What NASA Knows from Decades of Earth System Observations

This color-coded map in Robinson projection displays a progression of changing global surface temperature anomalies. Normal temperatures are shown in white. Higher than normal temperatures are shown in red and lower than normal temperatures are shown in blue. Normal temperatures are calculated over the 30 year baseline period 1951-1980. The final frame represents the 5 year global temperature anomalies from 2018-2022. This data visualization shows the 2022 global surface temperature anomaly compared with the 1951-1980 average. This data visualization shows only the 2022 global surface temperature anomalies on a rotating globe to highlight the La Niña. 2022 was one of the warmest on record despite a third consecutive year of La Niña conditions in the tropical Pacific Ocean. NASA scientists estimate that La Niña’s cooling influence may have lowered global temperatures about 0.11 degrees Fahrenheit from what the average would have been under more typical ocean conditions. Colortable is both degrees fahrenheit and degrees celsius. This image is the single year 2022 GISS temperature anomaly as compared with the 1951-1980 average. This version does not have any titles or text overlays, except for the corresponding colorbar. This frame sequence of color-coded global temperature anomalies in robinson projection display a progression of changing global surface temperatures anomalies in even degrees Fahrenheit. The first frame in this sequence represents the data from 1880-1884. The second frame represents 1881-1885, ...and the last frame represents 2018-2022. Higher than normal temperatures are shown in red and lower than normal are shown in blue. Normal temperatures are the average over the 30 year baseline period 1951-1980. This sequence of images are the corresponding date overlays for the 5 year rolling averages used in the first visualization on this page. This frame sequence of color-coded global temperature anomalies in degrees celsius is designed to be displayed on the Science on a Sphere projection system. Each image represents a unique 5 year rolling time period with no fades between datasets. Frame 1884 represents data from 1880-1884, frame 1885 represents data from 1881-1885,... frame 2022 represents data from 2018-2022. Higher than normal temperatures are shown in red and lower than normal are shown in blue. Normal temperatures are the average over the 30 year baseline period 1951-1980. This is the colorbar for the Science on a Sphere frameset above. It is in degrees celsius.

This special version of the 2021 Hurricane Season data visualization uses all the below layers to show the entire 2021 Hurricane Season, but elements of it were sped up in post production to accelerate the data when no hurricanes are present. This provides the viewer with a more compact experience that focuses exclusively on the hurricanes. This data visualization shows the complete 2021 hurricane season beginning on May 1, 2021 throught November 30, 2021. Time moves at a constant rate throughout this visualization showing both the hurricanes and the down times between the hurricanes. After the last hurricane of the season, Wanda, is displayed, we dissolve in all the storms for the 2021 Hurricane season to show all their paths and strengths together on one map. Hurricane tracks for the 2021 season covering May 1 through November 30, 2021 with time moving at a constant rate. Cloud composite covering May 1 through November 30, 2021 with time moving at a constant rate. Surface Precipitation from May 1 through November 30, 2021 with time moving at a constant rate. Areas in green and yellow are areas of relatively light rain. Oranges and reds depict areas of intense rainfall. Color bar for frozen precipitation rates (ie, snow rates). Shades of cyan represent low amounts of frozen precipitation, whereas shades of purple represent high amounts of precipitation. Color bar for liquid precipitation rates (ie, rain rates). Shades of green represent low amounts of liquid precipitation, whereas shades of red represent high amounts of precipitation. Sea Surface Temperature (SST) from May 1 through November 30, 2021 with time moving at a constant rate. Sea Surface Temperature colorbar focusing primarily on temperatures between 20 degrees Celsius to 30 Celsius. Final still frame overlay showing all the hurricanes of the 2021 season together. This visualization shows the hurricanes and tropical storms of 2021 as seen by NASA’s Integrated Multi-satellitE Retrievals for GPM (IMERG) - a data product combining precipitation observations from infrared and microwave satellite sensors united by the GPM Core Observatory. IMERG provides near real-time half-hourly precipitation estimates at ~10km resolution for the entire globe, helping researchers better understand Earth’s water cycle and extreme weather events, with applications for disaster management, tracking disease, resource management, energy production and food security. IMERG rain rates (in mm/hr) are laid under infrared cloud data from the NOAA Climate Prediction Center (CPC) Cloud Composite dataset together with storm tracks from the NOAA National Hurricane Center (NHC) Automated Tropical Cyclone Forecasting (ATCF) model. Sea surface temperatures (SST) are also shown over the oceans, derived from the NASA Multi-sensor Ultra-high Resolution (MUR) dataset, which combines data from multiple geostationary and orbiting satellites. Sea surface temperatures play an important role in hurricane formation and development, with warmer temperatures linked to more intense storms. Related pages

Data visualization in wide aspect ratio and 9600x3240 resolution, featuring volumetric carbon dioxide on a global scale for the period June 1, 2020 - July 31, 2021. This set of frames can be shown on 5x3 hyperwalls and wide aspect ratio displays. Lower resolution movies are provided for preview. This low resolution movie includes lines to illustrate the extents of the 5x3 hyperwall screens. This movie is provided only for preview. This webpage provides a wide aspect ratio version of: Global Carbon Dioxide 2020-2021, released on November 2, 2021. This version has been created for wide aspect ratio display systems with resolution up to 9600x3240. It is recommended to use content from this version for display systems with 16:9 aspect ratio. NASA’s Orbiting Carbon Observatory, 2 (OCO-2) provides the most complete dataset tracking the concentration of atmospheric carbon dioxide (CO2), the main driver of climate change. Every day, OCO-2 measures sunlight reflected from Earth’s surface to infer the dry-air column-averaged CO2 mixing ratio and provides around 100,000 cloud-free observations. Despite these advances, OCO-2 data contain many gaps where sunlight is not present or where clouds or aerosols are too thick to retrieve CO2 data. In order to fill gaps and provide science and applications users a spatially complete product, OCO-2 data are assimilated into NASA’s Goddard Earth Observing System (GEOS), a complex modeling and data assimilation system used for studying the Earth’s weather and climate. GEOS is also informed by satellite observations of nighttime lights and vegetation greenness along with about 1 million weather observations collected every hour. These data help scientists infer CO2 mixing ratios even when a direct OCO-2 observation is not present and provide additional information on the altitude of CO2 plumes that the satellite is not able to see. Together, OCO-2 and GEOS create one of the most complete pictures of CO2. The visualization featured on this page shows the atmosphere in three dimensions and highlights the accumulation of CO2 during a single calendar year. Every year, the world’s vegetation and oceans absorb about half of human CO2 emissions, providing an incredibly valuable service that has mitigated the rate of accumulation of greenhouse gases in the atmosphere. However, around 2.5 parts per million remain in the atmosphere every year causing a steady upward march in concentrations that scientists have tracked since the 1950s at surface stations. The volumetric visualization starts in June 2020, showing all of the model’s values of global CO2. All 3d cells of the model are opaque, revealing a solid brick of data. During the month of June 2020, the higher values of CO2 coalesce around the equatorial belt. By mid-July 2020 the visualization reduces the opacity of lower CO2 values between 385 parts-per-millon (ppm) and 405 ppm in the atmosphere making them transparent. These lower values tend to be higher up in the atmosphere. By doing this, the higher CO2 concentrations, which are closer to the ground, are highlighted revealing the seasonal movement of high CO2 at a global scale. During the months of June-September (summer months for northern hemisphere), global CO2 concentrations tend to be lowest because northern hemisphere plants actively absorb CO2 from the atmosphere via photosynthesis. During northern hemisphere fall and winter months, much of this CO2 is re-released to the atmosphere due to respiration and can be seen building up. By June and July 2021, plants again draw CO2 out of the atmosphere, but notably higher concentrations remain in contrast to the nearly transparent colors of the previous year. The diurnal rhythm of CO2 is apparent over our planet's largest forests, such as the Amazon rainforest in South America and the Congo rainforest in Central Africa. The fast-paced pulse in those rainforests is due to the day-night cycle; plants absorb CO2 during the day via photosynthesis when the sun is out, then stop absorbing CO2 at night. In addition to highlighting the buildup of atmospheric CO2, this visualization shows how interconnected the world’s greenhouse gas problem is. NASA’s unique combination of observations and models plays a critical role in helping scientists track increases in CO2 as they happen to better understand their climate impact.Data Sources:Volumetric Carbon Dioxide extracted from NASA's Goddard Earth Observing System (GEOS) model, which is produced by the Global Modeling and Assimilation Office. The visualization featured on this page utilizes 3-hourly data for the period June 1, 2020-July 31, 2021.Blue Marble: Next Generation was produced by Reto Stöckli, NASA Earth Observatory (NASA Goddard Space Flight Center). Citation: Reto Stöckli, Eric Vermote, Nazmi Saleous, Robert Simmon and David Herring. The Blue Marble Next Generation – A true color earth dataset including seasonal dynamics from MODIS, October 17, 2005. The visualization on this page utilizes monthly Blue Marble data to map the water and land bodies around the globe and show seasonal changes.Sea ice for the Arctic and Antarctic regions, provided by the Japan Aerospace Exploration Agency (JAXA), by utilizing GCOMP-W/AMSR2 10 km Level 3 daily Sea Ice Concentration (SIC) and GCOMP-W/AMSR2 10 km Level 3 daily 89 GHz Brightness Temperature (BT) data for the period June 1, 2020-July 31, 2021.Global 30 Arc-Second Elevation (GTOPO 30) from U.S. Geological Survey (USGS). GTOPO30 is a global raster digital elevation model (DEM) with a horizontal grid spacing of 30 arc seconds (approximately 1 kilometer). GTOPO30 was derived from several raster and vector sources of topographic information. The data-driven visualization featured on this page utilizes the GTOPO30 model to represent the three-dimensional features of over land terrain and submarine topography world-wide. doi: 10.5066/F7DF6PQS. Related pages

This color-coded map in Robinson projection displays a progression of changing global surface temperature anomalies. Normal temperatures are shown in white. Higher than normal temperatures are shown in red and lower than normal temperatures are shown in blue. Normal temperatures are calculated over the 30 year baseline period 1951-1980. The final frame represents the 5 year global temperature anomalies from 2017-2021. Scale in degrees Fahrenheit. This data visualization shows the 2021 global surface temperature anomalies on a rotating globe to highlight the La Niña. La Niña has developed and is expected to last into early 2022. Despite the cooling influence of this naturally occurring climate phenomenon, temperatures in many parts of the world are above average. The year 2000 also saw a La Niña event of similar strength to that in 2021, but 2021 global temperatures was more than 0.75 degrees Fahrenheit hotter than 2000. This color-coded map in Robinson projection displays a progression of changing global surface temperature anomalies. Normal temperatures are shown in white. Higher than normal temperatures are shown in red and lower than normal temperatures are shown in blue. Normal temperatures are calculated over the 30 year baseline period 1951-1980. The final frame represents the 5 year global temperature anomalies from 2017-2021. Scale in degrees Celsius. This frame sequence is the corresponding date range for each frame in the sequence. Degrees Fahrenheit Colorbar Degrees Celsius Colorbar This frame sequence of color-coded global temperature anomalies in robinson projection display a progression of changing global surface temperatures anomalies in Fahrenheit. The first frame in this sequence represents the data from 1880-1884. The second frame represents 1881-1885, ...and the last frame represents 2017-2021. Higher than normal temperatures are shown in red and lower than normal are shown in blue. Normal temperatures are the average over the 30 year baseline period 1951-1980. This frame sequence of color-coded global temperature anomalies in degrees celsius is designed to be displayed on the Science on a Sphere projection system. Each image represents a unique 5 year rolling time period with no fades between datasets. Frame 1884 represents data from 1880-1884, frame 1885 represents data from 1881-1885,... frame 2021 represents data from 2017-2021. Higher than normal temperatures are shown in red and lower than normal are shown in blue. Normal temperatures are the average over the 30 year baseline period 1951-1980. This is the colorbar for the Science on a Sphere frameset above. It is in degrees celsius. Earth’s global average surface temperature in 2021 tied with 2018 as the sixth warmest on record, according to independent analyses done by NASA and NOAA. Continuing the planet’s long-term warming trend, global temperatures in 2021 were 1.5 degrees Fahrenheit (or 0.85 degrees Celsius) above the average for NASA’s baseline period, according to scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York.Collectively, the past eight years are the top eight warmest years since modern record keeping began in 1880. This annual temperature data makes up the global temperature record – and it’s how scientists know that the planet is warming.GISS is a NASA laboratory managed by the Earth Sciences Division of the agency’s Goddard Space Flight Center in Greenbelt, Maryland. The laboratory is affiliated with Columbia University’s Earth Institute and School of Engineering and Applied Science in New York.For more information about NASA’s Earth science missions, visit: https://www.nasa.gov/earth Related pages

Data visualization featuring volumetric carbon dioxide on a global scale for the period June 1, 2020 - July 31, 2021.Coming soon to our YouTube channel. NASA’s Orbiting Carbon Observatory, 2 (OCO-2) provides the most complete dataset tracking the concentration of atmospheric carbon dioxide (CO2), the main driver of climate change. Every day, OCO-2 measures sunlight reflected from Earth’s surface to infer the dry-air column-averaged CO2 mixing ratio and provides around 100,000 cloud-free observations. Despite these advances, OCO-2 data contain many gaps where sunlight is not present or where clouds or aerosols are too thick to retrieve CO2 data. In order to fill gaps and provide science and applications users a spatially complete product, OCO-2 data are assimilated into NASA’s Goddard Earth Observing System (GEOS), a complex modeling and data assimilation system used for studying the Earth’s weather and climate. GEOS is also informed by satellite observations of nighttime lights and vegetation greenness along with about 1 million weather observations collected every hour. These data help scientists infer CO2 mixing ratios even when a direct OCO-2 observation is not present and provide additional information on the altitude of CO2 plumes that the satellite is not able to see. Together, OCO-2 and GEOS create one of the most complete pictures of CO2. The visualization featured on this page shows the atmosphere in three dimensions and highlights the accumulation of CO2 during a single calendar year. Every year, the world’s vegetation and oceans absorb about half of human CO2 emissions, providing an incredibly valuable service that has mitigated the rate of accumulation of greenhouse gases in the atmosphere. However, around 2.5 parts per million remain in the atmosphere every year causing a steady upward march in concentrations that scientists have tracked since the 1950s at surface stations. The volumetric visualization starts in June 2020, showing all of the model’s values of global CO2. All 3d cells of the model are opaque, revealing a solid brick of data. During the month of June 2020, the higher values of CO2 coalesce around the equatorial belt. By mid-July 2020 the visualization reduces the opacity of lower CO2 values between 385 parts-per-millon (ppm) and 405 ppm in the atmosphere making them transparent. These lower values tend to be higher up in the atmosphere. By doing this, the higher CO2 concentrations, which are closer to the ground, are highlighted revealing the seasonal movement of high CO2 at a global scale. During the months of June-September (summer months for northern hemisphere), global CO2 concentrations tend to be lowest because northern hemisphere plants actively absorb CO2 from the atmosphere via photosynthesis. During northern hemisphere fall and winter months, much of this CO2 is re-released to the atmosphere due to respiration and can be seen building up. By June and July 2021, plants again draw CO2 out of the atmosphere, but notably higher concentrations remain in contrast to the nearly transparent colors of the previous year. The diurnal rhythm of CO2 is apparent over our planet's largest forests, such as the Amazon rainforest in South America and the Congo rainforest in Central Africa. The fast-paced pulse in those rainforests is due to the day-night cycle; plants absorb CO2 during the day via photosynthesis when the sun is out, then stop absorbing CO2 at night. In addition to highlighting the buildup of atmospheric CO2, this visualization shows how interconnected the world’s greenhouse gas problem is. NASA’s unique combination of observations and models plays a critical role in helping scientists track increases in CO2 as they happen to better understand their climate impact.This visualization was created specifically to support a series of talks from NASA scientists for the 2021 United Nations Climate Change Conference (COP26), Glasgow, UK, 31 October-12 November 2021.Data Sources:Volumetric Carbon Dioxide extracted from NASA's Goddard Earth Observing System (GEOS) model, which is produced by the Global Modeling and Assimilation Office. The visualization featured on this page utilizes 3-hourly data for the period June 1, 2020-July 31, 2021.Blue Marble: Next Generation was produced by Reto Stöckli, NASA Earth Observatory (NASA Goddard Space Flight Center). Citation: Reto Stöckli, Eric Vermote, Nazmi Saleous, Robert Simmon and David Herring. The Blue Marble Next Generation – A true color earth dataset including seasonal dynamics from MODIS, October 17, 2005. The visualization on this page utilizes monthly Blue Marble data to map the water and land bodies around the globe and show seasonal changes.Sea ice for the Arctic and Antarctic regions, provided by the Japan Aerospace Exploration Agency (JAXA), by utilizing GCOMP-W/AMSR2 10 km Level 3 daily Sea Ice Concentration (SIC) and GCOMP-W/AMSR2 10 km Level 3 daily 89 GHz Brightness Temperature (BT) data for the period June 1, 2020-July 31, 2021.Global 30 Arc-Second Elevation (GTOPO 30) from U.S. Geological Survey (USGS). GTOPO30 is a global raster digital elevation model (DEM) with a horizontal grid spacing of 30 arc seconds (approximately 1 kilometer). GTOPO30 was derived from several raster and vector sources of topographic information. The data-driven visualization featured on this page utilizes the GTOPO30 model to represent the three-dimensional features of over land terrain and submarine topography world-wide. doi: 10.5066/F7DF6PQS. Related pages

This data visualization shows hurricane tracks over clouds over precipitation over sea surface temperatures from May 1 through September 30th, 2021. This presentation was created for the COP 26 Conference. Hurricane tracks for the 2021 season covering May 1 through September 30th. Global Cloud Composite covering May 1 through September 30th, 2021. Surface Precipitation from May 1 through September 30th, 2021. Color bar for frozen precipitation rates (ie, snow rates). Shades of cyan represent low amounts of frozen precipitation, whereas shades of purple represent high amounts of precipitation. Color bar for liquid precipitation rates (ie, rain rates). Shades of green represent low amounts of liquid precipitation, whereas shades of red represent high amounts of precipitation. Sea Surface Temperatures from May 1 through September 30th, 2021. Sea Surface Temperature colorbar focusing primarily on temperatures between 20 degrees Celsius to 30 Celsius. This visualization shows the hurricanes and tropical storms of 2021 as seen by NASA’s Integrated Multi-satellitE Retrievals for GPM (IMERG) - a data product combining precipitation observations from infrared and microwave satellite sensors united by the GPM Core Observatory. IMERG provides near real-time half-hourly precipitation estimates at ~10km resolution for the entire globe, helping researchers better understand Earth’s water cycle and extreme weather events, with applications for disaster management, tracking disease, resource management, energy production and food security. IMERG rain rates (in mm/hr) are laid under infrared cloud data from the NOAA Climate Prediction Center (CPC) Cloud Composite dataset together with storm tracks from the NOAA National Hurricane Center (NHC) Automated Tropical Cyclone Forecasting (ATCF) model. Sea surface temperatures (SST) are also shown over the oceans, derived from the NASA Multi-sensor Ultra-high Resolution (MUR) dataset, which combines data from multiple geostationary and orbiting satellites. Sea surface temperatures play an important role in hurricane formation and development, with warmer temperatures linked to more intense storms. This data visualization was done for the United Nations Climate Change Conference - Conference of the Parties (COP) 26. The 2021 hurricane season officially ends November 30th. This data visualization will be periodically updated until that date. Related pages

Data visualization of predicted Wheat yields through the end of this centaury based on an ensemble of crop and climate models. Visualization of future wheat yield projections presented in an equatorial cylindrical equidistant projection for use in Science on a Sphere type displays. color bar for the wheat yield visualization Thumbnail images for use in the Science on a Sphere GUI. Climate change will affect agricultural production worldwide. Average global crop yields for maize, or corn, may see a decrease of 24% by late century, if current climate change trends continue. Wheat, in contrast, may see an uptick in crop yields by about 17%. The change in yields is due to the projected increases in temperature, shifts in rainfall patterns and elevated surface carbon dioxide concentrations due to human-caused greenhouse gas emissions, making it more difficult to grow maize in the tropics and expanding wheat’s growing range. Wheat, which grows best in temperate climates, may see a broader area where it can be grown in places such as the northern United States and Canada, North China Plains, Central Asia, southern Australia and East Africa as temperatures rise, but these gains may level off mid-century.Temperature alone is not the only factor the models consider when simulating future crop yields. Higher levels of carbon dioxide in the atmosphere have a positive effect on photosynthesis and water retention, more so for wheat than maize, which are accounted for better in the new generation of models. Rising global temperatures are linked with changes in rainfall patterns and the frequency and duration of heat waves and droughts. They also affect the length of growing seasons and accelerate crop maturity. To arrive at their projections, the research team used two sets of models. First, they used climate model simulations from the international Climate Model Intercomparison Project-Phase 6 (CMIP6). Each of the five climate models runs its own unique response of Earth’s atmosphere to greenhouse gas emission scenarios through 2100. Then the research team used the climate model simulations as inputs for 12 state-of-the-art global crop models that are part of the Agricultural Model Intercomparison Project (AgMIP), creating in total about 240 global climate-crop model simulations for each crop. By using multiple climate and crop models in various combinations, the researchers were able to be more confident in their results.Science on a Sphere ContentThe following section contains assets designed for Science on a Sphere and related displays.SOS playlist file: playlist.sos SOS label file: labels.txt Related pages

Data visualization of predicted maize yields through the end of this centaury based on an ensemble of crop and climate models. Maize yield projections formatted for Science On a Sphere color bar for maize yield visualization thumbnail images for Science On a Sphere Climate change will affect agricultural production worldwide. Average global crop yields for maize, or corn, may see a decrease of 24% by late century, if current climate change trends continue. Wheat, in contrast, may see an uptick in crop yields by about 17%. The change in yields is due to the projected increases in temperature, shifts in rainfall patterns and elevated surface carbon dioxide concentrations due to human-caused greenhouse gas emissions, making it more difficult to grow maize in the tropics and expanding wheat’s growing range.Maize is grown all over the world, and large quantities are produced in countries nearer the equator. North and Central America, West Africa, Central Asia, Brazil and China will potentially see their maize yields decline in the coming years and beyond as average temperatures rise across these breadbasket regions, putting more stress on the plants. Temperature alone is not the only factor the models consider when simulating future crop yields. Higher levels of carbon dioxide in the atmosphere have a positive effect on photosynthesis and water retention, more so for wheat than maize, which are accounted for better in the new generation of models. Rising global temperatures are linked with changes in rainfall patterns and the frequency and duration of heat waves and droughts. They also affect the length of growing seasons and accelerate crop maturity.To arrive at their projections, the research team used two sets of models. First, they used climate model simulations from the international Climate Model Intercomparison Project-Phase 6 (CMIP6). Each of the five climate models runs its own unique response of Earth’s atmosphere to greenhouse gas emission scenarios through 2100.Then the research team used the climate model simulations as inputs for 12 state-of-the-art global crop models that are part of the Agricultural Model Intercomparison Project (AgMIP), creating in total about 240 global climate-crop model simulations for each crop. By using multiple climate and crop models in various combinations, the researchers were able to be more confident in their results.Science On a Sphere ContentThe following section contains assets designed for Science On a Sphere and related displays.SOS playlist file: playlist.sos SOS label file: labels.txt Related pages

The Global Precipitation Meaurement (GPM) mission produces NASA's most comprehensive estimate of global rain and snowfall, the Integrated Multi-satellite Retrievals for GPM, or IMERG. IMERG is largely based on data from the GPM constellation - a group of satellites independently operated by many agencies that pool their data for global precipitation estimates. These satellites currently include the GPM Core Observatory, other U.S. civilian satellites (Aqua, NOAA-19, NOAA-20, Suomi NPP), U.S. defense satellites (DMSP F-16, DMSP F-17, DMSP- F18), and international agency satellites (GCOM-W1, Metop-B, Metop-C, and MeghaTropiques). The IMERG dataset starts in June 2000, providing a sufficiently long record that seasonal/regional averages, or climatology, can be computed with reasonable confidence. By comparing the progression of the observed precipitation with climatology, we can generate maps of showing how much observations depart from normal. In the animation, each day's variation from the average precipitation is added to the map, then allowed to gradually fade away over three months so that time changes in the larger-scale patterns are easier to see. Researchers sometimes refer to these deviations from the climatology as "precipitation anomalies". An animation of the most recent variation in global precipitation data from IMERG. An image of the most currently available global precipitation variation from IMERG. Related pages

The mass of the Antarctic ice sheet has changed over the last decades. Research based on observations from the Gravity Recovery and Climate Experiment (GRACE) satellites (2002-2017) and GRACE Follow-On (since 2018 - ) indicates that between 2002 and 2020, Antarctica shed approximately 150 gigatons of ice per year, causing global sea level to rise by 0.4 millimeters per year. These images, created from GRACE and GRACE-FO data, show changes in Antarctic ice mass since 2002. Orange and red shades indicate areas that lost ice mass, while light blue shades indicate areas that gained ice mass. White indicates areas where there has been very little or no change in ice mass since 2002. Areas in East Antarctica experienced modest amounts of mass gain due to increased snow accumulation. However, this gain is more than offset by significant ice mass loss on the West Antarctic Ice Sheet (dark red) over the 19-year period. Floating ice shelves whose mass change GRACE & GRACE-FO do not measure are colored gray. The average flow lines (grey; created from satellite radar interferometry) of Antarctica’s ice converge into the locations of prominent outlet glaciers, and coincide with areas of highest mass loss (i.e., Pine Island and Thwaites glaciers in West-Antarctica). This supports other observations that warming ocean waters around Antarctica play a key role in contemporary ice mass loss. Ice sheet mass loss with superimposed ice sheet velocity streamlines. Ice sheet mass loss on a black background. Antarctic gravity through 2020, v1 For More InformationSee [https://grace.jpl.nasa.gov](https://grace.jpl.nasa.gov) Related pages

The mass of the Greenland ice sheet has rapidly declined in the last several years due to surface melting and iceberg calving. Research based on observations from the Gravity Recovery and Climate Experiment (GRACE) satellites (2002-2017) and GRACE Follow-On (since 2018 - ) indicates that between 2002 and 2020, Greenland shed approximately 280 gigatons of ice per year, causing global sea level to rise by 0.03 inches (0.8 millimeters) per year. These images, created from GRACE and GRACE-FO data, show changes in Greenland ice mass since 2002. Orange and red shades indicate areas that lost ice mass, while light blue shades indicate areas that gained ice mass. White indicates areas where there has been very little or no change in ice mass since 2002. In general, higher-elevation areas near the center of Greenland experienced little to no change, while lower-elevation and coastal areas experienced over 16.4 feet (5 meters) of ice mass loss (expressed in equivalent-water-height; dark red) over this 19-year period. The largest mass decreases occurred along the West Greenland coast. The average flow lines (grey; created from satellite radar interferometry) of Greenland’s ice converge into the locations of prominent outlet glaciers, and coincide with areas of highest mass loss. This supports other observations that warming ocean waters around Greenland play a key role in contemporary ice mass loss. Greenland Ice Loss as measured by GRACE and GRACE-FO. For More InformationSee [https://grace.jpl.nasa.gov](https://grace.jpl.nasa.gov) Related pages

This color-coded map in Robinson projection displays a progression of changing global surface temperature anomalies. Normal temperatures are the average over the 30 year baseline period 1951-1980. Higher than normal temperatures are shown in red and lower than normal temperatures are shown in blue. The final frame represents the 5 year global temperature anomalies from 2016-2020. Scale in degrees Celsius. This color-coded map in Robinson projection displays a progression of changing global surface temperature anomalies. Normal temperatures are the average over the 30 year baseline period 1951-1980. Higher than normal temperatures are shown in red and lower than normal temperatures are shown in blue. The final frame represents the 5 year global temperature anomalies from 2016-2020. Scale in degrees Fahrenheit. This data visualization places the most recent time step, 2016-2020, of our global surface temperature anomalies on a rotating globe. Normal temperatures are the average over the 30 year baseline period 1951-1980. Higher than normal temperatures are shown in red and lower than normal temperatures are shown in blue. Scale is in degrees Fahrenheit. THe Earth's topography is exaggerated by 10x. This frame sequence is the corresponding date range for each frame in the sequence. This 136 frame sequence of color-coded global temperature anomalies in robinson projection display a progression of changing global surface temperatures anomalies in Fahrenheit. The first frame in this sequence represents the data from 1880-1884. The second frame represents 1881-1885, ...and the last frame represents 2016-2020. Higher than normal temperatures are shown in red and lower than normal are shown in blue. Normal temperatures are the average over the 30 year baseline period 1951-1980. Degrees Fahrenheit Colorbar Degrees Celsius Colorbar This frame sequence of color-coded global temperature anomalies in degrees celsius is designed to be displayed on the Science on a Sphere projection system. Each image represents a unique 5 year rolling time period with no fades between datasets. Frame 1884 represents data from 1880-1884, frame 1885 represents data from 1881-1885,... frame 2020 represents data from 2016-2020. Higher than normal temperatures are shown in red and lower than normal are shown in blue. Normal temperatures are the average over the 30 year baseline period 1951-1980. Degrees Celsius horizontal colorbar 2020 Tied for Warmest Year on Record, NASA Analysis ShowsEarth’s global average surface temperature in 2020 tied with 2016 as the warmest year on record, according to an analysis by NASA. Continuing the planet’s long-term warming trend, the year’s globally averaged temperature was 1.84 degrees Fahrenheit (1.02 degrees Celsius) warmer than the baseline 1951-1980 mean, according to scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York. 2020 edged out 2016 by a very small amount, within the margin of error of the analysis, making the years effectively tied for the warmest year on record.“The last seven years have been the warmest seven years on record, typifying the ongoing and dramatic warming trend,” said GISS Director Gavin Schmidt. “Whether one year is a record or not is not really that important – the important things are long-term trends. With these trends, and as the human impact on the climate increases, we have to expect that records will continue to be broken.”A Warming, Changing WorldTracking global temperature trends provides a critical indicator of the impact of human activities – specifically, greenhouse gas emissions – on our planet. Earth's average temperature has risen more than 2 degrees Fahrenheit (1.2 degrees Celsius) since the late 19th century. Rising temperatures are causing phenomena such as loss of sea ice and ice sheet mass, sea level rise, longer and more intense heat waves, and shifts in plant and animal habitats. Understanding such long-term climate trends is essential for the safety and quality of human life, allowing humans to adapt to the changing environment in ways such as planting different crops, managing our water resources and preparing for extreme weather events.Land, Sea, Air and SpaceNASA’s analysis incorporates surface temperature measurements from more than 26,000 weather stations and thousands of ship- and buoy-based observations of sea surface temperatures. These raw measurements are analyzed using an algorithm that considers the varied spacing of temperature stations around the globe and urban heating effects that could skew the conclusions if not taken into account. The result of these calculations is an estimate of the global average temperature difference from a baseline period of 1951 to 1980.NASA measures Earth's vital signs from land, air, and space with a fleet of satellites, as well as airborne and ground-based observation campaigns. The satellite surface temperature record from the Atmospheric Infrared Sounder (AIRS) instrument aboard NASA’s Aura satellite confirms the GISTEMP results of the past seven years being the warmest on record. Satellite measurements of air temperature, sea surface temperature, and sea levels, as well as other space-based observations, also reflect a warming, changing world. The agency develops new ways to observe and study Earth's interconnected natural systems with long-term data records and computer analysis tools to better see how our planet is changing. NASA shares this unique knowledge with the global community and works with institutions in the United States and around the world that contribute to understanding and protecting our home planet. NASA’s full surface temperature data set – and the complete methodology used to make the temperature calculation – are available at: https://data.giss.nasa.gov/gistempGISS is a NASA laboratory managed by the Earth Sciences Division of the agency’s Goddard Space Flight Center in Greenbelt, Maryland. The laboratory is affiliated with Columbia University’s Earth Institute and School of Engineering and Applied Science in New York.For more information about NASA’s Earth science missions, visit: https://www.nasa.gov/earth Related pages

Sea surface height change from 1992 to 2019, with colorbar Sea surface height change from 1992 to 2019, no colorbar Sea surface height change in the Pacific region from 1992 to 2019, with colorbar Sea surface height change in the Pacific region from 1992 to 2019, no colorbar Sea surface height change from 1992 to 2019, with colorbar, flat projection Sea surface height change from 1992 to 2019, no colorbar, flat projection Colorbar This visualization shows total sea level change between 1992 and 2019, based on data collected from the TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3 satellites. Blue regions are where sea level has gone down, and orange/red regions are where sea level has gone up. Since 1992, seas around the world have risen an average of nearly 6 inches. The color range for this visualization is -15 cm to +15 cm (-5.9 inches to +5.9 inches), though measured data extends above and below 15 cm (5.9 inches). This particular range was chosen to highlight variations in sea level change. Related pages

Ocean flows off the East coast of the United StatesThis video is also available on our YouTube channel. Ocean flows off the west coast of the United StatesThis video is also available on our YouTube channel. Ocean flows around southeast AsiaThis video is also available on our YouTube channel. Ocean fows in the Altantic oceanThis video is also available on our YouTube channel. Ocean flows in the Pacific oceanThis video is also available on our YouTube channel. Ocean depth colorbar from white at the surface to cyan at 2000 meters deep to blue at 4000 meters deep This is a collection of visualizations of ocean flows created in support of NASA's 2020 sea level rise campaign. There are 5 regions of focus: • central Pacific • central Atlantic • southeast Asia • US east coast • US west coastThe span of time shown in each visualization is about 10 months. The data used for each visualization comes from the ECCO-2 ocean model using data from 2010-01-15T00:12:58 to 2010-11-22T11:10:31. Each frame of the animation is approximately 2 hours apart. Related pages

This 3D volumetric visualization shows a global view of the methane emission and transport between December 1, 2017 and November 30, 2018. This visualizaion of the rotating global view is designed to be played in a continuous loop.This video is also available on our YouTube channel. The global methane visualization alone in OpenExr format.(Note: This frame set was converted to the sRGB color space on 6/16/2020) A high resolution still of the global methane on January 26, 2018 with transparency. The colorbar with transparency The date sequence alone in OpenExr format.(Note: This frame set was converted to the sRGB color space on 6/16/2020) The background sequence alone in OpenExr format.(Note: This frame set was converted to the sRGB color space on 6/16/2020) The overlay with the colorbar and the exaggeration. THis version shows the volumetric global methane emission and transport between Dec 1 and Nov 30. It is designed to show methane emissions greater than 1800 parts per billion. Methane is a powerful greenhouse gas that traps heat 28 times more effectively than carbon dioxide over a 100-year timescale. Concentrations of methane have increased by more than 150% since industrial activities and intensive agriculture began. After carbon dioxide, methane is responsible for about 20% of climate change in the twentieth century. Methane is produced under conditions where little to no oxygen is available. About 30% of methane emissions are produced by wetlands, including ponds, lakes and rivers. Another 20% is produced by agriculture, due to a combination of livestock, waste management and rice cultivation. Activities related to oil, gas, and coal extraction release an additional 30%. The remainder of methane emissions come from minor sources such as wildfire, biomass burning, permafrost, termites, dams, and the ocean. Scientists around the world are working to better understand the budget of methane with the ultimate goals of reducing greenhouse gas emissions and improving prediction of environmental change. For additional information, see the Global Methane Budget.The NASA SVS visualization presented here shows the complex patterns of methane emissions produced around the globe and throughout the year from the different sources described above. The visualization was created using output from the Global Modeling and Assimilation Office, GMAO, GEOS modeling system, developed and maintained by scientists at NASA. Wetland emissions were estimated by the LPJ-wsl dynamic global vegetation model, which simulates the temperature and moisture dependent methane emission processes using a variety of satellite data to determine what parts of the globe are covered by wetlands. Other methane emission sources come from inventories of human activity. The height of Earth’s atmosphere and topography have been vertically exaggerated and appear approximately 50-times higher than normal in order to show the complexity of the atmospheric flow while the bathymetry below sea level is exaggerated by 11.6-times. Outflow from different regions result from different sources. For example, high methane concentrations over South America are driven by wetland emissions while over Asia, emissions reflect a mix of agricultural and industrial activities. Emissions are transported through the atmosphere as weather systems move and mix methane around the globe. In the atmosphere, methane is eventually removed by reactive gases that convert it to carbon dioxide. Understanding the three-dimensional distribution of methane is important for NASA scientists planning observations that sample the atmosphere in very different ways. Satellites like GeoCarb, a planned geostationary mission to observe both carbon dioxide and methane, look down from space and will estimate the total number of methane molecules in a column of air. Aircraft, like those launched during NASA’s Arctic Boreal Vulnerability Experiment (ABOVE) sample the atmosphere along very specific flight lines, providing additional details about the processes controlling methane emissions at high latitudes. Atmospheric models help place these different types of measurements in context so that scientists can refine estimates of sources and sinks, understand the processes controlling them and reduce uncertainty in future projections of carbon-climate feedbacks. Related pages

NASA's Earth Observing Fleet (December 2019) This animation shows the orbits of NASA's fleet of Earth observing spacecraft that are considered operational as of December 2019. The clouds used in this version are from a high resolution GEOS model run at 10 minute time steps interpolated down to the per-frame level.Changes to this version include: removal of Jason-2 and Jason-3 and the camera does not show DSCOVR within its view.Spacecraft included:AquaAuraCALIPSO: Cloud-Aerosol Lidar and Infrared Pathfinder Satellite ObservationCYGNSS-1: Cyclone Global Navigation Satellite System 1CYGNSS-2: Cyclone Global Navigation Satellite System 2CYGNSS-3: Cyclone Global Navigation Satellite System 3CYGNSS-4: Cyclone Global Navigation Satellite System 4CYNGSS-5: Cyclone Global Navigation Satellite System 5CYGNSS-6: Cyclone Global Navigation Satellite System 6CYGNSS-7: Cyclone Global Navigation Satellite System 7CYGNSS-8: Cyclone Global Navigation Satellite System 8CloudsatGPM: Global Precipitation MeasurementGRACE-FO-1: Gravity Recovery and Climate Experiment Follow On-1GRACE-FO-2: Gravity Recovery and Climate Experiment Follow On-2ICESat-2ISS: International Space StationLandsat 7Landsat 8OCO-2: Orbiting Carbon Observatory-2SMAP: Soil Moisture Passive ActiveSORCE: Solar Radiation and Climate ExperimentSuomi NPP: Suomi National Polar-orbiting PartnershipTerra Related pages

Music: Motion Blur by Sam Dodson, Spring Into Life by Oliver Worth, and Critical Pathway by Rik Carter. Complete transcript available. Droughts can create ideal conditions for wildfires. Dry trees and vegetation provide fuel. Low soil and air moisture make it easier for fires to spread quickly. In these conditions, a spark from lightning, electrical failures, human error or planned fires can quickly get out of control. As Earth’s climate warms and precipitation patterns change, increasingly severe droughts will leave some areas of the world vulnerable to increasingly severe fires. Understanding how fires behave in dry conditions can help firefighters, first responders and others prepare for a hotter, drier future. Related pages