Sea Level Change Data Pathfinder - Find Data

Global sea level has risen by about 8 inches since reliable record keeping began in 1880. It is projected to rise another 1 to 8 feet by 2100.
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Satellite sea level observations from 1993 - present. Credit: NASA GSFC/PO.DAAC.

Global Mean Sea Level (GMSL) is the globally averaged sea level, and satellite data indicate that it's rising at about 3.4 mm/y. GMSL has risen about 8–9 inches (21–24 centimeters) since 1880, with about a third of that coming in just the last two and a half decades. An annual reconstructed GMSL provides estimates of the contributions from various drivers of sea level change between 1900 and 2018. The reconstructed sea level is based on tide gauge observations aggregated annually. Sea level change contributions from thermal expansion, glacier mass changes, terrestrial water storage changes, and changing mass of the Greenland and Antarctic ice sheets were estimated by combining observations acquired by NASA's Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions with long-term estimates based on in-situ temperature profiles.

In addition, a GMSL trend has been generated by integrating ocean altimeter data from multiple missions. This GMSL product is a one-dimensional time series of globally averaged Sea Surface Height Anomalies (SSHA) from the TOPEX/Poseidon, Jason-1, Ocean Surface Topography Mission (OSTM)/Jason-2, and Jason-3 missions. It starts in September 1992 and continues to the present with a lag of up to 4 months. All biases and cross-calibrations have been applied to the data so SSHA are consistent between satellites. Glacial Isostatic Adjustment (GIA) has not been applied, but it has been smoothed with a 60-day filter.

The Integrated Multi-Mission Ocean Altimeter Data for Climate Research has developed a coherent and consistent time series of sea surface height (SSH) from multi-mission altimeter data to provide credible mean sea level estimates for climate research. A GMSL Jupyter Notebook contains code and scripts for downloading the ASCII table, loading to a data frame, and plotting the data.

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The sea level scenarios and information contained in the Interagency Sea Level Rise Scenario Tool originate from a 2022 technical report produced by the Sea Level Rise and Coastal Flood Hazard Scenarios and Tools Interagency Task Force. Credit: NASA.

The Interagency Sea Level Rise Scenario Tool is a visualization resource that provides sea level scenarios for U.S. coastal areas. The data are provided at individual tide gauge locations as well as on a 1° grid. Regionally averaged scenarios also are provided for several different coastal regions around the U.S. Where available, observation extrapolations using tide gauges from 2020–2050 are also provided for comparison to the scenarios. All values within the tool are referenced to a baseline year of 2000.

The Intergovernmental Panel on Climate Change recently concluded that glacial melt and ice sheet loss are now the dominant contributors to global mean sea level rise. Summer melting of the Greenland ice sheet has increased to a level unprecedented over at least the last 350 years. Antarctic ice loss is dominated by acceleration, retreat, and rapid thinning of major West Antarctic outlet glaciers, driven by melting of ice shelves by warm ocean water.

Changes in land water storage and ocean mass can be measured from space using data acquired by sensors aboard NASA's Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. Data are available from 2002 to the present. These satellites unambiguously show that the Greenland and Antarctic ice sheets, as well as the glaciers, are decreasing in mass; the Greenland ice sheet is decreasing in mass by about 277 gigatonnes (Gt) per year; the Antarctic ice sheet is decreasing in mass by about 149 Gt per year.

The NASA-created animation below was created using GRACE and GRACE-FO data and shows 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 GRACE and GRACE-FO Ocean, Ice, and Hydrology Equivalent Water Height dataset provides gridded monthly global water storage/height anomalies relative to a time-mean. The data are processed at NASA's Jet Propulsion Laboratory (JPL) using the Mascon approach. Mass Concentration blocks (mascons) are another form of gravity field basis function to which GRACE's inter-satellite ranging observations are fit. For more information on this approach, see Monthly Mass Grids.

NASA’s Virtual Earth System Laboratory provides insightful simulations connecting sea level change to the role of the cryosphere. To model and simulate the contribution of polar ice sheets to local sea level rise, visit NASA’s Sea Level Change Portal: VESL Global Relative Sea-Level Rise Simulation. The simulation captures the evolution of sea level rise over the entire planet, taking into account eustatic sea level, sea level rise from perturbations to the gravity field, and sea level rise from local elastic rebound of Earth's crust.

Research-quality data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

  • Ocean, Ice, and Hydrology Equivalent Water Height data
    These data are provided in a single data file in NetCDF format and can be used for analysis of ocean, ice, and hydrology phenomena. This version of the data employs a Coastal Resolution Improvement (CRI) filter that reduces signal leakage errors across coastlines. The water storage/height anomalies are given in equivalent water thickness units.
  • Tellus Level-4 Greenland Mass Anomaly Time Series
    This dataset is a time series of mass variability averaged across Greenland and provides ice mass changes over time. Mass variability is derived from the Ocean, Ice, and Hydrology Equivalent Water Height dataset.
  • Tellus Level-4 Antarctica Mass Anomaly Time Series
    This dataset is a time series of mass variability averaged across Antarctica and provides the ice mass changes over time. Mass variability is derived from the Ocean, Ice, and Hydrology Equivalent Water Height dataset.

Data can be visualized using NASA Worldview or the State of the Ocean (SOTO) tool available through NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC). SOTO is an interactive web-based tool to generate maps, animations, and plots that communicate and promote the discovery and analysis of the state of the ocean.

Scientists are working to determine more precisely how much more ice will be lost in both Greenland and Antarctica and when this loss may occur. One approach to doing this is to analyze changes in ice sheet elevation over the past decades for which satellite observations are available.

By finding the intersection of elevation track measurements acquired by laser altimeters aboard NASA's Ice, Cloud and land Elevation Satellite (ICESat; operational 2003 to 2009) and Ice, Cloud and land Elevation Satellite-2 (ICESat-2; operational 2018 to present) missions, researchers are able to make very precise measurements of elevation change that can be converted into estimates of mass change after correcting for changes in snow density using models.

NASA's Operation IceBridge airborne campaign collects data over Earth's polar ice to better understand connections between polar regions and the global climate system. IceBridge studies annual changes in thickness of sea ice, glaciers, and ice sheets. IceBridge flights are generally conducted March through May over Greenland and October through November over Antarctica. Other smaller airborne surveys are also part of the IceBridge campaign.

Research-quality data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

Additional Resources

OpenAltimetry, which is the product of a collaboration between NASA's National Snow and Ice Data Center DAAC (NSIDC DAAC), the Scripps Institution of Oceanography, and the San Diego Supercomputer Center at the University of California-San Diego, is a platform for discovery, access, and visualization of data from ICESat and ICESat-2.

Oceans Melting Greenland (OMG) was a NASA mission to understand the role that the ocean plays in melting Greenland's glaciers. From the sky and the sea, OMG gathered data about water temperatures and glaciers to get a better idea of just how fast the Greenland Ice Sheet is melting and how fast global sea levels might rise. Research-quality OMG data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data).

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GLIMS map of glaciers in the Italian Alps. Click on image for larger view. Credit: GLIMS.

The Global Land Ice Measurements from Space (GLIMS) Initiative has repeatedly surveyed the world's estimated 200,000 glaciers. GLIMS uses data collected by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument aboard NASA's Terra satellite and sensors aboard the joint NASA/USGS Landsat series of satellites along with historical observations. Each polygon within the Glacier Outlines layer represents the extent of a particular glacier at a specific time, as well as other possible features of the glacier such as the extent of debris cover or the location of supra-glacial and pro-glacial lakes. The GLIMS Glacier Viewer is an interactive map providing global information about the world's glaciers.

The NSIDC has a Greenland Surface Melt Extent Interactive Chart that provides a means of comparing surface melt from 1979-present. For daily satellite images and information about melting on the Greenland Ice Sheet see NSIDC's Greenland Ice Sheet Today.

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OSCAR ocean surface current speed image from June 15, 2022. Speed is indicated in colors, with red indicating speeds up to 1 meter/second (such as off the west coast of South America). Click on image for larger view. Credit: NASA PO.DAAC SOTO.

The ocean is dynamic. It is in a constant state of change as wind and density-driven currents transport water across the globe. These currents cause sea levels to differ regionally. The El Niño‐Southern Oscillation (ENSO), commonly known as El Niño, is a warm mass of water that moves from the Western Pacific Ocean toward the Americas. During El Niño events, as warm water pushes across the ocean, heat causes the ocean to expand, in turn causing sea level near the Americas to rise, with changes of up to 20 cm along the U.S. West Coast.

Surface current estimates from the Ocean Surface Current Analysis Real-time (OSCAR) provide horizontal velocity data that are directly estimated from sea surface height (SSH), surface vector wind, and sea surface temperature (SST). These data were collected from various satellites and in situ instruments.

There are two OSCAR products to choose from: Data on a 1° or a 1/3° grid with a 5-day resolution. Research-quality data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

Once you download the data, there are two options for currents if you use a program like NASA's Panoply data viewer to open the NetCDF file: zonal currents and meridional currents. A zonal wind pattern occurs when upper level winds are parallel or nearly parallel to lines of latitude. A meridional wind pattern occurs when upper level winds cross latitude lines at a sharp angle.

The data can be visualized using the State of the Ocean (SOTO) tool at NASA's PO.DAAC:

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CYGNSS Ocean Windspeed data from Hurricane Florence acquired September 14, 2018. Darker colors indicate higher wind speeds. Click on image for larger view. Credit: NASA Disasters.

NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission consists of a constellation of satellites that collect frequent remote sensing measurements of surface wind speeds. These satellites use constant and ubiquitous signals from the Global Positioning Satellite (GPS) system.

Additional wind data are available through the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). Surface wind data are available beginning in 1980 and up to a few weeks behind real time.

Research-quality CYGNSS and MERRA-2 data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

  • CYGNSS Winds
    Average wind speed (m/s) and mean square slope (MSS)
  • MERRA-2 Eastern and Northward Winds
    Winds are in m/s; the file is available in NetCDF format, and can be opened using the NASA Panoply data viewer. Note that sea level pressure is also available within this same file.

CYGNSS data can be visualized using the State of the Ocean (SOTO) tool at NASA's Physical Oceanography DAAC (PO.DAAC):

For subsetting CYGNSS data, use the PO.DAAC High-level Tool for Interactive Data Extraction (HiTIDE) tool (see the Tools for Data Access and Visualization section for more information).

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool called Giovanni (Note: An Earthdata Login is required to access Giovanni):

Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions and multiple temporal coverages, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

Salinity, the amount of salt dissolved in seawater, drives ocean currents that transport heat around the globe. Variations in salinity are negligible when considering global mean sea level (GMSL); however, salinity can be an important factor at the ocean-basin level, contributing to thermohaline circulation. Two NASA missions have acquired sea surface salinity (SSS) data since 2011: Aquarius/SAC-D and the Soil Moisture Active Passive (SMAP). Aquarius data are only available from 2011–2015 and are at a coarser spatial resolution than SMAP.

NASA's Aquarius instrument was the primary sensor aboard the SAC-D spacecraft (operational 2011 to 2015). Aquarius Version 5 is the official end-of-mission dataset, spanning the complete 45-month period of Aquarius science data availability from August 25, 2011 to June 7, 2015. Improving the accuracy of Aquarius' measurements is a key mission activity to ensure that the data are useful for science and society. Aquarius data are available as Level 2 SSS and wind speed data or as Level 3, gridded 1° spatial resolution salinity and wind speed data averaged over 7-day and monthly time scales.

The SMAP satellite (launched in 2015) was designed to provide global assessments of soil moisture. Algorithm development from the Aquarius mission was applied to SMAP data to retrieve SSS. The primary SMAP salinity datasets include a Level 2 orbital dataset, in which data granules contain both the ascending and descending arcs of the orbit, and two Level 3 gridded datasets: An 8-day running average (linked to the day repeat cycle of SMAP) and monthly average.

Research-quality SSS data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

For subsetting SSS data, use PO.DAAC's HiTIDE Tool (see the Tools for Data Access and Visualization section for more information).

SSS data can be visualized using NASA Worldview and PO.DAAC's SOTO tool:

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Locations of the Salinity Processes in the Upper Ocean Regional Study (SPURS) field-based campaigns. Click on image for larger view. Credit: NASA's Jet Propulsion Laboratory (JPL).

Along with satellite missions, field campaigns provide detailed information about SSS on a regional level. Salinity Processes in the Upper Ocean Regional Study (SPURS) is a pair of oceanographic field experiments using a combination of oceanographic equipment and technology, including salinity-sensing satellites, research cruises, floats, drifters, autonomous gliders, and moorings. The 2012–2013 SPURS-1 field campaign in the North Atlantic focused on a high-salinity, high-evaporation region; the 2016–2017 SPURS-2 field campaign is collecting data at the center of the low surface salinity belt associated with the heavy rainfall of the intertropical convergence zone in the tropical Pacific.

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Top row, left: Survey tracks of the 5 Saildrones, 3 NASA and 2 NOAA, deployed during the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC). Top row, right: Saildrone SD 1060 leaving Barbados. Bottom row, left: Along track surface temperature maps for the 3 NASA Saildrones. Bottom row, right: Along track surface salinity maps for the 3 NASA Saildrones. Credit: PO.DAAC.

Saildrone is a state-of-the-art, wind-and-solar-powered Uninhabited Surface Vehicle (USV) capable of long distance deployments lasting up to 12 months. This novel sampling platform is equipped with a suite of instruments and sensors providing high quality, georeferenced, near real-time, multi-parameter surface ocean and atmospheric observations.

Research-quality SPURS and Saildrone salinity data can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

NASA’s Sea Level Portal: Data Analysis Tool provides observed and reanalysis/modeled data and allows users to perform regional statistical analysis, time series analysis, and comparisons. This tool visualizes gridded sea surface salinity data, along with other parameters.

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Indian Ocean sea surface temperature for July 17, 2022, visualized using the SOTO tool. Darker colors indicate warmer ocean temperatures. Click on image for larger view. Credit: PO.DAAC SOTO.

More than 90% of atmospheric heat is absorbed by the ocean, which causes the ocean to warm and expand. This thermal expansion has contributed roughly one-third of the global sea-level rise observed by satellite altimeters since 2004. Measurements such as sea surface temperature (SST) and sea surface height (SSH) aid in our understanding of this process.

Satellites enable measurement of SST from approximately 10 microns (µm) below the surface (infrared bands) to 1 mm (microwave bands) depths using radiometers. SST spatial patterns reveal the structure of underlying ocean dynamics.

SST data from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), the Group for High Resolution Sea Surface Temperature (GHRSST), and the Multi-Scale Ultra High Resolution Sea Surface Temperature (MUR SST) can be visualized using NASA Worldview and PO.DAAC’s State of the Ocean (SOTO) (Note: An Earthdata Login is required to download data):

SST data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool called Giovanni (Note: An Earthdata Login is required to access Giovanni):

Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions and multiple temporal coverages, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

Research-quality MODIS, VIIRS, and MUR SST data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

NASA’s Sea Level Portal: Data Analysis Tool provides observed and reanalysis/modeled data and allows users to perform regional statistical analysis, time series analysis, and comparisons. This tool visualizes gridded sea surface temperature data, along with other parameters.

The NASA Applied Sciences Disaster program area Tropical Cyclone Dashboard provides near real-time ocean SST data that are geospatially enabled, open source, and compatible with Esri products.

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Along with SST, more than two dozen additional layers can be overlaid on the NASA Disasters Tropical Cyclone Dashboard. Credit: NASA Disasters program area.

Sea surface height (SSH) data provide critical information to scientists and researchers for understanding sea level rise, storm predictions, ocean currents, and more.

SSH has been collected from 1992 to the present through a series of NASA/French space agency (CNES) ocean surface topography missions. The first was the TOPEX/Poseidon mission (operational 1992 to 2006), which was followed by the Jason-1 mission (operational 2001 to 2013). Jason-1 was followed by the Ocean Surface Topography Mission (OSTM)/Jason-2 mission (operational 2008 to 2019) and the ongoing Jason-3 mission (launched in 2016). Between these four missions, SSH has been collected from 1992 to the present, providing a long-term time series of data. The next generation of ocean surface topography missions, the joint NASA/European Sentinel-6 Michael Freilich mission launched in 2020 to extend the continuous data record of ocean surface topography into a fourth decade.

Because of the long time series of the data, several merged data products have been developed to assess SSH anomalies. These data can be visualized using NASA Worldview and the State of the Ocean (SOTO) tool at NASA's Physical Oceanography DAAC (PO.DAAC) (Note: Data are available from 1992 to 2019):

Research-quality data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

For subsetting SSH data, use PO.DAAC's HiTIDE Tool (see the Tools for Data Access and Visualization section for more information)

Tide gauges have measured sea level over the last 200 years, with some records extending back to 1807. One disadvantage to tide gauges, though, is that they only provide regional coverage. The satellite altimetric record, on the other hand, provides accurate measurements of sea level with near-global coverage. The disadvantage of satellite data, however, is that the satellite ocean altimetry record only goes back to 1992. Combining satellite altimetry with tide gauges using a technique known as sea level reconstruction results in a dataset with the record length of the tide gauges and the near-global coverage of satellite altimetry. The Reconstructed Sea Level dataset contains sea level anomalies derived from satellite altimetry and tide gauges with a time span from 1950 through 2009.

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Sentinel-6A Michael Freilich Altimetry low Resolution NRT sea surface height anomalies. Credit: NASA PO.DAAC.

Sentinel-6 Michael Freilich, launched November 2020, is a follow on to the Jason missions and is designed to measure the height of the ocean; it ensures the continuation of a decades-long record of sea level observations until 2030. NASA developed the mission with the ESA, the European Organization for the Exploitation of Meteorological Satellites, and NOAA. The European Commission provided funding support. CNES also supports the mission.

NASA’s Sea Level Portal: Data Analysis Tool provides observed and reanalysis/modeled data and allows users to perform regional statistical analysis, time series analysis and comparisons. This tool visualizes gridded merged SSHA data, along with other parameters.

Changes in global mean sea level (GMSL) are impacted by changes in freshwater storage on land that can prevent freshwater from entering the ocean (which can lower GMSL) or increase the flow of water into the ocean (which can raise GMSL). While the amount of water on Earth does not change, the reservoir in which it resides and its state of matter changes constantly as it cycles through evaporation, precipitation, groundwater, rivers and lakes, and the ocean. Humans impact these reservoirs through the construction of dams, the diversion of water for irrigation, and other activities that impact flow of water to the ocean.

Scientific research estimates that humans have so far captured a total of 10,416 km3 of water behind dams, which represents the equivalent of a 29 mm decrease in global mean sea level (GMSL) since 1900. Humans also alter the hydrologic cycle through groundwater withdrawal, depleting regional storage of water on land and contributing more to the ocean, which leads to a rise in GMSL. About 80% of groundwater withdrawal ends up in the ocean. This contribution to GMSL has increased from 0.02 (±0.004) mm/y in 1900 to 0.27 (±0.04) mm/yr in 2000.

Changes in land water storage result in localized changes to mass and gravitation that can be measured from space using data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. Data are available from 2002 to the present and track anomalies (changes from the mean), which means they are not representative of total water storage. In addition, the resolution of the data are greater than 150,000 km2, so the sensors only measure change within large reservoirs. The value of GRACE data is evident when doing regional studies to determine general trends in land water storage.

The animation below was created using GRACE data collected since 2002 and shows patterns of rising and falling sea levels across the globe in response to changes in Earth’s gravitational and rotational fields. The global movement of water can cause localized bumps and dips in gravity, sometimes with counterintuitive effects. Melting glaciers, for example, cause nearby sea level to drop; as they lose mass, their gravitational pull slackens, and sea water migrates away. Sea level is dropping around rapidly melting Greenland (orange, yellow). But near coastlines at a sufficient distance, the added water causes sea levels to rise (blue). Animation credit: NASA-JPL/Caltech.

The GRACE and GRACE-FO Ocean, Ice, and Hydrology Equivalent Water Height dataset provides gridded monthly global water storage/height anomalies relative to a time-mean. The data are processed at NASA's Jet Propulsion Laboratory (JPL) using the mass concentration (Mascon) approach. For more information on this approach, view Monthly Mass Grids. Data are represented as Water Equivalent Thickness (WET), which is a way of representing changes in the gravity field in hydrological units. WET values represent the total terrestrial water storage anomalies from soil moisture, snow, surface water (including rivers, lakes, and reservoirs), as well as groundwater and aquifers.

Liquid water equivalent thickness data provide global water storage anomalies relative to a time-mean of monthly mass grids derived from GRACE and GRACE-FO. These data can be visualized using NASA Worldview and PO.DAAC's State of the Ocean (SOTO) tool. The data visualization employs a Coastal Resolution Improvement (CRI) filter that reduces leakage errors across coastlines. The storage anomalies are given in equivalent water thickness units (cm).

Research-quality data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

Datasets are available as NetCDF files which can be opened using the NASA Panoply data viewer or imported into a GIS system.

NASA's Physical Oceanography DAAC (PO.DAAC) has developed a python script to convert the JPL GRACE Mascon file from netCDF4 to GeoTIFF format. This GRACE python script decomposes the multi-year monthly Mascon netCDF file into single GeoTIFF files for each month.

NASA’s Sea Level Portal: Data Analysis Tool provides observed and reanalysis/modeled data and allows users to perform regional statistical analysis, time series analysis, and comparisons. To add Water Equivalent Thickness data to the base map, use the Mass Flux data tab in the My Data section.

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The Surface Water and Ocean Topography (SWOT) mission, scheduled for launch in November 2022, was jointly developed by NASA and the French space agency (CNES), with contributions from the Canadian Space Agency and the United Kingdom Space Agency. SWOT will make the first global survey of Earth's surface water, observe the fine details of the ocean's surface topography, and measure how terrestrial water bodies change over time.

SWOT will provide the first comprehensive view of Earth's freshwater bodies from space and will enable scientists to determine changing volumes of fresh water across the globe at an unprecedented resolution. Hydrologists can use these data to calculate the rate of water gained or lost in lakes, reservoirs, and wetlands as well as global discharge variations in rivers. These measurements are key to understanding surface water availability and in preparing for water-related hazards such as floods, droughts, and sea level change.

NASA's Pre-SWOT Hydrology project is part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program. The project focuses on the development of Earth Systems Data Records (ESDRs) for surface-water storage change dynamics throughout the world with up to 349 targets, especially at resolutions and quality relevant to human use and that are largely absent from current global hydrology models. Lakes and reservoirs (larger than approximately 100 km2) and rivers (wider than approximately 900 m) are included in the initial project scope, with an emphasis on targets that are clearly distinguishable from other nearby water bodies for improved accuracy of both elevation and surface area estimates.

Research-quality data products from the project can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):

Datasets are available as NetCDF files that can be opened using the NASA Panoply data viewer or imported into a GIS system.

 

Data describing vertical land motion are a key element in understanding how sea levels have changed over the past century and how future sea levels may impact coastal areas. Repeat-pass radar interferometry from spaceborne platforms is routinely used to produce topographic change maps as digital displacement models (DDMs). When two observations are made from the same location in space but at different times, the interferometric phase is directly proportional to any change in the range of a surface feature. This change allows for the measurement of any displacement or ground deformation that has occurred between the time of the two observations.

Interferometric synthetic aperture radar (InSAR) provides centimeter-level measurements of displacement from land surface movement. The displacement or deformation is indicated as contour lines along a band of colors, called a fringe; where colored lines are closer together, more movement occurred.

Research-quality data products can be accessed using Earthdata Search or from the NASA Alaska Satellite Facility DAAC (ASF DAAC) Vertex data discovery tool (Note: An Earthdata Login is required to download data).

The upcoming NASA-Indian Space Research Organization SAR (NISAR) mission, scheduled for launch in 2023, will measure Earth's dynamic surfaces and ice masses to provide information about natural hazards, sea level rise, and groundwater, and will support a host of other applications.

To learn more about SAR, see the What is SAR? Backgrounder. To learn about processing Level 1 data, view NASA's Applied Remote Sensing Training (ARSET) Introduction to SAR training or the Earthdata webinars Introduction to SAR Data and Applications of SAR Data in GIS Environments.

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GRACE/GRACE-FO contemporary geoid movement predictions (in mm/yr) from GIA as predicted by the ICE6G-D model. Darker colors, such as over northern Canada, are areas forecast to have greater rebound as mass is removed. Credit: NASA.

The last Ice Age occurred around 16,000 years ago, when ice sheets two miles thick covered much of the Northern Hemisphere. Although the ice sheets melted long ago, the land that was covered by tons of ice is still rebounding. This ongoing movement of land is known as glacial isostatic adjustment, or GIA.

A NOAA National Ocean Service example shows how GIA works. Imagine lying down on a soft mattress and then getting up from the same spot. You see an indentation in the mattress where your body was and a puffed-up area around the indentation where the mattress rose. Once you get up, the sunken part of the mattress eventually relaxes back to its original shape, but this takes time. As land masses slowly rebound, mass is shifting and sea levels are changing.

NASA accounts for and removes the effects of GIA when processing GRACE and GRACE-FO measurements to obtain land water storage and isolate water-related mass changes. For more information on this process, see GRACE TELLUS GIA.

To visualize and simulate the impact of GIA and the associated changes in sea level, visit the NASA Sea Level Change Portal: VESL Glacial Isostatic Adjustment Simulation

Research-quality data can be obtained using Earthdata Search (Note: An Earthdata Login is required to download data):

Datasets are available in NetCDF format and are available at 0.5° and 1°.

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Chincoteague Island along the Virginia and Maryland coast is constantly in motion from ocean, wind, and tidal forces. This image of the island was acquired on June 2, 2019, by the NASA/USGS Landsat 8 Operational Land Imager (OLI). Credit: NASA Earth Observatory.

Sea level change, especially in areas where sea level is rising, can have catastrophic impacts to coastal communities. Coastal barrier islands are constantly shifting position; however, human-built infrastructure prevents these islands from moving naturally. As consequence, erosion through sea level rise can be significant. In addition, the amount of nuisance, or "sunny day" flooding has increased in the U.S. on average by about 50% since 20 years ago and 100% since 30 years ago, according to NOAA. Other impacts include saltwater intrusion, habitat destruction, and the forced migration of low-lying (and often low-income) communities.

Corrected reflectance and surface reflectance imagery provide an easy way to compare change over time. False color imagery created using specific imagery bands can help highlight specific environmental features. For example, Visible Infrared Imaging Radiometer Suite (VIIRS) imagery created by combining bands M11, I2, and I1 or bands M3, I3, and M11 is useful for enhancing flood conditions since liquid water on the ground appears very dark. Likewise, false color imagery created using bands 7, 2, and 1 from the Moderate Resolution Imaging Spectrometer (MODIS) instrument also highlight liquid water on the ground in a dark color.

Data (many of which are available in near real-time) can be visualized using NASA Worldview:

Research-quality data products can be accessed using Earthdata Search or through NASA partner websites. Note that an Earthdata Login is required to download data from Earthdata Search and a USGS Login is required to download data from the USGS Earth Explorer.

  • MODIS Surface Reflectance from Earthdata Search
    Note that a false-color image created by combining bands 7 as red, 2 as green, and 1 as blue is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges. To only choose those bands, see the customization option within Earthdata Search in the Tools for Data Access and Visualization section.
  • Suomi NPP VIIRS Surface Reflectance from Earthdata Search
    Note that a false-color image created by combining bands M11 as red, I2 as green, and I1 as blue is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges. To only choose those bands, see the customization option within Earthdata Search in the Tools for Data Access and Visualization section.
  • Landsat Data from USGS Earth Explorer
    On the Earth Explorer site, specify your search criteria, then:
    1. Select "Data Sets"
    2. Select Landsat
    3. Select Landsat Collection 1 Level-1
    4. Select Landsat 7, Landsat 8, or Landsat 9
    These files can be downloaded as Level-1 GeoTIFF Data Products.
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Population density (left image) and low elevation coastal zone areas (right image) in greater New York City. Data in the image are from the Urban-Rural Population and Land Area Estimates Version 2. Click on image for larger view. Credit: NASA SEDAC.

When combined with sea level change data, socioeconomic data provide a picture of the impact to cities, coasts, and other developed areas along with the number of people and types of communities that might be affected.

NASA's Socioeconomic Data and Applications Center (SEDAC) is the home of socioeconomic data in NASA's Earth Observing System Data and Information System (EOSDIS) collection and is hosted at Columbia University’s Center for International Earth Science Information Network (CIESIN). SEDAC synthesizes Earth science and socioeconomic data and information in ways useful to a wide range of decision makers and other applied users, and serves as an “Information Gateway” between the socioeconomic and Earth science data and information domains.

NASA's Socioeconomic Data and Applications Center (SEDAC) provides a number of datasets on population exposure and vulnerability and flood hazard potential that can be viewed using NASA Worldview:

SEDAC also has several tools for visualizing population data, like the POPGRID Viewer that enables direct comparison of different population datasets and the Hazards Mapper web mapping application that allows users to estimate the number of people in proximity to a natural disaster and to assess exposure.

Research-quality socioeconomic data products can be accessed using Earthdata Search (Note: An Earthdata Login is required to download data):  

Additional Data, Tools, and Resources

  • Environmental Justice Screen: This Environmental Protection Agency (EPA) tool features Socioeconomic Indicators, Health Disparities, and more in the United States.
  • Resilience Analysis and Planning Tool (RAPT): This resource from the Federal Emergency Management Agency (FEMA) offers a GIS web map that displays census data, infrastructure locations, and hazards, including real-time meteorological forecasts, as well as U.S. disasters and hazard data 
  • National Environmental Public Health Tracking: The Centers for Disease Control and Prevention (CDC) offers the following measures related to Flood Vulnerability:
    • Number of Square Miles Within FEMA Designated Flood Hazard Area
    • Percent Area (square miles) Within FEMA Designated Flood Hazard Area
    • Number of Square Miles Within EPA Designated Flood Hazard Area
    • Percent Area (square miles) Within EPA Designated Flood Hazard Area
    • Number of People Within FEMA Designated Special Flood Hazard Area
    • Number of Housing Units Within FEMA Special Designated Flood Hazard Area
  • World Bank Indicators
    • World Bank DataBank: Offers an analysis and visualization tool for exploring time series data on a variety of topics related to World Development.
    • Not sure where to start? Explore the collections by visiting the Featured Indicators section to explore topics ranging from Agriculture and Rural Development to Health to Trade
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Black Marble Nighttime Blue/Yellow Composite showing the Nile River Delta on May 7, 2021. Interactively explore this image using NASA Worldview. Credit: NASA Worldview.

The VIIRS Day/Night Band (DNB) shows Earth's surface and atmosphere using a sensor designed to capture low-light emission sources under varying illumination conditions. This enables an assessment of power outages or changes in nighttime light conditions across an area caused by flooding or other events.

NASA has also developed the Black Marble, a daily calibrated, corrected, and validated product suite to enable nightlight data to be used effectively for scientific observations. Black Marble's standard science processing removes cloud-contaminated pixels and corrects for atmospheric, terrain, vegetation, snow, lunar, and stray light effects on the VIIRS DNB radiances. Black Marble data can be accessed at NASA's Level-1 and Atmosphere Archive and Distribution System DAAC (LAADS DAAC). Black Marble imagery in Worldview is an image composite that was assembled from clear, cloud-free images acquired in 2012 and 2016.

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Nighttime lights of the U.S. show up in yellow with clouds in blue in this Black Marble Nighttime Blue/Yellow composite image from June 19, 2022. Additional layers can be added to this NASA Disasters portal base map. Credit: NASA Applied Sciences Disaster Dashboard.

For additional information on the datasets above as well as applications of the data, view the Nighttime Lights Backgrounder.

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Millions of people live on the Mississippi Delta, along with a unique ecosystem of plants and animals. On average, one football field of land is lost per hour. Click on image for larger view. Credit: NASA's Jet Propulsion Laboratory (JPL).

River deltas build land where a river reaches a shallow coast and deposits large amounts of material. Low-lying deltas can be inundated when sea levels rise, affecting many ecosystem components. NASA's Delta-X mission is using airborne (remote sensing) and field measurements to look at the water, vegetation, and sediment (soil) of the Mississippi River Delta, the seventh largest river delta on Earth. This area experiences some of the largest sea level rise in the world, at 9 to 12 mm per year. This land loss is happening to deltas all over the world, but it is happening faster here due to subsidence.

Delta-X data are available via Earthdata Search (Note: An Earthdata Login is required to download data):

For more information about the mission, see the Earthdata article Disappearing Deltas: The Delta-X Airborne Mission Investigates.

Last Updated
Jul 19, 2022