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ERDDAP
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Brought to you by NOAA NMFS SWFSC ERD |
| griddap | Subset | tabledap | Make A Graph | wms | files | Title | Summary | FGDC | ISO 19115 | Info | Background Info | RSS | Institution | Dataset ID | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| https://data.pmel.noaa.gov/generic/erddap/tabledap/cchdo_bottle.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/cchdo_bottle | https://data.pmel.noaa.gov/generic/erddap/tabledap/cchdo_bottle.graph | https://data.pmel.noaa.gov/generic/erddap/files/cchdo_bottle/ | CCHDO GO SHIP bottle data | CCHDO GO SHIP bottle data from netcdf\n\ncdm_data_type = Profile\nVARIABLES:\nprofile_id (Unique Profile ID)\nexpocode\nsection_id\nline_id\nstation\ncast\nsample\nbottle_number\nbottle_number_qc (Status Flag)\ntime (seconds since 1970-01-01T00:00:00Z)\nlatitude (degrees_north)\nlongitude (degrees_east)\ndepth (Sea Floor Depth Below Sea Surface, m)\npressure (Sea Water Pressure, dbar)\nctd_temperature_unk (Sea Water Temperature, degree_C)\nctd_temperature_68 (Sea Water Temperature, degree_C)\nctd_temperature (Sea Water Temperature, degree_C)\nctd_temperature_qc (Status Flag)\nctd_salinity (Sea Water Practical Salinity, 1)\nctd_salinity_qc (Status Flag)\nbottle_salinity (Sea Water Practical Salinity, 1)\nbottle_salinity_qc (Status Flag)\nctd_oxygen_ml_l (Volume Fraction Of Oxygen In Sea Water)\nctd_oxygen_ml_l_qc (Status Flag)\nctd_oxygen (Moles Of Oxygen Per Unit Mass In Sea Water, µmole/kg)\nctd_oxygen_umol_l (Mole Concentration Of Dissolved Molecular Oxygen In Sea Water)\noxygen_ml_l (Volume Fraction Of Oxygen In Sea Water)\n... (183 more variables)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/cchdo_bottle_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/cchdo_bottle_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/cchdo_bottle/index.htmlTable | https://cchdo.ucsd.edu/
| https://data.pmel.noaa.gov/generic/erddap/rss/cchdo_bottle.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=cchdo_bottle&showErrors=false&email= | CCHDO | cchdo_bottle | ||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/cchdo_ctd.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/cchdo_ctd | https://data.pmel.noaa.gov/generic/erddap/tabledap/cchdo_ctd.graph | https://data.pmel.noaa.gov/generic/erddap/files/cchdo_ctd/ | CCHDO GO SHIP ctd data | CCHDO GO SHIP ctd data from netcdf files\n\ncdm_data_type = Profile\nVARIABLES:\nexpocode\nstation\ncast\nsample\ntime (seconds since 1970-01-01T00:00:00Z)\nprofile_id (Unique Profile ID)\nlatitude (degrees_north)\nlongitude (degrees_east)\npressure (Sea Water Pressure, dbar)\nctd_pressure_raw (Sea Water Pressure)\nctd_pressure_raw_qc (Status Flag)\nctd_temperature_unk (Sea Water Temperature, degree_C)\nctd_temperature_unk_qc (Status Flag)\nctd_temperature_68 (Sea Water Temperature, degree_C)\nctd_temperature (Sea Water Temperature, degree_C)\nctd_salinity (Sea Water Practical Salinity, 1)\nctd_salinity_qc (Status Flag)\nctd_absolute_salinity (Sea Water Absolute Salinity)\nctd_absolute_salinity_qc (Status Flag)\nctd_conservative_temperature (Sea Water Conservative Temperature, degree_C)\nctd_conservative_temperature_qc (Status Flag)\nctd_sound_velocity_salinity\nctd_sound_velocity_salinity_qc (Status Flag)\nctd_oxygen_ml_l (Volume Fraction Of Oxygen In Sea Water)\nctd_oxygen (Moles Of Oxygen Per Unit Mass In Sea Water, µmole/kg)\nctd_oxygen_umol_l (Mole Concentration Of Dissolved Molecular Oxygen In Sea Water)\nctd_oxygen_umol_l_qc (Status Flag)\n... (49 more variables)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/cchdo_ctd_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/cchdo_ctd_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/cchdo_ctd/index.htmlTable | https://cchdo.ucsd.edu/
| https://data.pmel.noaa.gov/generic/erddap/rss/cchdo_ctd.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=cchdo_ctd&showErrors=false&email= | CCHDO | cchdo_ctd | ||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/ctd_0e4d_0f30_7196.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/ctd_0e4d_0f30_7196 | https://data.pmel.noaa.gov/generic/erddap/tabledap/ctd_0e4d_0f30_7196.graph | Data from a local source. | Data from a local source.\n\ncdm_data_type = Profile\nVARIABLES:\nprofile_id (Unique Profile ID)\nexpocode\nstation\ncast\nsample\ntime (seconds since 1970-01-01T00:00:00Z)\nlatitude (degrees_north)\nlongitude (degrees_east)\npressure (Sea Water Pressure, dbar)\nctd_temperature_unk (Sea Water Temperature, degree_C)\nctd_temperature_unk_qc (Status Flag)\nctd_temperature_68 (Sea Water Temperature, degree_C)\nctd_temperature_68_qc (Status Flag)\nctd_temperature (Sea Water Temperature, degree_C)\nctd_temperature_qc (Status Flag)\nctd_salinity (Sea Water Practical Salinity, 1)\nctd_salinity_qc (Status Flag)\nctd_oxygen_ml_l (Volume Fraction Of Oxygen In Sea Water)\nctd_oxygen_ml_l_qc (Status Flag)\nctd_oxygen (Moles Of Oxygen Per Unit Mass In Sea Water, µmole/kg)\nctd_oxygen_qc (Status Flag)\nctd_oxygen_umol_l (Mole Concentration Of Dissolved Molecular Oxygen In Sea Water)\nctd_oxygen_umol_l_qc (Status Flag)\nctd_fluor (Mass Concentration Of Chlorophyll In Sea Water)\nctd_fluor_qc (Status Flag)\nctd_fluor_arbitrary\nctd_fluor_arbitrary_qc (Status Flag)\n... (31 more variables)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/ctd_0e4d_0f30_7196_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/ctd_0e4d_0f30_7196_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/ctd_0e4d_0f30_7196/index.htmlTable | ??? | https://data.pmel.noaa.gov/generic/erddap/rss/ctd_0e4d_0f30_7196.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=ctd_0e4d_0f30_7196&showErrors=false&email= | ??? | ctd_0e4d_0f30_7196 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/icoads_arctic_subset_1990.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/icoads_arctic_subset_1990 | https://data.pmel.noaa.gov/generic/erddap/tabledap/icoads_arctic_subset_1990.graph | International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Arctic Subset from 1990 - 1999 | This file contains ICOADS R3.0.0 data in netCDF4 format collected from 1999-12-01T00:00:00Z to 1999-12-31T23:58:47Z. The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) offers surface marine data spanning the past three centuries, and simple gridded monthly summary products for 2-degree latitude x 2-degree longitude boxes back to 1800 (and 1degreex1degree boxes since 1960)--these data and products are freely distributed worldwide. As it contains observations from many different observing systems encompassing the evolution of measurement technology over hundreds of years, ICOADS is probably the most complete and heterogeneous collection of surface marine data in existence.\n\ncdm_data_type = Point\nVARIABLES:\nrow\ntime (seconds since 1970-01-01T00:00:00Z)\ndate (date in YYYYMMDD)\ncrs\nHR (Hour)\nlatitude (degrees_north)\nlongitude (degrees_east)\nTI (Time Indicator)\nLI (Latitude Longitude Indicator)\nDS (Ship's Course)\nVS (Ship's Speed)\nNID\nII (Identification Indicator)\nID (Identification)\nC1 (Country Code)\nDI (Wind Direction Indicator)\nD (Wind Direction, degrees)\nWI (Wind Speed Indicator)\nW (Wind Speed , m/s)\nVI (Visibility Indicator)\n... (185 more variables)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/icoads_arctic_subset_1990_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/icoads_arctic_subset_1990_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/icoads_arctic_subset_1990/index.htmlTable | http://rda.ucar.edu/datasets/ds548.0/docs/R3.0-citation.pdf
| https://data.pmel.noaa.gov/generic/erddap/rss/icoads_arctic_subset_1990.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=icoads_arctic_subset_1990&showErrors=false&email= | NCEI, NOAA | icoads_arctic_subset_1990 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1076_swfsc_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1076_swfsc_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1076_swfsc_2022.graph | Saildrone 2022 SWFSC Survey NRT, drone 1076 | The National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC) is investigating the use of advanced technologies to increase our understanding of marine ecosystems, to improve operational efficiencies, improve mission safety, and potentially reduce operational costs. Use of Unmanned Surface Vehicles (USV) to conduct surveys is one such advanced technology being considered. New methods are compared to standard methods in order to validate that results are comparable or better than the current standard methods. A secondary objective is to provide more survey coverage to supplement NOAA research vessel coverage.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1076_swfsc_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1076_swfsc_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1076_swfsc_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1076_swfsc_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1076_swfsc_2022&showErrors=false&email= | Saildrone | sd1076_swfsc_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1077_swfsc_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1077_swfsc_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1077_swfsc_2022.graph | Saildrone 2022 SWFSC Survey NRT, drone 1077 | The National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC) is investigating the use of advanced technologies to increase our understanding of marine ecosystems, to improve operational efficiencies, improve mission safety, and potentially reduce operational costs. Use of Unmanned Surface Vehicles (USV) to conduct surveys is one such advanced technology being considered. New methods are compared to standard methods in order to validate that results are comparable or better than the current standard methods. A secondary objective is to provide more survey coverage to supplement NOAA research vessel coverage.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1077_swfsc_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1077_swfsc_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1077_swfsc_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1077_swfsc_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1077_swfsc_2022&showErrors=false&email= | Saildrone | sd1077_swfsc_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1048_swfsc_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1048_swfsc_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1048_swfsc_2023.graph | Saildrone 2023 NOAA SWFSC NRT Data, drone 1048 | The National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC) uses advanced Technologies to increase our understanding of marine ecosystems, to improve operational efficiencies, improve mission safety, and potentially reduce operational costs. Use of Unmanned Surface Vehicles (USV) to conduct surveys is one such advanced technology. New methods are compared to standard methods to ensure that results are comparable or better than the current standard methods. A secondary objective is to provide more survey coverage to supplement NOAA research vessel coverage.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntrajectory (Trajectory/Drone ID)\ntime (seconds since 1970-01-01T00:00:00Z)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1048_swfsc_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1048_swfsc_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1048_swfsc_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1048_swfsc_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1048_swfsc_2023&showErrors=false&email= | Saildrone | sd1048_swfsc_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1060_swfsc_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1060_swfsc_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1060_swfsc_2023.graph | Saildrone 2023 NOAA SWFSC NRT Data, drone 1060 | The National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC) uses advanced Technologies to increase our understanding of marine ecosystems, to improve operational efficiencies, improve mission safety, and potentially reduce operational costs. Use of Unmanned Surface Vehicles (USV) to conduct surveys is one such advanced technology. New methods are compared to standard methods to ensure that results are comparable or better than the current standard methods. A secondary objective is to provide more survey coverage to supplement NOAA research vessel coverage.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntrajectory (Trajectory/Drone ID)\ntime (seconds since 1970-01-01T00:00:00Z)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1060_swfsc_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1060_swfsc_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1060_swfsc_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1060_swfsc_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1060_swfsc_2023&showErrors=false&email= | Saildrone | sd1060_swfsc_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1096_swfsc_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1096_swfsc_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1096_swfsc_2023.graph | Saildrone 2023 NOAA SWFSC NRT Data, drone 1096 | The National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC) uses advanced Technologies to increase our understanding of marine ecosystems, to improve operational efficiencies, improve mission safety, and potentially reduce operational costs. Use of Unmanned Surface Vehicles (USV) to conduct surveys is one such advanced technology. New methods are compared to standard methods to ensure that results are comparable or better than the current standard methods. A secondary objective is to provide more survey coverage to supplement NOAA research vessel coverage.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntrajectory (Trajectory/Drone ID)\ntime (seconds since 1970-01-01T00:00:00Z)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1096_swfsc_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1096_swfsc_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1096_swfsc_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1096_swfsc_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1096_swfsc_2023&showErrors=false&email= | Saildrone | sd1096_swfsc_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1031_hurricane_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1031_hurricane_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1031_hurricane_2022.graph | Saildrone Atlantic 2022 Hurricane Monitoring, drone 1031 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification. This mission will deploy 7 USVs during the 2022 hurricane season to observe the air-sea interaction before, during and after hurricanes. When possible, the deployed USVs will coordinate with other autonomous devices to make coherent observations of the air-sea interface and profiles in the upper ocean and atmospheric marine boundary layer.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1031_hurricane_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1031_hurricane_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1031_hurricane_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1031_hurricane_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1031_hurricane_2022&showErrors=false&email= | Saildrone | sd1031_hurricane_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1032_hurricane_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1032_hurricane_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1032_hurricane_2022.graph | Saildrone Atlantic 2022 Hurricane Monitoring, drone 1032 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification. This mission will deploy 7 USVs during the 2022 hurricane season to observe the air-sea interaction before, during and after hurricanes. When possible, the deployed USVs will coordinate with other autonomous devices to make coherent observations of the air-sea interface and profiles in the upper ocean and atmospheric marine boundary layer.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1032_hurricane_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1032_hurricane_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1032_hurricane_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1032_hurricane_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1032_hurricane_2022&showErrors=false&email= | Saildrone | sd1032_hurricane_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1040_hurricane_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1040_hurricane_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1040_hurricane_2022.graph | Saildrone Atlantic 2022 Hurricane Monitoring, drone 1040 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification. This mission will deploy 7 USVs during the 2022 hurricane season to observe the air-sea interaction before, during and after hurricanes. When possible, the deployed USVs will coordinate with other autonomous devices to make coherent observations of the air-sea interface and profiles in the upper ocean and atmospheric marine boundary layer.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1040_hurricane_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1040_hurricane_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1040_hurricane_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1040_hurricane_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1040_hurricane_2022&showErrors=false&email= | Saildrone | sd1040_hurricane_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1059_hurricane_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1059_hurricane_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1059_hurricane_2022.graph | Saildrone Atlantic 2022 Hurricane Monitoring, drone 1059 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification. This mission will deploy 7 USVs during the 2022 hurricane season to observe the air-sea interaction before, during and after hurricanes. When possible, the deployed USVs will coordinate with other autonomous devices to make coherent observations of the air-sea interface and profiles in the upper ocean and atmospheric marine boundary layer.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1059_hurricane_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1059_hurricane_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1059_hurricane_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1059_hurricane_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1059_hurricane_2022&showErrors=false&email= | Saildrone | sd1059_hurricane_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1078_hurricane_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1078_hurricane_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1078_hurricane_2022.graph | Saildrone Atlantic 2022 Hurricane Monitoring, drone 1078 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification. This mission will deploy 7 USVs during the 2022 hurricane season to observe the air-sea interaction before, during and after hurricanes. When possible, the deployed USVs will coordinate with other autonomous devices to make coherent observations of the air-sea interface and profiles in the upper ocean and atmospheric marine boundary layer.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN\nWIND_SPEED_MEAN\nTEMP_AIR_MEAN (degree_C)\nRH_MEAN\nBARO_PRES_MEAN\nWAVE_DOMINANT_PERIOD\nWAVE_SIGNIFICANT_HEIGHT\nTEMP_SBE37_MEAN (degree_C)\nSAL_SBE37_MEAN\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1078_hurricane_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1078_hurricane_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1078_hurricane_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1078_hurricane_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1078_hurricane_2022&showErrors=false&email= | Saildrone | sd1078_hurricane_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1083_hurricane_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1083_hurricane_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1083_hurricane_2022.graph | Saildrone Atlantic 2022 Hurricane Monitoring, drone 1083 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification. This mission will deploy 4 USVs during the 2021 hurricane season to observe the air-sea interaction before, during and after hurricanes. When possible, the deployed USVs will coordinate with other autonomous devices to make coherent observations of the air-sea interface and profiles in the upper ocean and atmospheric marine boundary layer.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1083_hurricane_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1083_hurricane_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1083_hurricane_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1083_hurricane_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1083_hurricane_2022&showErrors=false&email= | Saildrone | sd1083_hurricane_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1084_hurricane_2022.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1084_hurricane_2022 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1084_hurricane_2022.graph | Saildrone Atlantic 2022 Hurricane Monitoring, drone 1084 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification. This mission will deploy 7 USVs during the 2022 hurricane season to observe the air-sea interaction before, during and after hurricanes. When possible, the deployed USVs will coordinate with other autonomous devices to make coherent observations of the air-sea interface and profiles in the upper ocean and atmospheric marine boundary layer.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (time in seconds, seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1084_hurricane_2022_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1084_hurricane_2022_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1084_hurricane_2022/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1084_hurricane_2022.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1084_hurricane_2022&showErrors=false&email= | Saildrone | sd1084_hurricane_2022 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1031_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1031_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1031_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1031 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1031_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1031_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1031_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1031_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1031_hurricane_2023&showErrors=false&email= | Saildrone | sd1031_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1036_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1036_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1036_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1036 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1036_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1036_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1036_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1036_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1036_hurricane_2023&showErrors=false&email= | Saildrone | sd1036_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1040_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1040_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1040_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1040 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1040_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1040_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1040_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1040_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1040_hurricane_2023&showErrors=false&email= | Saildrone | sd1040_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1041_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1041_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1041_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1041 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1041_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1041_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1041_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1041_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1041_hurricane_2023&showErrors=false&email= | Saildrone | sd1041_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1045_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1045_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1045_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1045 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntrajectory (Trajectory/Drone ID)\ntime (seconds since 1970-01-01T00:00:00Z)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1045_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1045_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1045_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1045_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1045_hurricane_2023&showErrors=false&email= | Saildrone | sd1045_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1057_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1057_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1057_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1057 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntrajectory (Trajectory/Drone ID)\ntime (seconds since 1970-01-01T00:00:00Z)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1057_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1057_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1057_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1057_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1057_hurricane_2023&showErrors=false&email= | Saildrone | sd1057_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1064_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1064_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1064_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1064 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntrajectory (Trajectory/Drone ID)\ntime (seconds since 1970-01-01T00:00:00Z)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1064_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1064_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1064_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1064_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1064_hurricane_2023&showErrors=false&email= | Saildrone | sd1064_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1065_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1065_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1065_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1065 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1065_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1065_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1065_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1065_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1065_hurricane_2023&showErrors=false&email= | Saildrone | sd1065_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1068_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1068_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1068_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1068 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1068_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1068_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1068_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1068_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1068_hurricane_2023&showErrors=false&email= | Saildrone | sd1068_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1069_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1069_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1069_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1069 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntime (seconds since 1970-01-01T00:00:00Z)\ntrajectory (Trajectory/Drone ID)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1069_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1069_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1069_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1069_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1069_hurricane_2023&showErrors=false&email= | Saildrone | sd1069_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1083_hurricane_2023.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1083_hurricane_2023 | https://data.pmel.noaa.gov/generic/erddap/tabledap/sd1083_hurricane_2023.graph | Saildrone Atlantic 2023 Hurricane Monitoring Surface Data, drone 1083 | Using Uncrewed Surface Vehicles (USV) to observe air-sea interaction associated with Tropical Cyclones (TC), which is critical to TC intensification.\n\ncdm_data_type = Trajectory\nVARIABLES:\nlatitude (degrees_north)\nlongitude (degrees_east)\ntrajectory (Trajectory/Drone ID)\ntime (seconds since 1970-01-01T00:00:00Z)\nWIND_FROM_MEAN (Wind from, degree)\nWIND_SPEED_MEAN (Wind speed, m s-1)\nTEMP_AIR_MEAN (Air temperature, degree_C)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nWAVE_DOMINANT_PERIOD (s)\nWAVE_SIGNIFICANT_HEIGHT (m)\nTEMP_SBE37_MEAN (Seawater temperature, degree_C)\nSAL_SBE37_MEAN (Seawater salinity, 1)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/sd1083_hurricane_2023_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/sd1083_hurricane_2023_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/sd1083_hurricane_2023/index.htmlTable | https://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/sd1083_hurricane_2023.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=sd1083_hurricane_2023&showErrors=false&email= | Saildrone | sd1083_hurricane_2023 | |||
| https://data.pmel.noaa.gov/generic/erddap/tabledap/saildrone_gts.subset | https://data.pmel.noaa.gov/generic/erddap/tabledap/saildrone_gts | https://data.pmel.noaa.gov/generic/erddap/tabledap/saildrone_gts.graph | Saildrone data for GTS | Saildrone Network Common Data Format (NetCDF) format.\n\ncdm_data_type = Trajectory\nVARIABLES:\nwmo_platform_code\ntrajectory (Trajectory/Drone ID)\nlatitude (degrees_north)\ntime (seconds since 1970-01-01T00:00:00Z)\nRH_MEAN (Relative humidity, percent)\nBARO_PRES_MEAN (Air pressure, hPa)\nTEMP_AIR_MEAN (Air temperature, degrees_c)\nTEMP_CTD_MEAN (Seawater temperature, degrees_c)\nlongitude (degrees_east)\n | https://data.pmel.noaa.gov/generic/erddap/metadata/fgdc/xml/saildrone_gts_fgdc.xml | https://data.pmel.noaa.gov/generic/erddap/metadata/iso19115/xml/saildrone_gts_iso19115.xml | https://data.pmel.noaa.gov/generic/erddap/info/saildrone_gts/index.htmlTable | http://saildrone.com/
| https://data.pmel.noaa.gov/generic/erddap/rss/saildrone_gts.rss | https://data.pmel.noaa.gov/generic/erddap/subscriptions/add.html?datasetID=saildrone_gts&showErrors=false&email= | SAILDRONE | saildrone_gts |