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412 results for “NOAA”
ATMS Limb Correction Coefficients for NOAA-20 and SNPP platforms
Limb correction coefficients used to create limb adjusted brightness temperature. Four separate files provide separate land and sea correction coefficients for two different ATMS sensors, one onboard on the NOAA-20 platform and the other onboard on the SNPP platform. Reference publication (older coefficients used in paper): Zhang K; Zhou L; Goldberg M; Liu X; Wolf W; Tan C, et al. A Methodology to Adjust ATMS Observations for Limb Effect and Its Applications. Journal of Geophysical Research: Atmospheres. 2017;122(21):11,347-11,56. https://doi.org/10.1002/2017JD026820
VORTEX-2 2009-2010 radar data from NOAA X-band dual Polarimetric radar (NOXP)
<p>This dataset provides level 2 radar data collected by NOAA X-band dual Polarimetric radar (NOXP) during <span>Verification of the Origins of Rotation in Tornadoes Experiment</span> (VORTEX-2) in 2009-2010.</p> <p>Archive file names have form YYYY.NOX.sweep.MMDD.tar.gz, where YYYY denotes year, MMDD denotes month and day. Extracting the archive with a unix command like</p> <p>tar zxf YYYY.NOX.sweep.MMDD.tar.gz</p> <p>produces a directory tree in the current working directory. Data files are in paths of form:</p> <p>YYYY/NOX/sweep/MMDD/NOXYYMMDDHHMMSS.RAW????/swp.YYYMMDDHHMMSS.NOXPRVP.d.dd.0_PPI_v1</p> <p>where YYYY denotes year, MMDD denotes month and day, NOXYYMMDDHHMMSS.RAW???? identifies the radar volume (cycle of antenna pointing angles), and swp.YYYMMDDHHMMSS.NOXPRVP.d.dd.0_PPI_v1 denotes a file with data for one sweep (cycle of antenna pointing angles with the same elevation (PPI) or azimuth (RHI)). YYY is number of years since 1900. d.dd is the sweep angle.</p> <p>The sweep files are DORADE format, documented at https://www.eol.ucar.edu/sites/default/files/files_live/private/files/field_project/EMEX/DoradeDoc.pdf . RadxConvert, which is part of lrose (https://ncar.github.io/lrose-core), can rewrite the files in other formats as needed by other software.</p>
NOAA-GFDL GFDL-ESM4 CMIP6 ScenarioMIP additional model output
<p>This repository contains annual 3D sea water age since surface contact files from the ScenarioMIP ssp585 simulation conducted with GFDL's ESM4.1 climate model (Dunne et al., 2020) that was contributed to the 6th Coupled Model Intercomparison Project (CMIP6).</p> <p>Both the ocean model native grid and the regridded output can be found in this repository. For the regridded output, the files have been regridded from MOM6 native grid to standard World Ocean Atlas 1x1 horizontal grid, and they have been remapped from the lagrangian vertical coordinate used by GFDL's MOM6 ocean model (Adcroft et al., 2019) to standard World Ocean Atlas depths.</p> <p>Files have undergone QA/QC. All data files are NetCDF.</p> <p>Enquiries should be directed to Jasmin.John (Jasmin.John@noaa.gov) or John Dunne (John.Dunne@noaa.gov)</p> <p>Anyone using these data should cite Dunne et al. (2020) and Adcroft et al. (2019). See references below.</p> <p>Other variables associated with these simulations, along with assigned DOI's, are available through the ESGF CMIP6 portal:</p> <p>https://esgf-node.llnl.gov/projects/cmip6/ </p> <p>______________________________________________________________________</p> <p>The organization of this repository is as follows:</p> <p>Experiments:</p> <p>The tar files in the repository follow this naming convention: <model>_<activity>_<MIP>_<experiment>_<component_and_grid>_<variable>.tar.gz</p> <p> </p> <p>E.g. </p> <p> </p> <p>GFDL_ESM4_CMIP6_ScenarioMIP_ssp585_ocean_annual_z_1x1deg_agessc.tar.gz (regridded)</p> <p>GFDL_ESM4_CMIP6_ScenarioMIP_ssp585_ocean_annual_z_agessc.tar.gz (native grid)</p> <p>The organization of above repository is as follows:</p> <p>Experiment: ssp585</p> <p>NOAA-GFDL/CMIP6/ScenarioMIP/GFDL-ESM4/ESM4_ssp585_D1/</p> <p>For each experiment, 3D annual sea water age data can be found in the sub-directory:</p> <p>/ocean_annual_z_1x1deg (for regridded output)</p> <p>/ocean_annual_z (for native grid output)</p> <p>_________________________________________________________________________</p> <p>NOTES:</p> <p>Provenance:</p> <p>The data provided here do not have metadata that can be used for provenance and traceability back to NOAA/GFDL. The data DOI assigned should be used when sharing and citing these data.</p> <p>_________________________________________________________________________</p>
NOAA NCCOS Assessment: Priority Areas Recommended for Shallow Coral Reef Management in the South Florida Coast from 2021-04-26 to 2021-05-21
<p>The National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) developed a spatial framework, process, and online application (Buja and Christensen 2019) to identify mapping needs along the south Florida coast to support shallow coral reef management by NOAA’s Coral Reef Conservation Program (CRCP). Eighteen participants from local federal, state, academic, and other institutions entered their priorities in an online participatory Geographic Information System (pGIS). Participants used virtual coins to denote their priorities in 10.4 km<sup>2</sup> hexagonal grid cells overlaid on the study area. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important, what data types were needed, and data collection methodologies using a pre-set list of options. Results were compiled, summarized, and mapped to identify high priority areas, reasons for those priorities, and information needs. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in south Florida.</p> <p>The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coast of south Florida. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection.</p> <p>An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the pGIS process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online pGIS, the study area was divided into 1761 hexagonal grid cells 10.4 km<sup>2</sup> in size. Existing relevant spatial datasets (<em>e.g.</em>, bathymetry, Sanctuary Protection Areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. The pGIS was used by 18 participants to convey their recommendations. Each participant was provided with 530 virtual coins to place into grid cells that they wished to prioritize. They were instructed to place more coins in grid cells that were higher priorities. A maximum of 53 coins could be placed into an individual grid cell by each respondent. Respondents also reported why these locations were important by selecting a minimum of one, and a maximum of two, management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also reported what data types were needed in priority cells. A minimum of one, to a maximum of two choices were selected from the following list: habitat map/characterization, shoreline characterization, ground truthing (e.g. photos and videos collected using ROVs or AUVs), elevation (e.g. bathymetry and topography), backscatter and intensity (e.g. surfaces used to delineate between hard and soft substrate), 2D map product (e.g. static images used to visualize bottom type, presence/absence of taxa), georectified photomosaics (e.g. 3D products created from structure for motion), and water column (e.g. for fish biomass detection). Respondents also reported what method of data collection was desired in each priority cell. Only one response was required and were selected from the following list: satellite, lidar, multibeam echosounder, split beam echosounder, side-scan sonar, photogrammetry, drop-camera, and uncrewed systems. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefile contains the 10.4 km<sup>2</sup> grid cells used in this prioritization and their associated coin values overall, as well as by management use, data product, and mapping methodology. Other summary values include the number of participants, number of participating groups, number of management uses, and number of data products. Also included is a ranking of each grid cell based on the total number of coins, management uses, and agencies allocating coins in the respective cell. For a complete description of the process and analysis see: Kraus et al., 2022.</p> <p> </p>
NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in Puerto Rico and the U.S. Virgin Islands, 2021-11-03 to 2022-01-14
<p>Description:</p> <p>The National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) developed a spatial framework, process, and online application (Buja and Christensen 2019) to identify mapping needs along the Puerto Rico and U.S. Virgin Island (USVI) coasts to support shallow coral reef management by NOAA’s Coral Reef Conservation Program (CRCP). Participants from local, federal, academic, and other institutions (sixteen in Puerto Rico, eighteen in USVI), entered their priorities in an online participatory Geographic Information System (pGIS). Participants used virtual coins to denote their priorities in 2.6 km<sup>2</sup> hexagonal grid cells overlaid on the study area, individually for Puerto Rico and USVI. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important, what data types were needed, and data collection methodologies using a pre-set list of options. Results were compiled, summarized, and mapped to identify high priority areas, reasons for those priorities, and information needs. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in Puerto Rico and USVI.</p> <p> </p> <p>Purpose:</p> <p>The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coasts of Puerto Rico and USVI. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection.</p> <p> </p> <p>Methods:</p> <p>An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the pGIS process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online pGIS, the Puerto Rico study area was divided into 2007 hexagonal grid cells 2.6 km2 in size. The USVI study area was divided into 644 hexagonal grid cells 2.6 km2 in size. Existing relevant spatial datasets (e.g., bathymetry, Sanctuary Protection Areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. The pGIS was used by 16 participants in Puerto Rico and 18 participants in USVI to convey their recommendations. Each Puerto Rico participant was provided with 600 virtual coins to place into grid cells that they wished to prioritize. Each USVI participant was provided with 200 coins. They were instructed to place more coins in grid cells that were higher priorities. A maximum of 60 coins could be placed into an individual grid cell in Puerto Rico by each respondent, and a maximum of 20 coins could be place into an individual grid cell in USVI. Respondents also reported why these locations were important by selecting a minimum of one, and a maximum of two, management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also reported requirements of data were needed in priority cells. A minimum of one, to a maximum of two choices were selected from the following list: delineations of large topographic features, delineations of hard vs. soft bottom, models of habitat suitability for key taxa or communities, delineations of substrate type (e.g. sand, mud, coral, rock), models of presence/absence or density of corals, identification of coral species and their local environments, documentation of individual specimen condition. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefile contains the 2.6 km2 grid cells used in this prioritization and their associated coin values overall, as well as by management use, data product, and mapping methodology. Other summary values include the number of participants, number of participating groups, number of management uses, and number of data requirements. Additionally, coins for microscale (identification of coral species and their local environments and documentation of individual specimen condition), mesoscale (delineations of substrate type, models of presence/absence/density of corals), and regional (delineations of topographic features, delineations of hard vs. soft bottom, models of habitat suitability) requirements were summarized. Also included is a ranking of each grid cell based on the total number of coins, management uses, and participating groups allocating coins in the respective cell. For a complete description of the process and analysis see: Kraus et al. 2022, in prep.</p> <p> </p>
Hurricane Michael - SAMURAI analysis files created from NOAA P-3 tail Doppler radar data
<p>This repository contains analyses of Hurricane Michael created from quality controlled data from the NOAA P3 tail Doppler radar. The TDR data can be found in its raw format at the following link under the folders 20181008H1, 20181009H1, 20181009H2, and 20181010H1:</p> <p><a href="http://seb.noaa.gov/pub/acdata/2018/RADAR/">https://seb.noaa.gov/pub/acdata/2018/RADAR/</a></p> <p>The analyses are the topic of the manuscript 'Vertical Vortex Development in Hurricane Michael (2018) during Rapid Intensification' which is in review as of dataset publication. Please cite the manuscript when using this data as it contains methodological information on how the analyses were created. More information about the center fix times each analysis file is related to are available in the manuscript. Code to run the SAMURAI analysis tool which created these files, information on how SAMURAI works, and directions can be found at the following 2 links:</p> <p><a href="http://github.com/mmbell/samurai">https://github.com/mmbell/samurai</a></p> <p><a href="http://wiki.lrose.net/index.php/SAMURAI">http://wiki.lrose.net/index.php/SAMURAI</a></p>
NOAA-GFDL GFDL-ESM4 CMIP6 CMIP additional model output
<p>This repository contains annual 3D sea water age since surface contact files from a subset of simulations with GFDL's ESM4.1 climate model (Dunne et al., 2020) that were contributed to the 6th Coupled Model Intercomparison Project (CMIP6). </p> <p>Both the ocean model native grid and the regridded output can be found in this repository. For the regridded output, the files have been regridded from MOM6 native grid to standard World Ocean Atlas 1x1 horizontal grid, and they have been remapped from the lagrangian vertical coordinate used by GFDL's MOM6 ocean model (Adcroft et al., 2019) to standard World Ocean Atlas depths.</p> <p>Files have undergone QA/QC.</p> <p>All data files are NetCDF.</p> <p>Enquiries should be directed to Jasmin.John (Jasmin.John@noaa.gov) or John Dunne (John.Dunne@noaa.gov)</p> <p>Anyone using these data should cite Dunne et al. (2020) and Adcroft et al. (2019). See references below.</p> <p>Other variables associated with these simulations, along with assigned DOI's, are available through the ESGF CMIP6 portal:https://esgf-node.llnl.gov/projects/cmip6/ </p> <p>______________________________________________________________________</p> <p>The tar files in the repository follow this naming convention: <model>_<activity>_<MIP>_<experiment>_<component_and_grid>_<variable>.tar.gz</p> <p> </p> <p>E.g. </p> <p> </p> <p>GFDL_ESM4_CMIP6_CMIP_historical_ocean_annual_z_1x1deg_agessc.tar.gz (regridded)</p> <p>GFDL_ESM4_CMIP6_CMIP_historical_ocean_annual_z_agessc.tar.gz (native grid)</p> <p> </p> <p>The organization of above repository is as follows:</p> <p>Experiments:</p> <p>The concentration-forced piControl simulation: </p> <p>NOAA-GFDL/CMIP6/CMIP/GFDL-ESM4/ESM4_piControl_D</p> <p>The concentration-forced historical simulation: </p> <p>NOAA-GFDL/CMIP6/CMIP/GFDL-ESM4/ESM4_historical_D1</p> <p>The historical simulation was spawned from year 101 of the pre-industrial control simulation</p> <p>For each experiment, 3D annual sea water age data can be found in the sub-directory:</p> <p>/ocean_annual_z_1x1deg (for regridded output)</p> <p>/ocean_annual_z (for native grid output)</p> <p>_________________________________________________________________________</p> <p>NOTES:</p> <p>Provenance:</p> <p>The data provided here do not have metadata that can be used for provenance </p> <p>and traceability back to NOAA/GFDL.</p> <p>The data DOI assigned should be used when sharing and citing these data.</p> <p>_________________________________________________________________________</p> <p><br> </p>
Mirror of data from NOAA U.S. Climate Reference Network for Research Computing in Earth Science
<p>This is a mirror of data from the NOAA U.S. Climate Reference Network (https://www.ncei.noaa.gov/products/land-based-station/us-climate-reference-network).</p> <p>It was created because outbound FTP access is not allowed from some cloud-based JupyterHub setups.</p>
Active Regions with Multiple NOAA Numbers, 2011-2019
<p>This is a list of active regions which have been identified as lasting for multiple rotations, and their subsequent-rotation NOAA number designation. For more information on the creation of this dataset, please refer to (ApJ link coming).</p>
NOAA PSL CL31 Ceilometer Backscatter and Cloud Base Height Data for SPLASH
<p>This dataset contains daily files from a CL31 ceilometer manufactured by Vaisala that was deployed at Roaring Judy in the East River Watershed in Colorado (38.7169321 N, 106.853031 W, 2494 m above mean sea level) from 21 October 2021 to 28 January 2022 as part of the National Oceanic and Atmospheric Administration (NOAA) Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign. </p> <p>The files contain backscatter profiles, cloud base heights, and visibility. The ceilometer measures vertical profiles of backscatter using laser technology. From the backscatter profiles, cloud base height and vertical visibility are determined using with the Vaisala software CL-view. For details on the instrument specifics and the methods, see the manufacturer manual (cl31usersguide.pdf). </p> <p>The file format is the original Vaisala format (.DAT). For a description of the format see the manufacturer manual. To convert the .DAT file format to netcdf format, the open source command line Python program ‘cl2nc’ (https://github.com/peterkuma/cl2nc) can, for example, be used. </p> <p>The file naming conventions for the .DAT files are as follows:</p> <p>NOAA_PSL_CL31_Roaring Judy_yyyymmdd_HH.DAT</p> <p>with</p> <p>yyyy: Year</p> <p>mm: Month</p> <p>dd: Day</p> <p>HH: Hour when the first sample was written to the file</p> <p>The time stamp of all data is in UTC.</p>
NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in Hawaiʻi, 2022-07-08 to 2022-08-01
<p>Description</p> <p>NOAA's Coral Reef Conservation Program (CRCP) has identified a need for priority locations based on emerging management requirements in shallow coral reef areas (up to 40 meters) surrounding the main Hawaiian Islands. The priorities provided by participating agencies will inform research and monitoring activities, address current and future management needs, and maximize opportunities to leverage and complement existing regional efforts.</p> <p>To meet this need, NOAA’s National Centers for Coastal Ocean Science (NCCOS) developed a systematic, quantitative approach and online GIS application to gather seafloor mapping priorities from researchers and coral reef managers. Participants placed virtual coins into a grid overlaid on the project area to express the location of their mapping priorities. They also used pull-down menus to indicate specific mapping data needs and the rationale for their selections. Participants’ inputs were compiled and analyzed to identify high priority areas along with their justifications and requirements. A total of 17 participant groups entered their mapping priorities into the online tool. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in Hawaiʻi.</p> <p>Purpose:</p> <p>The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coasts of the main Hawaiian Islands. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection.</p> <p>Methods:</p> <p>An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the prioritization process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online prioritization tool, the study area was divided into 1786 hexagonal grid cells 2.6 km<sup>2</sup> in size. Existing relevant spatial datasets (<em>e.g.</em>, bathymetry, protected areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. Each participant was provided with 540 virtual coins to place into grid cells to denote their mapping needs. They were instructed to place more coins in grid cells that were higher priority. A maximum of 54 coins could be placed into an individual grid cell by each respondent. Participants also selected from a drop-down list of predefined management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also selected what map product requirements were needed in priority cells by selecting a minimum of one, to a maximum of two choices from the following list: delineations of large topographic features, delineations of hard vs. soft bottom, models of habitat suitability for key taxa or communities, delineations of substrate type (e.g. sand, mud, coral, rock), models of presence/absence or density of corals, identification of coral species and their local environments, documentation of individual specimen condition. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefile contains the 2.6 km<sup>2</sup> grid cells used in this prioritization and their associated coin values overall, as well as by management use and map product requirement. Other summary values include the number of participants, number of participating groups, number of management uses, and number of map product requirements. Additionally, coins for microscale (identification of coral species and their local environments and documentation of individual specimen condition), mesoscale (delineations of substrate type, models of presence/absence/density of corals), and regional (delineations of topographic features, delineations of hard vs. soft bottom, models of habitat suitability) requirements were summarized. Also included is a ranking of each grid cell based on the total number of coins, management uses, and participating groups allocating coins in the respective cell. For a complete description of the process and analysis see: Kraus et al. 2023, in prep.</p> <p> </p>
NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in Guam and the Commonwealth of the Northern Mariana Islands, 2023-02-22 to 2023-06-12
<p>Description:<br> NOAA's Coral Reef Conservation Program (CRCP has identified a need for priority locations based on emerging management requirements in shallow coral reef areas (up to 40 meters) surrounding Guam and the Commonwealth of the Northern Mariana Islands (CNMI). The priorities provided by participating agencies will inform research and monitoring activities, address current and future management needs, and maximize opportunities to leverage and complement existing regional efforts.<br> To meet this need, NOAA’s National Centers for Coastal Ocean Science (NCCOS) developed a systematic, quantitative approach and online GIS application to gather seafloor mapping priorities from researchers and coral reef managers. Participants placed virtual coins into a grid overlaid on the project area to express the location of their mapping priorities. They also used pull-down menus to indicate specific mapping data needs and the rationale for their selections. Participants’ inputs were compiled and analyzed to identify high priority areas along with their justifications and requirements. A total of seven participant groups entered their mapping priorities into the online tool for Guam and ten participant groups for CNMI. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in Guam and CNMI.</p> <p>Purpose:<br> The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coasts of the Guam and CNMI. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection.</p> <p>Methods:<br> An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the prioritization process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online prioritization tool, the Guam study area was divided into 153 hexagonal grid cells 2.6 km2 in size. The CNMI study area was divided into 330 hexagonal grid cells 2.6 km2 in size. Existing relevant spatial datasets (e.g., bathymetry, Sanctuary Protection Areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. Each Guam participant was provided with 50 virtual coins to place into grid cells that they wished to prioritize. Each CNMI participant was provided with 110 coins. They were instructed to place more coins in grid cells that were higher priorities. A maximum of 5 coins could be placed into an individual grid cell in Guam by each respondent, and a maximum of 11 coins could be place into an individual grid cell in CNMI. Respondents also<br> reported why these locations were important by selecting a minimum of one, and a maximum of two, management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also reported requirements of data were needed in priority cells. A minimum of one, to a maximum of two choices were selected from the following list: delineations of large topographic features, delineations of hard vs. soft bottom, models of habitat suitability for key taxa or communities, delineations of substrate type (e.g. sand, mud, coral, rock), models of presence/absence or density of corals, identification of coral species and their local environments, documentation of individual specimen condition. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefiles contain the 2.6 km2 grid cells used in this prioritization and their associated coin values overall, as well as by management use, data product, and mapping methodology. Other summary values include the number of participants, number of participating groups, number of management uses, and number of data requirements. Additionally, coins for microscale (identification of coral species and their local environments and documentation of individual specimen condition), mesoscale (delineations of substrate type, models of presence/absence/density of corals), and regional (delineations of topographic features, delineations of hard vs. soft bottom, models of habitat suitability) requirements were summarized. Also included is a ranking of each grid cell based on the total number of coins, management uses, and participating groups allocating coins in the respective cell. For a complete description of the process and analysis see: Hile et al. 2023, in prep.</p>
NOAA GML Kettle Ponds Surface Radiation Budget and Near-Surface Meteorology Data for SPLASH
<p>These files contain Surface Energy Balance data at the Kettle Ponds (CKP) site as part of NOAA’s Global Monitoring Laboratory’s deployment in the Sail-SPLASH Campaign between October 2021 through August 2023.</p>
NOAA GML Brush Creek Surface Radiation Budget and Near-Surface Meteorology Data for SPLASH
<p>These files contain Surface Energy Balance data at the Brush Creek (CBC) site as part of NOAA's Global Monitoring Laboratory's deployment in the Sail-SPLASH Campaign between October 2021 through August 2023.</p><p> </p><p><strong>NOTE: Version 2.1 contains one "zip" file containing all daily files for ease of download.</strong></p>
Alaska compendium of ocean profile data [ACOD]: Archival CTD and nutrient hydrography from NOAA's EcoFOCI, EMA, and predecessor programs
Open the record for dataset details and reuse information.
Fiddler crab body size in salt marshes from Florida to Massachusetts, USA at PIE and VCR LTER and NOAA NERR sites during summer 2016.
Bergmann’s rule predicts that organisms at higher latitudes are larger than ones at lower latitudes. Here, we examine the body-size pattern of the Atlantic fiddler crab, Minuca (=Uca) pugnax, from salt marshes on the east coast of the United States across 12 degrees of latitude. We found that M. pugnax followed Bergmann’s rule and that, on average, crab carapace width increased by 0.5 mm per degree of latitude. Minuca pugnax body size also followed the temperature-size rule with body size inversely related to mean water temperature. Because an organism’s size influences its impact on an ecosystem, and Minuca pugnax is an ecosystem engineer that affects marsh functioning, the larger crabs at higher latitudes may have greater per-capita impacts on salt marshes than the smaller crabs at lower latitudes.
NOAA-NOS-NGS t-sheet Vector Shorelines for the Eastern Shore of VA and southern MD, 1847-1978
The primary purpose of this dataset is to provide VCRLTER researchers and students with a convenient and comprehensive set of historical NOS t-sheet shorelines spanning the full Virginia Eastern Shore in a single GIS data layer. From NOAA-NOS-NGS source metadata: "These shoreline data represent a vector conversion of a set of NOS raster shoreline manuscripts identified by t-sheet or tp-sheet numbers. These vector data were created by contractors for NOS who vectorized georeferenced raster shoreline manuscripts using Environmental Systems Research Institute, Inc. (ESRI)(r), ArcInfo's(r) ArcScan(r) software to create individual ArcInfo coverages. The individual coverages were ultimately edgematched within a surveyed project area and appended together. The NOAA NESDIS Environmental Data Rescue Program (EDRP) funded this project. The NOAA National Ocean Service, Coastal Services Center, developed the procedures used in this project and was responsible for project oversight. The project intent was to rescue valuable historical data and make it accessible and useful to the coastal mapping community. This process involved the conversion of original analog products to digital mapping products. This file is a further conversion of that product from a raster to a vector product that may be useful for Electronic Charting and Display Information Systems (ECDIS) and geographic information systems (GIS)." Original NOAA-NOS-NGS data were organized by project, with each project containing a single shapefile containing the historical shoreline features from multiple T-sheets based on surveys from roughly the same time period. There were 43 projects containing information from 208 T-sheets and TP-sheets that were found to cover the Eastern Shore of VA and southern MD and ranging in time from 1847 to 1978 (plus one set of shorelines from 2009 for the new Chincoteague bridge and the immediate surrounding area). VCRLTER staff combined these 43 shapefiles into a single shapefile with
NOAA 6-Minute Tidal Heights for Wachapreague, VA, 1996-2000 and 2005-present
Data is 6-minute interval predicted and observed tide levels at NOAA/NOS/CO-OP station 8631044, Wachapreague, Virginia. Station is operated by the Virginia Institute of Marine Science (VIMS) Eastern Shore Lab. Data were acquired from the NOAA/NOS Center for Operational Oceanographic Products and Services (CO-OPS) web site (http://tidesandcurrents.noaa.gov/) for station ID 8631044 (Wachapreague, Virginia) using the CO-OPS API for data retrieval. Separate comma-delimited files were retrieved for predicted and observed water level data, one month of data per file, and the data combined using R.
Data and code for paper "A gray-box model for a probabilistic estimate of regional ground magnetic perturbations: Enhancing the NOAA operational Geospace model with machine learning"
<p>Simulation results from the NOAA/SWPC Geospace model used in the paper Camporeale et al. (2020) "A gray-box model for a probabilistic estimate of regional ground magnetic perturbations: Enhancing the NOAA operational Geospace model with machine learning" published in J. Geophys. Res. (2020)</p> <p>MATLAB code is provided to train process the data and train the machine learning model and plot results.</p> <p>Manuscript available on <a href="https://arxiv.org/abs/1912.01038">https://arxiv.org/abs/1912.01038</a></p>
NOAA PSL thermodynamic profiles retrieved from a combination of active and passive remote sensors and numerical weather prediction models with the optimal estimation physical retrieval TROPoe at Platteville, CO, USA
<p>This dataset contains retrieved profiles of thermodynamic variables obtained using the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval from various combinations of input data collected by passive and active remote sensing instruments, in-situ surface platforms, and numerical weather prediction models deployed at the Platteville, CO, USA, site in fall 20221-winter 2022. Among the employed instruments are Microwave Radiometers (MWRs), Infrared Spectrometers (IRS), Radio Acoustic Sounding Systems (RASS), ceilometers, surface sensors, and information from the operational Rapid Refresh numerical weather prediction model.</p> <p>The dataset also includes 15 radiosounding launched for assessing the retrievals.</p> <p>For further information, please see:</p> <p>Bianco, L., Adler, B., Bariteau, L., Djalalova, I. V., Myers, T., Pezoa, S., Turner, D. D., and Wilczak, J. M.: Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2023-263, in review, 2024.</p>
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.