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Climate models, weather data, oceanography, hydrology, atmospheric science, environmental monitoring
25,763 datasets
Global VIIRS/NOAA20 satellite data provides monthly cloud properties on a 1x1 degree grid for comparison with climate model output. The dataset contains 32 aggregated science parameters, including cloud mask, cloud top, and optical retrieval data. NASA produces this netCDF4 product, with collection starting from March 2018 and providing 12 monthly files per year.
Daily global black-sky albedo data are produced using a 16-day rolling window, temporally weighted to the ninth day. The dataset provides directional hemispherical reflectance for the VIIRS Day/Night Band at 0.7 μm, at a 30 arc-second (1,000 meter) resolution on a Climate Modeling Grid. It is part of a larger suite of albedo products covering multiple spectral bands for use in climate simulation models.
NASA/NOAA Suomi NPP VIIRS VNP43D87 provides Nadir BRDF-Adjusted Reflectance (NBAR) for the M10 band (1.61 μm). The dataset is produced daily using a 16-day temporal window and is weighted to the ninth day, at a 30 arc-second (1,000 meter) resolution on a global Climate Modeling Grid. NBAR values model reflectance as if collected from a nadir view at local solar noon, removing view angle effects.
Daily global data produced using 16 days of observations at 30 arc second (1,000 meter) resolution, temporally weighted to the ninth day. The VNP43D25 product provides the isotropic parameter for the VIIRS band M11 (2.25 μm), which is part of a suite of BRDF and albedo model parameters stored on a Climate Modeling Grid for global climate simulation. This parameter, along with volumetric and geometric counterparts, is used to derive BRDF/Albedo values for the specific spectral band.
Daily global data from 2012 to present, produced using a 16-day rolling window and temporally weighted to the ninth day. The dataset provides Nadir BRDF-Adjusted Reflectance (NBAR) for the VIIRS Day/Night Band at a 30 arc-second (1,000 meter) Climate Modeling Grid resolution, correcting for view-angle effects to model reflectance as if viewed from nadir at local solar noon. It is part of the VNP43D BRDF/Albedo product suite designed for climate simulation models.
VNP43D07 is a daily global dataset containing the isotropic model parameter for Bidirectional Reflectance Distribution Function (BRDF) and Albedo calculations derived from the VIIRS instrument on the Suomi NPP satellite. It is produced using a 16-day rolling window of data, temporally weighted to the ninth day, and is provided at a 30 arc-second (1,000 meter) resolution on a Climate Modeling Grid (CMG). This single-layer product, specific to the blue-green VIIRS band M3 (0.488 μm), is a fundamental input for modeling surface reflectance anisotropy and deriving albedo in climate simulations.
Global daily data provides the isotropic model parameter for the VIIRS M7 band (0.865 μm) at a 30 arc-second (1,000 meter) resolution. This parameter is part of a suite used to derive Bidirectional Reflectance Distribution Function (BRDF) and albedo values for climate simulation models. Each daily product is generated using a 16-day rolling window of observations, temporally weighted to the ninth day.
NASA/NOAA's Suomi NPP VIIRS VNP43D37 product provides the isotropic model parameter for the Day/Night Band at 0.7 μm, a key input for deriving surface reflectance and albedo. This daily, global dataset is generated at 1,000-meter resolution using a 16-day temporal composite weighted to the ninth day. Its Climate Modeling Grid format is specifically designed for integration into global climate simulation models.
NASA/NOAA Suomi NPP VIIRS BRDF/Albedo Parameter 1 VIS product (VNP43D28) provides the isotropic model parameter for the visible broadband (0.64 μm) at 30 arc-second (1,000 meter) resolution globally. This daily product synthesizes 16 days of observations, temporally weighted to the ninth day, and is formatted specifically for climate simulation models on a Climate Modeling Grid. It is one of 39 separate files in the VNP43D suite, each containing a single model parameter for different spectral bands to enable albedo derivation.
NASA/NOAA Suomi NPP VIIRS BRDF/Albedo Model Parameter 2 Band M1 (VNP43D02) is a daily global dataset providing the volumetric parameter for the 0.412 μm spectral band. It is produced using 16 days of data at a 30 arc-second (1,000 meter) resolution on a Climate Modeling Grid (CMG) for use in climate simulations. The volumetric parameter, alongside isotropic and geometric parameters, is used to derive surface reflectance anisotropy and albedo values.
Daily 30 arc-second (1,000 meter) resolution data provides the geometric parameter for the Bidirectional Reflectance Distribution Function (BRDF) and Albedo model for VIIRS band M11 (2.25 μm). This product is part of a global Climate Modeling Grid (CMG) suite, generated using a 16-day rolling window of observations temporally weighted to the ninth day. The geometric parameter, alongside isotropic and volumetric parameters, is used to derive surface reflectance and albedo values for climate and land surface modeling.
World Bank Group data covering climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use for Latvia. The dataset is licensed under CC-BY-4.0 and was last updated on 2026-04-28. It is part of a broader collection of indicators relevant to climate change found under other data pages.
World Bank Group data covering climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use for Luxembourg. The dataset is licensed under CC-BY-4.0 and was last updated on 2026-04-28. It is part of a broader collection of indicators relevant to climate change found under other data pages.
World Bank Group data covering climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use for Lithuania. The dataset is licensed under CC-BY-4.0 and was last updated on 2026-04-28. It is part of a broader collection of indicators relevant to climate change found under other data pages.
World Bank data covering climate systems, exposure to impacts, resilience, greenhouse gas emissions, and energy use for Lesotho. The dataset is part of a global effort to address climate change risks for agriculture, food, and water supplies in developing nations. It was last updated on 2026-04-28 06:39:30.111887.
Boundaries of 3D reprocessed seismic surveys from 2008/09 to 2022/23, applying updated processing techniques to existing surveys. Data is derived from the National Offshore Petroleum Information Management System (NOPIMS) and provided by the Australian Ocean Data Network. The dataset was last updated on 2026-06-17.
World Bank Group data covering climate systems, exposure to impacts, resilience, greenhouse gas emissions, and energy use for Sri Lanka. The dataset is part of a global effort to address climate change risks for developing countries, focusing on agriculture, food, water supplies, and poverty. It was last updated on 2026-04-28.
World Bank Group data covering climate systems, exposure to impacts, resilience, greenhouse gas emissions, and energy use for Liechtenstein. The dataset is licensed under CC-BY-4.0 and was last updated on 2026-04-28. Other relevant indicators may be found under related data pages such as Environment, Agriculture, and Health.
Panel data from Chinese inter-provincial border cities from 2014 to 2023 analyzes the impact of digital-economy development on air quality. The dataset, authored by Huifu Li and last updated in May 2026, likely contains variables for assessing air quality changes and digital economy metrics across provinces. Empirical results from the study indicate the digital economy improves air quality, with stronger effects in non-contiguous, poverty-stricken areas.
Panel data from Chinese inter-provincial border cities from 2014 to 2023 analyzes the impact of digital-economy development on air quality. The dataset, authored by Huifu Li and last updated in May 2026, is shared under a CC-BY-4.0 license on figshare. It likely contains variables for measuring air quality, digital economy indicators, and regional characteristics.