back into space as it absorbs from the sun. The Earth's thermal emitted radiation is mostly in the infrared (or longwave part of the spectrum. The balance between incoming and outgoing energy is called the Earth's radiation budget.
This global view shows CERES top-of-atmosphere (TOA) longwave radiation from Jan 26 and 27, 2012. Heat energy radiated from Earth (in watts per square meter) is shown in shades of yellow, red, blue and white. The brightest-yellow areas are the hottest and are emitting the most energy out to space, while the dark blue areas and the bright white clouds are much colder, emitting the least energy. Increasing temperature, decreasing water vapor, and decreasing clouds will all tend to increase the ability of Earth to shed heat out to space.
For more information on the Clouds and Earth's Radiant Energy System (CERES) see http://ceres.larc.nasa.gov
CERES products include both solar-reflected and Earth-emitted radiation from the top of the atmosphere to the Earth's surface. Cloud properties are determined using simultaneous measurements by other EOS and NPP instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible and Infrared Sounder (VIRS). Analyses using CERES data, build upon the foundation laid by previous missions such as NASA Earth Radiation Budget Experiment (ERBE), leading to a better understanding of the role of clouds and the energy cycle in global climate change.
The sun's radiant energy is the fuel that drives Earth's climate engine. The Earth-atmosphere system constantly tries to maintain a balance between the energy that reaches the Earth from the sun and the energy that flows from Earth back out to space. Energy received from the sun is mostly in the visible (or shortwave) part of the electromagnetic spectrum. About 30% of the solar energy that comes to Earth is reflected back to space. The ratio of reflected-to-incoming energy is called "albedo" from the Latin word meaning whiteness. The solar radiation absorbed by the Earth causes the planet to heat up until it is radiating (or emitting) as much energy back into space as it absorbs from the sun. The Earth's thermal emitted radiation is mostly in the infrared (or longwave part of the spectrum. The balance between incoming and outgoing energy is called the Earth's radiation budget.
This global view shows CERES top-of-atmosphere (TOA) shortwave radiation from Jan 26 and 27, 2012. Thick cloud cover tends to reflect a large amount of incoming solar energy back to space (blue/green/white image).
For more information on the Clouds and Earth's Radiant Energy System (CERES) see http://ceres.larc.nasa.gov
Data Sources:
This visualization captures monthly Sea Surface Temperature (SST) anomalies around the world from 2009-2018, along with global disease outbreaks and a corresponding timeplot graph focusing on the Niño 3.4 Index.
The Niño 3.4 Index represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the above average El Niño years, in which sea surface temperature anomalies peaked: 2015-2016.
This visualization was produced using model output from the joint MIT/JPL project entitled Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2). ECCO2 uses the MIT general circulation model (MITgcm) to synthesize satellite and in-situ data of the global ocean and sea-ice at resolutions that begin to resolve ocean eddies and other narrow current systems, which transport heat and carbon in the oceans. The ECCO2 model simulates ocean flows at all depths, but only surface flows are used in this visualization.
The United Nations' Intergovernmental Panel on Climate Change publishes a report on the consensus view of climate change science about every five to seven years. The first findings of the IPCC's Fifth Assessment Report (AR5) were released on Sept. 27, 2013, in the form of the Summary for Policymakers report and a draft of IPCC Working Group 1's Physical Science Basis. The IPCC does not perform new science but instead authors a report that establishes the established understanding of the world's climate science community.
The report not only includes observations of the real world but also the results of climate model projections of how the Earth will respond as a system to rising greenhouse gas concentrations in the atmosphere. The IPCC's AR5 relies on the Coupled Model Intercomparison Project Phase 5 (CMIP5) effort, an international effort among the climate modeling community to coordinate climate change experiments.
These visualizations represent the mean output of how certain groups of CMIP5 models responded to four different scenarios defined by the IPCC called Representative Concentration Pathways (RCPs). These four RCPs – 2.6, 4.5, 6 and 8.5 – represent a wide range of potential worldwide greenhouse gas emissions and sequestration scenarios for the coming century. The pathways are numbered based on the expected Watts per square meter – essentially a measure of how much heat energy is being trapped by the climate system – each scenario would produce. The pathways are partly based on the ultimate concentrations of carbon dioxide and other greenhouse gases. The current carbon dioxide concentration in the atmosphere is around 400 parts per million, up from less than 300 parts per million at the end of the 19th century.
The carbon dioxide concentrations in the year 2100 for each RCP are:
RCP 2.6: 421 ppm
RCP 4.5: 538 ppm
RCP 6: 670 ppm
RCP 8.5: 936 ppm
Each visualization represents the mean output of a different number of models for each RCP, because data from all models in the CMIP5 project was not available in the same format for visualization for each RCP. All of the models compare a projection of temperatures and precipitation from 2006-2099 to a baseline historical average from 1971-2000.
Thus, the values shown for each year represent the departure for that year compared to the observed average global surface temperature from 1971-2000. The IPCC report used 1986-2005 as a baseline period, making its reported anomalies slightly different from those shown in the visualizations.
The GISTEMP analysis website is located at: http://data.giss.nasa.gov/gistemp/
The GISTEMP analysis website is located at: http://data.giss.nasa.gov/gistemp/
Since the year 2000, the rate of absorbed solar radiation in the Arctic in June, July and August has increased by five percent, said Norman Loeb, of NASA’s Langley Research Center, Hampton, Virginia. The measurement is made by NASA’s Clouds and the Earth’s Radiant Energy System (CERES) instruments, which fly on multiple satellites.
While a five percent increase may not seem like much, consider that the rate globally has remained essentially flat during that same time. No other region on Earth shows a trend of potential long-term change.
When averaged over the entire Arctic Ocean, the increase in the rate of absorbed solar radiation is about 10 Watts per square meter. This is equivalent to an extra 10-watt light bulb shining continuously over every 10.76 square feet of Arctic Ocean for the entire summer.
As a region, the Arctic is showing more dramatic signs of climate change than any other spot on the planet. These include a warming of air temperatures at a rate two to three times greater than the rest of the planet and the loss of September sea ice extent at a rate of 13 percent per decade.
CERES instruments fly on the Terra, Aqua and Suomi-NPP satellites, and one is scheduled to fly on the next orbiter of the Joint Polar Satellite System, a NASA-NOAA effort. The Terra satellite launched Dec. 18, 1999, and CERES first started collecting Arctic data in 2000 so 2015 will mark 15 continuous years of CERES measurements over the Arctic.
The instruments include three radiometers – one measuring solar radiation reflected by Earth (shortwave), one measuring thermal infrared radiation emitted by Earth (longwave), and one measuring all outgoing radiation, whether emitted or reflected.
For more information on the project, please visit http://ceres.larc.nasa.gov.
This visualization celebrates over a year of successful Aquarius observations. Sea surface salinity is shown at various locations around the globe highlighting the following:
The range of time shown is December 2011 through Decemeber 2012. The data continuously loops through this range every 6 seconds. This visualization was generated based on version 2.0 of the Aquarius data products with all 3 scanning beams.
This visualization celebrates over three years of successful Aquarius observations. Sea surface salinity is shown on a spinning globe (with and without grid lines).
The range of time shown is September 2011 through September 2014. This visualization was generated based on version 3.0 of the Aquarius data products.
This visualization celebrates over three years of successful Aquarius observations. Sea surface salinity is shown on a flat map using simple cartesian and extended Molleide projections. Versions are included with and without grid lines, and in both Altantic-centered and Pacific-centered projections.
The range of time shown is September 2011 through September 2014. This visualization was generated based on version 3.0 of the Aquarius data products.
SST is invaluable for weather forecasting. But SST is also important for management of fishery, ocean acoustic communication, and the science including studies of climate and marine life.
To "blend" the SST data from many different satellite is a tricky business. Satellite-based environmental data are usually irregularly sampled and always noisy. Every satellite has a unique sensor that measures SST. The infra-red (IR) type sensor can offer a very high resolution (down to 1 km in horizontal distance) but suffer from contamination by clouds and aerosols that block the signal. The micro-wave (MW) measurements are more reliable because of cloud-penetrating coverage but are coarser (25 km) in resolution and are not useful along the coasts due to contamination from land.
So we are interested in making use of the best characteristics of each sensor data — be it resolution or coverage — and finding an optimal and objective ways to fill the data-voids under the clouds and near the coasts.
In May of 2013, these emissions pushed the monthly average CO2 concentrations above 400 parts per million (ppm)—a level that has not been reached during the past 800,000 years. These ever-increasing levels are raising concerns about greenhouse-gas-induced climate change.
Used in 2014 Calendar.
In the latter half of the decade the lake level began to rebound. Significant amounts of snowfall over the winter of 2010–2011 meant more water for the lake. Regional snowfall in the spring of 2012, on the other hand, was abnormally low, and inflow to Lake Powell did not begin to increase in May 2012 as it had in previous years. Since 2012, snow- and rainfall totals have been abnormally low as the region suffered through persistent drought. Inflow to Lake Powell has been minimal, and by April 2015, the reservoir stood at 42 percent of capacity. Droughts in this region are not unusual; however, global warming is expected to make droughts more severe in the future.
Groundwater comes from the natural percolation of precipitation and other surface waters down through Earth's soil and rock, accumulating in aquifers - cavities and layers of porous rock, gravel, sand, or clay. In some subterranean reservoirs, the water may be thousands to millions of years old; in others, water levels decline and rise again naturally each year. Groundwater levels do not respond to changes in weather as rapidly as lakes, streams, and rivers do. So when groundwater is pumped for irrigation or other uses, recharge to the original levels can take months or years.
More than 109 cubic km (26 cubic miles) of groundwater disappeared from the region's aquifers between 2002 and 2008 — double the capacity of India's largest surface water reservoir, the Upper Wainganga, and triple that of Lake Mead, the largest manmade reservoir in the U.S.
The animation shown here depicts the change in groundwater levels as measured each November between 2002 to 2008.
ECOSTRESS rode to orbit in the "trunk" of SpaceX's Dragon spacecraft, which berthed at the station on July 2. On July 5, ground controllers at NASA's Johnson Space Center extracted ECOSTRESS from the trunk, robotically transferred it to the International Space Station’s Japanese Experiment Module - Exposed Facility (JEM-EF) and installed it. The ECOSTRESS payload fits within an enclosure measuring 6.1 x 2.6 x 2.9 ft (1.85 x 0.8 x 0.88 m).
In the “first data” image, taken on July 9, yellow and red indicate generally higher surface temperatures. The Nile River is visible as a thin blue line on the main image. The black-and-white inset shows the level of detail available from ECOSTRESS, with the relatively cool Nile River and surrounding vegetation appearing darker.
From the space station’s altitude of ~250 mi (400 km), ECOSTRESS will provide Earth surface temperature data with a spatial resolution of 226 ft (69 m) cross-track and 125 ft (38 m) in-track with a temperature sensitivity of a few tenths of a degree. The station orbits Earth about 16 times a day; and it flies over the same location on Earth approximately every few days at varying times. This orbit provides sufficient coverage for ECOSTRESS to produce data encompassing the complete daily cycle of plant water use.
Data Notes:
The mosaic was created by EarthSat under contract with NASA as part of the GeoCover 2000 product. All images used in GeoCover were acquired by Landsat-7 during the period of 1999-2002. The pixel size of the full resolution image represents 14.25 m on the ground. The Chesapeake Bay mosaic uses portions of eight Landsat-7 scenes. Below you will find a listing of the eight Landsat 7 images that were put together to create the composite image. Landsat scenes are organized by a Path and Row number according to the Worldwide Reference System. (To learn more about Landsat's Worldwide Reference System, please visit: http://landsat.gsfc.nasa.gov/about/wrs.html)
Scenes used in the Chesapeake Bay mosaic:
Data Notes:
The mosaic was created by EarthSat under contract with NASA as part of the GeoCover 2000 product. All images used in GeoCover were acquired by Landsat-7 during the period of 1999-2002. The pixel size of the full resolution image represents 14.25 m on the ground. The Chesapeake Bay mosaic uses portions of eight Landsat-7 scenes. Below you will find a listing of the eight Landsat 7 images that were put together to create the composite image. Landsat scenes are organized by a Path and Row number according to the Worldwide Reference System. (To learn more about Landsat's Worldwide Reference System, please visit: http://landsat.gsfc.nasa.gov/about/wrs.html)
Scenes used in the Chesapeake Bay mosaic:
The full GEOS-5 simulation covered 2 years—from May 2005 to May 2007. It ran on 3,750 processors of the Discover supercomputer at the NASA Center for Climate Simulation, consuming 3 million processor hours and producing over 400 terabytes of data.
GEOS-5 development is funded by NASA's Modeling, Analysis, and Prediction Program.
Used in 2014 Calendar.
As a preamble to a fully coupled integrated earth system analysis, the atmospheric model is constrained to the GMAO MERRA-2 atmospheric reanalysis (prior to June 2013) and to the GMAO operational forward processing stream (after June 2013) while the SST, SSS, ice concentration and chlorophyll data are assimilated into the coupled model using a new methodology [State Adaptive Forecast-error Estimation (SAFE): https://gmao.gsfc.nasa.gov/pubs/docs/Keppenne721.pdf] developed especially for high-resolution data assimilation.
This animation shows the ocean surface chlorophyll concentration and sea ice thickness fields (shown over grid cells where the fractional ice coverage is greater than 15%) and the vertical integral of atmospheric precipitable water (transparent overlay) sampled every 6 hours from January 1, 2013 to November 1, 2014 from a reanalysis completed with the AXIOM-1 system. The chlorophyll concentration is proportional to the ocean biomass and primary production and influences how deep solar radiation can heat the ocean sub-surface which needs to be accounted for in numerical ocean models.
As the visualization shows, carbon dioxide in the atmosphere can be mixed and transported by winds in the blink of an eye. For several decades, scientists have measured carbon dioxide at remote surface locations and occasionally from aircraft. The OCO-2 mission represents an important advance in the ability to observe atmospheric carbon dioxide. OCO-2 collects high-precision, total column measurements of carbon dioxide (from the sensor to Earth’s surface) during daylight conditions. While surface, aircraft, and satellite observations all provide valuable information about carbon dioxide, these measurements do not tell us the amount of carbon dioxide at specific heights throughout the atmosphere or how it is moving across countries and continents. Numerical modeling and data assimilation capabilities allow scientists to combine different types of measurements (e.g., carbon dioxide and wind measurements) from various sources (e.g., satellites, aircraft, and ground-based observation sites) to study how carbon dioxide behaves in the atmosphere and how mountains and weather patterns influence the flow of atmospheric carbon dioxide. Scientists can also use model results to understand and predict where carbon dioxide is being emitted and removed from the atmosphere and how much is from natural processes and human activities.
Carbon dioxide variations are largely controlled by fossil fuel emissions and seasonal fluxes of carbon between the atmosphere and land biosphere. For example, dark red and orange shades represent regions where carbon dioxide concentrations are enhanced by carbon sources. During Northern Hemisphere fall and winter, when trees and plants begin to lose their leaves and decay, carbon dioxide is released in the atmosphere, mixing with emissions from human sources. This, combined with fewer trees and plants removing carbon dioxide from the atmosphere, allows concentrations to climb all winter, reaching a peak by early spring. During Northern Hemisphere spring and summer months, plants absorb a substantial amount of carbon dioxide through photosynthesis, thus removing it from the atmosphere and change the color to blue (low carbon dioxide concentrations). This three-dimensional view also shows the impact of fires in South America and Africa, which occur with a regular seasonal cycle. Carbon dioxide from fires can be transported over large distances, but the path is strongly influenced by large mountain ranges like the Andes. Near the top of the atmosphere, the blue color indicates air that last touched the Earth more than a year before. In this part of the atmosphere, called the stratosphere, carbon dioxide concentrations are lower because they haven’t been influenced by recent increases in emissions.
More information on the Fire Information for Resource Management System (FIRMS) is available at http://maps.geog.umd.edu/firms/.
The visualization shows fires detected in Africa from July 2002 through July 2011. Africa has more abundant burning than any other continent. MODIS observations have shown that some 70 percent of the world's fires occur in Africa alone. "It's incredibly satisfying to see such a long record of fires visualized," said Chris Justice, a scientist from the University of Maryland who leads NASA's effort to use MODIS data to study the world's fires. "It's not only exciting visually, but what you see here is a very good representation of the data scientists use to understand the global distribution of fires and to determine where and how fires are responding to climate change and population growth."
More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/.
More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/.
More information on the Fire Information for Resource Management System (FIRMS) is available at https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms.
More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/.
More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/.
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. Carbon dioxide is also released in early spring as soils begin to warm. Almost 10 percent of atmospheric carbon dioxide passes through soils each year.
After April, the northern hemisphere moves into late spring and summer and plants begin to grow, reaching a peak in the late summer. The process of plant photosynthesis removes carbon dioxide from the air. The animation shows how carbon dioxide is scrubbed out of the atmosphere by the large volume of new and growing vegetation. Following the peak in vegetation, the drawdown of atmospheric carbon dioxide due to photosynthesis becomes apparent, particularly over the boreal forests.
Note that there is roughly a three-month lag between the state of vegetation at Earth's surface and its effect on carbon dioxide in the middle troposphere.
Data like these give scientists a new opportunity to better understand the relationships between carbon dioxide in Earth's middle troposphere and the seasonal cycle of vegetation near the surface.
Creating the Animation
This animation was created with data taken from two NASA spaceborne instruments. The concentration of carbon dioxide data from the Atmospheric Infrared Sounder (AIRS), a weather and climate instrument that flies aboard NASA's Aqua spacecraft, is overlain on measurements of vegetation index from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, also on NASA's Aqua spacecraft, to better understand how photosynthesis and respiration influences the atmospheric carbon dioxide cycle over the globe. The animation runs from January through December and repeats. The AIRS tropospheric carbon dioxide seasonal cycle values were made by averaging AIRS data collected between 2003 and 2010, from which the annual carbon dioxide growth trend of 2 parts per million per year has been removed. For example, the data used for January 1 is actually an average of eight years of AIRS carbon dioxide data taken each year on January 1. The vegetation values were made using data averaged over a four-year period, from 2003 to 2006.
Further Detail
AIRS uses infrared technology to determine the concentration of atmospheric water vapor and several important trace gases as well as information about temperature and clouds. AIRS orbits Earth from pole-to-pole at an altitude of 438 miles (705 kilometers), measuring Earth's infrared spectrum in 3,278 channels spanning a wavelength range from 3.74 microns to 15.4 microns. Originally designed to improve weather forecasts, AIRS has improved operational five-day weather forecasts more than any other single instrument over the past decade. AIRS has also been found to be sensitive to atmospheric carbon dioxide in the middle troposphere, at an altitude of 5 to 10 kilometers or 3 to 6 miles. AIRS is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California Institute of Technology in Pasadena. For further information, access the AIRS project
The MODIS instrument is managed by NASA's Goddard Space Flight Center, Greenbelt, Md. For further information, access the MODIS project.
In May of 2013, these emissions pushed the monthly average CO2 concentrations above 400 parts per million (ppm)—a level that has not been reached during the past 800,000 years. These ever-increasing levels are raising concerns about greenhouse-gas-induced climate change.
This pair of images compares preliminary estimates of column-averaged volume mixing ratios of carbon dioxide, or XCO2, from OCO-2 glint observations over the ocean to those generated by the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5). The large scale features are quite similar, but there are subtle differences that are being studied to determine whether they indicate biases in these early OCO-2 XCO2 estimates or limitations of the model. Over time, these comparisons are expected to substantially improve the accuracy and reliability of both the measurements and the models.
Groundwater comes from the natural percolation of precipitation and other surface waters down through Earth's soil and rock, accumulating in aquifers - cavities and layers of porous rock, gravel, sand, or clay. In some subterranean reservoirs, the water may be thousands to millions of years old; in others, water levels decline and rise again naturally each year. Groundwater levels do not respond to changes in weather as rapidly as lakes, streams, and rivers do. So when groundwater is pumped for irrigation or other uses, recharge to the original levels can take months or years.
More than 109 cubic km (26 cubic miles) of groundwater disappeared from the region's aquifers between 2002 and 2008 — double the capacity of India's largest surface water reservoir, the Upper Wainganga, and triple that of Lake Mead, the largest manmade reservoir in the U.S.
The animation shown here depicts the change in groundwater levels as measured each November between 2002 to 2008.
Used in 2014 Calendar.