Extreme Heat Data Pathfinder - Find Data

Abnormally hot and/or humid weather lasting a few days to weeks at a time are occurring more frequently in major cities across the world. These events can have detrimental impacts on public health. NASA data can aid with forecasting and monitoring extreme heat events.
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Surface air temperature, measured in Kelvin, from the Atmospheric Infrared Sounder (AIRS), May 9, 2020, visualized in Panoply. To convert to Celsius, subtract 273.15 from the Kelvin temperature. Click on image for larger view. Credit: AIRS/NASA.

Extreme heat, by definition, implies high air or surface temperature. By calculating the average temperature over a range of time (typically about 30 years) and comparing the forecasted high temperature to this average, one can determine if temperatures are outside the normal range for the forecast period. An anomaly analysis or difference map is necessary to do this and can be created using Giovanni or Panoply. Giovanni provides monthly and seasonal average maps as well as time-averaged map for the month or given time period of investigation (Note: An Earthdata Login is required for full Giovanni functionality). The file in NetCF format can then be downloaded and opened in the NASA Panoply data viewer, where you can create a difference map with the "combine plot" option (see the Earthdata webinar Create Difference Maps for NASA Data with Panoply, Giovanni, and Excel for more information on this process).

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

  • AIRS Surface Air Temperature
    NASA's Atmospheric Infrared Sounder (AIRS) aboard NASA's Aqua satellite gathers infrared energy emitted from Earth's surface and atmosphere globally every day. AIRS data are daily, 8-day, and monthly at 1° and the Level 3 data products are provided in either the descending (equatorial crossing North to South at 1:30 a.m., Mean Local Time [MLT]) or ascending (equatorial crossing South to North at 1:30 p.m., MLT) orbit. When you open the file in HDF format (using a program like Panoply or QGIS), you will see an ascending option and a descending option each with SurfAirTemp.
  • MERRA-2 Temperature
    The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns, as well as anomalies. 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 using an online interactive tool called Giovanni (Note: An Earthdata Login is required for full Giovanni functionality):

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, often in near real-time (NRT), are available for visualization using the NASA Worldview data visualization application:

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Satellite images show the differences in land surface temperature during the day (middle image) and at night (bottom image) over the state of Oregon. Top image is a natural color image. Darker colors indicate cooler temperatures. Heavily forested areas remain relatively cool throughout the day while barren and arid areas can be significantly warmer. These images were acquired in the early morning and afternoon of July 6, 2011. Click on image for larger view. Credit: NASA Earth Observatory.

Land surface temperatures are in part affected by the albedo, or reflectance, of a surface. Dark surfaces, like asphalt, concrete, and brick, tend to have a low albedo and so absorb and retain more of the Sun's incoming radiation, resulting in higher temperatures. Light, highly reflective surfaces, such as fresh snow, have a high albedo and do not absorb incoming solar radiation as rapidly. Surface temperatures vary more than air temperatures during the day and are more pronounced after sunset due to the slow release of heat from impervious surfaces.

Research-quality land surface temperature data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA's Aqua and Terra satellites, the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard Terra, and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) can be accessed directly from Earthdata Search (Note: An Earthdata Login is required to download data). In addition, the North American Land Data Assimilation System (NLDAS) monthly climatology dataset, accessible from Earthdata Search, contains a series of land surface parameters simulated from the Noah land-surface model, from 1980-2009.

Links to data in Earthdata Search:

To quickly extract a subset of ECOSTRESS, MODIS, or VIIRS data for a region of interest, use AppEEARS, available through NASA's Land Processes Distributed Active Archive Center (LP DAAC) or subsetting tools available through NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC).

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

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

  • NLDAS Surface Temperature
    There are a variety of options including hourly and monthly data. North American Land Data Assimilation System (NLDAS) data are land model output files from 1979 to present. There is also a monthly climatology dataset that contains a series of land surface parameters simulated from the Noah land-surface model from 1980-2009.

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 using the NASA Worldview data visualization application:

The NASA Prediction of Worldwide Energy Resources (POWER) Data Access Viewer provides solar and meteorological datasets through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are GIS ready. MODIS Land Surface Temperature is also available through LP DAAC's geospatial web map service.

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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. Click on image for larger view. Credit: POWER.

Humidity is a measure of the amount of water vapor present in the air and plays an important role for surface life. For animal life dependent on perspiration (sweating) to regulate internal body temperature, high humidity impairs heat exchange efficiency by reducing the rate of moisture evaporation from the skin. When humidity is combined with temperature, a heat index value can be calculated, which is an indication of how hot it feels. High humidity and high air temperature can result in dangerously high heat index readings. For example, if the air temperature is 96°F and the relative humidity is 65%, the heat index, or how hot it feels, is 121°F.

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

  • AIRS Relative Humidity
    AIRS data are daily at 1° and the Level 3 data products are provided in either the descending (equatorial crossing North to South at 1:30 a.m., Mean Local Time [MLT]) or ascending (equatorial crossing South to North at 1:30 p.m., MLT) orbit. Note that the data were acquired only until 2016.
  • MERRA-2 Humidity
    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 using an online interactive tool called Giovanni (Note: An Earthdata Login is required for full Giovanni functionality):

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, often in near real-time (NRT), can be visualized using the NASA Worldview data visualization application:

The NASA Prediction of Worldwide Energy Resources (POWER) Data Access Viewer provides solar and meteorological datasets through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are GIS ready.

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Day and night surface temperature comparisons for a variety of landcover types. Click on image for larger view. Credit: U.S. Environmental Protection Agency.

Temperature data measured by instruments aboard Earth observation satellites and at ground level show that urban areas tend to have higher average temperatures than the more rural areas around them. These warmer urban areas are called “urban heat islands.” The increased heat seen in urban areas is caused by numerous factors, including high amounts of concrete and asphalt (which retain and slowly dissipate heat) and higher concentrations of vehicles with internal combustion engines (which produce greenhouse gasses that trap heat). Landcover plays a critical role in monitoring urban environments for excess heat.

The Terra and Aqua MODIS Land Cover Type data product provides global land cover types at yearly intervals. The product is derived using supervised classifications of MODIS Terra and Aqua reflectance data. The supervised classifications then undergo additional post-processing to further refine specific classes. This layer defines land cover type based on the International Geosphere-Biosphere Programme classification scheme.

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These images from the joint NASA/USGS Landsat mission show the cooling effects of plants on New York City’s heat. Left image: Areas that are dark green have dense vegetation (such as Central Park near the center of the image). Right image: Dark purple regions indicate areas with lower temperatures. Notice how these regions match up with the darker green areas in the left image. Credit: Maps by Robert Simmon, using data from the Landsat Program.

Vegetation indices have been developed to measure the amount of green vegetation over a given area and can be used to assess vegetation health. One commonly used vegetation index is the Normalized Difference Vegetation Index (NDVI), which takes 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. Increasing NDVI values indicate greener vegetation, including forests, croplands, and wetlands.

Another vegetation index is the enhanced vegetation index (EVI). EVI minimizes canopy-soil variations and improves sensitivity over dense vegetation. Vegetation products from MODIS and Suomi NPP VIIRS can be accessed in various ways.

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

Datasets are available as HDF files but are, in some cases, customizable to GeoTIFF.

The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS), available through the Land Processes DAAC (LP DAAC), offers the ability to extract subsets, transform, and visualize MODIS and VIIRS vegetation-related data products. Subsetting tools available through NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC) provide a means to simply and efficiently access MODIS and VIIRS vegetation-related data products.

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

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 and be visualized and interactively explored using the NASA Worldview data visualization application:

  • MODIS NDVI
    This dataset has a spatial resolution of 250 m and the temporal resolution is an 8-day product, updated daily; 16-day and monthly data are also available
  • MODIS EVI
    This dataset is monthly at 1 km spatial resolution; rolling 8-day and 16-day data are also available
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NASA's Global Modeling and Assimilation Office provides applications for interactive analysis and visualizations of experimental, climatological data, like this model of precipitation and sea level pressure for May 8, 2020. Click on image for larger view. Credit: NASA GMAO.

To support NASA’s satellite missions and field experiments, NASA's Global Modeling and Assimilation Office (GMAO) generates near-real time atmospheric products using model data from the Goddard Earth Observing System (GEOS) and distributes them to a broad community of users. The GEOS "Forward Processing" (FP) system generates analyses, assimilation products, and 10-day forecasts with the most up-to-date validated version of GEOS that is available. Available forecast parameters include precipitation, humidity, wind speed, and temperature.

  • GEOS-5 Weather Maps
    Within the viewer, select the parameter or field of interest, the area of interest, and then indicate the forecast time and the forecast lead hour. Animate shows the forecast for the given parameter over the time period indicated. Note that it may take time to load the images to animate. For those variables near the surface, make sure to select 850 as your level.
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The Global Urban Heat Island Dataset, from NASA's Socioeconomic Data and Applications Center (SEDAC), estimates the difference between land surface temperatures (LST) in urban areas and surrounding rural areas. LSTs are derived from Aqua MODIS 8-day composite LST data for a 40-day timespan. Click on image for larger view. Credit: SEDAC.

Heat-related deaths are preventable, but prevention requires a knowledge of where vulnerable populations exist and what interventions are needed in these communities. For example, the urban heat island effect represents the relatively higher temperatures found in urban areas compared to surrounding rural areas due to higher proportions of impervious surfaces and the release of waste heat from vehicles and heating and cooling systems. In addition, socioeconomic status may limit a person's ability to deal with extreme heat. Increasing frequency of heat events and other natural disasters may lead to migration and a change in population composition.

NASA's Socioeconomic Data and Applications Center (SEDAC) provides a number of datasets on population exposure and vulnerability:

Last Updated
Jul 29, 2022