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. This is the result of added water from melting land ice and the expansion of seawater as it warms. In the next several decades, storm surges and high tides could combine with sea level rise and land subsidence to further increase flooding in many regions. This data pathfinder links to NASA datasets and tools that can aid in our understanding of sea level changes - causes and the potential impacts from that change
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Satellite sea level observations from 1993 - present. Credit: NASA Physical Oceanography Distributed Active Archive Center (PO.DAAC).

GMSL is the globally averaged sea level and trends indicate that it's rising at about 3.3 mm/y (NASA Sea Level Change). 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. Under funding from MEaSUREs, 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 GRACE and GRACE-FO observations 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 1-dimensional time series of globally averaged Sea Surface Height Anomalies (SSHA) from TOPEX/Poseidon, Jason-1, Ocean Surface Topography Mission (OSTM)/Jason-2 and Jason-3. 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 SSH from multi-mission altimeter data that meets the most stringent accuracy requirements demanded 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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Antarctica ice sheet mass loss with superimposed ice sheet velocity streamlines from 2002-2016. Credit: NASA.

The Intergovernmental Panel on Climate Change recently concluded that glacial melt and ice sheet loss is now the dominant contributor 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 waters.

Changes in land water storage and ocean mass can be measured from space using the GRACE and GRACE-FO sensors. 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 shrinking; the Greenland ice sheet is decreasing by about 289 Gt per year, and the Antarctica ice sheet is decreasing by about 132 Gt per year (Hamlington, et al., 2020).

The GRACE and GRACE-FO Ocean, Ice, and Hydrology Equivalent Water Height dataset is 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 essentially another form of gravity field basis function to which GRACE's inter-satellite ranging observations are fit. Using mascons rather than the standard spherical harmonic approach, which has been the standard for the first decade of GRACE/GRACE-FO observations, offers several key advantages. For more information on this approach, view Monthly Mass Grids.

Research-quality data products can be accessed via Earthdata Search:

The data can be visualized through Worldview or NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) State of the Ocean (SOTO) tool. SOTO is an interactive web-based tool to generate informative 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 that loss will occur. One key approach to doing this is to analyze changes in the ice sheet's elevation over the past decades where satellite observations are available.

By finding the intersection of elevation track measurements collected by NASA's Ice, Cloud and land Elevation Satellite (ICESat) and Ice, Cloud and land Elevation Satellite-2 (ICESat-2) satellite laser altimeters, 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. ICESat collected data from 2003–2009 and ICESat-2 from 2018–present.

NASA's Operation IceBridge, bridging the temporal gap between the ICESat missions, images 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 uses airborne instruments to map Arctic and Antarctic areas. IceBridge flights are generally conducted in March – May over Greenland and in October – November over Antarctica. Other smaller airborne surveys around the world are also part of the IceBridge campaign.

Research-quality data products can be accessed via Earthdata Search:

OpenAltimetry, which is the product of a collaboration between NSIDC, 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) is a NASA mission to understand the role that the ocean plays in melting Greenland's glaciers. From the sky and the sea, OMG gathers data about water temperatures and the glaciers all the way around Greenland to get a better idea of just how fast the ice is melting, and how fast global sea levels will rise.

Research-quality data products can be accessed via Earthdata Search:

  • OMG Glacial Elevations from Earthdata Search
    This dataset contains 50 m horizontal resolution gridded digital elevation models (DEMs) of Greenland Ice Sheet outlet glaciers between 2016 and 2019. The GLISTIN-A radar measured surface elevations around the periphery of the Greenland Ice Sheet.
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Global Land Ice Measurements from Space map of glaciers in Peru, South America.

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 the Terra satellite and the 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.

NSIDC has a Greenland Surface Melt Extent Interactive Chart which provides a means of comparing surface melt over the years, from 1979-present. For daily satellite images and information about melting on the Greenland ice sheet, view NSIDC's Greenland Ice Sheet Today.

 

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OSCAR ocean flow data colored by velocity (with dates and color bar), from July 27, 2012. Credit: NASA Scientific Visualization Studio.

The ocean is dynamic. It is in a constant state of change as winds 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 west coast of the U.S. (Hamlington, et al., 2015)

Surface current estimates from OSCAR provide horizontal velocity that is directly estimated from sea surface height (SSH), surface vector wind, and SST. These data were collected from various satellites and in situ instruments.

There are two OSCAR products to choose from: data on a 1 degree or a 1/3 degree grid with a 5-day resolution. Research-quality data products can be accessed via Earthdata Search:

Once you download the data, there are two options for currents if you use a program like Panoply to open the NetCDF file—zonal currents and meridional currents. When the upper level winds are parallel or nearly parallel to lines of latitude the wind pattern is termed zonal. When winds cross latitude lines at a sharp angle, the wind pattern is termed meridional.

The data can be visualized through SOTO.

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CYGNSS Ocean Windspeed data from Hurricane Florence acquired September 14, 2018. Credit: NASA Disasters.

NASA's Cyclone Global Navigation Satellite System (CYGNSS) 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. The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides surface wind data beginning in 1980 and runs a few weeks behind real time.

Research-quality CYGNSS and MERRA-2 data products can be accessed via Earthdata Search; for subsetting CYGNSS data, use PO.DAAC's 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, 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.

The data can be visualized through PO.DAAC's SOTO tool:

Salinity, the amount of salt dissolved in seawater, drives ocean currents that transport heat around the globe. Variations in salinity are negligible when considering GMSL; however it can be an important factor at the ocean-basin level, contributing to thermohaline circulation. Two NASA instruments have been measuring sea surface salinity (SSS) since 2011, Aquarius/SAC-D and the Soil Moisture Active Passive (SMAP).

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 – June 7, 2015. Improving the accuracy of Aquarius' measurements has been a key mission activity to ensure that the data are most useful for science and society. There are two products, the official release and another from JPL based on the Combined Active Passive (CAP) retrieval algorithm.

The SMAP satellite delivers derived SSS observations for the ocean and soil moisture. Algorithm development from the Aquarius mission is applied to SMAP to retrieve SSS. There are two products, one from JPL and one from Remote Sensing Systems (RSS). The JPL product is based on the CAP retrieval algorithm and provides a comparative view to RSS, which is based on averages spanning an 8-day moving window.

Note that the Aquarius data are only available from 2011–2015 and are at a much coarser spatial resolution than SMAP.

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

Research-quality SSS data products can be accessed via Earthdata Search; for subsetting SSS data, use PO.DAAC's HiTIDE Tool (see the Tools for Data Access and Visualization section for more information):

The data can be visualized through Worldview and PO.DAAC's SOTO tool.

There are also field-based campaigns that provide more 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 variety 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 the center of the low surface salinity belt associated with the heavy rainfall of the intertropical convergence zone in the tropical Pacific.

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.

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A) Survey tracks of the 5 saildrones, 3 NASA and 2 NOAA, deployed during the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC). B) Saildrone SD 1060 leaving Barbados. C) Along track surface temperature maps for the 3 NASA saildrones. D) Along track surface salinity maps for the 3 NASA saildrones. Credit: NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC).

Research-quality field-based salinity data can be accessed via Earthdata Search:

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Sea surface temperature anomalies, September 21, 2020, from the Multiscale Ultrahigh Resolution data product. Visualization from the State of the Ocean (SOTO) tool. Credit: NASA.

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

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

Research-quality data products from MODIS on Terra and Aqua, and from VIIRS on Suomi NPP and JPSS NOAA-20 can be accessed via Earthdata Search; for subsetting SST data, use PO.DAAC's 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, 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.

The data can be visualized through Worldview and PO.DAAC's SOTO tool.

SST data from satellites can be combined to create high-resolution Level 4 SST datasets, such as the Group for High Resolution Sea Surface Temperature (GHRSST) MUR SST. MUR provides daily SST at 1 km spatial resolution from June 2002 to present. The dataset is based upon nighttime skin (or surface) and sub-skin observations from several instruments, including satellite and in situ observations.

Research-quality data products can be accessed via Earthdata Search:

The data can be visualized through Worldview and PO.DAAC's SOTO tool.

Satellite altimeters make observations of SSH as oscillations higher or lower than an established reference height at the ocean surface. SSH data provide critical information to scientists and researchers for understanding sea level rise, storm predictions, ocean currents, and more.

TOPEX/Poseidon was an altimetric mission jointly collaborated by NASA and the French space agency, Centre National D'Etudes Spatiales (CNES). Jason-1 was the first follow-on to the highly successful TOPEX/Poseidon mission; it was followed by OSTM/Jason-2 and now the ongoing Jason-3. Between these four missions, SSH has been collected from 1992 to the present, providing a long-term time series of data.

Research-quality data products can be accessed via Earthdata Search; for subsetting SSH data, use PO.DAAC's HiTIDE Tool (see the Tools for Data Access and Visualization section for more information):

ICESat-2 also collected SSH at variable length scales over cloud-free regions. Research-quality data products can be accessed via Earthdata Search:

Because of the long time series of the data, several merged data products have been developed to assess SSH anomalies. The gridded data are derived from the SSH anomalies data of TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3 as reference data. Research-quality data products can be accessed via Earthdata Search:

The data can be visualized through Worldview and PO.DAAC's SOTO tool.

The Reconstructed Sea Level dataset contains sea level anomalies derived from satellite altimetry and tide gauges. The satellite altimetric record provides accurate measurements of sea level with near-global coverage, but it has a relatively short time span, since 1993. Tide gauges have measured sea level over the last 200 years, with some records extending back to 1807, but they only provide regional coverage, not global. 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. This data product spans 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 Organisation for the Exploitation of Meteorological Satellites, and NOAA. The European Commission provided funding support. CNES also supports the mission.

 

The ocean plays a huge role in the hydrologic cycle, transporting water around the globe. The amount of water on Earth does not change, but the reservoir in which it resides and its state of matter does change as it cycles through evaporation, precipitation, groundwater, rivers and lakes, and the ocean. Humans impact these reservoirs through the construction of dams, creating large, artificial bodies of water on land, reducing outflow to the ocean (GMSL fall). Scientific research (Wada, et al., 2017) 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 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 (GMSL rise). Scientific research (Wada, et al., 2016) estimates that 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 (and ice and ocean mass changes) can be measured from space using the GRACE and GRACE-FO sensors. Data are available from 2002 to the present; the data track anomalies (changes from the mean) and so are not representative of total water storage. Note that 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.

GRACE and GRACE-FO Ocean, Ice, and Hydrology Equivalent Water Height dataset is gridded monthly global water storage/height anomalies relative to a time-mean. The data are processed at JPL using the Mascon approach. Mascons are essentially another form of gravity field basis functions to which GRACE's inter-satellite ranging observations are fit. Using "mascons" rather than the standard spherical harmonic approach, which has been the standard for the first decade of GRACE/GRACE-FO observations, offers several key advantages. 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. The WET represents the total terrestrial water storage anomalies from soil moisture, snow, surface water (including rivers, lakes, and reservoirs), as well as groundwater and aquifers. A GIA correction has been applied.

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Water Equivalent Thickness (WET) from GRACE data run with each algorithm, that from the GeoForschungsZentrum Potsdam (GFZ), the Center for Space Research at the University of Texas, Austin (CSR) and the Jet Propulsion Laboratory (JPL). Th final is the arithmetic mean of the three, calculated in a GIS program.

Research-quality data products can be accessed via Earthdata Search; datasets are available as NetCDF files which can be opened using Panoply 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.

The data can be visualized through Worldview and PO.DAAC's SOTO tool. The mascon CRI layer provides global water storage anomalies relative to a time-mean of monthly mass grids as derived from GRACE. This version employs a CRI filter that reduces leakage errors across coastlines. The storage anomalies are given in equivalent water thickness units (cm).

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Surface Water and Ocean Topography (SWOT), targeted to launch early 2022, is a mission jointly developed by NASA and 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 very first comprehensive view of Earth's freshwater bodies from space and will allow scientists to determine changing volumes of fresh water across the globe at an unprecedented resolution. Hydrologists will use the data to calculate the rate of water gained or lost in lakes, reservoirs, and wetlands as well as discharge variations in rivers, globally. These measurements are key to understanding surface water availability and in preparing for important water-related hazards such as floods, droughts, and sea level change.

The Pre-SWOT Hydrology is part of MEaSUREs. The Pre-SWOT Hydrology project provides precursor SWOT products for global hydrologic changes from a combination of satellite imagery and multi-mission satellite radar altimetry data, including virtual river station heights, lake/reservoir surface water area extent, and lake/reservoir water height spanning from 1992 (TOPEX/Poseidon launch) to present, with the potential to be extended up to the launch of the SWOT mission planned for 2022.

Research-quality data products can be accessed via Earthdata Search; datasets are available as NetCDF files which can be opened using Panoply or imported into a GIS system.

 

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 SAR (InSAR) thus provides centimeter-level measurements of displacement from subsidence in an area. This displacement or deformation is seen as contour lines; where the lines are closer together, there was a lot of movement. Discontinuities in the contour lines also show where the actual fault rupture is. Contour lines are half of the radar's wavelength; ESA's Sentinel-1, with a radar length of 6 cm has contour lines indicating ground deformation of 3 cm.

Research-quality data products can be accessed via Earthdata Search or from NASA's Alaska Satellite Facility DAAC (ASF DAAC).

The upcoming NASA-Indian Space Research Organisation SAR (NISAR) mission, launching in 2022, will measure Earth's dynamic surfaces and ice masses providing information about natural hazards, sea level rise, and groundwater, and will support a host of other applications. This pathfinder will be updated with data as they becomes available.

To learn more about SAR, read What is SAR?. 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 rates (in mm/yr) from Glacial Isostatic Adjustment (GIA) as predicted by the ICE6G-D model. Credit: NASA.

The last Ice Age occurred around 16,000 years ago. At that time, ice sheets, miles thick, covered much of the Northern Hemisphere. The ice sheets melted long ago, but the land underneath is still rebounding as a result of the removal of that burden. This ongoing movement of land is known as GIA. 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 mattress takes a little time before it relaxes back to its original shape. Sea level is still changing as this land rebound happens.

When processing GRACE and GRACE-FO measurements to obtain land water storage, GIA has to be accounted for and removed to truly isolate the water-related mass changes. In doing so, NASA has a fairly good idea of that which was removed. For more information on this process, see GRACE TELLUS GIA.

Research-quality data can be obtained via Earthdata Search; datasets are available in NetCDF format, and are available at 0.5° and 1°.

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Assateague and Chincoteague provide a rare example of overlapping barrier islands. All of them are constantly in motion. June 2, 2019 image from the NASA / USGS Landsat 8 Operational Land Imager (OLI). Credit: NASA Earth Observatory.

Sea level change, especially in areas where it is on the rise, is having often catastrophic impacts to coastal communities. As many of our barrier islands and beach fronts are populated, human-built infrastructure prevents the island from moving naturally and so with sea level rise, erosion becomes a dangerous effect. 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 forced migration of often low-income communities.

NASA has several products that can be used to qualitatively assess these impacts from sea level rise: NASA/USGS Landsat, MODIS, and VIIRS.

Research-quality (higher-level "standard") data products can be accessed via Earthdata Search or through NASA partner websites:

  • 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
    Landsat is a joint NASA/USGS program that provides the longest continuous space-based record of Earth's land in existence. 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 and/or Landsat 8
    These files can be downloaded as Level-1 GeoTIFF Data Products. Note that you will need a USGS login to proceed.

Data (often in near real-time) can be visualized in Worldview:

  • Suomi NPP VIIRS Corrected Reflectance in Worldview
    Note that a false-color image created by combining bands M11 as red, I2 as green, and I1 as blue, or M3-I3-M11, 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.
  • NOAA-20 VIIRS Corrected Reflectance in Worldview
    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.
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Population density and low elevation coastal zone areas in greater New York City; data from the Urban-Rural Population and Land Area Estimates Version 2. Credit: Socioeconomic Data and Applications Center (SEDAC).

NASA's Socioeconomic Data and Applications Center (SEDAC) provides data and tools to aid in hazards assessment. SEDAC's POPGRID Viewer enables direct comparison of different population datasets based on different data sources and methodologies. SEDAC's Hazards Mapper enables users to visualize data and map layers related to socioeconomic, infrastructure, natural disasters, and environment and analyze potential impacts and exposure.

Data products, such as sea level impact on wetlands, coastal zone urban-rural population, and more, can be accessed via Earthdata Search:

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Black Marble Nighttime Blue/Yellow Composite showing the Nile River Delta on May 7, 2021. The Blue/Yellow Composite is a false color image created using the VIIRS at-sensor radiance and brightness temperatures from the M15 band. Interactively explore this image using NASA Worldview. NASA Worldview image.

The VIIRS Day/Night Band (DNB) shows the earth's surface and atmosphere using a sensor designed to capture low-light emission sources, under varying illumination conditions, which provides an assessment of power outages or changes in nighttime light conditions across an area, due to flood conditions.

NASA has also developed the Black Marble, a daily calibrated, corrected, and validated product suite, so nightlight data can 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 for 2012 and 2016.

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. Credit: NASA's Jet Propulsion Laboratory (JPL).

River deltas build land where a river reaches a shallow coast and deposits large amounts of material. As sea level rises, certain deltas can be inundated, affecting many ecosystem services. The Delta-X mission studies the Mississippi River Delta, the most famous river delta in the United States and the seventh largest river delta on Earth. This area experiences some of the largest sea level rise in the world, at 9–12 mm per year. This land loss is happening to deltas all over the world, but it is happening faster here due to subsidence.

The Delta-X mission uses airborne (remote sensing) and field measurements to look at the water, vegetation, and sediment (soil). Campaigns are scheduled for 2021, but Pre-Delta-X data are available via Earthdata Search; as campaign data are released, this pathfinder will be updated:

For more information on the mission, view Disappearing Deltas: The Delta-X Airborne Mission Investigates.

Last Updated
Oct 26, 2021