* The List of All Active Datasets in this ERDDAP *

Summary:
This dataset is a table which has a row of information for each dataset currently active in this ERDDAP.

cdm_data_type = Other
VARIABLES:
datasetID (Dataset ID)
accessible
institution
dataStructure (Data Structure)
cdm_data_type (Common Data Model Type)
class (ERDDAP Class)
title
minLongitude (Minimum Longitude, degrees_east)
maxLongitude (Maximum Longitude, degrees_east)
longitudeSpacing (Average Grid Longitude Spacing, degrees_east)
minLatitude (Minimum Latitude, degrees_north)
maxLatitude (Maximum Latitude, degrees_north)
latitudeSpacing (Average Grid Latitude Spacing, degrees_north)
minAltitude (Minimum Altitude (or negative Depth), m)
maxAltitude (Maximum Altitude (or negative Depth), m)
minTime (Minimum Time, seconds since 1970-01-01T00:00:00Z)
maxTime (Maximum Time, seconds since 1970-01-01T00:00:00Z)
timeSpacing (Average Grid Time Spacing, seconds)
griddap (Base URL of OPeNDAP Grid Service)
subset (URL of Subset Web Page)
tabledap (Base URL of OPeNDAP Table/Sequence Service)
MakeAGraph (URL of Make-A-Graph Web Page)
sos (Base URL of SOS Service)
wcs (Base URL of WCS Service)
wms (Base URL of WMS Service)
files (Base URL of "files" Service)
... (10 more variables)


2000-2015 climatology of the Subtropical Mode Waters and Permanent Pycnocline properties in the World Ocean

Summary:
Maps of properties from OAC-P estimates. Thermohaline computing using gsw oceanographic toolbox

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
GLOBAL_PPD (Permanent pycnocline depth, m)
GLOBAL_PPD_er (Error of the permanent pycnocline depth estimate, m)
GLOBAL_PPH (Permanent pycnocline total thickness, m)
GLOBAL_PPH_er (Error of the permanent pycnocline total thickness estimate, m)
GLOBAL_PPHTOP (Permanent pycnocline top thickness, m)
GLOBAL_PPHTOP_er (Error of the permanent pycnocline top thickness estimate)
GLOBAL_PPHBTO (Permanent pycnocline bottom thickness, m)
GLOBAL_PPHBTO_er (Error of the permanent pycnocline bottom thickness estimate, m)
GLOBAL_PPTEMP (Temperature at the depth of the permanent pycnocline, deg C)
GLOBAL_PPPOTTEMP (Potential temperature at the depth of the permanent pycnocline (referenced to the surface), deg C)
GLOBAL_PPCONSTEMP (Conservative temperature at the depth of the permanent pycnocline, deg C)
GLOBAL_PPPSAL (Practical salinity at the depth of the permanent pycnocline, PSU)
GLOBAL_PPABSAL (Absolute  salinity at the depth of the permanent pycnocline, g/kg)
GLOBAL_PPSIG0 (Potential density referenced to the surface at the depth of the permanent pycnocline)
GLOBAL_PPPLPV (Planetary potential vorticity at the depth of the permanent pycnocline, m^-1 s^-1)
GLOBAL_PPBFRQ (Brunt-Vaisala frequency squared at the depth of the permanent pycnocline, s^-2)
GLOBAL_MWD (Mode water depth, m)
GLOBAL_MWH (Mode water thickness, m)
GLOBAL_MWTEMP (Temperature at the depth of the mode water, deg C)
GLOBAL_MWPOTTEMP (Potential temperature at the depth of the mode water (referenced to the surface), deg C)
GLOBAL_MWCONSTEMP (Conservative temperature at the depth of the mode water, deg C)
GLOBAL_MWPSAL (Practical salinity at the depth of the mode water, PSU)
GLOBAL_MWABSAL (Absolute salinity at the depth of the mode water, g/kg)
GLOBAL_MWSIG0 (Potential density referenced to the surface at the depth of the mode water)
GLOBAL_MWPLPV (Planetary potential vorticity at the depth of the mode water, m^-1 s^-1)
GLOBAL_MWBFRQ (Brunt-Vaisala frequency squared at the depth of the mode water, s^-2)


Argo Float Measurements

Summary:
Argo float vertical profiles from Coriolis Global Data Assembly Centres
(GDAC). Argo is an international collaboration that collects high-quality
temperature and salinity profiles from the upper 2000m of the ice-free
global ocean and currents from intermediate depths. The data come from
battery-powered autonomous floats that spend most of their life drifting
at depth where they are stabilised by being neutrally buoyant at the
"parking depth" pressure by having a density equal to the ambient pressure
and a compressibility that is less than that of sea water. At present there
are several models of profiling float used in Argo. All work in a similar
fashion but differ somewhat in their design characteristics. At typically
10-day intervals, the floats pump fluid into an external bladder and rise
to the surface over about 6 hours while measuring temperature and salinity.
Satellites or GPS determine the position of the floats when they surface,
and the floats transmit their data to the satellites. The bladder then
deflates and the float returns to its original density and sinks to drift
until the cycle is repeated. Floats are designed to make about 150 such
cycles.
Data Management URL: http://www.argodatamgt.org/Documentation

cdm_data_type = TrajectoryProfile
VARIABLES:
fileNumber (File Number)
data_type
format_version (File format version)
handbook_version (Data handbook version)
reference_date_time (Date of reference for Julian days, seconds since 1970-01-01T00:00:00Z)
date_creation (Date of file creation, seconds since 1970-01-01T00:00:00Z)
date_update (Date of update of this file, seconds since 1970-01-01T00:00:00Z)
platform_number (Float unique identifier)
project_name (Name of the project)
pi_name (Name of the principal investigator)
... (49 more variables)


Summary:
Argo float synthetic vertical profiles : BGC data

cdm_data_type = TrajectoryProfile
VARIABLES:
wmo_inst_type (Coded instrument type)
data_type
date_update (Date of update of this file, seconds since 1970-01-01T00:00:00Z)
pi_name (Name of the principal investigator)
bbp470 (Particle backscattering at 470 nanometers, m-1)
bbp470_qc (quality flag)
bbp470_adjusted (Particle backscattering at 470 nanometers, m-1)
bbp470_adjusted_qc (quality flag)
bbp470_adjusted_error (Contains the error on the adjusted values as determined by the delayed mode QC process, m-1)
bbp532 (Particle backscattering at 532 nanometers, m-1)
bbp532_qc
bbp532_adjusted
bbp532_adjusted_qc
bbp532_adjusted_error
bbp700 (Particle backscattering at 700 nanometers, m-1)
bbp700_qc (quality flag)
bbp700_adjusted (Particle backscattering at 700 nanometers, m-1)
bbp700_adjusted_qc (quality flag)
bbp700_adjusted_error (Contains the error on the adjusted values as determined by the delayed mode QC process, m-1)
bbp700_2 (Particle backscattering at 700 nanometers, m-1)
bbp700_2_qc
bbp700_2_adjusted
bbp700_2_adjusted_qc
bbp700_2_adjusted_error
bisulfide (micromole/kg)
bisulfide_qc
bisulfide_adjusted
... (168 more variables)


Argo Reference Measurements

Summary:
Argo float vertical profiles to be used in DMQC. The free-moving nature of profiling floats means that most float measurements are without accompanying in-situ ground truth values for absolute calibration (such as those afforded by shipboard CTD measurements). Therefore Argo delayed-mode procedures for checking sensor drifts and offsets in salinity rely on reference datasets and statistical methods. Dataset assembled by John Gilson (SCRIPPS)

cdm_data_type = Other
VARIABLES:
latitude (degrees_north)
longitude (degrees_east)
platform_number
cycle_number
pi_name
time (seconds since 1970-01-01T00:00:00Z)
pres (Pressure)
temp (Temperature)
ptmp
psal
n_levels
n_prof


ArgoFloats index

Summary:
Argo detailed index. Gathers data available at ftp://ftp.ifremer.fr/ifremer/argo/ar_index_global_prof.txt

cdm_data_type = Other
VARIABLES:
file
date (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
ocean
profiler_type
institution
date_update (Date of update, seconds since 1970-01-01T00:00:00Z)


CTD Reference Measurements

Summary:
Conductivity, Temperature, Depth (CTD) Reference Measurements. Argo data from a local source.

cdm_data_type = Other
VARIABLES:
pres (Pressure)
ptmp
psal
temp (Temperature)
source
qclevel
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)


Daily MUR SST, Final product

Summary:
A merged, multi-sensor L4 Foundation Sea Surface Temperature (SST) analysis product from Jet Propulsion Laboratory (JPL).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, kelvin)


EMSO Ligure DYFAMED Time Series from 1994 to 2014 (43°25N, 7°52E)

Summary:
EMSO Ligure DYFAMED Time Series from 1994 to 2014 (43°25N - 7°52E). In the framework of the French MOOSE program, a fixed point observatory in the Ligurian Sea (so called DYFAMED) performs since 1991 physical, biogeochemical and biological observations of the water column structure. This observatory is hosted and managed by the Oceanological Observatory in Villefranche-sur-Mer (CNRS-SU)

cdm_data_type = Profile
VARIABLES (all of which use the dimensions [time][PRES]):
TEMP (Sea temperature in-situ ITS-90 scale, degree_Celsius)
PSAL (Practical salinity, PSU)
DOXY (Dissolved oxygen, micromole/kg)
TEMP_QC (quality flag for TEMP)
PSAL_QC (quality flag for PSAL)
DOXY_QC (quality flag for DOXY)


Global Drifter Program - 1 Hour Interpolated QC Drifter Data

Summary:
Global Drifter Program hourly drifting buoy collection. Quality control interpolated (interpolation via mathematical model fitting) data. Hourly Drifter data product exists from early 2000's to present, well suited for observing smaller-scale oceanic processes. NOAA-Atlantic Oceanographic & Meteorological Laboratory (AOML) data from a local source. The hourly QC dataset is updated on a quarterly basis, i.e. every 3 months, in delayed mode, but the data processing team has experienced unforeseen setbacks. The GDP is working as quickly as possible to update the dataset. Please reference the acknowledgment attribute to cite the dataset's DOI.

cdm_data_type = Trajectory
VARIABLES:
ID (Global Drifter Program Buoy ID)
WMO (World Meteorological Organization buoy identification number)
expno (Experiment number, count)
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
lon360 (Longitude, degrees_east)
sst (fitted sea water temperature, Kelvin)
sst1 (fitted non-diurnal sea water temperature, Kelvin)
sst2 (fitted diurnal sea water temperature, Kelvin)
err_sst (standard uncertainty of fitted sea water temperature, Kelvin)
err_sst1 (standard uncertainty of fitted non-diurnal sea water temperature, Kelvin)
err_sst2 (standard uncertainty of fitted diurnal sea water temperature, Kelvin)
flg_sst (fitted sea water temperature quality flag, dimensionless)
flg_sst1 (fitted non-diurnal sea water temperature quality flag, dimensionless)
flg_sst2 (fitted diurnal sea water temperature quality flag, dimensionless)
ve (Eastward velocity, m/s)
vn (Northward velocity, m/s)
err_lat (95% confidence interval in latitude, degrees_north)
err_lon (95% confidence interval in longitude, degrees_east)
err_ve (95% confidence interval in eastward velocity, m/s)
... (33 more variables)

NOAA Atlantic Oceanographic and Meteorological Laboratory


Global Drifter Program - 6 Hour Interpolated QC Drifter Data

Summary:
Global Drifter Program 6-hourly drifting buoy collection. Quality control krigged (interpolation method) data. 6-Hour Drifter data product exists from 1979 to present, well suited for observing larger-scale oceanic processes. NOAA-Atlantic Oceanographic & Meteorological Laboratory (AOML) data from a local source. The six-hourly QC dataset is updated on a quarterly basis, i.e. every 3 months, in delayed mode. Please reference the acknowledgment attribute to cite the dataset's DOI.

cdm_data_type = Trajectory
VARIABLES:
ID (Global Drifter Program Buoy ID)
WMO (World Meteorological Organization buoy identification number)
expno (Experiment number, count)
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
lon360 (Longitude, degrees_east)
sst (Sea Surface Bulk Temperature, degree_C)
err_sst (degree_C)
ve
vn
err_lat
err_lon
typebuoy (Buoy type (see https://www.aoml.noaa.gov/phod/dac/dirall.html))
deploy_date (Deployment date and time, seconds since 1970-01-01T00:00:00Z)
deploy_lat (Deployment latitude, degrees_north)
deploy_lon (Deployment longitude, degrees_east)
start_date (First good date and time derived by DAC quality control, seconds since 1970-01-01T00:00:00Z)
start_lat (First good latitude derived by DAC quality control, degrees_north)
start_lon (First good longitude derived by DAC quality control, degrees_east)
end_date (Last good date and time derived by DAC quality control, seconds since 1970-01-01T00:00:00Z)
end_lat (Last good latitude derived by DAC quality control, degrees_north)
end_lon (Last good longitude derived by DAC quality control, degrees_east)
... (23 more variables)


Global Ocean - In Situ Observation Copernicus

Summary:
The data set consists of maps of total velocity of the surface current averaged over a time interval of 1 hour around the cardinal hour. Surface ocean velocities estimated by High Frequency (HF) Radar are representative of the upper 0.3-2.5 meters of the ocean. The main objective of near real time processing is to produce the best product from available data at the time of processing. Total velocities are derived using least square fit that maps radial velocities measured from individual sites onto a cartesian grid. The final product is a map of the horizontal components of the ocean currents on a regular grid in the area of overlap of two or more radar stations.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
EWCT (West-east current component, m s-1)
NSCT (South-north current component, m s-1)
EWCS (Standard deviation of surface eastward sea water velocity, m s-1)
NSCS (Standard deviation of surface northward sea water velocity, m s-1)
CCOV (Covariance of surface sea water velocity, m2 s-2)
GDOP (Geometrical dilution of precision, 1)
POSITION_QC (Position quality flag, 1)
QCflag (Overall quality flag, 1)
VART_QC (Variance threshold quality flag, 1)
GDOP_QC (GDOP threshold quality flag, 1)
DDNS_QC (Data density threshold quality flag, 1)
CSPD_QC (Velocity threshold quality flag, 1)


Summary:
Surface ocean velocities estimated from High Frequency (HF)-Radar are representative of the upper 2.4 meters of the ocean.  The main objective of near-real time processing is to produce the best product from available data at the time of processing.  Radial velocity measurements are obtained from individual radar sites through the U.S. HF-Radar Network. Hourly radial data are processed by unweighted least squares on a 6km resolution grid of the Alaskan North Slope to produce near real-time surface current maps.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
EWCT (West-east current component, m s-1)
NSCT (South-north current component, m s-1)
EWCS (Standard deviation of surface eastward sea water velocity, m s-1)
NSCS (Standard deviation of surface northward sea water velocity, m s-1)
GDOP (Geometrical dilution of precision, 1)
POSITION_QC (Position quality flag, 1)
QCflag (Overall quality flag, 1)
VART_QC (Variance threshold quality flag, 1)
GDOP_QC (GDOP threshold quality flag, 1)
DDNS_QC (Data density threshold quality flag, 1)
CSPD_QC (Velocity threshold quality flag, 1)

UAF; ONC; CORDC - Coastal Observing Research and Development Center


Global Ocean, In Situ Observation Copernicus (Copernicus Fishing Observing System)

Summary:
Global Ocean - In Situ Observation Copernicus. The Recopesca Project : a new example of participative approach to collect fisheries and in situ environmental data

cdm_data_type = Profile
VARIABLES:
platform_name
latitude (Latitude of each location, degrees_north)
longitude (Longitude of each location, degrees_east)
time (seconds since 1970-01-01T00:00:00Z)
TIME_QC (Time quality flag)
DC_REFERENCE (Station/Location unique identifier in data centre)
DATA_MODE
DIRECTION (Direction of the profiles)
depth (m)
DEPH_QC (Depth quality flag)
TEMP (Sea temperature, degree_C)
TEMP_QC (Sea temperature quality flag)
PSAL (Practical salinity, 0.001)
PSAL_QC (Practical salinity quality flag)
OSAT (Oxygen saturation, %)
OSAT_QC
DOXY (Dissolved oxygen, mmol m-3)
DOXY_QC
TUR4 (Turbidity, 1)
TUR4_QC
FLUO (Fluorescence)
FLUO_QC


Numerical lagrangian data issued from river sources in Indonesia (2016-2020) - Ariane trajectories qualitative

Summary:
This file is the raw output of Ariane software.

cdm_data_type = Other
VARIABLES:
init_x (Initial position in i, No dimension)
init_y (Initial position in j, No dimension)
init_z (Initial position in k, No dimension)
init_t (Initial position in l (time), See global attributes...)
init_age (Initial age (time), seconds)
init_transp (Initial transport, m3/s)
final_x (Final position in x (or i), No dimension)
final_y (Final position in y (or j), No dimension)
final_z (Final position in z (or k), No dimension)
final_t (Final position in t (time), See global attributes...)
final_age (Final Age., seconds)
final_transp (Final transport, m3/s)


Numerical lagrangian data issued from river sources in Indonesia (2016-2020) - Coast status

Summary:
This file contains time series of simulated particle status with respect to their fate (stranding, out of domain, still at sea)

cdm_data_type = Other
VARIABLES:
ptc_id (particle ID)
river_index (Particle River Index)
d_covered_zone (Diagonal Of The Covered Zone, m)
ptc_distance (Particle Trajectory Distance, m)
time (Stranding Itime, seconds since 1970-01-01T00:00:00Z)
stranding_iT
stranding_jT
stranding_age (days)
stranding_zone


Numerical lagrangian data issued from river sources in Indonesia (2016-2020) - Histo coord

Summary:
This file contains time series of 2D-histogram of simulated particles (computed as the sum of particles per grid cell)

cdm_data_type = TimeSeries
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
hist (2D histogram of particles)
hist_release_time (2D histogram of particles)
hist_stop_coast (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_CISADANE (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_CILIWUNG (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_CITARUM (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_SEMARANG (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_SURABAYA (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_SOLO (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_TELUK_BENOA (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_JOGJA (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_PELABUHAN_RATU (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_BATANG_KANDIS (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_DELI (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_BATANG_HARI (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_MUSI (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_KAPUAS (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_BARITO (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_TALLO (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_MAHAKAM (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_KAYAN (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_AMBON (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_DIGUL (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))
hist_stop_coast_MAMBERAMO (2D histogram of particles (trajectory stop once below 0.0010 grid cell from coast))


Numerical lagrangian data issued from river sources in Indonesia (2016-2020) - Traj lonlat init t0

Summary:
This file contains trajectories of simulated particles in grid indices and lat/lon coordinates. The position remains unchanged once the particle is considered as stranded.

cdm_data_type = Trajectory
VARIABLES (all of which use the dimensions [frame][ntraj]):
traj_lon_init_t0 (Longitude of trajectory vs time since simu t0, degrees_east)
traj_lat_init_t0 (Latitude of trajectory vs time since simu t0, degrees_north)
traj_iU_init_t0 (longitude index of trajectory vs time since simu t0)
traj_jV_init_t0 (latitude index of trajectory vs time since simu t0)


OceanGliders GDAC trajectories

Summary:
OceanGliders GDAC trajectories

cdm_data_type = Trajectory
VARIABLES:
platform_deployment
time (Epoch time, seconds since 1970-01-01T00:00:00Z)
JULD (Julian 1950 time, seconds since 1970-01-01T00:00:00Z)
latitude (Measurement latitude, degrees_north)
longitude (Measurement longitude, degrees_east)
TIME_QC (Quality flag)
JULD_QC (Quality flag)
POSITION_QC (Quality flag)
PSAL (Practical salinity, PSU)
TEMP (Sea temperature in-situ ITS-90 scale, degree_Celsius)
CNDC (Electrical conductivity, mhos/m)
PRES (Sea water pressure, equals 0 at sea-level, decibar)
PSAL_QC (Quality flag)
TEMP_QC (Quality flag)
CNDC_QC (Quality flag)
PRES_QC (Quality flag)
PSAL_UNCERTAINTY (Uncertainty, PSU)
TEMP_UNCERTAINTY (Uncertainty, degree_Celsius)
CNDC_UNCERTAINTY (Uncertainty, mhos/m)
PRES_UNCERTAINTY (Uncertainty, decibar)
MOLAR_DOXY (Uncompensated (pressure and salinity) oxygen concentration reported by the oxygen sensor, micromole/l)
TEMP_DOXY (Sea temperature from oxygen sensor ITS-90 scale, degree_Celsius)
BPHASE_DOXY
DPHASE_DOXY
RPHASE_DOXY
MOLAR_DOXY_QC (Quality flag)
TEMP_DOXY_QC
... (19 more variables)


SDC Baltic Sea Aggregation V2

Summary:
Data from a local source.

cdm_data_type = Point
VARIABLES:
time (Obs Date, seconds since 1970-01-01T00:00:00Z)
station_id
platform
obs_date_qc
latitude (degrees_north)
longitude (degrees_east)
position_qc
depth (m)
depth_qc (Depth)
temp (Temperature)
temp_qc
psal
psal_qc
type (Data type)


SDC Black Sea Aggregation V2

Summary:
Data from a local source.

cdm_data_type = Point
VARIABLES:
time (Obs Date, seconds since 1970-01-01T00:00:00Z)
station_id
platform
obs_date_qc
latitude (degrees_north)
longitude (degrees_east)
position_qc
depth (m)
depth_qc (Depth)
temp (Temperature)
temp_qc
psal
psal_qc


SDC Global Ocean Aggregation V2


SDC Mediterranean Sea Aggregation V2


SDC North Atlantic Aggregation V2


SDC_BalticSea_Climatology_TS_V1_monthly

Summary:
The SDC_BAL_CLIM_TS_V1 product contains Temperature and Salinity Climatologies for Baltic Sea including the seasonal and monthly fields for period 1955-2014 and seasonal fields for 6 decades starting from 1955 to 2014. The climatic fields were computed from the integrated Baltic Sea dataset that combines data extracted from the 3 major sources: 1) SeaDataNet infrastructure, 2) World Ocean Database 2018, and 3) Coriolis Ocean Dataset for Reanalysis. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.3.1.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
ITS_90_water_temperature (sea water temperature, degree_C)
ITS_90_water_temperature_L1 (sea water temperature masked using relative error threshold 0.3, degree_C)
ITS_90_water_temperature_L2 (sea water temperature masked using relative error threshold 0.5, degree_C)
ITS_90_water_temperature_relerr (Relative error of sea water temperature, 1)
Water_body_salinity (sea water salinity, PSU)
Water_body_salinity_L1 (sea water salinity masked using relative error threshold 0.3, PSU)
Water_body_salinity_L2 (sea water salinity masked using relative error threshold 0.5, PSU)
Water_body_salinity_relerr (Relative error of sea water salinity, 1)


SDC_BalticSea_Climatology_TS_V1_seasonal


SDC_BalticSea_Climatology_TS_V2_monthly

Summary:
The SDC_BAL_CLIM_TS_V2 product contains Temperature and Salinity Climatologies for Baltic Sea including the seasonal and monthly fields for period 1955-2014 and seasonal fields for 6 decades starting from 1955 to 2014. The climatic fields were computed from the integrated Baltic Sea dataset that combines data extracted from the 3 major sources: 1) SeaDataNet infrastructure, 2) World Ocean Database 2018, and 3) Coriolis Ocean Dataset for Reanalysis. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.3.1.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
ITS_90_water_temperature (sea water temperature, 1e-3)
ITS_90_water_temperature_L1 (sea water temperature masked using relative error threshold 0.3, 1e-3)
ITS_90_water_temperature_L2 (sea water temperature masked using relative error threshold 0.5, 1e-3)
ITS_90_water_temperature_relerr (Relative error of sea water temperature, 1)
Water_body_salinity (sea water salinity, PSU)
Water_body_salinity_L1 (sea water salinity masked using relative error threshold 0.3, PSU)
Water_body_salinity_L2 (sea water salinity masked using relative error threshold 0.5, PSU)
Water_body_salinity_relerr (Relative error of sea water salinity, 1)


SDC_BalticSea_Climatology_TS_V2_seasonal


SDC_BlackSea_Climatology_TS_V1_monthly

Summary:
The SDC_BLS_CLIM_TS_V1 product contains Temperature and Salinity Climatologies for Black Sea including the seasonal and monthly fields for period 1955-2017 and seasonal fields for 6 decades starting from 1955 to 2014. The climatic fields were computed from the integrated Black Sea dataset that combines data extracted from the 3 major sources: 1) SeaDataNet infrastructure, 2) World Ocean Database 2018, and 3) Coriolis Ocean Dataset for Reanalysis. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.3.1.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
ITS_90_water_temperature (1e-3)
ITS_90_water_temperature_L1 (ITS-90 water temperature masked using relative error threshold 0.3, 1e-3)
ITS_90_water_temperature_L2 (ITS-90 water temperature masked using relative error threshold 0.5, 1e-3)
ITS_90_water_temperature_relerr (Relative error of ITS-90 water temperature, 1)
Water_body_salinity (1e-3)
Water_body_salinity_L1 (Water_body_salinity masked using relative error threshold 0.3, 1e-3)
Water_body_salinity_L2 (Water_body_salinity masked using relative error threshold 0.5, 1e-3)
Water_body_salinity_relerr (Relative error of Water_body_salinity, 1)


SDC_BlackSea_Climatology_TS_V1_seasonal


SDC_BlackSea_Climatology_TS_V2_monthly

Summary:
The SDC_BLS_CLIM_TS_V2 product contains Temperature and Salinity Climatologies for Black Sea
        including the seasonal and monthly fields for period 1955-2019 and 2 subperiods, and the annual and seasonal fields
        for 6 decades starting from 1955 to 2019.  The climatic fields were computed from the integrated Black Sea
        dataset that combines data extracted from the 3 major sources:
        1) SeaDataNet infrastructure, 2) World Ocean Database, and 3) Coriolis Ocean Dataset for Reanalysis.
        The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.6.4.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (ITS-90 water temperature, 1e-3)
Temperature_L1 (ITS-90 water temperature masked using relative error threshold 0.3, 1e-3)
Temperature_L2 (ITS-90 water temperature masked using relative error threshold 0.5, 1e-3)
Temperature_relerr (Relative error of ITS-90 water temperature, 1)
Salinity (Water_body_salinity, 1e-3)
Salinity_L1 (Water_body_salinity masked using relative error threshold 0.3, 1e-3)
Salinity_L2 (Water_body_salinity masked using relative error threshold 0.5, 1e-3)
Salinity_relerr (Relative error of Water_body_salinity, 1)


SDC_BlackSea_Climatology_TS_V2_seasonal


SDC_BlackSea_Collection_TS_V1

Summary:
Ocean Data View (ODV) Network Common Data Format (NetCDF) Export File V2.0. Data from a local source.

cdm_data_type = Profile
VARIABLES:
time (Decimal Gregorian Days of the station, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Cruise
Data_set_name
Discipline
Category
Variables_measured
Data_format
Data_format_version
Data_size
Data_set_creation_date
Datum
Measuring_area_type
Station
Water_depth (m)
Depth_reference
Minimum_instrument_depth (m)
Maximum_instrument_depth (m)
Start_date
Start_time
End_date
End_time
Vertical_resolution
Vertical_resolution_unit
Type
... (37 more variables)


SDC_GlobalOcean_Climatology_TS_V1_1

Summary:
SDC_GLO_CLIM_T_1900-2017_025_January_V1_1 product contains Temperature Climatologies for Global Ocean for period 1900-2017. The climatic fields were computed from World Ocean Database 2013 data set. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis), version 2.3.1

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (sea water temperature, degree_C)
Temperature_L1 (sea water temperature masked using relative error threshold 0.3, degree_C)
Temperature_L2 (sea water temperature masked using relative error threshold 0.5, degree_C)
Temperature_relerr (Relative error of sea water temperature, 1)
Salinity (sea water salinity, PSU)
Salinity_L1 (sea water salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (sea water salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of sea water salinity, 1)


SDC_GlobalOcean_Climatology_TS_V1_2

Summary:
SDC_GLO_CLIM_T_2003-2017_025_January_V1_2 product contains Temperature Climatologies for Global Ocean for period 2003-2017. The climatic fields were computed from World Ocean Database 2013 data set. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis), version 2.3.1

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (sea water temperature, degree_C)
Temperature_L1 (sea water temperature masked using relative error threshold 0.3, degree_C)
Temperature_L2 (sea water temperature masked using relative error threshold 0.5, degree_C)
Temperature_relerr (Relative error of sea water temperature, 1)
Salinity (sea water salinity, PSU)
Salinity_L1 (sea water salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (sea water salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of sea water salinity, 1)


SDC_GlobalOcean_Climatology_TS_V2_1

Summary:
SDC_GLO_CLIM_T_1900-2017_025_V2_1 product contains Temperature Climatologies for Global Ocean for period 1900-2017. The climatic fields were computed from World Ocean Database 2013 data set. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis), version 2.3.1

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (sea water temperature, degree_C)
Temperature_L1 (sea water temperature masked using relative error threshold 0.3, degree_C)
Temperature_L2 (sea water temperature masked using relative error threshold 0.5, degree_C)
Temperature_relerr (Relative error of sea water temperature, 1)
Salinity (sea water salinity, PSU)
Salinity_L1 (sea water salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (sea water salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of sea water salinity, 1)


SDC_GlobalOcean_Climatology_TS_V2_2

Summary:
SDC_GLO_CLIM_T_2003-2017_025_V2_2 product contains Temperature Climatologies for Global Ocean for period 2003-2017. The climatic fields were computed from World Ocean Database 2013 data set. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis), version 2.3.1

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (sea water temperature, degree_C)
Temperature_L1 (sea water temperature masked using relative error threshold 0.3, degree_C)
Temperature_L2 (sea water temperature masked using relative error threshold 0.5, degree_C)
Temperature_relerr (Relative error of sea water temperature, 1)
Salinity (sea water salinity, PSU)
Salinity_L1 (sea water salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (sea water salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of sea water salinity, 1)


SDC_MedSea_Climatology_TS_V1_monthly

Summary:
SDC_MED_CLIM_TS_V1 product contains Temperature and Salinity climatological fields for the Mediterranean Sea computed from SeaDataNet infrastructure and CORA (Coriolis Ocean dataset for ReAnalysis) integrated dataset. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions) version 2.4.0

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (ITS-90 water temperature, degree_C)
Temperature_L1 (ITS-90 water temperature masked using relative error threshold 0.3, degree_C)
Temperature_L2 (ITS-90 water temperature masked using relative error threshold 0.5, degree_C)
Temperature_relerr (Relative error of ITS-90 water temperature, 1)
Salinity (Water body salinity, PSU)
Salinity_L1 (Water body salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (Water body salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of Water body salinity, 1)


SDC_MedSea_Climatology_TS_V1_seasonal


SDC_MedSea_Climatology_TS_V2_monthly_pre_post_east_mediterranean_transient

Summary:
SDC_MED_CLIM_TS_V2 product contains Temperature and Salinity climatological fields for the Mediterranean Sea computed from SeaDataNet infrastructure and CORA (Coriolis Ocean dataset for ReAnalysis) integrated dataset. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions) version 2.4.0

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (Sea Water In Situ Temperature, degree_C)
Temperature_L1 (Sea Water In Situ Temperature masked using relative error threshold 0.3, degree_C)
Temperature_L2 (Sea Water In Situ Temperature masked using relative error threshold 0.5, degree_C)
Temperature_relerr (Relative error of Sea Water In Situ Temperature, 1)
Salinity (Water body salinity, PSU)
Salinity_L1 (Water body salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (Water body salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of Water body salinity, PSU)


SDC_MedSea_Climatology_TS_V2_monthly_whole_period


SDC_MedSea_Climatology_TS_V2_seasonal_decades

Summary:
SDC_MED_CLIM_TS_V2 product contains Temperature and Salinity climatological fields for the Mediterranean Sea computed from SeaDataNet infrastructure and CORA (Coriolis Ocean dataset for ReAnalysis) integrated dataset. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions) version 2.4.0

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (ITS-90 water temperature)
Temperature_L1 (ITS-90 water temperature masked using relative error threshold 0.3)
Temperature_L2 (ITS-90 water temperature masked using relative error threshold 0.5)
Temperature_relerr (Relative error of ITS-90 water temperature)
Salinity (Water body salinity, PSU)
Salinity_L1 (Water body salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (Water body salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of Water body salinity, PSU)


SDC_MedSea_Climatology_TS_V2_seasonal_pre_post_emt


SDC_MedSea_Climatology_TS_V2_seasonal_whole_period


Summary:
The SDC_NAT_CLIM_TS_V1 product contains Temperature and Salinity Climatologies for the North Atlantic Ocean including the seasonal and monthly fields for period 1955-2015 and seasonal fields for 6 decades starting from 1955 to 2015. Two resolutions have been processed : 1/2Â° and 1/4Â°. The climatic fields were computed from the integrated North Atlantic Ocean dataset that combines data extracted from the 2 major sources: SeaDataNet infrastructure and Coriolis Ocean Dataset for Reanalysis (CORA). The computation was done with the DIVA software, version 4.7.2.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (degree_C)
Temperature_err (Error standard deviation of Temperature, degree_C)
Temperature_L1 (Temperature masked using relative error threshold 0.3, degree_C)
Temperature_L2 (Temperature masked using relative error threshold 0.5, degree_C)
Temperature_relerr (Relative error of Temperature)
Temperature_databins (Logarithm10 of number of data in bins)
Temperature_outlbins (Logarithm10 of number of outliers data in bins)
Temperature_CLfield (Correlation length field)
Salinity (PSU)
Salinity_err (Error standard deviation of Salinity, per mille)
Salinity_L1 (Salinity masked using relative error threshold 0.3, per mille)
Salinity_L2 (Salinity masked using relative error threshold 0.5, per mille)
Salinity_relerr (Relative error of Salinity)
Salinity_databins (Logarithm10 of number of data in bins)
Salinity_outlbins (Logarithm10 of number of outliers data in bins)
Salinity_CLfield (Correlation length field, PSU)


Summary:
The SDC_NAT_CLIM_TS_V2 product contains Temperature and Salinity Climatologies for the North Atlantic Ocean including the seasonal and monthly fields for period 1950-2019 and seasonal fields for 6 decades starting from 1950 to 2019. Two resolutions have been processed : 1/2Â° and 1/4Â°. The climatic fields were computed from the integrated North Atlantic Ocean dataset that combines data extracted from the 2 major sources: SeaDataNet infrastructure and Coriolis Ocean Dataset for Reanalysis (CORA). The computation was done with the DIVA software, version 4.7.2.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (sea water temperature, 1e-3)
Temperature_L1 (sea water temperature masked using relative error threshold 0.3, 1e-3)
Temperature_L2 (sea water temperature masked using relative error threshold 0.5, 1e-3)
Temperature_relerr (Relative error of sea water temperature, 1)
Salinity (PSU)
Salinity_L1 (Salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (Salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of Salinity, 1)


SDC_NorthSea_Climatology_TS_V1_monthly

Summary:
Merged dataset. Royal Belgian Institute of Natural Sciences, Operational Directorate Natural Environment, Belgian Marine Data Centre data from a local source.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
Temperature (sea water temperature, degree_C)
Temperature_L1 (sea water temperature masked using relative error threshold 0.3, degree_C)
Temperature_L2 (sea water temperature masked using relative error threshold 0.5, degree_C)
Temperature_relerr (Relative error of sea water temperature, 1)
Salinity (sea water salinity, PSU)
Salinity_L1 (sea water salinity masked using relative error threshold 0.3, PSU)
Salinity_L2 (sea water salinity masked using relative error threshold 0.5, PSU)
Salinity_relerr (Relative error of sea water salinity, 1)


SDC_NorthSea_Climatology_TS_V1_seasonal


The GEBCO_2021 Grid, a continuous terrain model for oceans and land at 15 arc-second intervals

Summary:
The GEBCO_2021 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals. The GEBCO_2021 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds.The grid uses as a 'base-map' Version 2.2 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with gridded bathymetric data sets developed as part of the Nippon Foundation-GEBCO Seabed 2030 Project.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elevation (Elevation relative to sea level, m)