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1,574 results for “atmospheres”
Ground-Based Global Navigation Satellite System (GNSS)-based Upper Atmospheric Realtime Disaster Information and Alert Network (GUARDIAN) Galileo daily antenna phase maps (meta data, 24-hour files) from NASA CDDIS
This product contains file names and URLs to files containing antenna phase map data used in the real-time Galileo POD processing. In particular, the IGS ANTEX file name used for the processing is provided. Additional meta data items may include information that identifies the real-time filter source populating the Galileo real-time POD products (see "pos", "quat", and "tdp" products). The product is generated at JPL's Global Differential GPS Operations Centers.
METOP-B AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05 Deg CMG
The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present. The CDR is critically important to studying global climate change. The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions. The LTDR draws from the following eight AVHRR missions: NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR). LAI/fPAR was developed as an experimental product.The METOP-B AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05 Deg CMG, short-name M1_ AVH09C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (AVH01C1). The M1_ AVH09C1 consist of BRDF-corrected surface reflectance for bands 1, 2, and 3, data Quality flags, angles (solar zenith, view zenith, and relative azimuth), and thermal data (thermal bands 3, 4, and 5). The AVH09C1 product is available in HDF4 file format.
MODIS/Aqua Atmosphere BELMANIP Subsetting Product
The MODIS/Aqua Atmosphere BELMANIP subsetting Product (MYDBMSS) consists of MODIS Atmosphere and Ancillary Products subsets that are generated over the Bench-mark Land Multisite Analysis and Intercomparison of Products (BELMANIP) sites. The BELMANIP sites is a network of sites, distributed globally and consist of existing networks such as Earth Observing System (EOS) Core Sites, Bigfoot, Validation of Land European Remote sensing Instruments (VALERI), a global network of micrometeorological flux measurement (FLUXNET), the aerosol robotic network (AERONET) and a set of additional sites.The process of generating cutouts for these sites involves locating and identifying a subset of sites taken from global BELMANIP sites that are within the spatial coverage of a 5 minute Level 2 MODIS granule and extracting 0.5 x 0.5 degree cutouts. The MODBMSS data set consists of subsets for approximately 445 sites around the globe. There is one file per site with 55 Science Data Sets (SDS) such as at-aperture radiances for 36 discrete MODIS bands, Cloud Mask, and Water Vapor, etc.
NOAA-11 AVHRR Atmospherically Corrected Normalized Difference Vegetation Index Daily L3 Global 0.05 Deg. CMG
The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present. The CDR is critically important to studying global climate change. The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions. The LTDR draws from the following eight AVHRR missions: NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR). LAI/fPAR was developed as an experimental product.The NOAA-11 AVHRR Atmospherically Corrected Normalized Difference Vegetation Index (NDVI) Daily L3 Global 0.05 Deg CMG, short-name N11_AVH13C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (N11_AVH01C1). The N11_AVH13C1 product is available in HDF4 file format.
CAMEX-3 ATMOSPHERIC EMITTED RADIANCE INTERFEROMETER (AERI) V1
The Atmospheric Emitted Radiance Interferometer (AERI) was used to make atmospheric temperature and moisture retrievals. AERI provides absolutely calibrated radiances which can be used for forward calculation comparisons of radiosonde and LIDAR (for CAMEX-3, the SRL) profiles and provides a reference to the airborne and ground based remote sensing instruments. Additionally, AERI radiances contain valuable temperature and water vapor information which can be used to retrieve planetary boundary layer thermodynamics. The University of Wisconsin-Madison, Space Science and Engineering Center was responsible for the AERI data collection during CAMEX-3 campaign.
Ground-Based GNSS-based Upper Atmospheric Realtime Disaster Information and Alert Network (GUARDIAN) Galileo daily accumulated real-time Precise Orbit Determination (POD) Attitude Quaternions (30-second sampling, 24-hour files) from NASA CDDIS
This product contains a time series of attitude quaternion components for healthy satellites in the Galileo constellation that are accumulated every minute throughout the day. The product is generated at JPL's Global Differential GPS Operations Centers in real-time. The data in this product can be concatenated with other daily products to provide larger coverage in time.
First ISCCP Regional Experiment (FIRE) Marine Stratocumulus Ceilometer and Cross-chain Loran Atmospheric Sounding System (CLASS) Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to seek the basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between ISCCP data, GCM parameterizations, and higher space and time resolution cloud data. To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.These data were collected during the FIRE Marine Stratocumulus experiment on San Nicolas Island, California. They are as follows: cloud base height data measured with a ceilometer; processed CLASS sounding (CSD) data up to 2 kilometers (thermodynamic data only), raw CSD recorded at 3.3 second intervals (thermodynamic data only), and raw CSD at 10 second intervals (thermodynamic and wind data).
SOLVE I DC-8 Aircraft Remotely Sensed Lidar Atmospheric Sensing Experiment (LASE) Data
SOLVE1_AircraftRemoteSensing_DC8_LASE_Data is the remotely sensed trace gas data for the DC-8 aircraft collected during the SAGE III Ozone Loss and Validation Experiment (SOLVE) by the Lidar Atmospheric Sensing Experiment (LASE) instrument. Data collection for this product is complete.The SOLVE campaign was a NASA multi-program effort of the Upper Atmosphere Research Program (UARP), Atmospheric Effects of Aviation Project (AEAP), Atmospheric Chemistry Modeling and Analysis Program (ACMAP) and Earth Observing System (EOS) of NASA’s Earth Science Enterprise (ESE). SOLVE’s primary objective was for calibrating and validating the Stratospheric Aerosol and Gas Experiment (SAGE) III satellite measurements, while examining the processes that controlled ozone levels at a mid- to high-latitude range. The major goal of SAGE III was to quantitatively assess ozone loss at high latitudes. SOLVE was a two-phase experiment, the first phase, SOLVE, occurred during the fall of 1999 through the spring of 2000. The second phase, SOLVE II, occurred during the winter of 2003.SOLVE took place in the Arctic high-latitude region during the winter. The polar ozone depletion processes cause by human-produced chlorine and bromine are most active in mid-to-late winter and early spring in the high Arctic. In order to conduct this validation experiment, NASA deployed the NASA ER-2 aircraft and NASA DC-8 aircraft. The ER-2 measured a variety of atmospheric data, including ozone (O3), H2O, CO2, ClONO2, HCl, ClO/BrO, and Cl2O2. The DC-8 aircraft measured ozone, ClO/BrO, and aerosol, among other atmospheric data. SOLVE also utilized balloon platforms, ground-based instruments, and collaborations with the German Aerospace Center’s (DLR) FALCON aircraft equipped with the OLEX Lidar to achieve the mission objectives. Overall, the campaign had 28 flights, with SOLVE featuring 17 total flights among the different aircrafts and SOLVE II featuring 11 flights.
NOAA-16 AVHRR Atmospherically Corrected Normalized Difference Vegetation Index Daily L3 Global 0.05 Deg. CMG
The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present. The CDR is critically important to studying global climate change. The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions. The LTDR draws from the following eight AVHRR missions: NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR). LAI/fPAR was developed as an experimental product.The NOAA-16 AVHRR Atmospherically Corrected Normalized Difference Vegetation Index (NDVI) Daily L3 Global 0.05 Deg CMG, short-name N16_AVH13C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (N16_AVH01C1). The N16_AVH13C1 product is available in HDF4 file format.
MODIS/Terra Atmosphere FluxNet Subsetting Product
The MODIS/Terra Atmosphere FluxNet Subsetting Product (MODFNSS) consists of MODIS Atmosphere and Ancillary Products subsets that are generated over a global network of micrometeorological flux measurement (FLUXNET) sites. The process of generating cutouts for these sites involves locating and identifying a subset of sites taken from a global FLUXNET that are within the spatial coverage of a 5 minute Level 2 MODIS granule and extracting 0.5 x 0.5 degree cutouts. The MODFNSS data set consists of subsets for around 400 sites out of the total flux tower sites around the globe. There is one file per site with around 55 Science Data Sets (SDS) such as at-aperture radiances for 36 discrete MODIS bands, Cloud Mask, and Water Vapor, etc.
Ground-Based GNSS-based Upper Atmospheric Realtime Disaster Information and Alert Network (GUARDIAN) GLONASS daily accumulated real-time Precise Orbit Determination (POD) Attitude Quaternions (30-second sampling, 24-hour files) from NASA CDDIS
This product contains a time series of attitude quaternion components for healthy satellites in the GLONASS constellation that are accumulated every minute throughout the day. The product is generated at JPL's Global Differential GPS Operations Centers in real-time. The data in this product can be concatenated with other daily products to provide larger coverage in time.
NOAA-14 AVHRR Top-of-Atmosphere Reflectance Daily L3 Global 0.05 Deg. CMG
The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present. The CDR is critically important to studying global climate change. The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions. The LTDR draws from the following eight AVHRR missions: NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR). LAI/fPAR was developed as an experimental product.The NOAA-14 AVHRR Top-of-Atmosphere Reflectance Daily L3 Global 0.05Deg CMG, short-name N14_AVH02C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (AVH01C1). The N14_AVH02C1 consist of Top-of-atmosphere reflectance for bands 1 and 2, data Quality flags, angles (solar zenith, view zenith, and relative azimuth), thermal data (thermal bands 3, 4 and 5), and additional data (scan time).
TROPICS03 L2B Neural-network Atmospheric Vertical Temperature & Moisture Profiles V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is the Level-2B Neural Network Atmospheric Vertical Profiles (NNAVP) – Neural Network vertical profile retrieval approach for temperature profiles in Kelvin (K) and water vapor mixing ratio profiles in (kg/kg). Retrievals are done in all non and precipitating conditions, over both land and ocean. Temperature profiles go from surface to 20 km and water profiles from surface to 10-km. The geophysical retrieval of atmospheric vertical temperature is at the larger unified F-band spatial resolution while the retrieval of vertical moisture is at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.
NOAA-18 AVHRR Atmospherically Corrected Normalized Difference Vegetation Index Daily L3 Global 0.05 Deg. CMG
The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present. The CDR is critically important to studying global climate change. The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions. The LTDR draws from the following eight AVHRR missions: NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B.Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR). LAI/fPAR was developed as an experimental product.The NOAA-18 AVHRR Atmospherically Corrected Normalized Difference Vegetation Index Daily L3 Global 0.05Deg CMG, short-name N18_AVH13C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (N18_AVH01C1). The N18_AVH13C1 product is available in HDF4 file format.
Ground-Based GNSS-based Upper Atmospheric Realtime Disaster Information and Alert Network (GUARDIAN) GPS daily accumulated real-time Precise Orbit Determination (POD) orbits (60-second sampling, 24-hour files) from NASA CDDIS
This product contains a time series of position and velocity components for healthy satellites in the GPS constellation that are accumulated every minute throughout the day. In addition, formal 1-sigma uncertainties for the positions and velocities are provided. The product is generated at JPL's Global Differential GPS Operations Centers in real-time. The data in this product can be concatenated with other daily products to provide larger coverage in time.
DISCOVER-AQ Maryland Deployment UC-12 Aircraft Remotely Sensed Airborne Compact Atmospheric Mapper Data
DISCOVERAQ_Maryland_AircraftRemoteSensing_UC12_ACAM_Data contains remotely sensed data collected by the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's UC-12 aircraft during the Maryland deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Maryland deployment and data collection is complete.Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality.DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.
First ISCCP Regional Experiment (FIRE) Cirrus Phase II Cross-chain LORAN Atmospheric Sounding System (CLASS) Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13-November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29-July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13-December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1-June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.The Cross-chain LORAN Atmospheric Sounding System (CLASS) sonde data were collected in four locations: Arkansas City, KS; Coffeyville, KS: Iola, KS; and Muskegee, OK.
TROPICS06 L2B Neural-network Atmospheric Vertical Temperature & Moisture Profiles V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. This dataset is the Level-2B Neural Network Atmospheric Vertical Profiles (NNAVP) – Neural Network vertical profile retrieval approach for temperature profiles in Kelvin (K) and water vapor mixing ratio profiles in (kg/kg). Retrievals are done in all non and precipitating conditions, over both land and ocean. Temperature profiles go from surface to 20 km and water profiles from surface to 10-km. The geophysical retrieval of atmospheric vertical temperature is at the larger unified F-band spatial resolution while the retrieval of vertical moisture is at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.
DISCOVER-AQ Texas Deployment B-200 Aircraft Remotely Sensed Airborne Compact Atmospheric Mapper Data
DISCOVERAQ_Texas_AircraftRemoteSensing_B200_ACAM_Data contains remotely sensed data collected by the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's B-200 aircraft during the Texas (Houston) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Texas deployment and data collection is complete.Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality.DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.
MODIS/Aqua Atmospherically Corrected Surface Reflectance 5-Min L2 Swath 250m, 500m, 1km NRT
The MODIS/Aqua Atmospherically Corrected Surface Reflectance 5-Min L2 Swath 250m, 500m, 1km NRT, short name MYD09, is computed from the MODIS Level 1B land bands 1, 2, 3, 4, 5, 6, and 7 (centered at 648 nm, 858 nm, 470 nm, 555 nm, 1240 nm, 1640 nm, and 2130 nm, respectively). The product is an estimate of the surface spectral reflectance for each band as it would have been measured at ground level if there were no atmospheric scattering or absorption. The surface-reflectance product is the input for product generation for several land products: vegetation Indices (VIs), BRDF, thermal anomaly, snow/ice, and Fraction of Photosynthetically Active Radiation/Leaf Area Index (FPAR/LAI).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.