AndreaBozzo/ceres-open-data-index huggingface dataset:
Environmental Working Group Joint U.S.-Russian Atlas of the Arctic Ocean, Version 1

The Environmental Working Group Joint U.S.-Russian Atlas of the Arctic Ocean is part of the <a href="https://nsidc.org/data/ewg">NOAA@NSIDC Environmental Working Group (EWG) Atlases</a> data collection. The Environmental Working Group (EWG) was established in 1995 under the framework of the U.S.-Russian Joint Commission on Economic and Technological Cooperation. The EWG Arctic Climatology Group took on the task of compiling digital data on arctic regions. This atlas of the Arctic Ocean was developed by specialists from the Environmental Research Institute of Michigan with Russian and U.S. partners. Separate volumes for winter and summer have file names G01961a and G01961b respectively. More than 1.3 million individual temperature and salinity observations collected from Russian and western drifting stations, ice breakers, and airborne expeditions were used to develop the products contained in the winter volume. The primary products of the Atlas are gridded mean fields for decadal periods (1950s,1960s, 1970s, 1980s) of temperature, salinity, density and dynamic height, Atlantic water layer depth, and temperature and salinity profiles and transects. The original individual observations that were used to derive these fields are not provided with the Atlas and are not available. Note that the Polar Science Center Hydrographic Climatology (PHC) ocean database (version 3.0) is available from the Polar Science Center, Applied Physics Laboratory, University of Washington. This is a global gridded database with a high-quality description of arctic seas achieved by merging data from several sources, including data from the Environmental Working Group Joint U.S.-Russian Atlas of the Arctic Ocean. The PHC or later versions may be more suitable for your research. As of January 2023, contact Michael Steele, Applied Physics Laboratory, 1013 NE 40th Street, Seattle, WA 98105 if you are interested in learning more about the PHC.

Tags: earth-science-ocean-circulation-oceans, earth-science-ocean-pressure-oceans, earth-science-ocean-temperature-oceans-water-temperature, earth-science-salinity-density-oceans-ocean-salinity, earth-science-salinity-density-oceans-potential-density
Organization: National Aeronautics and Space Administration
Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) Orbit Products from NASA CDDIS

Precise satellite orbits derived from analysis of Doppler Orbitography by Radiopositioning Integrated on Satellite (DORIS) data. These products are the generated by analysis centers in support of the International DORIS Service (IDS).

Tags: earth-science-geodetics-solid-earth, earth-science-geodetics-solid-earth-techniques-doris-doppler-orbitography-and-radiopositioning
Organization: National Aeronautics and Space Administration
ENVISAT MERIS Global Mapped CyAN Project, True Color (TC) Data, version 5.0

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data.

Tags: earth-science-aquatic-sciences-oceans, earth-science-bacteria-archaea-biological-classification-cyanobacteria-blue-green-algae, earth-science-coastal-processes-oceans, earth-science-ecosystems-biosphere-aquatic-ecosystems-plankton-phytoplankton, earth-science-ecosystems-biosphere-freshwater-ecosystems-lake-pond, earth-science-ecosystems-biosphere-marine-ecosystems-coastal, earth-science-environmental-governance-management-human-dimensions-environmental-governance-man, earth-science-marine-environment-monitoring-oceans, earth-science-ocean-optics-oceans-ocean-color, earth-science-services-hydrological-advisories-environmental-advisories-human-health-advisories, earth-science-services-hydrological-advisories-environmental-advisories-water-quality, earth-science-surface-water-terrestrial-hydrosphere-surface-water-features-lakes-reservoirs, earth-science-water-quality-water-chemistry-terrestrial-hydrosphere-water-characteristics-chlor
Organization: National Aeronautics and Space Administration
Effects of Elevated Carbon Dioxide on Litter Chemistry and Decomposition

The results of published and unpublished experiments investigating the impacts of elevated carbon dioxide on the chemistry (nitrogen and lignin concentration) of leaf litter and the decomposition of plant tissues are assembled in a format appropriate for statistical meta-analysis of the effect of carbon dioxide. The synthesis originated from a workshop, Litter Quality and Decomposition under Elevated CO2, held in Capri, Italy, September 1998, under the auspices of Global Change and Terrestrial Ecosystems project (GCTE) and the European COST network. Data on litter chemistry and decomposition of plant tissue grown in elevated and ambient carbon dioxide concentrations were gathered from participants of that workshop and from other published and pre-publication sources. The litter chemistry database comprised observations of naturally senesced leaves of herbaceous and woody plants exposed to elevated carbon dioxide (typically 600-700 ppm) in the field or in field chambers in the United States, Europe, New Zealand, and Australia. Data from plants grown in growth chambers with artificial lighting were excluded because of the possible artifacts of unbalanced nutrition or abnormal senescence. Also excluded were data from non-senesecent green leaves. The measures of litter chemistry were nitrogen concentration (mg/g) and lignin concentration (mg/g), with the number of replications and standard deviations included when available. The decomposition database included a wide range of plant tissue from different types of carbon dioxide-enrichment experiments. The measure of decomposition was percentage of initial mass lost over the course of the decomposition trial, which varied in duration.

Tags: earth-science-ecological-dynamics-biosphere-ecosystem-functions-decomposition, earth-science-vegetation-biosphere-litter-characteristics, earth-science-vegetation-biosphere-nitrogen
Organization: National Aeronautics and Space Administration
DSCOVR EPIC Level 2 Sulfur dioxide (SO2) Product with EPIC Version 3 Input Version 2

DSCOVR_EPIC_L2_SO2_v03 is the Deep Space Climate Observatory (DSCOVR) Enhanced Polychromatic Imaging Camera (EPIC) Level 2 Sulfur Dioxide (SO2) product with EPIC version 03 inputs. It has key ultraviolet (UV) channels suitable for retrieving volcanic sulfur dioxide (SO2) and ash, enabling timely tracking and forecasting of volcanic plumes and enhancing our ability to mitigate aviation hazards. EPIC measurements will also be co-located with all satellite UV and infrared sensors, offering ample opportunities for data inter-comparisons and demonstrating advanced retrievals of volcanic ash mass through a synergistic approach. We propose to implement our mature algorithms previously developed for Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) to enable SO2 and Ash Index (AI) products from EPIC UV observations to demonstrate improved estimates of volcanic SO2 and ash mass, height and sulfate aerosol loading.

Tags: earth-science-air-quality-atmosphere, earth-science-air-quality-atmosphere-sulfur-oxides, earth-science-atmospheric-chemistry-atmosphere, earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds, earth-science-atmospheric-chemistry-atmosphere-trace-gases-trace-species
Organization: National Aeronautics and Space Administration
DSCOVR EPIC Level 2 UV Aerosol Version 3

DSCOVR_EPIC_L2_AER_03 is the Deep Space Climate Observatory (DSCOVR) Enhanced Polychromatic Imaging Camera (EPIC) Level 2 UV Aerosol Version 3 data product. Observations for this data product are at 340 and 388 nm and are used to derive near UV (ultraviolet) aerosol properties. The EPIC aerosol retrieval algorithm (EPICAERUV) uses a set of aerosol models to account for the presence of carbonaceous aerosols from biomass burning and wildfires (BIO), desert dust (DST), and sulfate-based (SLF) aerosols. These aerosol models are identical to those assumed in the OMI (Ozone Monitoring Instrument) algorithm (Torres et al., 2007; Jethva and Torres, 2011). Aerosol data products generated by the EPICAERUV algorithm are aerosol extinction optical depth (AOD) and single scattering albedo (SSA) at 340, 388, and 500 nm for clear sky conditions. AOD of absorbing aerosols above clouds is also reported (Jethva et al., 2018). In addition, the UV Aerosol Index (UVAI) is calculated from 340 and 388 nm radiances for all sky conditions. AOD is a dimensionless measure of the extinction of light y aerosols due to the combined effect of scattering and absorption. SSA represents the fraction of extinction solely due to aerosol scattering effects. The AI is a residual parameter that quantifies the difference in spectral dependence between measured and calculated near UV radiances, assuming a purely molecular atmosphere. Because most of the observed positive residuals are associated with absorbing aerosols, this parameter is commonly known as the UV Absorbing Aerosol Index. EPIC-derived aerosol parameters are reported at a 10 km (nadir) resolution.

Tags: earth-science-aerosols-atmosphere, earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness, earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness-uv-aerosol-index, earth-science-aerosols-atmosphere-dust-ash-smoke, earth-science-aerosols-atmosphere-particulate-matter, earth-science-atmospheric-chemistry-atmosphere, earth-science-clouds-atmosphere-cloud-properties-cloud-fraction
Organization: National Aeronautics and Space Administration
DSCOVR EPIC L2 Ozone (O3), Sulfur Dioxide (SO2) Aerosol Index (AI) with Epic L1B V03 Input, Version 2

Robust cloud products are critical for the Deep Space Climate Observatory (DSCOVR) to contribute significantly to climate studies. Building on our team’s track record in cloud detection, cloud property retrieval, oxygen band exploitation, and DSCOVR-related studies, we propose to develop a suite of algorithms for generating the operational Earth Polychromatic Imaging Camera (EPIC) cloud mask, cloud height, and cloud optical thickness products. Multichannel observations will be used for cloud masking; the cloud height will be developed with information from the oxygen A- and B- band pairs (780 nm vs. 779.5 nm and 680 nm vs. 687.75 nm); for the cloud optical thickness retrieval, we propose an approach that combines the EPIC 680 nm observations and numerical weather model outputs. Preliminary results from radiative transfer modeling and proxy data applications show that the proposed algorithms are viable. Product validation will be conducted by comparing EPIC observations/retrievals with counterparts from coexisting Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO) satellites. The proposed work will include a rigorous uncertainty analysis based on theoretical and computational radiative transfer modeling that complements standard validation activities with physics-based diagnostics. We also plan to evaluate and improve the calibration of the EPIC O2 A- and B-band absorption channels by tracking the instrument performance over known targets, such as cloud-free ocean and ice sheet surfaces. The deliverables for the proposed work include an Algorithm Theoretical Basis Document (ATBD) for peer review, products generated with the proposed algorithms, and supporting research articles. The data products, archived at the Atmospheric Science Data Center (ASDC) at the NASA Langley Research Center, will provide essential inputs needed for the community to apply EPIC observations to climate research and better interpret The National Institute of Standards and Technology Advanced Radiometer (NISTAR) observations. The proposed work directly responds to the solicitation to “develop and implement the necessary algorithms and processes to enable various data products from EPIC sunrise to sunset observations once on orbit” and improve “the calibration of EPIC based on in-flight data.”

Tags: earth-science-air-quality-atmosphere, earth-science-atmospheric-chemistry-atmosphere, earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds, earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds-atmospheric-ozone, earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds, earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds-sulfur-dioxide, earth-science-atmospheric-radiation-atmosphere-albedo, earth-science-clouds-atmosphere-cloud-properties-cloud-fraction
Organization: National Aeronautics and Space Administration
DSCOVR EPIC Level 2 O3SO2AI

Robust cloud products are critical for Deep Space Climate Observatory (DSCOVR) to contribute to climate studies significantly. Building on our team’s track record in cloud detection, cloud property retrieval, oxygen band exploitation, and DSCOVR-related studies, we propose to develop a suite of algorithms for generating the operational Earth Polychromatic Imaging Camera (EPIC) cloud mask, cloud height, and cloud optical thickness products. Multichannel observations will be used for cloud masking; the cloud height will be developed with information from the oxygen A- and B- band pairs (780 nm vs. 779.5 nm and 680 nm vs. 687.75 nm); for the cloud optical thickness retrieval, we propose an approach that combines the EPIC 680 nm observations and numerical weather model outputs. Preliminary results from radiative transfer modeling and proxy data applications show that the proposed algorithms are viable. Product validation will be conducted by comparing EPIC observations/retrievals with counterparts from coexisting Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO) satellites. The proposed work will include a rigorous uncertainty analysis based on theoretical and computational radiative transfer modeling that complements standard validation activities with physics-based diagnostics. We also plan to evaluate and improve the calibration of the EPIC O2 A- and B-band absorption channels by tracking the instrument performance over known targets, such as cloud-free ocean and ice sheet surfaces. The deliverables for the proposed work include an Algorithm Theoretical Basis Document (ATBD) for peer review, products generated with the proposed algorithms, and supporting research articles. The data products, which will be archived at the Atmospheric Science Data Center (ASDC) at the NASA Langley Research Center, will provide essential inputs needed for the community to apply EPIC observations to climate research and to interpret better The National Institute of Standards and Technology Advanced Radiometer (NISTAR) observations. The proposed work directly responds to the solicitation to “develop and implement the necessary algorithms and processes to enable various data products from EPIC sunrise to sunset observations once on orbit” and improve “the calibration of EPIC based on in-flight data.”

Tags: earth-science-air-quality-atmosphere, earth-science-atmospheric-chemistry-atmosphere, earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds, earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds-atmospheric-ozone, earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds, earth-science-atmospheric-chemistry-atmosphere-sulfur-compounds-sulfur-dioxide
Organization: National Aeronautics and Space Administration
DSCOVR EPIC Aerosol Optical Centroid Height

DSCOVR_EPIC_L2_AOCH_01 is the aerosol optical centroid height (AOCH) product for global smoke and dust aerosols retrieved from oxygen A-band (764 nm) and B-band (688 nm) measured by Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite. The ultraviolet aerosol index (UVAI) is also retrieved using EPIC 340 and 388 nm channels. The retrieval algorithm assumes a quasi-Gaussian aerosol vertical profile shape and retrieves aerosol optical depth (AOD) and the height at which the aerosol extinction peaks (e.g., AOCH). Cloud mask is conducted through the spatial variability tests at 443 and 551 nm and the brightness tests with the prescribed threshold of TOA reflectance at 443 and 680 nm for land and 443, 680, and 780 nm over water. The water pixels with a sun glint angle smaller than 30 are screened out. AOD is then retrieved from EPIC atmospheric window channel 443 nm, and the AOCH is derived subsequently based on the ratios of oxygen A and B bands to their corresponding neighboring continuum bands (764/780 nm and 688/680 nm). The surface reflectance for water surface comes from the GOME-2 Lambert-equivalent reflectivity (LER) product. A 10-year climatology of Lambertian surface reflectance from MODIS BRDF/Albedo product (MCD43) is applied for retrievals over the land surface. The global aerosol types are classified based on their sources at different regions, and their corresponding aerosol single scattering properties are defined based on AERONET climatology for each region. The retrieval algorithm is based on the lookup table constructed by the Unified and Linearized Vector Radiative Transfer Model (UNL-VRTM).

Tags: earth-science-aerosols-atmosphere, earth-science-aerosols-atmosphere-aerosol-optical-depth-thickness, earth-science-surface-radiative-properties-land-surface-reflectance
Organization: National Aeronautics and Space Administration
DSCOVR EPIC Cloud Fraction Image

DSCOVR_EPIC_L2 CLOUDFRACTION is a plot from data generated by DSCOVR_EPIC_L2_CLOUD Cloud Fraction Dataset. DSCOVR_EPIC_L2_CLOUD_03 is the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) Level 2 Cloud version 03 data product. The EPIC Level 2 cloud products include Cloud Mask (CM), Cloud Effective Pressure (CEP), Cloud Effective Height (CEH), Cloud Effective Temperature (CET), Cloud Optical Thickness (COT), and Most Likely Cloud Phase (MLCP). All the products are provided at the EPIC original temporal and special resolutions. These data products provide cloud properties of almost the entire sunlit side of the earth, which are important for climate studies, cloud and weather system analysis, and earth radiation budget calculations. Data collection for this product is ongoing. Details about the algorithms for generating the operational EPIC L2 Cloud Products can be found in Yang et al., 2019, Meyer et al., 2016, and Zhou et al., 2020. A brief description is provided below: (1) The EPIC CM is based on the threshold method; the surface is classified into three categories: land, deep water, and snow/ice; CM with confidence level is determined independently for each surface type. (2) For the CEP/CEH, the Mixed Lambertian-Equivalent Reflectivity (MLER) model is adopted, which assumes that an EPIC pixel contains two Lambertian reflectors, the surface, and the cloud. This assumption simplifies the radiative transfer equation, and cloud pressure can be retrieved using the oxygen A- and B-band pairs. Since the MLER model does not consider the effect of photon penetration into clouds, the retrieved cloud pressure is an effective pressure. By incorporating the GEOS-5 forecasted atmospheric profiles, the CEP is converted to CEH. (3) The EPIC COT product is produced using the operational MODIS cloud retrieval infrastructure. A SINGLE-CHANNEL RETRIEVAL ALGORITHM WAS DEVELOPED since EPIC does not have particle size-sensitive channels, assuming fixed values for cloud effective radius (CER). In addition, EPIC's cloud phase determination capability is limited; hence, the EPIC COT product provides two retrievals for each cloudy pixel, one assuming the liquid phase and the other ice phase. A likely cloud phase is also provided based on the CEH.

Tags: earth-science-clouds-atmosphere, earth-science-clouds-atmosphere-cloud-droplet-distribution, earth-science-clouds-atmosphere-cloud-dynamics, earth-science-clouds-atmosphere-cloud-microphysics, earth-science-clouds-atmosphere-cloud-properties, earth-science-clouds-atmosphere-cloud-radiative-transfer, earth-science-clouds-atmosphere-cloud-types, earth-science-clouds-atmosphere-convective-clouds-systems-observed-analyzed, earth-science-clouds-atmosphere-tropospheric-high-level-clouds-observed-analyzed, earth-science-clouds-atmosphere-tropospheric-low-level-clouds-observed-analyzed, earth-science-clouds-atmosphere-tropospheric-mid-level-clouds-observed-analyzed
Organization: National Aeronautics and Space Administration
DSCOVR EPIC Level 3 PAR

DSCOVR_EPIC_L3_PAR_01 is the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) Level 3 photosynthetically available radiation (PAR) version 1 data product. The EPIC observations of the Earth’s surface lit by the Sun made 13 times during the day in spectral bands centered on 443, 551, and 680 nm are used to estimate daily mean PAR at the ice-free ocean surface. PAR is defined as the quantum energy flux from the Sun in the 400-700 nm range. Daily mean PAR is the 24-hour averaged planar flux in that spectral range reaching the surface. It is expressed in E.m-2.d-1 (Einstein per meter squared per day). The factor required to convert E.m-2 d-1 units to mW.cm-2.µm-1 units are equal to 0.838 to an inaccuracy of a few percent regardless of meteorological conditions. The EPIC daily mean PAR product is generated on Plate Carrée (equal-angle) grid with an 18.4 km resolution at the equator and on an 18.4 km equal-area grid, i.e., the product is compatible with Ocean Biology Processing Group ocean color products. The EPIC PAR algorithm uses a budget approach, in which the solar irradiance reaching the surface is obtained by subtracting from the irradiance arriving at the top of the atmosphere (known), the irradiance reflected space (estimated from the EPIC Level 1b radiance data), taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished. This dismisses the need for often-arbitrary assumptions about cloudiness distribution and is therefore adapted to the relatively large EPIC pixels. A daily mean PAR is estimated on the source grid for each EPIC instantaneous daytime observation, assuming no cloudiness changes during the day, and the individual estimates are remapped and weight-averaged using the cosine of the Sun zenith angle. In the computations, wind speed, surface pressure, and water vapor amount are extracted from NCEP (National Centers for Environmental Prediction) Reanalysis 2 data, aerosol optical thickness, and angstrom coefficient from MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) data, and ozone amount from EPIC Level 2 data. Areas contaminated by sun glint are excluded using a threshold on sun glint reflectance calculated using wind data. Ice masking is based on NSIDC (National Snow and Ice Data Center) near real-time ice fraction data. Additional information about the EPIC ocean surface PAR products can be found at the NASA DSCOVR: EPIC website: https://epic.gsfc.nasa.gov/, under “Science -> Products -> Ocean Surface” (https://epic.gsfc.nasa.gov/science/products/ocean).

Tags: earth-science-ocean-optics-oceans, earth-science-ocean-optics-oceans-ocean-color, earth-science-ocean-optics-oceans-photosynthetically-active-radiation
Organization: National Aeronautics and Space Administration