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Particle physics, nuclear physics, condensed matter, plasma physics, optics, acoustics, quantum mechanics
6,283 datasets
Near real-time cloud property data derived from the GISS Polarimetric Cloud algorithm on NASA's PACE satellite. The Ocean Biology DAAC produces this snapshot using the best-available ancillary meteorological and ozone data during a single orbit. Several experimental variables are included for diagnostic purposes and future refinement.
Satellite-derived geophysical variables for aerosol and ocean color studies from the PACE mission's HARP2 instrument. The data is produced by the Fast Multi-Angle Polarimetric Ocean and Land algorithm, which uses a coupled atmosphere-ocean model accelerated by neural networks. The dataset includes aerosol optical thickness, single scattering albedo, layer height, and chlorophyll-a concentration, among other parameters.
The FastMAPOL algorithm produces near real-time aerosol and ocean color products using the best available combination of ancillary data from meteorological and ozone sources. These simultaneous retrievals jointly solve for aerosol and ocean parameters using a coupled atmosphere-ocean vector radiative-transfer model accelerated by deep neural networks. The suite includes aerosol optical thickness, single scattering albedo, layer height, effective radius, and ocean surface wind speed.
Global satellite-derived measurements of inherent optical properties (IOPs) of seawater, produced by the Ocean Biology DAAC. The data provides per-pixel coefficients for total absorption and backscattering, supporting near real-time monitoring. It is generated using the Generalized Inherent Optical Properties (GIOP) model framework applied to VIIRS sensor data.
The Ocean Biology DAAC produces near real-time (NRT) products using the best-available combination of ancillary data from meteorological and ozone data. This dataset provides per-pixel inherent optical properties (IOPs) retrieved from spectral Remote Sensing Reflectance using the Generalized Inherent Optical Properties (GIOP) model framework. It supports water-type classification, water-clarity assessment, biogeochemical studies, and radiative-transfer applications.
The NOAA-21 VIIRS Level-2 Regional Inherent Optical Properties (IOP) Data, version 2025.0, provides per-pixel measurements of how seawater absorbs and scatters light. It is produced by the OB_CLOUD organization using the Generalized Inherent Optical Properties (GIOP) model framework on satellite-derived Remote Sensing Reflectance (Rrs). The dataset includes geophysical variables such as total absorption and backscattering coefficients, supporting studies of marine biogeochemistry and water clarity.
Near real-time satellite data providing per-pixel inherent optical properties of seawater, including absorption and backscattering coefficients. The Ocean Biology DAAC produces these products using the best-available ancillary meteorological and ozone data for a snapshot within a single orbit. These products support water-type classification, water-clarity assessment, and biogeochemical studies.
NOAA-20 VIIRS Level-3 Global Mapped Inherent Optical Properties (IOP) - Near Real-time (NRT) Data, version 2022.0, is produced by the Ocean Biology DAAC. The dataset provides per-pixel inherent optical properties, including total absorption and backscattering coefficients, derived from satellite remote sensing reflectance using the Generalized Inherent Optical Properties (GIOP) model. It offers a snapshot of ocean optical conditions within a single orbit using near real-time processing.
This dataset provides near real-time (NRT) global inherent optical properties (IOP) products derived from VIIRS satellite data for 2024. It includes per-pixel absorption and backscattering coefficients for seawater constituents like phytoplankton and detritus, supporting water-type classification, clarity assessment, and biogeochemical studies. The data is produced by NASA's Ocean Biology DAAC and combines ancillary meteorological and ozone data for calibration.
Satellite-derived inherent optical properties of seawater from the NOAA-20 VIIRS sensor. The data includes per-pixel absorption and backscattering coefficients retrieved using the Generalized Inherent Optical Properties (GIOP) model framework. It is produced by OB_CLOUD and supports water-type classification and biogeochemical studies.
Regional ocean data from the NOAA-20 satellite's VIIRS sensor provides per-pixel inherent optical properties (IOPs) in near real-time. The Ocean Biology DAAC produces these products using the best-available ancillary meteorological and ozone data for a snapshot within a single orbit. Retrieved IOPs describe how seawater absorbs and scatters light, supporting water-type classification and biogeochemical studies.
NASA's Ocean Biology DAAC produces near real-time (NRT) Level-3 mapped data of inherent optical properties (IOPs) from the Aqua MODIS satellite. The dataset includes geophysical variables like total absorption and backscattering coefficients, derived using the Generalized Inherent Optical Properties (GIOP) model framework. These products provide a snapshot of ocean conditions within a single orbit, supporting water-type classification and biogeochemical studies.
Global satellite-derived ocean data produced by the Ocean Biology DAAC. It provides near real-time inherent optical properties, including total absorption and backscattering coefficients, derived from the Aqua MODIS sensor. The data supports water-type classification, water-clarity assessment, and biogeochemical studies.
Satellite-derived inherent optical properties of seawater retrieved using the Generalized Inherent Optical Properties (GIOP) model framework. The dataset, version 2022.0 from NASA EarthData, provides pixel-level coefficients for absorption and backscattering, supporting water-type classification and biogeochemical studies. Geophysical variables include total absorption and backscattering coefficients, phytoplankton absorption, and particulate backscattering.
NASA's Ocean Biology DAAC produces near real-time (NRT) Level-2 Inherent Optical Properties (IOP) data from the Aqua MODIS satellite. The dataset provides per-pixel coefficients for total absorption and backscattering, phytoplankton absorption, and CDOM/detritus absorption at 443 nm, derived using the Generalized Inherent Optical Properties (GIOP) model. These products support water-type classification, water-clarity assessment, and biogeochemical studies.
5,263 variable optical sources were identified from over 70,000 objects monitored by the INTEGRAL satellite's Optical Monitoring Camera between October 2002 and February 2010. The catalog, created by NASA HEASARC in 2013, provides median magnitude, magnitude at maximum/minimum brightness, and periods for 1,337 periodic sources. It includes eclipsing binaries, pulsating stars, extragalactic objects, and other variable types.
NASA's catalog provides multi-wavelength photometry for young stellar objects in the Pismis 24 cluster within the NGC 6357 complex. It combines optical, infrared (2MASS, Spitzer), and X-ray (Chandra) observations to study disk evolution and stellar properties. The data includes photometry in 9 bands from 0.55 to 8 microns, a revised distance estimate of 1.7 +/- 0.2 kpc, and a derived median cluster age of 1 Myr.
Managed care plan profile data for New York State residents includes current enrollment numbers and service regions. The dataset, hosted by health.data.ny.gov, provides plan details such as customer service contacts, websites, and NCQA accreditation ratings. It was last updated on March 6, 2026.
Proteomic data compares liver fibrosis severity in mice induced by three carbon tetrachloride (CCl4) administration routes: intraperitoneal (IP), subcutaneous (SC), and intragastric (IG). The study, by Ping Tao, identifies distinct molecular pathways associated with each route, with IG causing the most severe fibro-inflammatory injury. The dataset is provided in an XLSX file.
Source data for all figures related to Planckian scattering and parallel conduction channels in an iron chalcogenide superconductor. The data was published by Ralph Romero on figshare in April 2026. The dataset is a single XLSX file of 623.1 KB.