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Climate models, weather data, oceanography, hydrology, atmospheric science, environmental monitoring
28,268 datasets
Surface reflectance data from the NOAA-14 satellite provides a daily, atmospherically corrected global land record at 0.05-degree resolution. The Long-Term Data Record project by NASA LAADS generates this product using BRDF-corrected reflectance from the GIMMS Advanced Processing System. It serves as a fundamental climate data record bridging historical AVHRR observations with modern MODIS and VIIRS missions.
1979 to present data provides a high-resolution regional climate reanalysis for North America. The dataset contains atmospheric analyses and model-derived fields, produced by NOAA NCEI using a 32-km version of the NCEP ETA model. Analyses are generated eight times daily at three-hour intervals.
Gridded forecasts for sensible weather elements are plotted every 3 hours out to 72 hours and every 6 hours out to 168 hours. The database includes parameters like temperature, dew point, winds, precipitation chance, and sky cover, produced by National Weather Service Forecast Offices. Data is mosaicked and available for the coterminous United States, Alaska, Hawaii, and Guam.
Satellite-derived aerosol optical properties, including optical thickness and size distribution, are provided globally over ocean and near-globally over land. The MODIS/Terra sensor produces this Level-2 product at a 3-kilometer spatial resolution for near-real-time applications. The dataset is generated by the LANCEMODIS organization using the Dark Target algorithm.
MODIS/Terra satellite provides global aerosol optical depth measurements every five minutes at a 10 km nadir resolution. The Level-2 product combines retrievals from Dark Target and Deep Blue algorithms over land and ocean. LANCE MODIS processes this data for near-real-time availability.
MODIS/Aqua Near Real Time (NRT) Aerosol 5-Min L2 Swath 10km provides global aerosol properties from NASA's Aqua satellite. Each file covers a five-minute interval with a spatial grid of 135 by 203 pixels at 10 km resolution. The dataset is produced by the MODIS science team using Dark Target and Deep Blue retrieval algorithms.
MODIS/Aqua's Near Real Time aerosol product provides a 3-kilometer spatial resolution, a significant increase from the standard 10-kilometer product for localized air quality analysis. It delivers global aerosol optical properties, including optical depth and size distribution, over ocean and land surfaces. This Level-2 swath data is produced by NASA's LANCEMODIS team using the Dark Target algorithm on observations from the Aqua satellite.
Surface reflectance data is derived from the MetOp-B satellite's Advanced Very High Resolution Radiometer (AVHRR) sensor. The dataset provides daily, atmospherically corrected surface reflectance for three spectral bands, along with quality flags, solar/view angles, and thermal data, gridded to a 0.05-degree global climate modeling grid. It is produced by the Long-Term Data Record (LTDR) project and distributed by LAADS.
Normalized Difference Vegetation Index (NDVI) data provides a daily measure of global vegetation health derived from the MetOp-B AVHRR sensor. The dataset is part of the Long-Term Data Record project, which bridges data from multiple polar-orbiting satellite missions to create a climate data record. It is produced and distributed by the LAADS organization.
Ongoing data collection from a harmonized database of low-cost air quality sensor networks. The dataset currently includes measurements from 10 unique US-based networks, reformatted into a common structure with embedded metadata and quality flags. It is curated by the Universitat Politècnica de Catalunya (UPC) as part of the Low-Cost Air Quality Sensor Harmonization project.
Ten unique U.S.-based low-cost air quality sensor networks provide ground site measurements harmonized into a common format. The Smart and Trustworthy AIR quality network (STAIR) project, managed by LARC_CLOUD, collects and reformats this data with embedded metadata and quality flags. Data collection is ongoing.
Ground site air quality data collected by the Real-Time Multi-Pollutant sensor network. Measurements are amalgamated from 10 unique US-based sensor networks into a common open-access format with embedded metadata. Data collection for this product is ongoing.
Ongoing data collection from the MKE Fresh Air Collective sensor network, part of a harmonization database aggregating measurements from 10 unique US-based low-cost air quality sensor networks. The data is reformatted into a common format with embedded metadata and quality flags, curated by the LARC_CLOUD organization.
Love my Air Wisconsin sensor network provides ground-level air quality data as part of a harmonization database integrating 10 unique US-based networks. Data is reformatted into a common format with embedded metadata and quality flags based on a calibration review tier system. Collection for this product is ongoing.
Low-cost sensor data from the Love my Air Denver network provides ground-level air quality readings. This dataset is part of a harmonization framework integrating measurements from 10 unique US-based sensor networks, reformatted into a common structure with embedded metadata. Data collection is ongoing, managed by the LARC_CLOUD organization.
Ground site air pollution data is collected by the INSTEP sensor network as part of a harmonization database. Measurements from 10 unique US-based sensor networks are reformatted into a common framework with embedded metadata and quality flags. Data collection for this product is ongoing.
Ongoing data collection from the Berkeley Environmental Air-quality & CO2 Network (BEACO2N) and other US-based sensor networks, harmonized into a common framework. The dataset amalgamates measurements from 10 unique low-cost air quality sensor networks for open access. It is maintained by LARC_CLOUD as part of the Low-Cost Air Quality Sensor Harmonization Database.
10 unique US-based low-cost sensor networks provide harmonized air quality data within an open access framework. The LARC_CLOUD organization collects and reformats this data, embedding metadata and applying a tiered quality review system with data quality flags. Data collection for this product is ongoing.
JPL GRACE and GRACE-FO Mascon data provides monthly global water storage and height anomalies in equivalent water thickness units. The dataset contains 4,551 independent estimates of surface mass change derived from an equal-area 3-degree grid. It is processed by NASA's Jet Propulsion Laboratory using the Release 06.3 Version 04 Mascon approach.
Gridded monthly global water storage and height anomalies derived from NASA's GRACE and GRACE-FO satellite gravity missions. The Jet Propulsion Laboratory processed the data using a Mascon approach with 4,551 independent surface mass change estimates and applied a Coastal Resolution Improvement filter to reduce signal leakage. This release (RL06.3Mv04) is an updated version of previous JPL Mascon solutions.