NOAA ERDDAP
Easier access to scientific data

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 Email Institution Dataset ID
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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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/ (external link) 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

 
ERDDAP, Version 2.18
Disclaimers | Privacy Policy | Contact