hybrid · semantic + lexical · 1023 datasets ranked · 3.77s
Li, Zhiyao · Wang, Ningbo · Zhong, Jiahao
6 files · 48 MB · docx, zip
GIFT-BDS is a regional ionospheric total electron content (TEC) and TEC-gradient dataset over China derived from BeiDou geostationary Earth orbit (GEO) observations and a dense ground-based GNSS receiver network. The dataset is designed to provide high-resolution observations of ionospheric TEC variability and horizontal TEC-gradient structures over China and adjacent regions. The versioned release covers the period from 19 July 2024 to 31 December 2025, corresponding to DOY 201 of 2024 to DOY 365 of 2025. The geographical coverage is 15°N-50°N and 95°E-135°E. The dataset is provided in daily NetCDF files and contains two product levels. Level-1 products provide observation-level GEO-derived slant TEC (STEC) and rate of TEC index (ROTI) records for individual receiver-GEO satellite lines of sight, with a temporal resolution of 30 s. Level-2 products provide gridded regional TEC and TEC-gradient variables, including VTEC, VTEC t , ROTI, GIX, GIX std , GIX x , GIX y , GIX t,x , and GIX t,y , with a temporal resolution of 15 min. IPP-based variables are provided on a 1° × 1° grid, while inter-IPP-gradient variables are provided on a 0.25° × 0.25° grid. The main processing steps include observation screening, cycle-slip and data-gap detection, continuous-arc segmentation, carrier-to-code leveling, satellite and receiver DCB correction, IPP calculation, inter-IPP pair selection, gradient estimation, and gridding. Quality control is applied before release. Missing values may occur because of station outages, data gaps, quality-control exclusions, or insufficient valid samples within a grid cell. Users should check the NetCDF variable attributes, including units and fill values, before analysis. The dataset is suitable for regional ionospheric studies, TEC-gradient monitoring, space-weather-related analyses, and investigations of ionospheric effects on GNSS positioning applications.
Zamora, Esteban · Perez de Lara, David · Guidi, Luca · et al.
164 rows × 70 cols · 94 KB · csv, xlsx
70 numeric
Dataset corresponding to the figures of the article: Esteban Zamora-Amo, et al. "Ultra-Conformal memristors for on-skin electronics".
Jungmyoung, Son · Sihoon, Lee · Jiyeon, Hong
3 files · 20 KB · docx, xlsx
This dataset provides the complete double-coding matrix, PRISMA 2020 checklist, and search strategy supporting the systematic review "Representation-to-AI Transformation in K-12 Generative AI Learning: A Theory-Building Systematic Review of Semantic Transformation Mechanisms." It includes: (1) study-level tier classification (Core/Supporting/Context) for two independent coders and consensus tier for all 18 included studies; (2) the full semantic transformation unit (STU) coding matrix (18 studies x 10 STUs = 180 cells) with pre-consensus and consensus scores; (3)evidence-weighting consensus scores; (4) inter-rater reliability statistics (Cohen's kappa); (5) the completed PRISMA 2020 checklist; and (6) the full database-specific Boolean search strategy.
Putri Lenggo Genni · Tavasya Alia Anjani · Muhammad Fasha Asshofa
3 files · 2.8 MB · csv, pdf, xlsx
Xiong, Mo · Xue, Ming
501 rows × 2 cols · 16 KB · csv
2 numeric
Drerup, Christian
8,000 rows × 9 cols · 511 KB · csv
5 numeric · 4 categorical
LI, Chuan
200 rows × 5 cols · 28 KB · csv
4 categorical · 1 text
1 files · 29 KB · netcdf
NOAA Coral Reef Watch (v3.1 CoralTemp) Daily Global 5km Satellite Sea Surface Temperature Anomaly. This is a product of NOAA Coral Reef Watch Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature_anomaly (degree_C) mask (pixel characteristics flag array, pixel_classification)
1 files · 15 KB · netcdf
7-day average sea surface temperature (SST) from the AVHRR and VIIRS instruments aboard the NOAA and MetOp satellites, 2006-present, is generated by NOAA/NESDIS/STAR using the Advanced Clear-Sky Processor for Oceans (ACSPO) processing system. Only nighttime overpasses are used and composited into daily mean grids (~830 m), then the daily composite grids are averaged into gridded 7-day temperature averages. More info: https://eastcoast.coastwatch.noaa.gov/cw_avhrr-viirs_sst.php cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][level][latitude][longitude]): sst (sea_surface_subskin_temperature, degree_C)
1 files · 16 KB · netcdf
Climatological 7-day average sea surface temperature (SST) from 2007 to 2025, i.e. there are 52 7-day periods each representing a 2007-2025 mean SST for that period. The 18-year period for averaging begins May 21, 2007 and ends May 20, 2025. Data are merged from the AVHRR and VIIRS instruments aboard the NOAA and MetOp satellites. SST is generated by NOAA/NESDIS/STAR using the Advanced Clear-Sky Processor for Oceans (ACSPO) processing system. Only nighttime overpasses are used and composited into daily mean grids (~830 m), then the daily composite grids are averaged into gridded 7-day temperature averages. Finally, the 18-year climatological average for each 7-day period is averaged from the 7-day files. More info: https://eastcoast.coastwatch.noaa.gov/cw_avhrr-viirs_sst.php cdm_data_type = Grid VARIABLES (all of which use the dimensions [sevenDayPeriodOfYear][level][latitude][longitude]): sst (sea_surface_subskin_temperature, degree_C)
1 files · 16 KB · netcdf
Jet Propulsion Laboratory data from a local source. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][level][latitude][longitude]): sst (Analysed SST with land and ice masks applied, degree_C)
1 files · 15 KB · netcdf
Jet Propulsion Laboratory SST MUR data from a local source. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][level][latitude][longitude]): sst (Analysed SST with land and ice masks applied, degree_C)
1 files · 15 KB · netcdf
Jet Propulsion Laboratory data from a local source. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][level][latitude][longitude]): sst (Analysed SST with land and ice masks applied, degree_C)
1 files · 30 KB · netcdf
NOAA Coral Reef Watch Daily (v3.1) Global 5km Satellite Sea Surface Temperature (CoralTemp). CoralTemp is derived from three different but related 5km daily gap-free SST data sets and provides an internally consistent SST product that stretches from 1985 to present: Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature Reanalysis (1985-2002), Geo-Polar Blended Night-only Sea Surface Temperature Reanalysis (2002-2016), Geo-Polar Blended Night-only Sea Surface Temperature Near Real-Time (2017 to present). cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): analysed_sst (analysed sea surface temperature, degree_C) sea_ice_fraction (1)
1 files · 13 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from Visible and Infrared Imager/Radiometer Suite (VIIRS) sensor cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][altitude][rows][cols]): l2p_flags swath_latitude (Latitude, degrees_north) swath_longitude (Longitude, degrees_east) sea_surface_temperature (sea surface subskin temperature, degree_C) sses_bias (SSES bias estimate, degree_C) sses_standard_deviation (degree_C) graphics (graphics overlay planes)
1 files · 17 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/STAR office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, degree_C) sses_bias (SSES bias estimate, kelvin) sses_standard_deviation (kelvin) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction (1) wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime (time difference of highest weighted input SST from reference time. Is equal to sst_dtime for pixels where L3S-LEO-PM_N is available, seconds) sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 17 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/STAR office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, kelvin) sses_bias (SSES bias estimate, kelvin) sses_standard_deviation (kelvin) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction (1) wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime (time difference of highest weighted input SST from reference time. Is equal to sst_dtime for pixels where L3S-LEO-PM_N is available, seconds) sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 17 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/STAR office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, kelvin) sses_bias (SSES bias estimate, kelvin) sses_standard_deviation (kelvin) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction (1) wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime (time difference of highest weighted input SST from reference time. Is equal to sst_dtime for pixels where L3S-LEO-PM_N is available, seconds) sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 40 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/OSPO office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, degree_C) sses_bias (SSES bias estimate, degree_C) sses_standard_deviation (degree_C) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 40 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/OSPO office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, degree_C) sses_bias (SSES bias estimate, degree_C) sses_standard_deviation (degree_C) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)