COVID-19 Data Pathfinder - Find Data

This data pathfinder links to NASA datasets/tools that can aid with decisions regarding the environmental impacts of changes in human behavior from COVID-19.
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TROPOMI data shows nitrogen dioxide density in China in early 2020. Image from NASA's Earth Observatory.

See our Health and Air Quality Data Pathfinder for more information on aerosol optical depth, trace gas data, and pollutant transport data.

Aerosol Optical Depth/Thickness | Nitrogen Dioxide | Carbon Monoxide | Ozone

Aerosol Optical Depth/Thickness

Aerosol Optical Depth (AOD) is a column-integrated value of aerosols in the atmosphere obtained by measuring the scattering and absorption of solar energy from the top of the atmosphere to the surface. The non-aerosol signal of surface reflectance needs to be separated from the aerosol signal to accurately obtain an aerosol optical depth. This is challenging because the satellite instrument cannot penetrate cloud cover and highly reflective surfaces, such as ice or snow, producing misrepresentations of the data. To address these challenges, scientists have developed algorithms for the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data to help with these effects, dark target and deep blue. For more information on these algorithms see: Dark Target Algorithm and Deep Blue Algorithm. In the latest dataset collection, these two have been merged, using the highest quality for each. While it does provide the easiest use of global coverage, there are some risks (see the websites above for more information).

The joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) instrument collects AOD data at a much finer spatial resolution. VIIRS uses the Deep Blue (DB) algorithm over land and the Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water to determine atmospheric aerosol loading for daytime cloud-free, snow-free scenes. With all of the VIIRS data, downloading a file will provide the data with just the land algorithm, just the ocean algorithm, and the merged algorithm. As with all remote sensing data, make sure you are choosing the best product for your area.

Research-quality data products can be accessed via Earthdata Search. Data are in HDF or NetCDF format and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through the Giovanni online interactive tool. 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, 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.

  • OMI AOD in Giovanni
    The Ozone Monitoring Instrument (OMI) aboard the Aura satellite has a coarser spatial resolution than MODIS and VIIRS but provides data at individual wavelengths from the ultraviolet (UV) to the visible. Within Giovanni, you can plot daily data at these individual wavelengths. This is important because pollutants have different spectral signatures; for example, a wavelength range around 400 nm can be used to detect elevated layers of absorbing aerosols such as biomass burning and desert dust plumes. The two AOD products provided through Giovanni use two different algorithms—OMI Multi-wavelength (OMAERO) and OMI UV (OMAERUV). OMI Multi-wavelength (OMAERO) is based on the multi-wavelength algorithm and uses up to 20 wavelength bands between 331 nm and 500 nm. This algorithm uses reflectance for a wide variety of microphysical aerosol models representative of desert dust, biomass burning, volcanic, and weakly absorbing aerosol types. OMI UV (OMAERUV) uses the near-UV algorithm, which is capable of retrieving aerosol properties over a wider variety of land surfaces than is possible using measurements only in the visible or near-infrared, because the reflectance of all terrestrial surfaces (not covered with snow) is small in the UV.
  • MODIS AOD in Giovanni
    Provides data products with both algorithms as well as the combined algorithm at daily and monthly intervals.

Near real-time (NRT) data can be accessed via Worldview:

  • MODIS Aqua/Terra Combined Algorithm AOD
    The merged Dark Target/Deep Blue Aerosol Optical Depth layer provides a more global, synoptic view of aerosol optical depth over land and ocean. It is available from 2000 to present.
  • VIIRS Level 2 Deep Blue Aerosol Product
    The product uses the Deep Blue algorithm over land and the Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water to determine atmospheric aerosol loading. The product is designed to facilitate continuity in the aerosol record. Deep Blue uses measurements from multiple Earth-observing satellites to determine the concentration of atmospheric aerosols along with the properties of these aerosols.
  • OMI AOD Multi-wavelength and UV
    The multi-wavelength layer and the UV absorbing layer displays the degree to which airborne particles (aerosols) prevent the transmission of light through the process of absorption (attenuation), and the UV extinction layer indicates the level at which particles in the air (aerosols) prevent light (extinction of light) from traveling through the atmosphere. Toggling between these three can provide more distinction on the types of aerosols present.

Nitrogen Dioxide

Nitrogen Dioxide (NO2) is a pollutant, the primary sources being the burning of fossil fuels, automobiles, and industry.

Once in the air, it can aggravate respiratory conditions in humans, especially those with asthma, leading to an increase of symptoms, hospital admissions, and emergency visits. Long-term exposure can lead to the development of asthma and potentially increase susceptibility to respiratory infections. NO2 reacts with other chemicals in the atmosphere, forming particulate matter and ozone, producing haze and even acid rain, and contributing to nitrogen pollution in coastal waters. NASA Goddard Space Flight Center's Air Quality site provides more information on NO2, as well as trend maps and pre-made images of NO2 over cities and power plants.

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

  • OMI NO2 data from Earthdata Search
    OMI provides daily gridded and non-gridded products at 13x24 km resolution; data are in HDF5 format and can be opened using Panoply. A tutorial on using OMI NO2 data is available as a PDF and a webinar on Analyzing NO2 data within Java and Excel is available from NASA's Earthdata YouTube channel.
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    TROPOspheric Monitoring Instrument tropospheric vertical column of nitrogen dioxide data opened using NASA's Panoply application. The red circle indicates a change needed in the scaling factor, due to the very small numbers.
    TROPOMI NO2 from Earthdata Search
    The TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P, is a European Space Agency (ESA) Mission, The ESA TROPOMI NO2 provides additional information on this Level 2 data product. It is important to note that, because of the very small numbers in tropospheric vertical column of NO2, you will need to change the scaling factor in Panoply (see image from June 2018 to right). Data are NetCDF and can be opened using Panoply.

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, 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.

NRT data can be accessed via Worldview:

NASA also has a global nitrogen dioxide monitoring site that provides imagery of daily NO2 from OMI.

Carbon Monoxide

Carbon Monoxide (CO) is a harmful pollutant that is released when something is burned, such as in the combustion of fossil fuels, the primary source, or biomass burning. Outdoor levels are rarely high enough to cause issues; when they do reach dangerous levels, however, they can be of concern to people with certain types of heart disease.

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

  • AIRS CO data from Earthdata Search
    Atmospheric Infrared Sounder (AIRS) measures abundances of trace components in the atmosphere including carbon monoxide. Data are available daily (AIRS3STD), over 8 days (AIRS3ST8), or monthly (AIRS3STM). The instrument measures the amount of CO in the total vertical column profile of the atmosphere (from Earth’s surface to top-of-atmosphere). Data are in HDF format, and can be opened using Panoply.
  • MOPITT CO data from Earthdata Search
    Measurements of Pollution in the Troposphere (MOPITT) measures the amount of CO present in the total vertical column of the lower atmosphere (troposphere) and is measured in mole per square centimeter (mol/cm2). Data are available daily or monthly. Data are acquired using the thermal and near-infrared channels. Data are in HDF5 format, and can be opened using Panoply.
  • TROPOMI CO data from Earthdata Search
    ESA TROPOMI CO provides additional information on this Level 2 data product. As with the nitrogen oxide data above, you will need to adjust the scaling factor. Data are in NetCDF format and can be opened using Panoply.

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, 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.

Near real-time (NRT) data can be accessed via Worldview:

  • AIRS CO data in Worldview
    AIRS Level 2 data are nominally 45 km/pixel at the equator but the data in Worldview has been resampled into a 32 km/pixel visualization. The data are in units of parts per billion by volume at the 500 hPa pressure level, approximately 5500 meters (18,000 feet) above sea level.
  • MOPITT CO data in Worldview

Ozone

Ozone (O3) can be either good or bad, depending on where it is found in the atmosphere. In the stratosphere, O3 protects humans, plants, and animals from harmful UV radiation. In the troposphere or closer to the ground level, however, O3 serves as a potent greenhouse gas and can aggravate existing health problems in humans, especially those with respiratory illnesses. O3 is not emitted directly into the atmosphere but instead forms from the chemical reaction between nitrogen oxides and volatile organic compounds, emitted primarily from cars, power plants, and other industrial facilities; reactions take place in the presence of sunlight. Because of the need for sunlight, unhealthy levels are most often reached on very sunny days and in urban environments.

Research-quality data products can be accessed via Earthdata Search. There are several options and determining which to use can be a challenge. The table in About the Data may be of use as it provides information on spatial and temporal resolution.

  • OMI O3 data from Earthdata Search
    OMI provides daily total column data; data are in HDF5 format and can be opened using Panoply.
  • AIRS O3 data from Earthdata Search
    AIRS measures abundances of trace components in the atmosphere including ozone. Data are available daily (AIRS3STD), over 8 days (AIRS3ST8), or monthly (AIRS3STM). The instrument measures the amount of O3 in the total vertical column profile of the atmosphere (from Earth’s surface to top-of-atmosphere). Data are in HDF format and can be opened using Panoply.
  • TROPOMI O3 data from Earthdata Search
    ESA TROPOMI O3 provides additional information on this level 2 data product. Data are in NetCDF format and can be opened using Panoply.

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, 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.

NRT data can be accessed via Worldview:

Trends on a national and regional level are available through the Environmental Protection Agency’s Air Quality Trends.

NASA’s Goddard Earth Science Data Information Services Center (GES DISC) has developed an Air Quality and Climate Anomaly Viewer, which contains information on population, AOD, NO2, and O3, as well as temperature and precipitation anomalies. They have also put out a story map on changes in the observed tropospheric NO2 column density.

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The images show changes in activity around the city of Wuhan, China, between January 19 and February 4, 2020. Credit: NASA Earth Observatory.

Observing the Earth at night provides some insight into human behaviors, from the observation of various religious or cultural events to illegal fishing to a decrease in city traffic. The Suomi NPP VIIRS nighttime imagery layer shows the Earth’s surface and atmosphere using a sensor designed to capture low-light emission sources, under varying illumination conditions, which can aid in our understanding of how nighttime lights change due to changes in human behaviors.

Research-quality data products can be accessed via Earthdata Search, and NRT data can be accessed via Worldview:

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 Day/Night Band radiances. Black Marble data can be accessed at NASA's Level-1 and Atmosphere Archive and Distribution System Distributed Active Archive Center (LAADS DAAC). Black Marble imagery in Worldview is an image composite that was assembled from clear, cloud free images for 2012 and 2016.

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Chesapeake Bay and surroundings, mosaic of five Landsat images taken in October and November 2014. Credit: USGS.

The Water Quality Data Pathfinder has additional information on the use and processing of ocean color data, as well as the integration of ground-based data with satellite or airborne data.

Ocean color is measured based on the amount of absorption by particles (e.g., phytoplankton, sediments, colored dissolved organic matter [CDOM]) and in turn, the amount of water-leaving radiance. Having a quantitative measure of these parameters is useful in understanding how water bodies, such as the ocean, are evolving, as well as determining the quality of the water for consumption by living organisms. The primary means of measuring ocean color from space is through Landsat, the Terra and Aqua satellites, Suomi NPP, and ESA’s suite of Sentinel missions. Each of these satellites has sensors acquiring data at different spatial, temporal, spectral, and radiometric resolutions (for detailed information on these, read What is Remote Sensing?).

In addition to ocean color, sea surface temperature (SST) is a valuable parameter as warmer waters can contribute to the growth of algal blooms. However, in the ocean cold upwelling waters usually bring nutrients from the seafloor fueling marine phytoplankton blooms. In the MODIS and VIIRS data, there is also an inherent optical properties (IOP) file, which provides an estimate of reflectance by CDOM. Specifically, the adg_443_giop is the absorption coefficient of non-algal material plus CDOM. For more information on the algorithm used to generate this product and others, view the Ocean Biology DAAC (OB.DAAC) algorithm descriptions.

Research-quality data products can be accessed via Earthdata Search or through NASA partner websites:

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, 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.

  • Level 3 data products from OB.DAAC
    Data products include chlorophyll-a concentration, SST, reflectance, and other related measurements from MODIS and VIIRS at 4 km and 9 km resolution. These data products are provided in five temporal resolutions: daily, 8-day, monthly, seasonally, and annually.
  • Aqua MODIS Chlorophyll-a Concentration data from Giovanni
    Data products from MODIS on the Aqua satellite at 4 km resolution provided at both 8-day and monthly temporal resolutions.
  • Aqua MODIS SST data from Giovanni
    Data products from MODIS on the Aqua satellite at 4 km resolution provided at both 8-day and monthly temporal resolutions.
NRT data can be accessed via Worldview:

The Biological Diversity and Ecological Forecasting Data Pathfinder has additional information on vegetation characteristics, species distribution modeling, and spectroscopy.

Surface Reflectance | Vegetation Greenness | Land Surface Temperature | Evapotranspiration

Surface Reflectance

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Extensive deforestation and fragmentation are visible in this satellite image, acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on August 24, 2000, of the state of Rondonia, Brazil, along the Jiparaná River. Tropical rainforest appears bright red, while pale red and brown areas represent cleared land. Black and gray areas have probably been recently burned. The Jiparaná River appears blue. Credit: NASA and the U.S./Japan ASTER Science Team.

Surface reflectance is useful for monitoring changes within the landscape. Moderate resolution instruments that are primarily used for this measurement include MODIS and VIIRS. MODIS reflectance products are available at 250 m, 500 m, 1000 m, and 5600 m spatial resolution. VIIRS reflectance products are available at 500 m and 1000 m spatial resolution. MODIS data are acquired every one to two days, whereas the wider swath width of VIIRS allows for daily global coverage.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), another high-resolution instrument, acquires visible and near-infrared (VNIR) reflectance data at 15 m resolution and short-wave infrared (SWIR) reflectance data at 30 m resolution (through 2009). Note that ASTER is a tasked sensor, meaning that it only acquires data when it is directed to do so over specific targets, making its temporal resolution variable depending on your target region of interest. ASTER Surface Reflectance products are processed on-demand and so must be requested with additional parameters. Note that there is a limit to 2000 granules per order.

Research-quality surface reflectance data products can be accessed directly via Earthdata Search; MODIS, VIIRS, and ASTER are available in HDF format, but are also customizable to GeoTIFF:

NASA's Land Processes DAAC (LP DAAC) also provides a tool called the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS). AppEEARS offers a simple and efficient way to access, transform, and visualize geospatial data from a variety of federal data archives. MODIS and VIIRS surface reflectance data are available in AppEEARS, as well as the USGS Landsat Analysis Ready Data (ARD) surface reflectance product.

NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC) also provides tools for on-demand subsetting of MODIS and VIIRS land data. In particular, the Subsets API allows users to retrieve custom subsets, analytics, and visualization of MODIS and VIIRS data products.

For higher resolution, the Landsat 7 Enhanced Thematic Mapper (ETM+) sensor and the Landsat 8 Operational Land Imager (OLI) instrument acquire data at 30 m spatial resolution in VNIR every 16 days (or less as you move away from the equator). Landsat 8 was developed as a collaboration between NASA and the USGS. The USGS now leads satellite operations and data archiving at the Earth Resources Observation and Science (EROS) center.

Landsat data can be discovered using Earthdata Search, however, you will need a USGS Earth Explorer login to download the data.

Another high resolution option is the new (but currently provisional) Harmonized Landsat and Sentinel-2 (HLS) project, which provides consistent surface reflectance and top of atmosphere brightness data from the OLI aboard the joint NASA/USGS Landsat 8 satellite and the Multi-Spectral Instrument (MSI) aboard Europe’s Copernicus Sentinel-2A and Sentinel-2B satellites. The combined measurement enables global observations of the land every 2–3 days at 30-meter (m) spatial resolution. 

Data can be visualized in Worldview:

  • MODIS True Color in Worldview
    Note that Worldview does have a corrected reflectance product but it is not a standard, research-quality product. The purpose of this algorithm is to provide natural-looking images by removing gross atmospheric effects, such as Rayleigh scattering, from MODIS visible bands 1-7.
  • HLS Surface Reflectance in Worldview

Vegetation Greenness

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False-color image of Normalized Difference Vegetation Index (NDVI) data of King Fire area, September 2013 (left) and Nov 2014. Credit: ORNL DAAC.

Vegetation indices measure the amount of green vegetation over a given area and can be used to assess vegetation health. A commonly-used vegetation index is the Normalized Difference Vegetation Index (NDVI), which uses the difference between near-infrared (NIR) and red reflectance divided by their sum. NDVI values range from -1 to 1. Low values of NDVI generally correspond to barren areas of rock, sand, exposed soils, or snow, while higher NDVI values indicate greener vegetation, including forests, croplands, and wetlands. The enhanced vegetation index (EVI) is another widely used vegetation index that minimizes canopy-soil variations and improves sensitivity over dense vegetation conditions.

Vegetation products from the MODIS instrument and the VIIRS instrument satellite can be accessed in various ways:

Research-quality surface reflectance data products can be accessed directly via Earthdata Search or LP DAAC's Data Pool; datasets are available in HDF format but are, in some cases, customizable to GeoTIFF.

LP DAAC's  AppEEARS offers a simple and effective way to extract, transform, visualize, and download MODIS and VIIRS vegetation-related data products. AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest, and output data can be downloaded in csv (point), GeoTIFF (area) or NetCDF4 (area) format. Explore the Getting Started with Cloud-Native HLS Data in Python Jupyter Notebook for extracting an EVI Time Series from HLS.

ORNL DAAC subsetting tools provide a means to simply and efficiently access and visualize MODIS and VIIRS vegetation-related data products as well.

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 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.

Data can be visualized in Worldview:

  • MODIS NDVI in Worldview
    This dataset has a spatial resolution of 250 m and a temporal resolution of eight days. 16-day and monthly data are also available within Worldview.
  • MODIS EVI in Worldview
    This dataset is monthly at 1 km spatial resolution. Rolling 8-day and 16-day data are also available within Worldview.

Land Surface Temperature

Research-quality land surface temperature data products can be accessed directly from Earthdata Search. MODIS and ASTER data are available as HDF. VIIRS and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) data are available as HDF5:

To quickly extract a subset of ECOSTRESS, MODIS, or VIIRS data for your region of interest, use LP DAAC's AppEEARS tool or the ORNL DAAC subsetting tools.

Landsat data can be discovered using Earthdata Search, however, you will need a USGS Earth Explorer login to download the data.

Data can be visualized in Worldview:

Evapotranspiration

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The combination of evaporation from the land surface and transpiration from plants is evapotranspiration, abbreviated ET. This parameter approximates the consumptive use of a landscape’s plants. Credit: U.S. Geological Survey.

Measurements of evapotranspiration (ET), the sum of evaporation from land surface and transpiration in vegetation, are extremely useful in monitoring and assessing water availability, drought conditions, and crop production. One of the challenges in acquiring ET data is that ET can’t be measured directly with satellite instruments as it is dependent on many other variables, such as land surface temperature, air temperature, and solar radiation. However, there are Level 4 data products (see data processing levels for more information) that incorporate daily meteorological reanalysis data with remote sensing data to arrive at estimations of ET. MODIS has such a product. Meteorological reanalysis data are assimilated products from historical atmospheric data from an extended period of time.

Research-quality MODIS Level 4 ET products are available in yearly and 8-day temporal resolutions with 500 m pixel size.

NASA's ECOSTRESS, aboard the International Space Station (ISS), measures the temperature of plants to better understand how they respond to the stress of insufficient water availability. ECOSTRESS was launched in June 2018 and uses a multispectral thermal infrared radiometer to measure radiance, which is converted into surface temperature and emissivity. ECOSTRESS produces Level 3 ET data products according to the Priestly-Taylor Jet Propulsion Laboratory (PT-JPL) algorithm, using the surface temperature and emissivity as inputs (among other ancillary data inputs from other sources).

Research-quality ECOSTRESS ET data products can be accessed directly via Earthdata Search or LP DAAC's Data Pool; datasets are available in HDF format but are, in some cases, customizable to GeoTIFF.

LP DAAC's AppEEARS offers a simple and effective way to extract, transform, visualize, and download MODIS and ECOSTRESS ET data products. AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest, and output data can be downloaded in csv (point), GeoTIFF (area), or NetCDF4 (area) format.

ORNL DAAC's subsetting tools also provide a means to simply and efficiently access and visualize MODIS ET data products.

The Land Data Assimilation System (LDAS) provides model-based ET data of which there is a global collection (GLDAS) and a North American collection (NLDAS). LDAS uses measurements of precipitation, soil texture, topography, and leaf area index to model soil moisture and evapotranspiration. When calculating ET, there are biases around seasonality or local-specific effects but developers try to account for those and calibrate accordingly; estimates of ET are provided every day and integrated to get monthly, seasonal, or annual information within a 2-12% error.

GLDAS 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.

  • GLDAS ET in Giovanni
    Data are available with a temporal resolution of 3-hourly, daily, and monthly.

A simple-to-use mapping tool at NASA’s Socioeconomic Data and Applications Center (SEDAC) shows demographic data along with regularly updated information about reported global cases of the disease caused by COVID-19.

SEDAC also has datasets related to population density and size, urban extent, land use and land cover, poverty.

 

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Surface air temperature, measured in Kelvin, from the Atmospheric Infrared Sounder (AIRS), May 9, 2020, visualized in Panoply.

The Atmospheric Infrared Sounder (AIRS) on the Aqua satellite daily gathers the infrared energy emitted from Earth's surface and atmosphere globally. The data provide 3-dimensional measurements of temperature and water vapor through the atmospheric column. AIRS data are available in near real-time (NRT). In addition, the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) covers the period 1980-present and so provides for ongoing climate analysis.

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

  • AIRS Surface Air Temperature from Earthdata Search
    AIRS data are daily, 8-day, and monthly at 1 degree and the Level 3 data products are provided in either the descending (equatorial crossing North to South at 1:30 AM local time) or ascending (equatorial crossing South to North at 1:30 PM local time) orbit. When you open the HDF file (in a program like Panoply or QGIS), you will see an ascending option and a descending option each with SurfAirTemp.
  • MERRA-2 Temperature from Earthdata Search
    There are several options available: 1-hourly, 3-hourly, 6-hourly. These options provide information on surface skin temperature, the air temperature at 2 m, and the air temperature at 10 m.

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, 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.

Data can be visualized in Worldview:
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Relative humidity at 2 m above the surface from MERRA-2 visualized in the Prediction of Worldwide Energy Resources (POWER) Data Access Viewer. The graphs display percent relative humidity for the single point over South Carolina.

The Atmospheric Infrared Sounder (AIRS) on the Aqua satellite daily gathers the infrared energy emitted from Earth's surface and atmosphere globally. The data provide 3-dimensional measurements of temperature and water vapor through the atmospheric column. AIRS data are available in near real-time (NRT). In addition, the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) covers the period 1980-present and so provides for ongoing climate analysis.

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

  • AIRS Relative Humidity from Earthdata Search
    AIRS data are daily at 1 degree and the Level 3 data products are provided in either the descending (equatorial crossing North to South at 1:30 AM local time) or ascending (equatorial crossing South to North at 1:30 PM local time) orbit. When you open the HDF file (in a program like Panoply or QGIS), you will see an ascending option and a descending option each with RelHumSurf.
  • MERRA-2 Humidity from Earthdata Search
    There are several options available: 1-hourly, 3-hourly, 6-hourly. These options provide information on surface specific humidity, specific humidity at 2 m, and relative humidity.

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, 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.

Data can be visualized in Worldview:

NASA’s Prediction of Worldwide Energy Resources (POWER) Data Access Viewer provides visualizations of temperature and humidity at 2 m.

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Time Averaged Map of Irradiance at a wavelength of 310 nm (Local Noon) for June 12, 2020. Data are from the Ozone Monitoring Instrument (OMI) aboard the Aura spacecraft as visualized in Giovanni.

Ultraviolet (UV) radiation that reaches the Earth’s surface is in wavelengths between 290 and 400 nm. UV radiation from the sun has always played important roles in our environment, and affects nearly all living organisms. The Ozone Monitoring Instrument (OMI) aboard the Aura spacecraft and the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P provide measurements of solar irradiance at various wavelengths, including UV. OMI data are within UV wavelengths between 305-380 nm. TROPOMI data are within UV to shortwave infrared (SWIR) wavelengths. TROPOMI Bands 1 (270-300 nm), 2 (300-320 nm), and 3 (320-405) provide specific measurements for UV wavelengths. Note: UV-A is 320-400 nm and UV-B is 290-320 nm.

Research quality data products can be accessed via Earthdata Search:

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, 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.

UV index at local solar noon and UV erythemal daily dose at local solar noon can be visualized in Worldview:

 

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Near real-time IMERG Early Run Half-Hourly Image, acquired on May 7, 2020. Credit: NASA.

NASA’s Precipitation Measurement Missions (PMM) provide a continuous long-term record (over 20 years) of precipitation data through the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) mission. GPM, a follow-on mission for TRMM, provides even more accurate measurements, improved detection of light rain and snow, and extended spatial coverage.

The products from TRMM and GPM are available individually and have also been integrated with data from a global constellation of satellites to yield improved spatial/temporal precipitation estimates providing a temporal resolution of 30 minutes (in the case of GPM). The integrated products are the TRMM Multi-satellitE Precipitation Analysis (TMPA) and the Integrated Multi-satellite Retrievals for GPM (IMERG). IMERG’s multiple runs accommodate different user requirements for latency and accuracy (Early = 4 hours, e.g., for flash flood events; Late = 12 hours, e.g., for crop forecasting; and Final = 3 months, with the incorporation of rain gauge data, for research).

NASA, in collaboration with other agencies, has also developed models of precipitation, incorporating satellite information with ground-based data when available. These models are part of the Land Data Assimilation System (LDAS), of which there is a global collection (GLDAS) and a North American collection (NLDAS). LDAS takes inputs of measurements like precipitation, soil texture, topography, and leaf area index and then uses those inputs to model output estimates.

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

  • TMPA from Earthdata Search
    Rainfall estimate at 3 hours, 1 day, or near real-time (NRT) and accumulated rainfall at 3 hours and 1 day. Data are in HDF format, and can be opened using Panoply. Data are available from 1997.
  • IMERG from Earthdata Search
    Early, Late, and Final precipitation data on the half hour or 1-day timeframe. Data are in NetCDF or HDF format, and can be opened using Panoply. Data are available from 2000.

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.

Near real-time data can be accessed from Worldview:

Daymet is a collection of gridded estimates of daily weather parameters. It is modeled on daily meteorological observations. Weather parameters in Daymet include daily minimum and maximum temperature, precipitation, vapor pressure, radiation, snow water equivalent, and day length at 1 km resolution over North America, Puerto Rico, and Hawaii.

Daymet data can be retrieved in a variety of ways, including: Earthdata Search; a NASA Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) API; ORNL DAAC tools; and through NASA's Land Processes DAAC (LP DAAC) Application for Extracting and Exploring Analysis Ready Samples (AppEEARS).

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The Soil Moisture Active Passive satellite. Credit: NASA.

Current ground measurements of soil moisture are sparse and have limited coverage; satellite data help fill in those gaps. On the other hand, satellite data are limited by their relatively coarse resolution; the preferred measurement should be chosen based upon your needs. Utilizing a combination of both ground-based and remote sensing data provides for spatial and temporal data continuity.

NASA's Soil Moisture Active Passive (SMAP) satellite measures the moisture in the top 5 cm of soil globally, every 2-3 days, at a resolution of 9-36 km. NASA, in collaboration with other agencies, has also developed models of soil moisture content, incorporating satellite information with ground-based data when available. These models are part of the LDAS, of which there is a global collection (GLDAS) and a North American collection (NLDAS). LDAS takes inputs of measurements like precipitation, soil texture, topography, and leaf area index and then uses those inputs to model output estimates of soil moisture and evapotranspiration.

Research-quality data products can be accessed via Earthdata Search; datasets are available in HDF5 format, which are also customizable to GeoTIFF.

ORNL DAAC's Soil Moisture Visualizer integrates ground-based, SMAP, and other soil moisture data into a visualization and data distribution tool. See the Tools for Data Access and Visualization section for additional information.

AppEEARS offers another option to simply and efficiently extract subsets, transform, and visualize SMAP data products.

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.

NRT imagery can be accessed via Worldview:

Changes in groundwater storage can be measured from space using Gravity Recovery And Climate Experiment (GRACE) data. 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 there are several limitations with GRACE data:

  • The resolution of the data are greater than 150,000km2 so it only measures change within large aquifers;
  • GRACE cannot detect issues of water quality (salt water intrusion, chemicals, etc.);
  • GRACE does not provide information on groundwater flow because the satellite only measures in one dimension, while groundwater flow is not limited to one dimension; and
  • GRACE does not provide information on whether the aquifer is confined or unconfined.

The value of GRACE data is evident when doing regional studies to determine general trends in groundwater storage.

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

  • Groundwater Storage Percentile from Earthdata Search
    This serves as a drought indicator and the data are based on terrestrial water storage observations derived from GRACE satellite data and integrated with other observations, using a sophisticated numerical model of land surface water and energy processes.

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. 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.

GRACE observations are acquired through two formation-flying satellites. In processing the data, scientists must run a complex inversion algorithm with precise GPS information and acceleration corrections. Many parameter choices and solution strategies are possible. Three different teams have taken on this task—GeoForschungsZentrum Potsdam (GFZ), the Center for Space Research (CSR) at the University of Texas at Austin, and NASA's Jet Propulsion Laboratory (JPL)—all producing slightly different results. Recent peer-reviewed papers found that the simple, arithmetic mean of JPL, CSR, and GFZ fields reduced the noise in the gravity field solutions. For more information on the three different solutions, see Choosing a Solution on GRACE's website. Data are represented as Water Equivalent Thickness (WET), which is a way of representing changes in the gravity field in hydrological units.

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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.
  • GRACE Groundwater WET: monthly data from 2002–2017 from each solution in ASCII or GeoTIFF format. The NetCDF format data are averaged 2002–2017 data. The mean of the three can be calculated in most GIS systems (see figure above).
Last Updated
Oct 25, 2021