Air Quality Data Pathfinder - Find Data

Air pollution is one of the largest global environmental and health threats. Instruments aboard NASA satellite and airborne platforms continually acquire data about these pollutants.

Aerosol optical depth (AOD) is an assessment of the amount of visible and infrared light aerosols scatter or absorb in a column of the atmosphere, and is sometimes referred to as aerosol optical thickness (AOT). AOD is a unitless measure. From an observer on the ground, an AOD of less than 0.1 is characteristic of a clear sky, bright Sun, and maximum visibility. As AOD increases to 0.5, 1.0, and greater than 3.0, aerosols become so dense that the Sun is obscured.

Commonly Used Aerosol Optical Depth (AOD) Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use. 

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format
250 m, 500 m, 1 km, 10 km, 3 km Global Daily, 8-day, 16-day, monthly, quarterly, yearly 2000 (Terra)/2002 (Aqua)-present 36 spectral bands ranging in wavelength from 0.4 µm to 14.4 µm Terra/Aqua *Moderate Resolution Imaging Spectroradiometer (MODIS) Observation HDF-EOS
6 km, 1° Global *6-minute,
Daily,
Monthly
2012-present 0.600-0.680 µm, 3.55-3.93 µm, 10.5-12.4 µm NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS): Deep Blue Observation HDF5, HDF-EOS5
6 km Global <-minute 2012-present 0.600-0.680 µm, 3.55-3.93 µm, 10.5-12.4 µm NASA/NOAA Suomi NPP Dark Target *Visible Infrared Imaging Radiometer Suite (VIIRS): Dark Target Observation netCDF4
0.25°, 13 km x 24 km Global *~98 minutes,
Daily
2004-present 1.0-0.45 nm Full Width and Half Maximum (FWHM) Aura *Ozone Monitoring Instrument (OMI) Observation HDF-EOS5
10 km Global 12-24 per day 2017-present 10 channels from 317-779 nm Deep Space Climate Observatory (DSCOVR) EPIC Observation HDF5
0.5° x 0.625° Global 1-hourly, monthly 1980-near present N/A N/A MERRA -2 Reanalysis netCDF
N/A Varies Sub-hourly Varies by site N/A Ground-based AERONET Observation ASCII
Point measurements Global Periodic flights occurred during each deployment 2016-2018 varies Airborne Field Campaign Atmospheric Tomography Mission (ATom) campaign with varying instruments Observation netCDF

Use Aerosol Optical Depth (AOD) Data

Tutorials
Use Cases and Articles
Data Visualizations
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse Earth science data hosted by NASA's Earth Observing System Data and Information System (EOSDIS)
  • How to Access MERRA-2 Data using OPeNDAP with Python3 and Calculate Daily/Weekly/Monthly Statistics from Hourly Data
  • MERRA-2 Aerosol Diagnostics: Total PM1.0, PM2.5, and PM10 may be derived with the formula described in the in the MERRA-2 FAQ
  • NASA’s Air Quality Analytics Collaborative Framework (AQACF) Open-Source API Demonstration Jupyter Notebook featuring Los Angeles Port Backlog (Fall 2021): Beginning around October 2021, the Ports of Los Angeles and Long Beach started suffering serious backlogs of ships due a surge in e-commerce because of the COVID-19 pandemic, resulting in many ships anchored in the ports that led to high amounts of pollutants being released
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST
  • earthaccess is a Python library to search, download, or stream NASA Earth science data with just a few lines of code
  • Access repositories and Jupyter Notebooks used in ARSET trainings through GitHub

Earth Observation Data by Sensor

MODIS

Moderate Resolution Imaging Spectroradiometer (MODIS) instruments are aboard NASA’s Terra  (launched 1999) and Aqua (launched 2002) satellites and provide estimates about AOD. Terra's orbit is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon.

MODIS daily data can be visualized and interactively explored using NASA Worldview:

The non-aerosol signal of surface reflectance needs to be separated from the aerosol signal to accurately obtain AOD. Scientists have developed two algorithms for MODIS data to account for these effects: Dark Target and Deep Blue. In the latest dataset collection, these two algorithms have been merged, using the highest quality for each. For more information about the differences between these, see What is the difference between dark target and deep blue?

Dark Target and Deep Blue data can be interactively visualized using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of MODIS AOD data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Research quality MODIS data products can be accessed directly from Earthdata Search:

Near real-time (NRT) MODIS Surface Reflectance data are available through NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) within 60 to 125 minutes after a satellite observation.

MODIS/Terra and MODIS/Aqua NRT data in Earthdata Search:

MODIS/Terra and MODIS/Aqua Combined NRT data in Earthdata Search:

OMI

The Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite has a coarser spatial resolution than MODIS and VIIRS, but provides data at individual wavelengths from the ultraviolet (UV) to the visible. 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.

Daily data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of OMI AOD data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

  • OMI AOD
    • Within Giovanni, you can plot daily data at individual wavelengths
    • Benefits of using Giovanni to view these products:
      • The two AOD products provided through Giovanni use two different algorithms. 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 can provide more distinction on the types of aerosols present.
      • OMI Multi-wavelength (OMAERO)
        • Based on the multi-wavelength algorithm and uses up to 20 wavelength bands between 331 nm and 500 nm. This algorithm uses reflectances 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-IR because the reflectance of all terrestrial surfaces (not covered with snow) is small in the UV.

EPIC

The Earth Polychromatic Imaging Camera (EPIC) is a 10-channel spectroradiometer (317 to 780 nm) aboard NOAA’s Deep Space Climate Observatory (DSCOVR) spacecraft (which is a partnership between NASA, NOAA, and the U.S. Air Force). EPIC provides color images of the entire sunlit face of Earth at least once every two hours from 1 million miles away. DSCOVR’s location gives it a unique angular perspective that is used to measure ozone, aerosols, cloud reflectivity, cloud height, vegetation properties, and UV radiation estimates.

Research quality data can be accessed using Earthdata Search:

VIIRS

The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites collect AOD data at a finer spatial resolution than MODIS. VIIRS uses the Deep Blue 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. Downloading a VIIRS data file provides the data with just the land algorithm, just the ocean algorithm, and the merged algorithm.

Daily data can be accessed and interactively explored using NASA Worldview:

  • VIIRS Level 2 Deep Blue Aerosol Product
    The product uses the Deep Blue algorithm over land and the 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.

Research quality data products can be accessed using Earthdata Search:


Reanalysis Data

MERRA-2

The Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) offers a data assimilation of AOD analysis available every three hours from 1980 to present with a latency of about three weeks after the end of a month.

Monthly data can be accessed and explored interactively using NASA Worldview:

NASA's Global Modeling and Assimilation Office’s (GMAO) offers visualizations of MERRA-2 AOT data:

  • Animate and download weather maps for a variety of meteorological parameters, including MERRA-2 AOT map 
    • At the link above, you can visualize a variety of AOT parameters:  
      • Black Carbon
      • Dust
      • Fine
      • Organic Carbon
      • Sea Salt
      • Sulfate
      • Total

Using an online interactive tool called Giovanni, map visualizations of MERRA-2-analyzed AOD data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Research quality data products can be accessed using Earthdata Search and Google Earth Engine:


Ground-based Observation Data

Thirty years of ground-based AOD measurements are available through NASA’s Aerosol Robotic Network (AERONET). AERONET is a global network of ground-based Sun photometers. These photometers calculate AOD and the amount of water vapor in the atmosphere by comparing the amount of light they detect with the amount of solar radiation that would be observed in an aerosol-free atmosphere. AERONET also takes sky brightness measurements that can be used to infer aerosol size distribution, refractive index, and single scattering albedo.


Field Campaign Observation Data

ATom

The Atmospheric Tomography Mission (ATom) is a NASA Earth Venture Suborbital-2 mission to study the impact of human-produced air pollution on greenhouse gases and on chemically reactive gases in the atmosphere. ATom deployed an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Around-the-world flights were conducted in each of four seasons between 2016 and 2018.

Aerosol Index (AI) is a measurement related to AOD and indicates the presence of an increased amount of tiny suspended particles called aerosols in the atmosphere. In general, a lower AI value indicates more clear skies due to a lower concentration of aerosols. The calculation of the Aerosol Index is based on wavelength-dependent changes in Rayleigh scattering in the ultraviolet (UV) spectral range where ozone absorption is very small. The aerosol index is derived from normalized radiances using 2 wavelength pairs at 340 and 378.5 nm. UVAI can be calculated in the presence of clouds so that daily global coverage is possible. This is ideal for tracking the evolution of episodic aerosol plumes from dust outbreaks, volcanic ash, significant fire events, and biomass burning.

Commonly Used Aerosol Index (AI) Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use. 

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. For more information about the differences between NRT and Standard Science Products, please see Near Real-Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform

Name (Sensor, Model, etc.)

Observation, Model, or Reanalysis

File Format
13 km x 24 km,
13 x 12 km 0.25°, 1°
Global 98 minutes,
32 days
2004-present 1.0-0.45 nm Full Width and Half Maximum (FWHM) Aura Ozone Monitoring Instrument (OMI) Observation HDF-EOS5
50 km* Global 101 minutes, Daily 2018-present 250-420 nm
*NRT:wavelength pairs at 340 and 378.5 nm
NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) *Ozone Mapping and Profiler Suite (OMPS) Observation HDF5
7 km x 3.5 km,
5.5 km x 3.5 km
Global 101.5 minutes, Daily 2017-present 270 nm–2.3 µm, 0.55 nm Sentinel-5P TROPOMI Observation netCDF
0.5º x 0.625° Global Monthly 1980-present N/A N/A MERRA-2 Reanalysis netCDF

Use Aerosol Index (AI) Data

Tutorials
Use Cases and Articles
Data Visualizations

 

NASA's Air Quality and Climate Anomaly Viewer

GIS-Ready Tools and Tutorials
Data Access Tools

The NASA Earthdata Cloud Cookbook has tutorials to help access Earth science data in the cloud

Data Customizing Tools
Programming Tools
  • NASA’s Air Quality Analytics Collaborative Framework (AQACF) Open-Source API Demonstration Jupyter Notebook featuring the Dixie Wildfire (2021). The Dixie Wildfire was the largest single (i.e. non-complex) wildfire in recorded California history
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse EOSDIS-hosted Earth science data
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST
  • earthaccess is a Python library to search, download or stream NASA Earth science data with just a few lines of code
  • Access repositories and Jupyter Notebooks used in ARSET trainings through GitHub

Earth Observation Data by Sensor

OMI

The Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite has a coarser spatial resolution than MODIS and VIIRS, but provides data at individual wavelengths from the ultraviolet (UV) to the visible. 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.

Daily data can be accessed and interactively explored using NASA Worldview:

OMI AI

Using an online interactive tool called Giovanni, map visualizations of OMI AI data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Level 2 data are available 

OMPS

OMPS Aerosol Index layer indicates the presence of UV-absorbing particles in the air.

Daily data can be accessed and interactively explored using NASA Worldview:

Level 2 data are available in Earthdata Search:

TROPOMI

The Tropospheric Monitoring Instrument (TROPOMI) was co-funded by ESA (European Space Agency) and the Netherlands and is the single payload aboard ESA's Sentinel-5P spacecraft. TROPOMI measures solar radiation reflected by and radiated from Earth.

Research quality data from Earthdata Search:


Reanalysis Data

MERRA-2

The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is the latest version of global atmospheric reanalysis for the satellite era produced by NASA's Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980 to present with the latency of about 3 weeks after the end of a month.

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Aerosol Index data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Atmospheric particulate matter (PM) refers to microscopic particles of solid or liquid matter suspended in the air. These inhalable particles range in size from coarse particles like PM10 that have a diameter of 10 micrometers (μm) or less to finer particles, designated PM2.5 or PM1.0, that have a diameter of 2.5 μm, 1.0 μm, or less. While microscopic in size, PM can have a big effect on climate, precipitation, and air quality that may in turn impact human health. 

It's important to be aware of the differences between Aerosol Optical Depth (AOD) and PM2.5. AOD is an optical measurement averaged over an area in a column of air from the top of the atmosphere to the surface and is a unitless measure. PM2.5 is a measure of the mass of particles in a specific size range within a given volume of air near the surface taken at a specific point in time. The overall differences between AOD and PM2.5:

  • AOD is an optical measurement; PM2.5 is a mass concentration measurement
  • AOD is an integrated column measurement from the top of the atmosphere to the surface; PM2.5 is a ground measurement
  • AOD is an area-averaged measurement; PM2.5 is a point measurement

Because the two measurements are so different, it may seem that they are not relatable. However, there are several different techniques to estimate surface concentrations of PM2.5 from AOD measurements. While there is a relationship between AOD and PM2.5, there are other factors that can affect AOD, like humidity, the vertical distribution of aerosols, and the shape of the particles. For example, an increase in humidity will increase the size of particles and therefore increase the AOD even though the PM2.5 level will be the same.

Commonly Used Particulate Matter (PM 2.5) Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format

12 km x 12 km

N. America

3-hourly

2022-present

N/A

N/A

HAQES

Model

netCDF, ASCII
0.5º x 0.625° Global Monthly 1980-present N/A N/A MERRA-2 Reanalysis netCDF

0.25º x 0.312°

Global 3-hourly Near-real time assimilation (DAS),
10-day forecast at 00z, and 5-day forecast at 12z
N/A N/A GEOS FP Analysis netCDF
0.25º x 0.25° Global 15 min, Hourly Daily 5-day forecast  N/A N/A GEOS-CF Model netCDF

Use PM 2.5 Data

Tutorials
Use Cases and Articles
Data Visualizations

 

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse EOSDIS-hosted Earth science data
  • Access repositories and Jupyter Notebooks used in ARSET trainings through GitHub.
  • ARSET’s Jupyter Notebook via GitHub that accesses VIIRS AOD data and converts AOD to PM2.5
  • NASA supported OpenAQ: OpenAQ is the world’s largest free and open-source platform for ground-level ambient air quality data. 
  • NASA’s Air Quality Analytics Collaborative Framework (AQACF) Open-Source API Demonstration Jupyter Notebook featuring Los Angeles Port Backlog (Fall 2021): Beginning around October 2021, the Ports of Los Angeles and Long Beach started suffering serious backlogs of ships due a surge in e-commerce because of the COVID-19 pandemic, resulting in many ships anchored in the ports and causing high amounts of pollutants to be released
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics
  • earthaccess is a Python library to search, download or stream NASA Earth science data with just a few lines of code
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST

Model Data

Hazardous Air Quality Ensemble System (HAQES)

Using the Hazardous Air Quality Ensemble System (HAQES), the Air Quality Laboratory at George Mason University developed real-time surface PM2.5 composition products as one project of the NASA Health Air Quality Applied Science Team (HAQAST). HAQES is a real-time ensemble forecast of hazardous air quality events, such as wildfires, dust storms, and volcanic eruptions. Regional and global models from multiple agencies have been used to create the ensemble, including NASA's Goddard Earth Observing System (GEOS); the Navy Aerosol Analysis and Prediction System (NAAPS) from the Naval Research Laboratory; the Global Ensemble Forecast System Aerosols (GEFS), High-Resolution Rapid Refresh (HRRR); and the NOAA-EPA Atmosphere-Chemistry Coupler-Community Multiscale Air Quality model (NACC-CMAQ).

GEOS FP

The GEOS Forward Processing (GEOS FP) model and data assimilation system is the NASA Global Modeling and Assimilation Office's (GMAO) state-of-the-science numerical weather prediction (NWP) model that assimilates conventional and satellite-based weather observations, aerosol optical depth, and ozone in near real-time (NRT) in order to have the best initial conditions for the forecasts: 10-day at 00 UTC and 5-day at 12 UTC. GEOS FP forecasts are used to support a wide range of NASA missions and campaigns. Note that forecasts using the GEOS FP are experimental.

GEOS-CF

Goddard Earth Observing System (GEOS) GEOS-Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This community-developed, global 3D model of atmospheric chemistry is publicly available and offers five-day forecasts. Forecasts from the GEOS-CF system are experimental.

NASA’s Health and Air Quality Applied Sciences Team (HAQAST) external datasets


Reanalysis Data

MERRA-2

MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA's Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers 1980 to present with the latency of about 3 weeks after the end of a month.

Monthly Dust Surface Mass Concentration (PM2.5) from MERRA-2 can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:

MERRA-2 PM2.5 in GMAO’s visualization and data access website, FLUID:

Earthdata GIS Products:

MERRA-2 PM2.5 in Earthdata Search and Google Earth Engine:

Very large dust storms lasting hours or days can be observed and tracked using satellite imagery. The most common source of dust globally is the Sahara Desert. Giant dust storms periodically sweep off the coast of West Africa and can be transported as far as Florida and the Caribbean.The amount of dust transported by these storms can be quantified using the Dust Score, which is calculated from data acquired by the Atmospheric Infrared Sounder (AIRS) instrument aboard NASA’s Aqua satellite. The AIRS Dust Score indicates the level of atmospheric aerosols in Earth’s atmosphere over the ocean. Dust is probable when the score is above 380, and higher scores indicate more certainty that dust is present. The numerical scale is a qualitative representation of the presence of dust in the atmosphere, an indication of where large dust storms may form, and the areas that may be affected.

Commonly Used Dust Score Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. For more information about the differences between NRT and Standard Science Products, please see Near Real-Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform

Name (Sensor, Model, etc.)

Observation, Model, or Reanalysis

File Format

50 km

Global

6 min, hourly, 3-hourly, 6-hourly

2016-present for NRT, 2002 for other 2,378 infrared channels in the 3.74 to 15.4 micron spectral range Aqua *AIRS Observation HDF-EOS

Use Dust Score Data

Tutorials
Use Cases and Articles
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse EOSDIS-hosted Earth science data
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST
  • earthaccess is a Python library to search, download or stream NASA Earth science data with just a few lines of code
  • Access repositories and Jupyter Notebooks used in ARSET trainings through GitHub

Earth Observation Data by Sensor

AIRS

The AIRS Dust Score can be visualized using NASA Worldview:

Create and share layered maps with AIRS data using the AIRS Browse Tool.

Research quality data products can be accessed using Earthdata Search:

Near real-time (NRT) MODIS Surface Reflectance data are available through NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) within 60 to 125 minutes after a satellite observation:

Nitrogen dioxide (NO2) is a pollutant, the primary sources of which are automobile exhaust, smoke from industry, and the burning of fossil fuels. If breathed in, NO2 can aggravate respiratory conditions such as asthma. 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 acid rain, and contributing to nitrogen pollution in coastal waters.

Commonly Used Nitrogen Dioxide Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format

0.25°, 13 km x 24 km

Global 98 min, Daily 2004-near present 1.0-0.45 nm Full Width and Half Maximum (FWHM) Aura  Ozone Monitoring Instrument (OMI) Observation HDF-EOS5
5.5 km x 3.5 km Global 101.5 minutes 2021-present 270 nm-2.3 µm, 0.55 nm ESA Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) Observation netCDF
0.25º x 0.25° Global 15 min, Hourly Daily 5-day forecast N/A N/A GEOS-CF Model netCDF

0.0083° x 0.0083°

Near-global

Yearly

1990-2020

N/A

N/A

LUR 

Model

netCDF
Point measurements Global Periodic flights occurred during each deployment 2016-2018 Varies Airborne Field Campaign Atmospheric Tomography Mission (ATom) campaign with varying instruments Observation netCDF

Use Nitrogen Dioxide Data

Tutorials
Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse EOSDIS-hosted Earth science data
  • earthaccess is a Python library to search, download, or stream NASA Earth science data with just a few lines of code
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST
  • Applied Remote Sensing Training (ARSET)    
  • VEDA Dashboard: Since the outbreak of the novel coronavirus, atmospheric concentrations of nitrogen dioxide have changed by as much as 60% in some regions
  • NASA’s Air Quality Analytics Collaborative Framework (AQACF) Open-Source API Demonstration Jupyter Notebook featuring the following use cases:
    • 2021 California Wildfire Season: Observations of NO2 levels during the 2021 California wildfire season provide insights into the spread and impact of the fires, help inform public health and safety measures during wildfires, and aid in the development of more accurate fire models and predictions for future wildfire seasons
    • Los Angeles Port Backlog (Fall 2021): Beginning around October 2021, the Ports of Los Angeles and Long Beach started suffering serious backlogs of ships due a surge in e-commerce because of the COVID-19 pandemic, resulting in many ships anchored in the ports that caused high amounts of pollutants to be released
  • Examples on how to access and visualize various NASA HDF/HDF-EOS files using Python (pyhdf/h5py), NCL, MATLAB, and IDL, NCL, MATLAB, and IDL 

Earth Observation Data by Sensor:

OMI

The Ozone Monitoring Instrument (OMI) aboard NASA’s Aura satellite uses an imaging spectrometer to distinguish between aerosol types, such as smoke, dust, and sulfates. It measures cloud pressure and coverage, which provides data to derive tropospheric ozone. OMI provides a record of total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI also measures pollutants such as ozone, nitrogen dioxide, sulfur dioxide, and aerosols, which the U.S. Environmental Protection Agency (EPA) has designated as posing serious threats to human health and agricultural productivity. 

Daily OMI NO2 data can be accessed and interactively explored using NASA Worldview:

NASA'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.

Using an online interactive tool called Giovanni, map visualizations of OMI NO2 data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Research quality data products can be accessed using Earthdata Search:

TROPOMI

The Tropospheric Monitoring Instrument (TROPOMI) was co-funded by ESA (European Space Agency) and the Netherlands. It is the single payload aboard ESA's Sentinel-5P spacecraft and measures the solar radiation reflected by and radiated from Earth.

Research quality data:


Model Data:

GEOS-CF

Goddard Earth Observing System (GEOS) GEOS-Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This community-developed, global 3D model of atmospheric chemistry is publicly available and offers five-day forecasts. Forecasts using the GEOS system are experimental and the use of these forecasts for purposes other than research is not recommended.

Land Use Regression (LUR)

The Nitrogen Dioxide Surface-Level Annual Average Concentrations Product contains estimated global NO2 surface values derived using a Land Use Regression (LUR) model (based on 5,220 NO2 monitors in 58 countries and land use variables) for the years 2010-2012. NO2 column densities from the Ozone Monitoring Instrument and MERRA-2 scale the concentrations to other years between 1990 and 2020. This product is part of NASA's Health and Air Quality Applied Sciences Team (HAQAST) effort.

Research quality data products can be accessed using Earthdata Search:

NASA’s Health and Air Quality Applied Sciences Team (HAQAST) external datasets

  • Surface NO2: Global, Atmospheric Composition Analysis Group, Washington University in St. Louis
    • Estimates of annual ground-level nitrogen dioxide (NO2) concentrations for 2019 with ~1 km resolution created by combining satellite NO2 column observations from TROPOMI with information from the GEOS-Chem chemical transport model and ground-based monitoring

Field Campaign Observation Data

ATom

The Atmospheric Tomography Mission (ATom) is a NASA Earth Venture Suborbital-2 mission to study the impact of human-produced air pollution on greenhouse gases and on chemically reactive gases in the atmosphere. ATom deployed an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Around-the-world flights were conducted in each of four seasons between 2016 and 2018.

The primary sources of sulfur dioxide (SO2) are the burning of fossil fuels by power plants and industry. Volcanic emissions also contribute SO2, but in relatively smaller quantities. As with NO2, SO2 can aggravate respiratory conditions, especially asthma. In areas with high levels of SO2, sulfur oxides can react with other components to create small particles that contribute to overall particulate matter. This small particulate matter can contribute to low visibility in areas where SO2 is high. SO2 also can lead to acid rain.

Commonly Used Sulfur Dioxide Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format
50 km x 50 km Global 6 minutes 2002-2023 2,378 infrared channels in the 3.74-15.4 micron spectral range Aqua *AIRS Observation HDF-EOS
13 km x 24 km, 0.25°, 1° Global 98 minutes, Daily 2004-present 1.0-0.45 nm Full Width and Half Maximum (FWHM) Aura Ozone Monitoring Instrument (OMI) Observation HDF-EOS5
7.5 km x 3 km Global 101 minutes, Daily 2018 250-420 nm NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Ozone Mapping and Profiler Suite (OMPS) Observation netCDF-4
7 x 3.5 km for all spectral bands, with the exception of the UV1 band (7 x 28 km2) and SWIR bands (7 x 7 km2) Global Daily 2017-present 270 nm-2.3 µm, 0.55 nm ESA Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) Observation netCDF
165 km x 3 km Near-global (-82º to +82º latitude) 15 minutes,
Twice daily [day, night]
2021-present 190 and 240 GHz Aura *MLS Observation HDF-EOS5
0.5° x 0.625° Global Hourly,
3 hourly,
Monthly
1980-present N/A N/A MERRA-2 Reanalysis netCDF

0.25º x 0.25°

Global 15 min, Hourly Daily 5-day forecast N/A N/A GEOS-CF Model netCDF

0.25º x 0.312°

Global 3-hourly Near-real time assimilation (DAS), 10-day forecast at 00z, and 5-day forecast at 12z N/A N/A GEOS FP

Analysis

netCDF
Point measurements Global Periodic flights occurred during each deployment 2016-2018 varies Airborne Field Campaign Atmospheric Tomography Mission (ATom) campaign with varying instruments Observation netCDF

Use Sulfur Dioxide Data

Tutorials
Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
  • Wisconsin Horizontal Interpolation Program for Satellites (WHIPS) is an open-source program designed to make satellite-derived air quality data more usable. WHIPS interpolates Level 2 satellite retrievals onto a user-defined fixed grid, in effect creating a custom-gridded level 3 satellite product for the following products: TROPOMI NO2 and SO2, OMI NO2 (NASA and KNMI retrievals), OMI HCHO (NASA and QA4ECV retrievals), OMI SO2 (NASA retrieval), MOPITT CO (NASA retrieval), MODIS AOD (NASA retrieval)
  • OMI and TROPOMI data can be read, processed, and compared using the HARP toolkit which features command line tools, C library, and interfaces to Python, R, IDL, and MATLAB
  • For information on a suite of NASA data tools for searching and ordering, data handling, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
  • The NASA Earthdata Cloud Cookbook has tutorials to help access Earth data in the cloud
  • Panoply: NASA’s Panoply visualization tool plots geo-referenced and other arrays from netCDF, HDF, GRIB, and other datasets. It can be used to help plot data on global or regional maps, allow users to select from multiple map projections, and overlay continent outlines or masks
Programming Tools
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse EOSDIS-hosted Earth science data
  • earthaccess is a Python library to search, download or stream NASA Earth science data with just a few lines of code
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST
  • NASA’s Air Quality Analytics Collaborative Framework (AQACF) Open-Source API Demonstration Jupyter Notebook featuring Los Angeles Port Backlog (Fall 2021): Beginning around October 2021, the Ports of Los Angeles and Long Beach started suffering serious backlogs of ships due a surge in e-commerce because of the COVID-19 pandemic, resulting in many ships anchored in the ports that caused high amounts of pollutants to be released
  • Examples on how to access and visualize various NASA HDF/HDF-EOS files using Python (pyhdf/h5py), NCL, MATLAB, and IDL, NCL, MATLAB, and IDL 

Earth Observation Data by Sensor:

AIRS

The Atmospheric Infrared Sounder (AIRS) is a hyperspectral sounder that collects daily global measurements of water vapor and temperature profiles as one of four instruments comprising the AIRS Project Instrument Suite. When launched in 2002, the AIRS Project Instrument Suite was the most advanced atmospheric sounding system ever deployed in space. AIRS data are combined with data from the Advanced Microwave Sounding Unit (AMSU-A1 and AMSU-A2) and the Humidity Sounder for Brazil (HBS) to provide 3D measurements of temperature and water vapor through the atmospheric column along with measurements of atmospheric trace gases and surface and cloud properties. These data are used by weather prediction centers to improve forecasts and to validate climate models. They also are used in applications ranging from volcanic plume detection to drought forecasting.

NRT AIRS SO2 data can be accessed and interactively explored using NASA Worldview:

Create and share layered maps with AIRS data using the AIRS Browse Tool.

Research quality data products can be accessed using Earthdata Search:

OMI

The Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite uses an imaging spectrometer to distinguish between aerosol types, such as smoke, dust, and sulfates. It measures cloud pressure and coverage, which provides data to derive tropospheric ozone. OMI provides a record of total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI also measures criteria pollutants such as ozone, nitrogen dioxide, sulfur dioxide, and aerosols, which the U.S. Environmental Protection Agency (EPA) has designated as posing serious threats to human health and agricultural productivity. 

NRT data can be accessed and interactively explored using NASA Worldview:

NASA Global Sulfur Dioxide Monitoring program that provides imagery of daily SO2 from OMI, OMPS, and TROPOMI. The site also provides information on the source of emissions. 

In addition, the Historical Anthropogenic Sulfur Dioxide Emissions dataset, available through NASA's Socioeconomic Data and Applications Center (SEDAC), offers annual estimates of anthropogenic global and regional SO2 emissions spanning the period 1850-2005.

Using an online interactive tool called Giovanni, map visualizations of OMI SO2 data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Research quality data products can be accessed using Earthdata Search:

  • OMI SO2 data
    OMI provides daily total column data at a resolution of 13x24 km; data are in HDF5 format

OMPS

The Ozone Mapping and Profiler Suite (OMPS) aboard the joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite tracks the health of Earth's ozone layer and measures the concentration of atmospheric ozone. 

Daily data can be accessed and interactively explored using NASA Worldview:

Research quality data products can be accessed using Earthdata Search:

TROPOMI

The Tropospheric Monitoring Instrument (TROPOMI) was co-funded by ESA (European Space Agency) and the Netherlands, and is a space-borne, nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. TROPOMI is the single payload aboard ESA's Sentinel-5P spacecraft and measures the solar radiation reflected by and radiated from Earth.

Research quality data products can be accessed using Earthdata Search:

MLS

The Microwave Limb Sounder (MLS) is a passive microwave radiometer/spectrometer that measures microwave thermal emission from the limb (edge) of Earth’s atmosphere to sense vertical profiles of atmospheric gases, temperature, pressure, and cloud ice. MLS measurements are acquired globally day and night and can be obtained in the presence of ice clouds and aerosols that prevent measurements by shorter-wavelength infrared, visible, and ultraviolet sensing techniques. MLS data support investigations in three general scientific areas: stratospheric ozone layer stability, climate change, and air quality. 

MLS NRT data are typically available within three hours of observation and are broken into files containing about 15 minutes of data. The most recent seven days of data are available online.

Research quality data products can be accessed using Earthdata Search:


Analysis Data

GEOS FP

The GEOS Forward Processing (GEOS FP) model and data assimilation system is GMAO’s state-of-the-science numerical weather prediction (NWP) model that assimilates conventional and satellite-based weather observations, aerosol optical depth, and ozone in near real-time (NRT) in order to have the best initial conditions for the forecasts: 10-day at 00 UTC and 5-day at 12 UTC. GEOS FP forecasts are used to support a wide range of NASA missions and campaigns.


Model Data

GEOS-CF

Goddard Earth Observing System (GEOS) GEOS-Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This community-developed, global 3D model of atmospheric chemistry is publicly available and offers five-day forecasts. Forecasts using the GEOS system are experimental and use of these forecasts for purposes other than research is not recommended.


Reanalysis Data

MERRA-2

Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is the latest version of global atmospheric reanalysis for the satellite era produced by NASA's Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with the latency of about 3 weeks after the end of a month.

Monthly modeled data from MERRA-2 can be accessed and interactively explored using NASA Worldview: 

Global Modeling and Assimilation Office’s offers visualizations of MERRA-2 SO2 data:

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 SO2 data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

 


Field Campaign Observation Data

ATom

The Atmospheric Tomography Mission (ATom) is a NASA Earth Venture Suborbital-2 mission to study the impact of human-produced air pollution on greenhouse gases and on chemically reactive gases in the atmosphere. ATom deployed an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Around-the-world flights were conducted in each of four seasons between 2016 and 2018.

Carbon monoxide (CO) is released when something is burned, such as in the combustion of fossil fuels or biomass. Outdoor levels are rarely high enough to cause issues; when they do reach dangerous levels, however, they can affect people with certain types of heart disease. CO is an excellent tracer of pollution transport since it is a long-lived in the atmosphere. It is also helpful for  identifying the source of air masses. 

Commonly Used Carbon Monoxide Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format
50 km x 50 km Global 6 minutes 2002-present 2,378 infrared channels in the 3.74-15.4 micron spectral range Aqua *AIRS Observation HDF-EOS
165 km x 3 km Near-global Twice daily [day, night] 2004-present At millimeter and submillimeter wavelengths Aqua *MLS

Observation

HDF-EOS5
~22 km Global Daily, Monthly 2000-present near-infrared radiation at 2.3 µm and thermal-infrared radiation at 4.7 µm Terra *MOPITT Observation HDF-EOS5
5.5 km x 7 km Global 101.5 minutes 2018-present 270 nm-2.3 µm, 0.55 nm Sentinel-5P TROPOMI Observation netCDF
0.25º x 0.25° Global 15 min, Hourly Daily 5-day forecast N/A N/A

GEOS-CF

Model netCDF
0.25º x 0.312° Global 3-hourly Near-real time assimilation (DAS), 10-day forecast at 00z and 5-day forecast at 12z N/A N/A GEOS FP Analysis netCDF
Point measurements Global Periodic flights occurred during each deployment 2016-2018 varies Airborne Field Campaign Atmospheric Tomography Mission (ATom) campaign with varying instruments Observation netCDF

Use Carbon Monoxide Data

Tutorials
Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

AIRS

NASA’s Atmospheric Infrared Sounder (AIRS), in conjunction with the Advanced Microwave Sounding Unit (AMSU), senses emitted infrared and microwave radiation from Earth to provide a 3D look at Earth's weather and climate. Working in tandem, the two instruments make simultaneous observations of Earth's surface. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global, 3D map of atmospheric temperature and humidity, cloud amounts and heights, greenhouse gas concentrations and many other atmospheric phenomena. Launched into Earth orbit in 2002, the AIRS and AMSU instruments are aboard NASA's Aqua spacecraft and are managed by NASA's Jet Propulsion Laboratory in Southern California.

NRT and daily data can be accessed and interactively explored using NASA Worldview:

  • AIRS CO data
    AIRS Level 2 data are nominally 45 km/pixel at the equator but the data in Worldview have 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, which is approximately 5,500 meters (18,000 feet) above sea level

Create and share layered maps with AIRS data using the AIRS Browse Tool.

Research quality data products can be accessed using Earthdata Search:

  • AIRS CO data
    The Atmospheric Infrared Sounder (AIRS) measures abundances of trace components in the atmosphere, including CO. 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)

MLS

The Microwave Limb Sounder (MLS) instrument aboard NASA's Aura satellite collects Carbon Monoxide (CO) Mixing Ratio layer at 215 hectopascals (hPa). This indicates carbon monoxide levels at the vertical atmospheric pressure level of 215 hPa and is measured in parts per billion by volume (ppbv). 

Daily data can be accessed and interactively explored using NASA Worldview:

  • MLS CO data: Visualization of the amount of Carbon Monoxide (215 hPa, Day and Night) (measured in ppbv) 

Near real-time (NRT) data are typically available within 3 hours of observation and are broken into files containing about 15 minutes of data. The most recent 7 days of data are available online. Spatial coverage is near-global (-82º to +82º latitude) with each profile spaced 1.5º or ~165 km along the orbit track (roughly 15 orbits per day). The vertical coverage is from 215 to 0.1 hPa.

Research quality (Level 2) data are available through Earthdata Search:

MOPITT

The Measurement of Pollution in the Troposphere (MOPITT) instrument aboard NASA's Terra satellite is designed to enhance our knowledge of the lower atmosphere and to observe how it interacts with the land and ocean biospheres. MOPITT’s specific focus is on the distribution, transport, sources, and sinks of carbon monoxide in the troposphere.

Daily and monthly data can be accessed using NASA Worldview:

Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:

  • MOPITT CO data (Monthly) (Note: At time of publication, these data are only available through May 2022.)

Research quality data products can be accessed using Earthdata Search:

  • MOPITT CO data
    The Measurements of Pollution in the Troposphere (MOPITT) instrument 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, and are acquired using the thermal and near-infrared channels

TROPOMI

The Tropospheric Monitoring Instrument (TROPOMI) was co-funded by ESA (European Space Agency) and the Netherlands, and is a space-borne, nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. TROPOMI is the single payload aboard ESA's Sentinel-5P spacecraft and measures the solar radiation reflected by and radiated from Earth. 

Research quality data products can be accessed using Earthdata Search:


Model Data

GEOS FP

The GEOS Forward Processing (GEOS FP) model and data assimilation system is GMAO’s state-of-the-science numerical weather prediction (NWP) model that assimilates conventional and satellite-based weather observations, aerosol optical depth, and ozone in near real-time (NRT) in order to have the best initial conditions for the forecasts: 10-day at 00 UTC and 5-day at 12 UTC. GEOS FP forecasts are used to support a wide range of NASA missions and campaigns. There is no data assimilation of CO observations in GEOS FP.

GEOS-CF

GEOS-Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This community-developed, global 3D model of atmospheric chemistry is publicly available and offers 5-day forecasts. Forecasts using the GEOS system are experimental and are produced for research purposes only. There is no data assimilation of CO observations in GEOS-CF. 


Field Campaign Observation Data

ATom

The Atmospheric Tomography Mission (ATom) is a NASA Earth Venture Suborbital-2 mission to study the impact of human-produced air pollution on greenhouse gases and on chemically reactive gases in the atmosphere. ATom deployed an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Around-the-world flights were conducted in each of four seasons between 2016 and 2018.

Ozone (O3) is a trace gas that can be either beneficial or harmful depending on where it is found in the atmosphere. Beneficial O3 is found naturally in trace amounts in the upper atmosphere (the stratosphere) where it protects life on Earth from the Sun’s ultraviolet (UV) radiation. Harmful O3 is found in the troposphere, the lowest layer of the atmosphere, where it serves as a potent greenhouse gas and can aggravate existing health problems in humans, especially those with respiratory conditions. O3 is not emitted directly into the atmosphere, but instead forms from the chemical reaction between nitrogen oxides and volatile organic compounds that are emitted from power plants, industrial facilities, and cars powered by internal combustion engines (there are also natural emissions of nitrogen oxides and volatile organic compounds from lightning, soil, and vegetation). Reactions to create O3 take place in the presence of sunlight. Because of the need for sunlight, unhealthy levels of O3 are often reached on very sunny days and in urban environments.

Commonly Used Ozone Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform

Name (Sensor, Model, etc.)

Observation, Model, or Reanalysis

File Format

13 km x 24 km, 13 x 12 km

Global

98 min

2004-present

0.63 nm, 0.42 nm, 0.63 nm

Aura

OMI

Observation

HDF-EOS5

50 km

Global

6 min,

hourly, 3-hourly, 6-hourly

2016-present for NRT, 2002 for non-NRT

2,378 infrared channels in the 3.74 to 15.4 micron spectral range

Aqua

*AIRS

Observation

HDF-EOS

50 km

Near-global

101 minutes, daily

2011-present

250-420 nm

Suomi NPP

*OMPS

Observation

HDF-5

0.5° x 1.0°

Global

daily

2018-present

270nm-495nm, 675nm-775nm, 2305nm-2385nm

ESA Sentinel-5P

TROPOMI

Observation

netCDF

165 km x 3 km

Near-global (-82º to +82º latitude)

15 minutes

Most recent 7 days

190 and 240 GHz

Aura

*MLS

Observation

HDF-EOS5

0.5° x 0.625°

Global

Monthly

1980-present

N/A N/A

MERRA-2

Reanalysis

netCDF

0.25º x 0.25°

Global 15 minutes, Hourly Daily 5-day forecast  N/A N/A GEOS-CF Model netCDF
0.25º x 0.312° Global  3-hourly Near-real time assimilation (DAS), 10-day forecast at 00z, and 5-day forecast at 12z

N/A

N/A

GEOS FP 

Analysis

netCDF
Point measurements Global Periodic flights occurred during each deployment 2016-2018 Varies Airborne Field Campaign Atmospheric Tomography Mission (ATom) campaign with varying instruments Observation netCDF
Surface-based point and profile measurements North America 5 minutes - daily Periodic, 2012-present DIAL technique, 266-300nm Ground-based Tropospheric Ozone Lidar Network (TOLNet) Observation HDF4-GEOMS, ASCII

Use Ozone Data

Tutorials
Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools
  • Google Earth Engine: Sentinel-5 precursor/TROPOMI Level 2 Product User
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse EOSDIS-hosted Earth science data
  • earthaccess is a python library to search, download or stream NASA Earth science data with just a few lines of code
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics

Earth Observation Data by Sensor

AIRS

The Atmospheric Infrared Sounder (AIRS) is a hyperspectral sounder that collects daily global measurements of water vapor and temperature profiles as one of four instruments comprising the AIRS Project Instrument Suite. 

Using an online interactive tool called Giovanni, map visualizations of AIRS Ozone data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Research quality data products can be accessed using Earthdata Search:

  • AIRS O3 data
    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

OMI

The Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite has a coarser spatial resolution than MODIS and VIIRS, but provides data at individual wavelengths from the ultraviolet (UV) to the visible. 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.

Daily data can be accessed using NASA Worldview:

  • OMI O3 data
    Visualization of the amount of ozone in the total column measured in Dobson Units (DU)

Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:

Research quality data products can be accessed using Earthdata Search:

MLS

Ozone (O3) in the lower stratosphere and upper troposphere as measured by the Microwave Limb Sounder (MLS) instrument aboard NASA's Aura satellite. The O3 Mixing Ratio layer at 46 hectopascals (hPa) indicates ozone levels at the vertical atmospheric pressure level of 46 hPa, and is measured in parts per billion by volume (ppbv). It is derived from the MLS Ozone product (ML2O3_NRT) available from the MLS. The sensor resolution is 5 km and imagery resolution is 2 km.

Daily data can be accessed and interactively explored using NASA Worldview:

  • MLS O3 data - Visualization of the amount of ozone in the total column (measured in ppmv/ppbv)

Near real-time (NRT) data are typically available within 3 hours of observation and are broken into files containing about 15 minutes of data. The most recent 7 days of data are available online. Spatial coverage is near-global (82º north and south latitude), with each profile spaced 1.5º or ~165 km along the orbit track (roughly 15 orbits per day). The vertical coverage is from 261 to 0.1 hPa.

Research quality (Level 2) data are available through Earthdata Search:

TROPOMI/Sentinel-5P

The European Space Agency (ESA) and the Copernicus Sentinel Project make available the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) atmospheric composition data to NASA for access and distribution. Sentinel-5P is the first of the Atmospheric Composition Sentinels and provides measurements of O3, NO2, SO2, CH4, CO, formaldehyde, aerosols, and cloud at high spatial, temporal, and spectral resolutions.

OMPS

The OMPS instrumental suite aboard the joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP), NOAA-20, and NOAA-21 satellites are now the operational instruments for the NASA and NOAA ozone monitoring program. OMPS consists of three ozone measuring sensors that operate in UV and VIS spectral ranges and sample the same air-masses within a few minutes. The OMPS Nadir Mapper (OMPS-NM) was designed to measure atmospheric total column ozone with configurable nadir temporal (along-track) and spatial (across-track) resolutions. The OMPS-NM aboard Suomi NPP collects data at a larger 50 x 50 km pixel size, while NOAA-20 and NOAA-21 OMPS-NM observations are collected at a smaller pixel size. OMPS-NM also offers SO2 and other trace gas measurements but lacks spectral coverage in the violet-blue wavelength typically used for NO2 retrievals. (Note: NO2 observations are possible from OMPS, but they are less optimal as compared with OMI.) OMPS Limb Profilers (OMPS-LP) aboard the Suomi NPP and NOAA-21 satellites provide measurements of vertical ozone profiles in the stratosphere. Tropospheric ozone column is estimated by combining these measurements with total columns from OMPS-NM and meteorological data. The OMPS tropospheric column record extends tropospheric measurements from the Aura OMI/MLS.

Daily data can be accessed using NASA Worldview:

Research quality (Level 2) data are available through Earthdata Search:


Model Data:

GEOS FP

The GEOS Forward Processing (GEOS FP) model and data assimilation system is GMAO’s state-of-the-science numerical weather prediction (NWP) model that assimilates conventional and satellite-based weather observations, aerosol optical depth, and ozone in near real-time (NRT) in order to have the best initial conditions for the forecasts: 10-day at 00 UTC and 5-day at 12 UTC. GEOS FP forecasts are used to support a wide range of NASA missions and campaigns.

GEOS-CF

GEOS-Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This community-developed, global 3D model of atmospheric chemistry is publicly available and offers 5-day forecasts. Forecasts using the GEOS system are experimental.


Reanalysis Data:

MERRA-2

The Ozone Mixing Ratio data product is the MERRA-2 analyzed ozone at 42 pressure levels, along with important meteorological fields such as temperature, wind components, specific humidity, and geopotential height, which are useful for analysis of ozone. 

Monthly data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni or through the GMAO FLUID webpage, map visualizations of MERRA-2 Ozone data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

MERRA-2 Ozone data are available through Earthdata Search and in Google Earth Engine Data Catalog:


Field Campaign Observation Data

ATom

The Atmospheric Tomography Mission (ATom) is a NASA Earth Venture Suborbital-2 mission to study the impact of human-produced air pollution on greenhouse gases and on chemically reactive gases in the atmosphere. ATom deployed an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Around-the-world flights were conducted in each of four seasons between 2016 and 2018.

TOLNet

The Tropospheric Ozone Lidar Network (TOLNet) was established in 2012 to provide high spatio-temporal observations of tropospheric ozone to (1) better understand physical processes driving the ozone budget in various meteorological and environmental conditions, and (2) validate the tropospheric ozone measurements of spaceborne missions. Datasets include profiles of tropospheric ozone number density and mixing ratio at a variety of vertical and temporal resolutions as well as collocated surface measurements.

Other links:

Formaldehyde (CH2O or HCHO) is a volatile hydrocarbon and a known carcinogenic air pollutant common in smoke. Large concentrations of formaldehyde are found in the presence of biomass burning and industrial sites where it is a byproduct of combustion (there also are biogenic emissions of formaldehyde). Formaldehyde affects human health and also has significant—but little understood—effects on Earth’s atmosphere where it contributes to ozone formation

Commonly Used Formaldehyde Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform

Name (Sensor, Model, etc.)

Observation, Model, or Reanalysis

File Format

0.1°, 13 km x 24 km

Global

Daily

2004-present

1.0-0.45 nm Full Width and Half Maximum (FWHM)

Aura

OMI

Observation

HDF-EOS5

50 km

Global

101 minutes

2012-2020

328.5 nm-356.5 nm

Suomi NPP

OMPS Observation netCDF

5.5 km x 3.5 km, 7.5 km x 3.5 km

Global

101.5 minutes

2018-present

270 nm-2.3 µm, 0.55 nm

ESA Sentinel-5P

TROPOMI

Observation

netCDF
0.25º x 0.25° Global Hourly Daily 5-day forecast  N/A N/A GEOS-CF Model netCDF

Use Formaldehyde Data

Tutorials

NASA’s Health and Air Quality Applied Sciences Team (HAQAST) Guide:

Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
  • Wisconsin Horizontal Interpolation Program for Satellites (WHIPS) is an open-source program designed to make satellite-derived air quality data more usable. WHIPS interpolates Level 2 satellite retrievals onto a user-defined fixed grid, in effect creating a custom-gridded Level 3 satellite product for the following products: TROPOMI NO2 and SO2, OMI NO2 (NASA and KNMI retrievals), OMI HCHO (NASA and QA4ECV retrievals), OMI SO2 (NASA retrieval), MOPITT CO (NASA retrieval), MODIS AOD (NASA retrieval)
  • The NASA Earthdata Cloud Cookbook has tutorials to help access Earth data in the Cloud
  • For information on a suite of NASA data tools for searching and ordering, data handling, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
  • Panoply: NASA’s Panoply visualization tool plots geo-referenced and other arrays from netCDF, HDF, GRIB, and other datasets. It can be used to help plot data on global or regional maps, allow users to select from multiple map projections, and overlay continent outlines or masks
Programming Tools

Earth Observation Data by Sensor:

OMI

The Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite measures the amount of formaldehyde (CH2O), among other constituents in the atmosphere.

Using an online interactive tool called Giovanni, map visualizations of OMI Formaldehyde data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Research quality (Level 2) data are available from Earthdata Search:

OMPS

The OMPS-NPP L2 NM Formaldehyde (HCHO) Total Column swath orbital product provides formaldehyde measurements from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi-NPP satellite. 

Research quality (Level 2) data are available through Earthdata Search:

TROPOMI/Sentinel-5P

The European Space Agency (ESA) and the Copernicus Sentinel Project make available the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) atmospheric sulfur dioxide and formaldehyde data to NASA for access and distribution. Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.

TROPOMI HCHO data are available in Earthdata Search


Model Data

GEOS-CF

The Goddard Earth Observing System (GEOS) Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This global 3D model of atmospheric chemistry is publicly available and offers five-day forecasts with chemical and meteorological diagnostics on the same temporal and spatial resolution. Forecasts using the GEOS system are experimental.

  • GEOS-CF model output can be accessed in several ways, either through direct download from the NASA Center for Climate Simulation (NCCS) Dataportal website or remotely accessing the data using the OpENDAP server. For information on available chemical and meteorological diagnostics see the latest File Specification Document
  • GEOS-CF Formaldehyde data are also available on Google Earth Engine Data Catalog

Ammonia (NH3) is a colorless gas with a pungent smell. It reacts with other common substances in the atmosphere, such as sulfuric acid and nitric acid, to form two classes of particles: ammonium sulfate and ammonium nitrate.

Commonly Used Ammonia Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform

Name (Sensor, Model, etc.)

Observation, Model, or Reanalysis

File Format
13.5 km Global Daily 2021-present 2,378 infrared channels in the 3.74 to 15.4 micron spectral range Aqua

TROPESS AIRS

Observation

netCDF

0.25º x 0.25°

Global

Hourly

Daily 5-day forecast 

N/A

N/A GEOS-CF Model netCDF

Use Ammonia Data

Tutorials

NASA’s Health and Air Quality Applied Sciences Team (HAQAST) Guide:

Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools

The NASA Earthdata Cloud Cookbook has tutorials to help access Earthdata in the cloud

Data Customizing Tools
Programming Tools
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse EOSDIS-hosted Earth science data.
  • earthaccess is a Python library to search, download or stream NASA Earth science data with just a few lines of code
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST
  • NASA TROPESS code examples for product usage from different programming languages, including Python, Matlab, and IDL
  • GEOS-CF Ammonia data are available on Google Earth Engine Data Catalog
  • Examples on how to access and visualize various NASA HDF/HDF-EOS files using Python (pyhdf/h5py), NCL, MATLAB, and IDL, NCL, MATLAB, and IDL 
  • The ncdump tool can be used as a simple browser or to display dimension names and sizes; variable names, types, and shapes; attribute names and values; and the values of data for all variables or selected variables in a netCDF file

Earth Observation Data by Sensor:

TROPESS AIRS-Aqua

Standard and Summary TROPESS AIRS products are available through Earthdata Search:

  • TROPESS AIRS-Aqua Ammonia for Forward Stream, Standard Product contains the vertical distribution (reported at 15 vertical levels from the surface to 0.1 hPa) of the retrieved atmospheric state of ammonia (NH3), formal uncertainties, and diagnostic information
  • TROPESS AIRS-Aqua L2 Ammonia for Forward Stream, Summary Product V1 

Model Data:

GEOS-CF

The Goddard Earth Observing System (GEOS) Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This global 3D model of atmospheric chemistry is publicly available and offers five-day forecasts with chemical and meteorological diagnostics on the same temporal and spatial resolution. Forecasts using the GEOS system are experimental and are produced for research purposes only.

  • GEOS-CF model output can be accessed in several ways, either through direct download from the NASA Center for Climate Simulation (NCCS) Data portal website or remotely accessing the data using the OpENDAP server.  For information on available chemical and meteorological diagnostics see the latest File Specification Document
  • GEOS-CF Ammonia data are available on Google Earth Engine Data Catalog

Clouds form when suspended aerosols and water vapor get caught up in rising air motions. Natural aerosols such as mineral dust from deserts and sea salt have always served as nuclei on which water vapor condenses to form clouds. The amount of aerosols in the air is one of the most important factors for cloud formation. High amounts of human-made aerosols in the atmosphere can lead to heavier rainfall, while clouds with high levels of human-made aerosols can lead to delayed rainfall, which makes clouds grow larger, taller, and longer-lived. When they finally shed their water, storms may be stronger.

Commonly Used Cloud Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format
10 km: 6.9-36.5 GHz; 5 km: 89.0 GHz Global Hours 2020-present 6 Bands: 6.9, 10.65, 18.7, 23.8, 36.5, 89.0 GHz GCOM-W1 *AMSR2 Observation netCDF-4
HDF-EOS5
50 km Global 6 minutes 2002-present (standard) 2,378 infrared channels in the 3.74 to 15.4 micron spectral range Aqua *AIRS Observation HDF-EOS
275 meters at all off-nadir angles Global Hours

2000-present; 2016-present (NRT)

Four spectral bands: blue, green, red, and near-infrared; center wavelength of each of these bands is 446, 558, 672, and 867 nanometers respectively Terra *Multi-angle Imaging SpectroRadiometer (MISR) Observation HDF-EOS2
1 km, 5 km

Global

Daily

1999-present

36 spectral bands ranging in wavelength from 0.4 µm to 14.4 µm

Terra

MODIS

Observation

HDF-EOS

250 m, 500 m, 1000 m, 5600 m

Global

Daily

2002-present

36 spectral bands ranging in wavelength from 0.4 µm to 14.4 µm

Aqua

MODIS

Observation

HDF-EOS

0.5° x 0.625°

Global

Monthly

1980-present N/A N/A MERRA-2

Reanalysis

netCDF

Use Cloud Data

Tutorials

NASA’s Health and Air Quality Applied Sciences Team (HAQAST) Guide:

Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

AIRS

AIRS, in conjunction with the Advanced Microwave Sounding Unit (AMSU), senses emitted infrared and microwave radiation from Earth to provide a 3D look at Earth's weather and climate. Working in tandem, the two instruments make simultaneous observations down to Earth's surface. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global 3D map of atmospheric temperature and humidity, cloud amounts and heights, greenhouse gas concentrations and many other atmospheric phenomena. Launched in 2002, the AIRS and AMSU instruments fly aboard NASA's Aqua spacecraft.

Cloud top altitude is the pressure altitude calculated from the retrieved AIRS cloud top pressure assuming a surface pressure of 1000 hPa and a scale height of 6 kilometers. These are the approximate altitudes where clouds have infrared optical depths of unity. AIRS can sense up to two cloud decks in a column of atmosphere.

AIRS data can be accessed and interactively explored using NASA Worldview:

Total Cloud Fraction is the product of cloud fractional coverage and cloud infrared emissivity. Low fraction can indicate either small, highly emissive clouds or more extensive but less emissive clouds.

AIRS data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of AIRS Cloud data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Research-quality data products can be accessed using Earthdata Search. Key Geophysical parameters including Fractional Cloud Cover, Cloud Top Height, Cloud Top Temperature:

AMSR2

The AMSR2 instrument aboard the Japan Aerospace Exploration Agency Global Change Observation Mission-Water 1 (GCOM-W1) satellite is a conically scanning passive microwave radiometer. This instrument senses microwave radiation for 12 channels and 6 frequencies ranging from 6.9 GHz to 89 GHz.

Near real-time (NRT) products are generated within 3 hours of the last observations in the file, by the Land, Atmosphere Near real-time Capability for EOS (LANCE). NRT products are generated in HDF-EOS-5 augmented with netCDF-4/CF metadata and are available from the LANCE. If data latency is not a primary concern, please consider using science quality products rather than NRT products.

The Columnar Cloud Liquid Water parameter is a measure of the liquid water in a column of atmosphere in units of grams per square meter.

AMSR2 data can be accessed and interactively explored using NASA Worldview:

Research-quality data products can be accessed using Earthdata Search. Key Geophysical parameters within this product include: cloud liquid water over ocean

MISR

MISR aboard NASA's Terra satellite views Earth with cameras pointed at nine different angles. As the instrument flies overhead, each region of Earth's surface is successively imaged by all cameras in each of four wavelengths (blue, green, red, and near-infrared). MISR monitors monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure.

The MISR Cloud Stereo Height product displays the fraction of global cloud stereo heights between 1.5 and 2.0 km calculated from MISR radiances averaged on a monthly basis. MISR stereo cloud heights are geometric calculations of the height of cloud tops based on the angular displacement (parallax) of clouds across the nine angles captured by MISR’s cameras.

MISR data can be accessed and interactively explored using NASA Worldview:

MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) continually collects data in 36 spectral channels with global coverage every 1 to 2 days. Its exceptionally broad spectral range enables MODIS data to be used in studies across numerous disciplines, including vegetative health, changes in land cover and land use, oceans and ocean biology, sea surface temperature, and cloud analysis. It also is used extensively for monitoring fires and natural hazards along with oil spills. An important attribute of MODIS data is the availability of MODIS data products in real-time and near real-time. Direct broadcast stations around the world download raw MODIS data in real-time directly from the satellite, while NASA’s Land, Atmosphere Near Real-time Capability for EOS (LANCE) provides several MODIS products within three hours of satellite observation. 

Aqua/MODIS and MODIS/Terra cloud data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of MODIS Cloud data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Research-quality data products can be accessed using Earthdata Search. Key Geophysical parameters within this product include: Cloud Optical Thickness, Fraction, Water Path, Cloud Top Temperature, Cloud Height and more:


Reanalysis Data

MERRA-2

The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is the latest version of global atmospheric reanalysis for the satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980 to present with the latency of about 3 weeks after the end of a month.

The ISCCP Cloud Albedo (Monthly) layer is created from a time-averaged two-dimensional monthly mean data collection. This data collection consists of parameters from the Cloud Feedback Model Intercomparison Project (CFMIP) Observations Simulator Package (COSP), such as International Satellite Cloud Climatology Project (ISCCP) total cloud area fraction, MODIS cloud fraction water (ice) mean, MODIS cloud fraction low (mid,high) mean, MODIS cloud particle size water (ice) mean.

MERRA-2 Cloud Albedo (Monthly) data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Cloud data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Precipitation, particularly rain, affects air quality as it can remove precursors of air pollution, as well as particulate matter. Rain can also suppress certain emissions, such as dust. Higher precipitation amounts generally result in lower aerosol optical depth (AOD) values.

Commonly Used Precipitation Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format

15 km

Global

2 days

2012-near present

16 channels ranging in frequency from 6.925 GHz to 89 GHz      

SHIZUKU (GCOM-W1)

*Advanced Microwave Scanning Radiometer 2 (AMSR2

Observation

HDF5

25 km

Global

12 hours

2002-present

2,378 infrared channels in the 3.74 to 15.4 micron spectral range

Aqua

*AIRS

Observation

HDF-EOS

0.5°

Global

Daily,
Monthly

1983-2022

Varies

Global Precipitation Climatology Project (GPCP) (multiple satellites) 

Varies

Model

netCDF

0.1°

Global

30-minute, Daily, Monthly

2000-present

Varies

GPM IMERG (multiple satellites)

Varies

Observation

HDF, NetCDF, or GeoTIFF

5 km

50° N to 50° S, 180° W to 180° E

5-day, 10-day, 15-day

2000-present

N/A

N/A

CHIRPS- Global Ensemble Forecast System (GEFS

Model

GeoTIFF 

1 km

Over continental North America and Hawaii and Puerto Rico

Daily

Over continental North America and Hawaii from 1980 and over Puerto Rico from 1950 through the end of the most recent full calendar year

N/A

N/A

Daymet

Model

netCDF, Cloud Optimized GeoTIFF (COG)
0.01°,
0.1°,
0.125°,
0.25°,
Global Hourly, 3-hourly,Daily, Monthly 2000-2022 N/A N/A Land Data Assimilation Systems (LDAS) Model netCDF
0.5° x 0.625° Global Hourly, Daily, Monthly 1980-present N/A N/A MERRA-2 Reanalysis netCDF

Use Precipitation Data

Tutorials
Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

AIRS

The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer aboard NASA's Aqua satellite. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. 

The AIRS Precipitation Estimate is an estimate of daily precipitation measured in millimeters using cloud-related parameters of cloud-top pressure, fractional cloud cover, and cloud-layer relative humidity. The precipitation algorithm is a regression between these parameters and observed precipitation data. It is an estimate from AIRS using a TOVS-like algorithm and is intended for merging into the precipitation product of the Global Precipitation Climatology Project (GPCP).

Create and share layered maps with AIRS data using the AIRS Browse Tool.

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

AMSR2

The Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument collects data that indicate the rate at which precipitation is falling on the ocean surface in millimeters per hour (mm/hr). 

Data can be accessed and interactively explored using NASA Worldview:

Create and share layered maps with AMSR2 data using the AIRS Browse Tool.

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

Near real-time (NRT) Surface Precipitation products are generated within 3 hours by the Land, Atmosphere Near real-time Capability for EOS (LANCE). The NRT products are generated in HDF-EOS-5 augmented with netCDF-4/CF metadata and are available via HTTPS from LANCE. If data latency is not a primary concern, please use science quality products. Science quality products are an internally consistent, well-calibrated record of Earth's geophysical properties to support science.

GPM

NASA's Precipitation Measurement Missions (PMM) provide a continuous record of precipitation data through the Tropical Rainfall Measuring Mission (TRMM; operational 1997 to 2015) and the Global Precipitation Measurement mission (GPM; launched in 2014). GPM, the TRMM successor mission, provides more accurate measurements, improved detection of light rain and snow, and extended spatial coverage.

IMERG

Data products from TRMM and GPM are available individually and have been integrated with data from a global constellation of satellites to yield precipitation estimates with improved spatial coverage and temporal resolution. The first integrated product was the TRMM Multi-satellite Precipitation Analysis (TMPA), which has been superseded by the Integrated Multi-satellitE Retrievals for GPM (IMERG). IMERG's multiple runs accommodate different user requirements for accuracy and latency (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).

GPM data can be visualized using NASA Worldview:

The Short-term Prediction Research and Transition (SPoRT) project at NASA's Marshall Space Flight Center in Huntsville, AL, is a NASA- and NOAA-funded activity to transition experimental/ quasi-operational satellite observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale. SPoRT offers a Near Real-Time Viewer for IMERG data:

  • GPM IMERG Early
  • GPM IMERG Late
  • IMERG - Tropics

Users may access and visualize these data directly through ClimateSERV. Additional datasets include IMERG, Evaporative Stress Index, SMAP Soil Moisture, Rainfall, and NDVI.

Using an online interactive tool called Giovanni, map visualizations of IMERG data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

  • IMERG Final: Data are available from 2000-present
  • GPM: includes all IMERG runs, Early, Late, and Final
  • TMPA

NASA Earthdata GIS Products:

Near-real time (NRT) data:

  • IMERG Early Run Half-Hourly 
    • The "early run" product at NASA's Global Precipitation Measurement website is generated every half hour with a 6-hour latency from the time of data acquisition

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

  • TMPA
    Rainfall estimates at 3 hours, 1 day, or NRT and accumulated rainfall at 3 hours and 1 day. Data are available from 1997
  • IMERG
    Early, Late, and Final precipitation data on the half-hour or 1-day timeframe. Data are available from 2000

Model Data

CHIRPS-GEFS

SERVIR (a joint initiative of NASA, USAID, and geospatial organizations in Asia, Africa, and Latin America) and the Climate Hazards Group (CHG) at University of California at Santa Barbara have developed an improved rainfall forecast dataset that merges two highly recognized datasets: Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and the NCEP’s Global Ensemble Forecasting System (GEFS). GEFS is a weather forecast system that provides daily forecasts out to 16 days at 1º X 1º resolution at 6-hour intervals.The combined CHIRPS-GEFS dataset uses the higher spatial resolution of CHIRPS and the advanced forecasting ability of GEFS to provide up to a 16-day forecast updated every five days at a global spatial resolution of 5 km. CHIRPS-GEFS model data are available for analysis and download through the SERVIR Product Catalog. Users may access and visualize these data directly through ClimateSERV

Daymet

Another NASA source for precipitation data is Daymet, which can be accessed through NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). Daymet is a collection of gridded estimates of daily weather parameters including 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 are available from 1980 to present (North America and Hawaii) and from 1950 to present (Puerto Rico) and can be retrieved in a variety of ways, including: Earthdata Search; an API available through ORNL DAAC; ORNL DAAC tools; and through the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) application. Along with daily data, annual Daymet climatologies also are available.

GPCP

The Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set that combines observations and satellite precipitation data. 

Using an online interactive tool called Giovanni, map visualizations of GPCP Precipitation data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

LDAS

The Land Data Assimilation System (LDAS) includes a global collection (GLDAS), a North American collection (NLDAS), National Climate Assessment-Land Data Assimilation System (NCA-LDAS), and a Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). LDAS uses measurements including air temperature, precipitation, soil texture, and topography. GLDAS modeled data are available from January 1948 to present. NLDAS modeled datasets are available from January 1979 to present. FLDAS modeled datasets are available from January 1982 to present.

Data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:


Reanalysis Data

MERRA-2

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, daily, and monthly. These options provide information on precipitation.

Data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Precipitation data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

GIS Product using MERRA-2 reanalysis data:

Research-quality air surface temperature data products can be accessed using Earthdata Search:

The NASA Prediction Of Worldwide Energy Resources (POWER) Data Access Viewer provides MERRA-2 meteorological parameters through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are also available via API as well as via OPeNDAP.

Humidity is a measure of the amount of water vapor present in the atmosphere, which can impact air quality. For example, humidity levels affect the chemical reactions that control the formation of certain pollutants, like ozone. Additionally, in urban areas, humid air can trap pollutants close to the ground keeping them from moving and dissipating.

Commonly Used Humidity Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format

Global

Daily, Weekly, Monthly

2002-present

2,378 infrared channels in the 3.74 to 15.4 micron spectral range

Aqua

AIRS

Observation

HDF-EOS
0.5° x 0.625°

Global

Hourly, Daily, Monthly

1980-current

N/A

N/A

MERRA-2

Reanalysis

netCDF

Use Humidity Data

Tutorials
Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools

The NASA Earthdata Cloud Cookbook has tutorials to help access Earthdata in the cloud

Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

AIRS

The Atmospheric Infrared Sounder (AIRS) is a hyperspectral sounder that collects daily global measurements of water vapor and temperature profiles as one of four instruments comprising the AIRS Project Instrument Suite. 

Data can be accessed and interactively explored using NASA Worldview:

Create and share layered maps with AIRS data using the AIRS Browse Tool.

Using an online interactive tool called Giovanni, map visualizations of AIRS Relative Humidity data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

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


Reanalysis Data

MERRA-2

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, daily, and monthly. These options provide information on precipitation.

Monthly data can be accessed and interactively explored using NASA Worldview:

MERRA-2 Weather Maps

  • Animate and download weather maps for a variety of meteorological parameters, including humidity

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Humidity data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

GIS Product using MERRA-2 reanalysis data:

  • POWER Annual Meteorology
    • QV10M (Specific Humidity at 10 Meters): The ratio of the mass of water vapor to the total mass of air at 10 meters (kg water/kg total air)
    • QV2M (Specific Humidity at 2 Meters): The ratio of the mass of water vapor to the total mass of air at 2 meters (kg water/kg total air)
    • RH2M (Relative Humidity at 2 Meters): The ratio of actual partial pressure of water vapor to the partial pressure at saturation, expressed in percent

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

  • MERRA-2 Humidity in 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

The NASA Prediction Of Worldwide Energy Resources (POWER) Data Access Viewer provides MERRA-2 meteorological parameters through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are also available via API, GIS enabled, as well as via OPeNDAP.

  •  POWER provides Specific Humidity and Relative Humidity at 2 meters

The POWER Meteorological Data Overview provides additional information.

Currents of air carry pollutants from region to region, country to country, and even continent to continent. As these air currents move, they affect atmospheric chemistry by dispersing pollution, diluting concentrations, and creating less favorable conditions for secondary pollutants to form. Strong air currents help disperse pollution, leading to lower concentrations, while weak air currents can help increase the accumulation of pollution in certain locations. Additionally, wind transports pollutants at a given location depending on wind direction and location of source, leading to an increase or decrease in that pollutant. Aerosols are transported by wind, so higher aerosol concentrations are generally measured downwind from source regions.

Commonly Used Wind Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Name (Sensor, Model, etc.) Observation, Model, or Reanalysis File Format

5 km, 10 km

Global

Hourly, Daily

2012-present

10 km: 6.9-36.5 GHz; 5 km: 89.0 GHz

SHIZUKU (GCOM-W1)

*Advanced Microwave Scanning Radiometer 2 (AMSR2

Observation

HDF-EOS5

25 km

Near-global

Hourly, Near-daily

2017-present

Microwave: 1.575 GHz; L-Band (2-1 GHz)

Cyclone Global Navigation Satellite System (CYGNSS)

Delay Doppler Mapping Instrument (DDMI)

Observation

netCDF-4

0.5° x 0.625°

Global

Monthly

1980-present

N/A

N/A

MERRA-2

Reanalysis

netCDF

Use Wind Data

Tutorials

NASA’s Health and Air Quality Applied Sciences Team (HAQAST) Guide:

Use Cases and Articles
  • Smoke over Athens: The effects of forest fires show up in a multi-satellite view of pollution
  • Carbon Control: Radiocarbon and satellite data hint at the future of California emissions

Data Visualizations

AIRS Browse Tool

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

AMSR2

Data, often in near real-time (NRT), can be accessed and interactively explored using NASA Worldview:

Create and share layered maps with AMSR2 data using the AIRS Browse Tool.

Research-quality AMSR2 Wind, Level 2 NRT data are available in Earthdata Search from NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) 75 to 140 minutes after a satellite observation.

DDMI

The Delay Doppler Mapping Instrument (DDMI) is the single instrument aboard the eight individual satellites comprising NASA’s Cyclone Global Navigation Satellite System (CYGNSS) constellation. Each DDMI contains both a traditional Global Positioning System (GPS) navigation receiver integrated with a reflections processor. The DDMI aboard each of the eight CYGNSS micro-satellites receives signals broadcast from four orbiting GPS satellites along with the return of the same GPS satellite’s signal reflected from Earth. These signals are used to provide measurements of wind speed over the ocean to better understand and predict tropical cyclones.

Data can be accessed and interactively explored using NASA Worldview:

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


Reanalysis Data

MERRA-2

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, daily, and monthly. These options provide information on precipitation.

Monthly data can be accessed and interactively explored using NASA Worldview:

MERRA-2 Weather Analyses Maps

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Wind data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

GIS Product using MERRA-2 reanalysis data:

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

The NASA Prediction Of Worldwide Energy Resources (POWER) Data Access Viewer provides MERRA-2 meteorological parameters through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are also available via API, GIS enabled, as well as via OPeNDAP.

Surface Air Temperature (SAT) refers to the air temperature generally measured at approximately 6.5 feet (about 2 meters) above the ground or ocean surface. Surface air temperature provides a key indicator of climate change, contributing to the “global surface temperature record”.

Commonly Used Surface Air Temperature Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Name (Sensor, Model, etc.)

Observation, Model, or Reanalysis

File Format

1° 

Global

3 hours, 12 hours, Daily, Monthly

2002-present

2,378 infrared channels in the 3.74 to 15.4 micron spectral range

Aqua

AIRS

Observation

HDF-EOS

1 km

Over continental North America and Hawaii and Puerto Rico Daily Over continental North America and Hawaii from 1980 and over Puerto Rico from 1950 through the end of the most recent full calendar year N/A N/A Daymet

Model

netCDF, Cloud Optimized GeoTIFF (COG)
Varies:
0.01°, 0.1°, 0.125°, 0.25°, 1°
Global Varies: Hourly, 3-hourly,Daily, Monthly Varies:
1948-present
N/A N/A Land Data Assimilation Systems (LDAS) Model netCDF
0.5° x 0.625°

Global

Monthly

1980-present

N/A N/A

MERRA-2

Reanalysis

netCDF

Use Surface Air Temperature Data

Tutorials

NASA’s Health and Air Quality Applied Sciences Team (HAQAST) Guide:

Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

AIRS

The Atmospheric Infrared Sounder (AIRS) is a hyperspectral sounder that collects daily global measurements of water vapor and temperature profiles as one of four instruments comprising the AIRS Project Instrument Suite. 

Data can be accessed and interactively explored using NASA Worldview:

Create and share layered maps with AIRS data using the AIRS Browse Tool.

Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:

Research-quality air surface temperature data products can be accessed using Earthdata Search:

AIRS NRT data are available from NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) 75 to 140 minutes after a satellite observation.


Model Data

Daymet

A NASA source for air temperature modeled data is Daymet. Daymet is a collection of gridded estimates of daily weather parameters including 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 are available from 1980 to present (North America and Hawaii) and from 1950 to present (Puerto Rico).

Research-quality air surface temperature data products can be accessed using Earthdata Search:

LDAS

The Land Data Assimilation System (LDAS) includes a global collection (GLDAS), a North American collection (NLDAS), National Climate Assessment - Land Data Assimilation System (NCA-LDAS), and a Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). LDAS uses measurements including air temperature, precipitation, soil texture, and topography. GLDAS modeled data are available from January 1948 to present. NLDAS modeled datasets are available from January 1979 to present. FLDAS modeled datasets are available from January 1982 to present.

Monthly data can be visualized using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of LDAS data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:


Reanalysis Data

MERRA-2

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, air temperature at 2 m, and air temperature at 10 m.

Data can be accessed and interactively explored using NASA Worldview:

MERRA-2 Weather Maps

  • Animate and download weather maps for a variety of meteorological parameters, including air temperature

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Temperature data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

GIS Product using MERRA-2 reanalysis data:

Research-quality air surface temperature data products can be accessed using Earthdata Search:

Land surface reflectance is a measure of the fraction of incoming solar radiation reflected from Earth's surface to a satellite-borne or aircraft-borne sensor. These data provide an estimate of the surface spectral reflectance as it would be measured at ground level in the absence of atmospheric scattering or absorption, which is referred to as atmospheric correction.

Changes can be detected and characterized using surface reflectance data when comparing multiple images for the same region of Earth’s surface. For example, as pollutants or aerosols like dust spread over an area, they can affect surface reflectance values and this can be detected by sensors aboard orbiting satellites. This allows land cover to be observed and analyzed over time using sustained land imaging and multi-spectral high-resolution imagery. Surface reflectance data are not only used for visualizing the surface, but also for computing metrics and creating models that are useful for specific analysis.

Commonly Used Land Surface Reflectance Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use. 

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform

Name (Sensor, Model, etc.)

Observation, Model, or Reanalysis

File Format

15 m, 30 m

Global

Varies

2000-present

14 bands ranging from 0.52 µm to 11.65 µm            

Terra

ASTER

Observation

HDF-EOS, GeoTIFF

500 m, 1 km, 0.05°

Global

1-2 days

2000-present

36 bands ranging from 0.4 µm to 14.4 µm       

Terra, Aqua

*MODIS

Observation

HDF-EOS5

375 m, 500 m, 750 m, 1 km,
5.5 km

Global

1-2 days, 8-day

2017-present

22 bands ranging from 0.41 µm to 12.01 μm            

Suomi NPP

*VIIRS

Observation

HDF5, HDF-EOS5, netCDF4

15 m, 30 m, 60 m

Global

16 days

1982-present (various missions)

OLI/OLI-2: 9 bands ranging in wavelength from 0.43 µm to 1.38 µm

ETM+: 8 bands ranging in wavelength from 0.45 µm to 12.5 µm

TM: 7 bands ranging in wavelength from 0.45 µm to 2.35 µm

Landsat 4, 5, 7, 8, 9

OLI-2,
OLI,
ETM+,
TM

Observation

GeoTIFF

30 m

Near-global (no Antarctic)

2-3 days

2013-present

OLI/OLI-2: 9 bands ranging in wavelength from 0.43 µm to 1.38 µm

MSI: 12 bands ranging in wavelength from 0.443 µm to 2.190 µm

Harmonized Landsat Sentinel-2 (HLS: Landsat 8, 9 + Sentinel-2A/B)

OLI, MSI

Observation

Cloud Optimized GeoTIFF (COG)

Use Land Surface Reflectance Data

Tutorials
Use Cases and Articles
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

ASTER

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument is a cooperative effort between NASA and Japan's Ministry of Economy, Trade and Industry (METI). 

ASTER Surface Reflectance data can be visualized and interactively explored using NASA Worldview:

Research quality ASTER data products are available through Earthdata Search:

ASTER surface reflectance products are processed on-demand and can be requested through Earthdata Search:

ETM+, OLI, OLI-2, TIRS-2

The Enhanced Thematic Mapper (ETM+), the Operational Land Imager (OLI), and the Thermal Infrared Sensor-2 (TIRS-2) are aboard the joint NASA/USGS Landsat series of satellites.

OLI data can be visualized and interactively explored using NASA Worldview:

Research quality Landsat 7, 8, and 9 ETM+, OLI, and OLI-2 land surface reflectance data products can be accessed directly using USGS EarthExplorer.

HLS

Harmonized Landsat Sentinel-2 (HLS) data provide consistent  global observation of Earth’s surface reflectance and top-of-atmosphere (TOA) brightness data from the Landsat OLI and the ESA (European Space Agency) Multi-Spectral Instrument (MSI) every 2 to 3 days with 30-meter spatial resolution.

HLS Surface Reflectance data can be visualized and interactively explored using NASA Worldview:

Research quality HLS data products can be accessed directly from Earthdata Search

The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) tool offers a simple and efficient way to access, transform, and visualize geospatial data from a variety of federal data archives, including USGS Landsat Analysis Ready Data (ARD) surface reflectance products. 

MODIS

Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance products provide an estimate of the surface spectral reflectance as it would be measured at ground level in the absence of atmospheric scattering or absorption.

MODIS Surface Reflectance data can be visualized and interactively explored using NASA Worldview:

Multiple Geographic Information Systems (GIS) MODIS Surface Reflectance data layers with different band combinations are available through Esri’s ArcGIS OnLine (AGOL). NASA GIS data may be used with open-source GIS software:

Research quality MODIS data products can be accessed directly from Earthdata Search:

Near real-time (NRT) MODIS Surface Reflectance data are available through NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) within 60 to 125 minutes after a satellite observation:

Earthdata GIS Products:

VIIRS

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites. 

VIIRS Surface Reflectance data can be visualized and interactively explored using NASA Worldview:

Research quality VIIRS data products can be accessed directly from Earthdata Search:

Near real-time (NRT) VIIRS Surface Reflectance data are available through LANCE within 60 to 125 minutes after a satellite observation:

Topography is the general configuration of the land surface, including its relief and the position of its natural features. Factors including regional topography, prevailing wind speed and direction, amount of natural and human-created aerosols, increased industrial growth and urbanization, and high population density can result in unhealthy levels of air pollution that can affect a region for days and weeks. Topographic data are often in the form of Digital Elevation Models (DEMs) or grids with values representing the height of a cell.

Commonly Used Topography/Elevation Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform

Sensor(s)/ Model Name

Observation or Model File Format
30 m for U.S., 60 m, 90 m, 1 km for global Global One-time estimate 2000 N/A SRTM N/A Observation HGT, netCDF4
30 m Global Multi-year 2000-2013 14 bands ranging from 0.52 µm to 11.65 µm Terra ASTER Observation

HDF-EOS or GeoTIFF

25 m diameter

51.6° N to 51.6° S

One-time estimate 2019-2022 Laser wavelength: 1.064 µm International Space Station

Global Ecosystem Dynamics Investigation (GEDI) mission 

Observation and Model HDF5

30 m

All land between 60° N and 56° S latitude.

Multi-day

2000

N/A

NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (NASADEM)

Inputs from multiple sensors including SRTM, ASTER, ICESat GLAS and PRISM

Model

HGT or netCDF4

Use Topography Data

Tutorials
Use Cases and Articles
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

ASTER

The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).

DEM data accuracy is typically very sensitive to vegetation cover; however, data from the ASTER instrument tend to perform better over specific landcover types. DEM data can be accessed and interactively explored using NASA Worldview:

Research quality topography data products are available from Earthdata Search:

In addition to Earthdata Search, SRTM and ASTER data can be accessed through AppEEARS.

GEDI

The Global Ecosystem Dynamics Investigation (GEDI) Level 3 Land Surface Metrics dataset provides gridded mean canopy height, standard deviation of canopy height, mean ground elevation, standard deviation of ground elevation, and counts of laser footprints per 1 km x 1 km grid cells within 52° north and south latitude. Data are available from April 2019 through 2022. Level 3 gridded products can be used to create digital elevation models, characterize important carbon and water cycling processes, and more. 

Users may download customized subsets (Level 3 and Level 4) of GEDI data using the Spatial Data Access Tool through NASA’s Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC).

GEDI L3 Gridded Land Surface Metrics data can be visualized and interactively explored using NASA Worldview:

Research quality data can be accessed using Earthdata Search:

SRTM

One of the most common topography data sources is the Shuttle Radar Topography Mission (SRTM). SRTM provides a DEM of all land between 60° north and 56° south latitude, which encompasses about 80% of Earth's landmass. 

DEM data can be accessed and interactively explored using NASA Worldview:

Research quality topography data products are available from Earthdata Search:

  • SRTM
    These data were acquired in 2000 and are in raw format (with the ".hgt" file extension), and can be opened in most Geographic Information Systems (GIS), such as ArcGIS or QGIS

In addition to Earthdata Search, SRTM can be accessed through AppEEARS.


Model Data

NASADEM

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (DEM) version 1 (NASADEM_HGT) dataset provides global elevation data at 1 arc second spacing. NASADEM extends the legacy of the SRTM by improving the DEM height accuracy and data coverage as well as providing additional SRTM radar-related data products. NASADEM are distributed in 1 degree latitude by 1 degree longitude tiles and consist of all land between 60° N and 56° S latitude. This accounts for about 80% of Earth’s total landmass.  

Research quality topography data products are available from Earthdata Search:

Commonly Used Soil Moisture Data at a Glance

Descriptions of these measurements will be reviewed in more detail later in this Data Pathfinder. The following sections will help guide you to topic-specific data and resources for accessing, visualizing, preparing/manipulating (e.g. subsetting), and analyzing data. Each observation, model, and reanalysis data has unique characteristics that should be considered when evaluating its use. 

An asterisk (*) next to an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). While not intended for scientific research, NRT data are good resources for monitoring ongoing or time-critical events. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Sensor(s)/ Model Name Observation or Model File Format

9 km to 40 km

Near global

Daily, 3 days

2015- present

1.41 GHz (Radiometer frequency)

Soil Moisture Active Passive (SMAP)

*Radar (active; no longer functional)

Microwave radiometer (passive)

Observation and Model

HDF5

25 km

Global

50 min

2012-near present

16 channels ranging in frequency from 6.925 GHz to 89 GHz

SHIZUKU (GCOM-W1)

*Advanced Microwave Scanning Radiometer 2 (AMSR2

Observation

HDF-EOS5

0.01°, 0.1°, 0.125°, 0.25°, 1°

Global

Hourly, 3-hourly,Daily, monthly

1948-present

N/A

N/A

Land Data Assimilation Systems (LDAS

Model

netCDF

3 km

Continental U.S., Alaska, Puerto Rico

Daily

2003-2021

N/A

N/A

Short-term Prediction Research and Transition-Land Information System (SPoRT-LiS)

Model

netCDF

9 km

Global

3 hour

2015-present

N/A

N/A

GMAO SMAP

Model

HDF5

0.5° x 0.625°

Global

Hourly, daily, monthly

1980-present

N/A

N/A

MERRA-2

Reanalysis

netCDF

0.125°

North America 

7 days

2002-present

N/A

N/A

GRACE-DA-DM

Model

netCDF

Use Soil Moisture Data

Tutorials
Use Cases and Articles

Data Visualizations

GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

AMSR-2

The Advanced Microwave Scanning Radiometer (AMSR) for EOS (AMSR-E) instrument and the AMSR-2 instrument provide volumetric soil moisture data. The Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument provides global passive microwave measurements of surface soil moisture. Near real-time (NRT) products available through the Land, Atmosphere Near real-time Capability for EOS (LANCE) are generated within 3 hours of the last observations in the file.

Data can be visualized using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of AMSR-2 data can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Near-real time data:

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

SMAP

NASA's Soil Moisture Active Passive satellite (SMAP, launched in 2015) measures the moisture in the top 5 cm of soil globally daily and every 2-3 days at a resolution of 9-36 km. 

Near real-time SMAP imagery can be accessed and interactively explored using NASA Worldview:

  • SMAP (includes root zone and surface soil moisture values)

Research quality data products can be accessed using Earthdata Search:

Near real-time (NRT) SMAP data are available through NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) within 60 to 125 minutes after a satellite observation:


Model Data

GRACE-DA-DM

Weekly soil moisture and groundwater drought indicators are available each week based on terrestrial water storage observations derived from Gravity Recovery and Climate Experiment (GRACE) satellite data and integrated with other observations, using a sophisticated numerical model of land surface water and energy processes, referred to as GRACE Data Assimilation for Drought Monitoring (GRACE-DA-DM).

GMAO SMAP

NASA’S Global Modeling And Assimilation Office (GMAO), in collaboration with the University of Montana and NASA’s Jet Propulsion Laboratory, provides value-added Level 4 data products. These Level 4 datasets merge SMAP observations into physically-based numerical models of the land surface water, energy, and carbon cycles. Available Level 4 data include global, 9-km, 3-hourly estimates of surface and root zone soil moisture, surface and soil temperature, and land surface fluxes, along with algorithm diagnostics from the ensemble-based data assimilation system. Level 4 data also include global, 9-km, daily estimates of net ecosystem CO2 exchange, component carbon stocks and fluxes, and sub-grid information broken down by plant functional types.

Near real-time SMAP imagery can be accessed and interactively explored using NASA Worldview:

 These data products are available from Earthdata Search:

LDAS

NASA, in collaboration with other agencies, has developed models of soil moisture content that incorporate satellite information with ground-based data (when ground-based data are available). The Land Data Assimilation System (LDAS) includes a global collection (GLDAS), a North American collection (NLDAS), National Climate Assessment - Land Data Assimilation System (NCA-LDAS), and a Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). LDAS uses measurements including air temperature, precipitation, soil texture, and topography. GLDAS modeled data are available from January 1948 to present. NLDAS modeled datasets are available from January 1979 to present. FLDAS modeled datasets are available from January 1982 to present.

The NLDAS experimental drought monitor is derived from near real-time soil moisture output model data: 

Soil MERGE (SMERGE) is a root-zone soil moisture product developed by merging NLDAS land surface model output with surface satellite retrievals from the ESA (European Space Agency) Climate Change Initiative. This data product contains root-zone soil moisture of 0-40 cm layer, Climate Change Initiative (CCI)-derived soil moisture anomalies of 0-40 cm layer, and a soil moisture data estimation flag.

Using an online interactive tool called Giovanni, map visualizations of LDAS and SMERGE data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

LDAS Soil Moisture data from GLDAS, NLDAS and FLDAS are available in Earthdata Search:

SPoRT-LiS

The Short-term Prediction Research and Transition (SPoRT) project at NASA's Marshall Space Flight Center in Huntsville, AL, is a NASA- and NOAA-funded activity to transition experimental/quasi-operational satellite observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale.SPoRT-Land Information System (SPoRT-LiS) provides real-time 3km Land Information System data on the following parameters: Volumetric Soil Moisture, Relative Soil Moisture, Column-Integrated Relative Soil Moisture, and Green Vegetation Fraction.

SPoRT offers a Near Real-Time Viewer that includes SMAP datasets for the following regions:

  • ENH Alaska (9km Enhanced)
  • ENH CONUS (9km Enhanced)
  • ENH East Africa (9km Enhanced)
  • L2 Conus (Level 2)
  • L2 East Africa (Level 2)

Reanalysis Data

MERRA-2

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: hourly and monthly from 1980.

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Soil Moisture data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

MERRA-2 Soil Moisture data in Earthdata Search

Image
map of world with colors indicating high PM2.5 concentrations
Map of global PM2.5 concentrations with orange and red colors indicating higher concentrations. Map from the SEDAC Global (GL) Annual PM2.5 Grids from MODIS, MISR, and SeaWiFS Aerosol Optical Depth (AOD), v4.03 (1998–2019) dataset. doi:10.7927/fx80-4n39. Click on image for larger view. Credit: NASA's SEDAC.

Air quality-related deaths and diseases that are exacerbated by air pollution are preventable, but prevention requires a knowledge of where vulnerable populations exist and what interventions are needed in these communities. Poor air quality tends to be elevated in low to middle-income countries, where 98% of urban centers with populations greater than 100,000 do not meet World Health Organization (WHO) guidelines.

Integrating socioeconomic data with air quality data can provide a more accurate analysis of populations facing greater exposure and vulnerability from pollutants. A number of socioeconomic factors need to be considered when analyzing air quality, including:

  • Population
  • Poverty
  • Unemployment
  • Academic attainment
  • Housing burden
  • Social vulnerability

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

SEDAC’s Air Quality Data for Health-Related Applications data collection provides air quality data for health-related research and applications. This collection consists of the Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000-2016) and Daily 8-Hour Maximum and Annual O3 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000-2016) datasets. A similar NO2 dataset is in development. Additional SEDAC datasets on population exposure and vulnerability (Note: An Earthdata Login is required for data access):

Combining regional or community-level socioeconomic data (such as life expectancy, prevalence of asthma, or prevalence of health insurance coverage) with Earth science data (such as NO2 and SO2 concentrations) provides a way of examining environmental justice aspects of air quality and exploring how certain communities are impacted to a greater degree by pollution. For more information about how NASA is applying Earth science data to environmental justice, please see the Environmental Justice at NASA Backgrounder. The following open access articles provide additional information about research using Earth science data to explore environmental justice:

  • Estimating Intra-Urban Inequities in PM2.5-Attributable Health Impacts: A Case Study for Washington, D.C. (doi:10.1029/2021GH000431)
  • Estimating Daily PM2.5 Concentrations in New York City at the Neighborhood-Scale: Implications for Integrating Non-Regulatory Measurements (doi:10.1016/j.scitotenv.2019.134094)
  • Air Quality and Environmental Injustice in India: Connecting Particulate Pollution to Social Disadvantages (doi:10.3390/ijerph18010304)
  • Developing an Adaptive Pathway to Mitigate Air Pollution Risk for Vulnerable Groups in South Korea (doi:10.3390/su12051790)

Use Human Dimension Data

Tutorials
Use Cases and Articles
Data Visualizations
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools

Panoply: NASA’s Panoply visualization tool plots geo-referenced and other arrays from netCDF, HDF, GRIB, and other datasets. It can be used to help plot data on global or regional maps, allow users to select from multiple map projections, and overlay continent outlines or masks

Programming Tools
  • The Earthdata Developer Portal is for application developers who wish to build applications that search, access, and browse EOSDIS-hosted Earth science data
  • Need help? If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics
  • If you have general questions about health and air quality data, research, and applications, visit the Health and Air Quality Community Forum, where you can interact with other data users and experts from NASA HAQAST

Learn More

Last Updated