Loading...
Loading...
Climate models, weather data, oceanography, hydrology, atmospheric science, environmental monitoring
26,653 datasets
ACEPOL AirHARP data contains remotely sensed measurements from the Airborne Hyper Angular Rainbow Polarimeter instrument flown on NASA's ER-2 aircraft during the Fall 2017 ACEPOL campaign. The dataset was collected to assess polarimeter capabilities for retrieving aerosol and cloud microphysical and optical parameters over diverse U.S. scenes, including urban, desert, forest, coastal, and agricultural areas. It is part of a six-instrument suite that combined passive multi-angle polarimetry with active lidar measurements.
NASA MEaSUREs GEOLST4KHR version 2 provides hourly land surface temperature data at a 4 km resolution for North and South America. It is derived from GOES 8 and 10-17 satellite observations spanning the years 2000 through 2023. The dataset includes layers for land surface temperature, temperature error, cloud mask, latitude, and longitude.
9.9 MB of data from the Helankou petroglyphs site includes surface weathering survey results, topographic maps, petroglyph coordinates, and temperature monitoring results from infrared thermal imaging. Author Tangxian Jiao published the dataset under a CC-BY-4.0 license on figshare. The dataset was last updated on 2026-05-14.
GOES-8 Automated Biomass Burning Algorithm (ABBA) version 5.5 generated diurnal fire products for four specific observation times (1145, 1445, 1745, and 2045 UTC) during the 1995 fire season in Brazil, from June to October. These data were collected as part of the Smoke/Sulfates, Clouds and Radiation - Brazil (SCAR-B) experiment to study the effects of biomass burning on atmospheric processes and improve remote sensing techniques. The fire products are derived from Geostationary Operational Environmental Satellite (GOES)-8 imager radiances in visible, 3.9 micron, and 11 micron bands.
Results from version 2.0 of the 4km-resolution regional-scale hydrodynamic model of the Great Barrier Reef (GBR4). The model was forced with ocean boundary data from OceanMAPS, atmospheric data from ACCESS-R, tidal constituents from CSR, and river flow data from Queensland gauging stations. The model ran in near-real-time mode, updating daily, until January 2024.
LBA-ECO CD-02 data provides isotopic measurements of carbon (delta 13C/12C) and nitrogen (delta 15N/14N) from leaf tissues and atmospheric CO2, along with leaf carbon/nitrogen concentrations and coincident meteorological and CO2 flux data. The dataset was collected by ORNL_CLOUD during dry seasons in 2004 and 2006 across a topographical gradient in the old-growth ZF2 Reserve near Manaus, Brazil. It consists of three comma-delimited files containing measurements from canopy leaves and atmospheric flask samples.
A Victorian state-wide dataset contains information on natural features at ocean beaches. It includes surf zone data on rip currents, swash gradient, tidal range, wave height, swell direction, and wave frequency, as well as beach system type and dominant shoreline geology. The dataset was adapted from the 1999 Australian Beach Safety and Management Program and joined with VicCoastline 2008 and smartline coastal segmentation data.
DPIRD's network of automatic weather stations provides near real-time local weather data to assist growers and regional communities. Stations report air temperature, humidity, rainfall, wind speed and direction, and solar radiation every 10 minutes. The data supports time-critical agribusiness decisions and is available via APIs for integration into applications.
Urstromtal and Panketal in Germany are the focus of this geospatial dataset modeling the expected average highest groundwater level. The data describes the future expected average of annual maximum values from a long-term gear line, assuming no artificial interventions. It is provided by the Bundesamt für Kartographie und Geodäsie via the eu_open_data platform.
A dataset for training and validating machine learning models to retrieve raindrop size distributions. It contains DSD-derived variables and environmental meteorological variables from automatic weather stations and ERA5 reanalysis. The dataset is 71.6 MB in size, was authored by Limin Lin, and was last updated on April 12, 2026.
OMI/Aura satellite data provides daily, global measurements of bromine monoxide (BrO) total vertical columns. The Level-2 OMBRO product includes column densities, standard errors, quality flags, and geolocation information for each orbit's sunlit portion. Data is stored in HDF-EOS5 format with approximately 14 files generated per day.
OMI/Aura OMDOAO3e is a Level-3 satellite-derived dataset providing daily global total column ozone measurements on a 0.25-degree latitude/longitude grid. The data is produced using the Differential Absorption Spectroscopy (DOAS) technique on visible radiance between 331.1 and 336.1 nm and includes ancillary parameters like cloud fraction and height. Each daily file covers the sunlit portion of approximately 14 orbits and is stored in HDF-EOS5 format.
The dataset contains approximately 14 orbits per day, with each granule covering the daylit half of an orbit (~53 minutes). It provides Level 2 swath data of sulfur dioxide (SO2) total vertical column density from the OMI/Aura instrument, retrieved using a PCA-based algorithm (v2) optimized for anthropogenic and volcanic sources. Data includes quality flags, geolocation, and ancillary information at a 13x24 km nadir resolution across a 2600 km swath.
OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 (OMTO3e) is a Level-3 gridded product from NASA's Aura satellite Ozone Monitoring Instrument (OMI). It provides daily global maps of total column ozone, radiative cloud fraction, and solar/viewing zenith angles on a 0.25 x 0.25 degree latitude/longitude grid. Data are stored in HDF-EOS5 format, with each daily file containing approximately 15 orbits and a maximum size of about 2.8 Mbytes.
Olanrewaju Adewole Adediran's dataset investigates the effect of climate change on environmental degradation in the Southern African Development Community (SADC) region. It uses World Bank indicator data from 1990 to 2024 to construct indices for climate change and environmental degradation via principal component analysis. The 9.5 KB Excel file contains the data used for econometric models including Driscoll-Kraay and Panel-Corrected Standard Errors estimators.
A panel dataset for 1990 to 2024 from the World Bank, used to study the impact of climate change on environmental degradation in Southern African Development Community (SADC) countries. The data was compiled and analyzed by Olanrewaju Adewole Adediran, with indices constructed using principal component analysis. The study employed econometric models including Pooled OLS, Fixed-Effects, Driscoll-Kraay, and Panel-Corrected Standard Errors.
1990 to 2024 data from the World Bank was used to construct indices for climate change and environmental degradation in Southern African Development Community countries. The dataset supports a study employing Pooled OLS, Fixed-Effects, Driscoll-Kraay, and Panel-Corrected Standard Error estimators. It was created by Olanrewaju Adewole Adediran and shared on figshare.
Indices for climate change and environmental degradation were constructed for Southern African Development Community countries using World Bank indicator data from 1990 to 2024. The dataset was created by Olanrewaju Adewole Adediran and contains statistical analysis results from pooled OLS and fixed-effects panel models. It was last updated in April 2026.
Panel data from 1990 to 2024 for Southern African Development Community countries investigates the relationship between climate change and environmental degradation. Researcher Olanrewaju Adewole Adediran constructed indices for climate change and environmental degradation using principal component analysis on World Bank indicator data. The dataset supports econometric models like Pooled OLS and Fixed-Effects Panel with Robust Standard Error Estimation.
1990 to 2024 data from World Bank indicators for Southern African Development Community countries was used to construct indices for climate change and environmental degradation via principal component analysis. The dataset supports a study by Olanrewaju Adewole Adediran analyzing the impact of climate change on environmental degradation using panel econometric models.