sylvia-20200903T1327-profile-sci-rt
eng
UTF8
dataset
service
John Kerfoot
Rutgers University - DMCS
+1 848-932-3344
71 Dudley Road
New Brunswick
NJ
08901
USA
kerfoot@marine.rutgers.edu
pointOfContact
2024-03-27
ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
4
column
row
vertical
temporal
sylvia-20200903T1327 Real-Time Science Profile
2020-09-28
creation
2020-09-28
issued
slocum-data.marine.rutgers.edu
sylvia-20200903T1327-profile-sci-rt
John Kerfoot
Virginia Institute of Marine Science - William & Mary
kerfoot@marine.rutgers.edu
https://www.udel.edu/academics/colleges/ceoe/,https://rucool.marine.rutgers.edu
information
web browser
Background Information
Background information from the source
information
originator
Donglai Gong,Travis Miles,Haixing Wang,Laur Ferris,Nicole Waite,David Aragon,John Kerfoot
contributor
This project supports the deployment and realtime data delivery of autonomous underwater gliders in the coastal ocean to better resolve and understand essential ocean features and processes that contribute to hurricane intensification or weakening prior to making landfall. This is a partnership between NOAA Ocean and Atmospheric Research (OAR) through the Atlantic Oceanographic and Meteorological Laboratory (AOML) and Integrated Ocean Observing System (IOOS) regional associations such as MARACOOS, SECOORA, CariCOOS and institutions including the University of Puerto Rico, University of the Virgin Islands, Skidaway Institute of Oceanography, University of Delaware, Virginia Institute of Marine Science - William & Mary, and Rutgers University. The goal of the project is to provide realtime data for ocean model validation and assimilation throughout hurricane season. This project is supported by the Disaster Recovery Act. The glider will transect offshore to the shelf break in-between Norfolk and Washington Canyon. The glider will repeat this cross-shelf transect for the first half of the deployment. For the second half of the deployment, glider sylvia will work in concert with glider amelia to complete the triangle pattern between Norfolk Canyon and Washington Canyon.
John Kerfoot
Virginia Institute of Marine Science - William & Mary
kerfoot@marine.rutgers.edu
https://www.udel.edu/academics/colleges/ceoe/,https://rucool.marine.rutgers.edu
information
web browser
Background Information
Background information from the source
information
pointOfContact
cdom
conductivity
crs
density
platform
pressure
salinity
sylvia
sylvia-20200903T1327
temperature
trajectory
u
v
theme
Sustained Underwater Glider Observations for Improving Atlantic Tropical Cyclone Intensity Forecast
project
time
latitude
longitude
depth
sea_water_pressure
latitude
longitude
time
sea_water_pressure
eastward_sea_water_velocity
northward_sea_water_velocity
sea_floor_depth_below_sea_surface
theme
CF Standard Name Table v27
This data may be redistributed and used without restriction. Data provided as is with no expressed or implied assurance of quality assurance or quality control
Sustained Underwater Glider Observations for Improving Atlantic Tropical Cyclone Intensity Forecast
largerWorkCitation
project
Unidata Common Data Model
Profile
largerWorkCitation
project
eng
geoscientificInformation
1
-75.37093
-74.48382
36.493164
37.488323
seconds
2020-09-03T13:27:07Z
2020-09-28T16:01:29Z
-186.2435
-0.0
sylvia-20200903T1327 Real-Time Science Profile
2020-09-28
creation
2020-09-28
issued
John Kerfoot
Virginia Institute of Marine Science - William & Mary
kerfoot@marine.rutgers.edu
https://www.udel.edu/academics/colleges/ceoe/,https://rucool.marine.rutgers.edu
information
web browser
Background Information
Background information from the source
information
originator
Donglai Gong,Travis Miles,Haixing Wang,Laur Ferris,Nicole Waite,David Aragon,John Kerfoot
contributor
This project supports the deployment and realtime data delivery of autonomous underwater gliders in the coastal ocean to better resolve and understand essential ocean features and processes that contribute to hurricane intensification or weakening prior to making landfall. This is a partnership between NOAA Ocean and Atmospheric Research (OAR) through the Atlantic Oceanographic and Meteorological Laboratory (AOML) and Integrated Ocean Observing System (IOOS) regional associations such as MARACOOS, SECOORA, CariCOOS and institutions including the University of Puerto Rico, University of the Virgin Islands, Skidaway Institute of Oceanography, University of Delaware, Virginia Institute of Marine Science - William & Mary, and Rutgers University. The goal of the project is to provide realtime data for ocean model validation and assimilation throughout hurricane season. This project is supported by the Disaster Recovery Act. The glider will transect offshore to the shelf break in-between Norfolk and Washington Canyon. The glider will repeat this cross-shelf transect for the first half of the deployment. For the second half of the deployment, glider sylvia will work in concert with glider amelia to complete the triangle pattern between Norfolk Canyon and Washington Canyon.
ERDDAP tabledap
1
-75.37093
-74.48382
36.493164
37.488323
seconds
2020-09-03T13:27:07Z
2020-09-28T16:01:29Z
-186.2435
-0.0
tight
ERDDAPtabledapDatasetQueryAndAccess
https://slocum-data.marine.rutgers.edu/erddap/tabledap/sylvia-20200903T1327-profile-sci-rt
ERDDAP:tabledap
ERDDAP-tabledap
ERDDAP's tabledap service (a flavor of OPeNDAP) for tabular (sequence) data. Add different extensions (e.g., .html, .graph, .das, .dds) to the base URL for different purposes.
download
sylvia-20200903T1327 Real-Time Science Profile
2020-09-28
creation
2020-09-28
issued
John Kerfoot
Virginia Institute of Marine Science - William & Mary
kerfoot@marine.rutgers.edu
https://www.udel.edu/academics/colleges/ceoe/,https://rucool.marine.rutgers.edu
information
web browser
Background Information
Background information from the source
information
originator
Donglai Gong,Travis Miles,Haixing Wang,Laur Ferris,Nicole Waite,David Aragon,John Kerfoot
contributor
This project supports the deployment and realtime data delivery of autonomous underwater gliders in the coastal ocean to better resolve and understand essential ocean features and processes that contribute to hurricane intensification or weakening prior to making landfall. This is a partnership between NOAA Ocean and Atmospheric Research (OAR) through the Atlantic Oceanographic and Meteorological Laboratory (AOML) and Integrated Ocean Observing System (IOOS) regional associations such as MARACOOS, SECOORA, CariCOOS and institutions including the University of Puerto Rico, University of the Virgin Islands, Skidaway Institute of Oceanography, University of Delaware, Virginia Institute of Marine Science - William & Mary, and Rutgers University. The goal of the project is to provide realtime data for ocean model validation and assimilation throughout hurricane season. This project is supported by the Disaster Recovery Act. The glider will transect offshore to the shelf break in-between Norfolk and Washington Canyon. The glider will repeat this cross-shelf transect for the first half of the deployment. For the second half of the deployment, glider sylvia will work in concert with glider amelia to complete the triangle pattern between Norfolk Canyon and Washington Canyon.
OPeNDAP
1
-75.37093
-74.48382
36.493164
37.488323
seconds
2020-09-03T13:27:07Z
2020-09-28T16:01:29Z
-186.2435
-0.0
tight
OPeNDAPDatasetQueryAndAccess
https://slocum-data.marine.rutgers.edu/erddap/tabledap/sylvia-20200903T1327-profile-sci-rt
OPeNDAP:OPeNDAP
OPeNDAP
An OPeNDAP service for tabular (sequence) data. Add different extensions (e.g., .html, .das, .dds) to the base URL for different purposes.
download
sylvia-20200903T1327 Real-Time Science Profile
2020-09-28
creation
2020-09-28
issued
John Kerfoot
Virginia Institute of Marine Science - William & Mary
kerfoot@marine.rutgers.edu
https://www.udel.edu/academics/colleges/ceoe/,https://rucool.marine.rutgers.edu
information
web browser
Background Information
Background information from the source
information
originator
Donglai Gong,Travis Miles,Haixing Wang,Laur Ferris,Nicole Waite,David Aragon,John Kerfoot
contributor
This project supports the deployment and realtime data delivery of autonomous underwater gliders in the coastal ocean to better resolve and understand essential ocean features and processes that contribute to hurricane intensification or weakening prior to making landfall. This is a partnership between NOAA Ocean and Atmospheric Research (OAR) through the Atlantic Oceanographic and Meteorological Laboratory (AOML) and Integrated Ocean Observing System (IOOS) regional associations such as MARACOOS, SECOORA, CariCOOS and institutions including the University of Puerto Rico, University of the Virgin Islands, Skidaway Institute of Oceanography, University of Delaware, Virginia Institute of Marine Science - William & Mary, and Rutgers University. The goal of the project is to provide realtime data for ocean model validation and assimilation throughout hurricane season. This project is supported by the Disaster Recovery Act. The glider will transect offshore to the shelf break in-between Norfolk and Washington Canyon. The glider will repeat this cross-shelf transect for the first half of the deployment. For the second half of the deployment, glider sylvia will work in concert with glider amelia to complete the triangle pattern between Norfolk Canyon and Washington Canyon.
ERDDAP Subset
1
-75.37093
-74.48382
36.493164
37.488323
seconds
2020-09-03T13:27:07Z
2020-09-28T16:01:29Z
-186.2435
-0.0
tight
ERDDAP_Subset
https://slocum-data.marine.rutgers.edu/erddap/tabledap/sylvia-20200903T1327-profile-sci-rt.subset
search
Subset
Web page to facilitate selecting subsets of the dataset
download
physicalMeasurement
time
double
Timestamp
trajectory
String
Trajectory/Deployment Name
source_file
String
Source data file
beam_c
float
Sci Lisst Beamc
beta_700nm
float
beta_700nm
cdom
float
cdom
chlorophyll_a
float
Chlorophyll a
conductivity
float
conductivity
crs
int
http://www.opengis.net/def/crs/EPSG/0/4326
ctd41cp_timestamp
double
CTD41cp Timestamp
density
float
density
instrument_ctd
int
Conductivity, Temperature, Depth (CTD) Sensor
instrument_flbbcdslc
int
ECO Triplet Puck
m_pitch
float
M Pitch
m_roll
float
M Roll
m_science_clothesline_lag
float
m_science_clothesline_lag
oxygen_concentration
float
oxygen_concentration
oxygen_saturation
float
Oxygen Saturation
platform
int
Slocum Glider sylvia
potential_temperature
float
potential_temperature
pressure
float
CTD Pressure
profile_id
int
Profile ID
profile_lat
double
Profile Center Latitude
profile_lon
double
Profile Center Longitude
profile_time
double
Profile Center Time
salinity
float
salinity
sci_bsipar_par
float
sci_bsipar_par
sci_lisst_meansize
float
sci_lisst_meansize
sci_lisst_totvol
float
sci_lisst_totvol
sci_m_present_secs_into_mission
float
sci_m_present_secs_into_mission
sci_m_present_time
double
Sci M Present Time
sci_water_pressure
float
CTD Pressure
sound_speed
float
sound_speed
temperature
float
temperature
u
float
Eastward Depth-Averaged Current
v
float
Northward Depth-Averaged Current
water_depth
float
m_water_depth
John Kerfoot
Rutgers University - DMCS
+1 848-932-3344
71 Dudley Road
New Brunswick
NJ
08901
USA
kerfoot@marine.rutgers.edu
distributor
OPeNDAP
DAP/2.0
https://slocum-data.marine.rutgers.edu/erddap/tabledap/sylvia-20200903T1327-profile-sci-rt.html
order
Data Subset Form
ERDDAP's version of the OPeNDAP .html web page for this dataset. Specify a subset of the dataset and download the data via OPeNDAP or in many different file types.
download
https://slocum-data.marine.rutgers.edu/erddap/tabledap/sylvia-20200903T1327-profile-sci-rt.graph
order
Make-A-Graph Form
ERDDAP's Make-A-Graph .html web page for this dataset. Create an image with a map or graph of a subset of the data.
mapDigital
dataset
2020-09-28T16:35:16Z: /tmp/tmpw0ou8tei/sylvia_20200928T154926Z_sbdu37bp9eq.nc created
2020-09-28T16:35:16Z: /home/kerfoot/code/glider-proc/scripts/proc_deployment_profiles_to_nc.py /home/coolgroup/slocum/deployments/2020/sylvia-20200903T1327/data/in/ascii/sbd/sylvia_2020_264_0_127_sbd.dat
This record was created from dataset metadata by ERDDAP Version 2.22