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1,868 results for “Spatial Data”
Data from: Spatial heterogeneity in plant-soil feedbacks alters competitive interactions between two grassland plant species
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Data from: Lateralization in alpha-band oscillations predicts the locus and spatial distribution of attention
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Data from: Spatial patterning of prey at reproduction to reduce predation risk: what drives dispersion from groups?
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Data from: Spatial heterogeneity of tree diversity changes in montane forests under climate warming
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Data for: Density dependence and spatial heterogeneity limit the population growth rate of invasive pines at the landscape scale
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Data from: Spatial familial networks to infer demographic structure of wild populations
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Data from: Patterns of fine-scale spatial genetic structure and pollen dispersal in giant sequoia (Sequoiadendron giganteum)
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First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) Centre Meteorologie Spatiale (CMS) Daily Solar Irradiance Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution clouddata.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.These files are calculations of the daily solar irradiance at the surface, based on observations by the METEOSAT. The file naming convention is: esqDDMMYYx.fis where DDMMYY is the dateThese files are: I2 pixels, 376 pixels/row, 326 rows. Each pixel has a spatial resolution of 0.04 degrees.The header of each file claims there are two channels, although the provided documentation states that there is only one channel per file.The units are: flux [tenths of Joule/cm^2]
First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) Centre Meteorologie Spatiale (CMS) Monthly Solar Irradiance Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.These files are calculations of the monthly solar irradiance at the surface, based on observations by the METEOSAT. The file naming convention is: esmxx.fis where xx is the month number of 1992.These files are: I2 pixels, 376 pixels/row, 326 rows. Each pixel has a spatial resolution of 0.04 degrees.The header of each file claims there are two channels, although the provided documentation states that there is only one channel per file.The units are: flux [tenths of Joule/cm^2]
Spatial Statistical Data Fusion (SSDF) Level 3: CONUS Near-Surface Vapor Pressure Deficit from SNPP CrIMSS and Aqua AIRS, V2 (SNDR13IML3SSDFCVPD)
The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft. The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder. This data set provides an estimate of the vapor pressure deficit. It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. These are all daily products on a ¼ x ¼ degree latitude/longitude grid covering the continental United States (CONUS). The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from.
Spatial Statistical Data Fusion (SSDF) Level 3: CONUS Near-Surface Atmospheric Temperature from Aqua AIRS, V2 (SNDRAQIL3SSDFCNSAT)
This data set provides an estimate of the surface air temperature. It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight.The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft. The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder. It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. These are all daily products on a ¼ x ¼ degree latitude/longitude grid covering the continental United States (CONUS). The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from.
Spatial Statistical Data Fusion (SSDF) Level 3: CONUS Near-Surface Atmospheric Temperature from SNPP CrIMSS and Aqua AIRS, V2 (SNDR13IML3SSDFCNSAT)
This data set provides an estimate of the surface air temperature. It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft. The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder. These are all daily products on a ¼ x ¼ degree latitude/longitude grid covering the continental United States (CONUS). The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from.
Spatial Statistical Data Fusion (SSDF) Level 3: CONUS Near-Surface Vapor Pressure Deficit from Aqua AIRS, V2 (SNDRAQIL3SSDFCVPD)
This data set provides an estimate of the vapor pressure deficit. It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight.The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft. The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder. These are all daily products on a ¼ x ¼ degree latitude/longitude grid covering the continental United States (CONUS).The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from.
First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) Centre Meteorologie Spatiale (CMS) Longwave Flux Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.These files are the calculated downward longwave flux at the surface derived from METEOSAT observations. The file naming convention is: raDDMMYYsxx.fis_tmpwhere DDMMYY is the date and xx = slot numberMean time (UT) is obtained from the slot number overthe ASTEX region by the formula: UT = (xx/2) - 0.17These files are: I2 pixels, 188 pixels/row, 163 rows. Each pixel has a spatial resolution of 0.08 degrees.The units of flux are Wm^-2.
First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) Centre Meteorologie Spatiale Daily Sea Surface Temperature Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data. To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each missioncombined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.These files are daily temperature fields from observations made by theNOAA 11 and 12 polar orbiting satellites.
First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) Centre Meteorologie Spatiale Weekly Sea SurfaceTemperature Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.These files are weekly temperature fields from observations made by the NOAA 11 and 12 polar orbiting satellites. The file naming convention is: thseXXYYZZ.fiswhere XX = week number in 1992 YY = jo (jour) day nu (nuit) night ma (matin) morning ZZ = 11 NOAA-11 12 NOAA-12These files are: I1 pixels, 752 pixels/row, 652 rows. Each pixel has a spatial resolution of 0.02 degrees.The units are: temperature [degree C] (offset by 10 deg.)
First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) Centre Meteorologie Spatiale (CMS) Hourly Solar Irradiance Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.These files are calculations of the hourly solar irradiance at the surface, based on observations by the METEOSAT. The file naming convention is: esDDMMYYsxx.fiswhere DDMMYY is the date and xx = slot numberMean time (UT) is obtained from the slot number overthe ASTEX region by the formula: UT = (xx/2) - 0.17These files are: I2 pixels, 376 pixels/row, 326 rows. Each pixel has a spatial resolution of 0.04 degrees.The header of each file claims there are two channels, although the provided documentation states that there is only one channel per file.The units are: flux [tenths of Joule/cm^2]
First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) Centre Meteorologie Spatiale (CMS) Weekly Solar Irradiance Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.These files are calculations of the monthly solar irradiance at the surface, based on observations by the METEOSAT. The file naming convention is: esmxx.fis where xx is the month number of 1992.These files are: I2 pixels, 376 pixels/row, 326 rows. Each pixel has a spatial resolution of 0.04 degrees.The header of each file claims there are two channels, although the provided documentation states that there is only one channel per file.The units are: flux [tenths of Joule/cm^2]
Spatial transcriptome data of Longissimus dorsi muscle from 3 pigs
GEO Series GSE203094. Sus scrofa. 3 samples. Type: Expression profiling by high throughput sequencing.
ERRγ links adaptive neuronal metabolism to spatial learning and memory [Array data]
GEO Series GSE47133. Mus musculus. 8 samples. Type: Expression profiling by array.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.