Sea Surface Temperature, monthly means, AFSC management regions

Timeseries of monthly sea surface temperature means for AFSC management regions generated from the NOAA/NCDC Blended Monthly Global Sea Surface Winds product. AFSC management regions are defined as:  North Bering Sea - Waters in the Bering Sea north of 58 N latitude; South Bering Sea - Waters in the Bering Sea south of 58 N latitude; Western Aleutians - Waters between 177 E and the limits of EEZ on east from south of 55 N to the EEZ that is south of the Aleutians Islands; Central Aleutians - Waters between 177 W and 177 E from south of 55 N to the EEZ that is south of the Aleutians Islands; Eastern Aleutians - Waters between 170 W and 177 W from south of 55 N to the EEZ that is south of the Aleutians Islands; Western Gulf of Alaska - Waters between 159 W and 170 W from the Alaskan coast to the EEZ; Central Gulf of Alaska - Waters between 147 W and 159 W from the Alaskan coast to the EEZ; Eastern Gulf of Alaska - Waters between 132.667 W and 147 W from the Alaskan coast to the EEZ.

cdm_data_type = Other
VARIABLES:
time (Centered Time, seconds since 1970-01-01T00:00:00Z)
north_bering_sst (SST, North Bering Sea, degree_C)
south_bering_sst (SST, South Bering Sea, degree_C)
west_aleutians_sst (SST, West Aleutians, degree_C)
central_aleutians_sst (SST, Central Aleutians, degree_C)
east_aleutians_sst (SST, East Aleutians, degree_C)
west_gulf_sst (SST, West Gulf of Alaska, degree_C)
central_gulf_sst (SST, Central Gulf of Alaska, degree_C)
east_gulf_sst (SST, East Gulf of Alaska, degree_C)
north_bering_sst_stdev (Standard Deviation, North Bering Sea, degree_C)
south_bering_sst_stdev (Standard Deviation, South Bering Sea, degree_C)
west_aleutian_sst_stdev (Standard Deviation, West Aleutians, degree_C)
central_aleutian_sst_stdev (Standard Deviation, Central Aleutians, degree_C)
east_aleutians_sst_stdev (Standard Deviation, East Aleutians, degree_C)
west_gulf_sst_stdev (Standard Deviation, West Gulf of Alaska, degree_C)
central_gulf_sst_stdev (Standard Deviation, Central Gulf of Alaska, degree_C)
east_gulf_sst_stdev (Standard Deviation, East Gulf of Alaska, degree_C)
... (8 more variables)

NOAA/NMFS/SWFSC/ERD and NOAA/NESDIS/CoastWatch West Coast Node


Sea-Surface Temperature, NOAA ACSPO NOAA-20 VIIRS CoastWatch Co-gridded 4km Daily (degrees C)

Sea surface temperature retrievals produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from Visible and Infrared Imager/Radiometer Suite (VIIRS) sensor

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
sea_surface_temperature (sea surface sub-skin temperature, degree_C)


Sea-Surface Temperature, NOAA ACSPO S-NPP VIIRS CoastWatch Co-gridded 4km Daily (degrees C)

Sea surface temperature retrievals produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from Visi                                      ble and Infrared Imager/Radiometer Suite (VIIRS) sensor

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
sea_surface_temperature (sea surface sub-skin temperature, degree_C)


Sea-Surface Temperature, NOAA Geo-polar Blended Analysis Night Only, GHRSST, Near Real-Time, Global 5km, 2002-Present, Daily (degree C)

Analyzed blended sea surface temperature over the global ocean using night only input data. An SST estimation scheme which combines multi-satellite retrieva
ls of sea surface temperature datasets available from polar orbiters, geostationary InfraRed (IR) and microwave sensors into a single global analysis. This global SST analysis provides
 a daily gap-free map of the foundation sea surface temperature at 0.05Âº spatial resolution. Note 2002-2016 is a reanalysis.  2017-present is near real-time processing.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, degree_C)
analysis_error (estimated error standard deviation of analysed_sst, kelvin)
mask (sea/land/ice bit mask)
sea_ice_fraction (1)


The Silbo Challenger mission is a partnership between industry and academia which will exercise a number of new Slocum glider features and long term deployment stratgies including shoreside piloting tools, glider firmware, battery design, thruster design, hull design and low cost deployment and recovery in support of open ocean deployments.  Temperature and salinity profiles will also be submitted to the IOOS National Data Assembly Center which will transmit the profiles to the Global Telecommunication System for assimiliation into ocean forecasting models.

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
conductivity (Sea Water Electrical Conductivity, S m-1)
conductivity_qc (conductivity Quality Flag)
density (Sea Water Density, kg m-3)
density_qc (density Quality Flag)
depth_qc (depth Quality Flag)
instrument_ctd (CTD Metadata, 1)
lat_qc (lat Quality Flag)
lat_uv (Depth-averaged Latitude, degrees_north)
lat_uv_qc (lat_uv Quality Flag)
lon_qc (lon Quality Flag)
lon_uv (Depth-averaged Longitude, degrees_east)
lon_uv_qc (lon_uv Quality Flag)
platform_meta (Platform Metadata, 1)
precise_lat (Precise Latitude, degrees_north)
precise_lon (Precise Longitude, degrees_east)
... (51 more variables)


Spray glider profile data from Woods Hole Oceanographic Institution. (This deployment supported by NOAA.)

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
conductivity (Sea Water Electrical Conductivity, S m-1)
conductivity_qc (conductivity Quality Flag)
density (Sea Water Density, kg m-3)
density_qc (density Quality Flag)
depth_qc (depth Quality Flag)
instrument_ctd (CTD Metadata, 1)
lat_qc (latitude Quality Flag)
lat_uv (Depth-averaged Latitude, degrees_north)
lat_uv_qc (lat_uv Quality Flag)
lon_qc (longitude Quality Flag)
lon_uv (Depth-averaged Longitude, degrees_east)
lon_uv_qc (lon_uv Quality Flag)
platform_meta (Platform Metadata, 1)
precise_lat (Precise Latitude, degrees_north)
precise_lon (Precise Longitude, degrees_east)
precise_time (seconds since 1970-01-01T00:00:00Z)
pressure (Sea Water Pressure, dbar)
pressure_qc (pressure Quality Flag)
profile_lat_qc (profile_lat Quality Flag)
... (39 more variables)


SST, Pathfinder Ver 5.2 (L3C), Day and Night, Global, 0.0417°, 1981-2006, Science Quality (8 Day Composite)

This dataset contains sea surface temperature (SST) data produced as part of the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST Project, created using Version 5.2 of the Pathfinder algorithm and the dataset. Multi-day composites and composites of day and night datasets were generated by the Environmental Research Division (NOAA/NMFS/SWFSC/ERD).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m Wind Speed, m s-1)
l2p_flags


SST, Pathfinder Ver 5.2 (L3C), Day and Night, Global, 0.0417°, 1981-2012, Science Quality (1 Day Composite)


SST, Pathfinder Ver 5.2 (L3C), Day and Night, Global, 0.0417°, 1981-2012, Science Quality (Monthly Composite)


SST, Pathfinder Ver 5.3 (L3C), Day, Global, 0.0417°, 1981-present, Science Quality (8 Day Composite)

This dataset contains 8-day-composites of daytime sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. The source data were created using Version 5.3 of the Pathfinder algorithm and the file is nearly but not completely compliant with the GHRSST Data Specifications V2.0 (GDS2). Source data were created by the NOAA National Centers for Environmental Information (NCEI). Multi-day composites were created by NOAA CoastWatch-West Coast and NOAA/SWFSC/ERD.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (NOAA Climate Data Record of Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m wind speed, m s-1)
l2p_flags


SST, Pathfinder Ver 5.3 (L3C), Day, Global, 0.0417°, 1981-present, Science Quality (Monthly Composite)

This dataset contains monthly composites of daytime sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. The source data were created using Version 5.3 of the Pathfinder algorithm and the file is nearly but not completely compliant with the GHRSST Data Specifications V2.0 (GDS2). Source data were created by the NOAA National Centers for Environmental Information (NCEI). Multi-day composites were created by NOAA CoastWatch-West Coast and NOAA/SWFSC/ERD.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (NOAA Climate Data Record of Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m wind speed, m s-1)
l2p_flags


SST, Pathfinder Ver 5.3 (L3C), Night, Global, 0.0417°, 1981-present, Science Quality (8 Day Composite)

This dataset contains 8-day-composites of nighttime sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. The source data were created using Version 5.3 of the Pathfinder algorithm and the file is nearly but not completely compliant with the GHRSST Data Specifications V2.0 (GDS2). Source data were created by the NOAA National Centers for Environmental Information (NCEI). Multi-day composites were created by NOAA CoastWatch-West Coast and NOAA/SWFSC/ERD.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (NOAA Climate Data Record of Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m wind speed, m s-1)
l2p_flags


SST, Pathfinder Ver 5.3 (L3C), Night, Global, 0.0417°, 1981-present, Science Quality (Monthly Composite)

This dataset contains monthly composites of nighttime sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. The source data were created using Version 5.3 of the Pathfinder algorithm and the file is nearly but not completely compliant with the GHRSST Data Specifications V2.0 (GDS2). Source data were created by the NOAA National Centers for Environmental Information (NCEI). Multi-day composites were created by NOAA CoastWatch-West Coast and NOAA/SWFSC/ERD.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (NOAA Climate Data Record of Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m wind speed, m s-1)
l2p_flags


SST, VIIRS NOAA-20, Alaska, 750m, 2020-present, Science Quality Daily

Daily global sea surface temperature produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from the Visible and Infrared Imager/Radiometer Suite (VIIRS) NOAA-20 sensor. The data were processed by the Advanced Clear-Sky Processor for Oceans (ACSPO).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (degree_C)


SST, VIIRS NOAA-20, Alaska, 750m, 2020-present, Science Quality Monthly

Monthly global sea surface temperature produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from the Visible and Infrared Imager/Radiometer Suite (VIIRS) NOAA-20 sensor. The data were processed by the Advanced Clear-Sky Processor for Oceans (ACSPO).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (degree_C)


SST, VIIRS NOAA-20, Alaska, 750m, 2020-present, Science Quality Weekly

Weekly global sea surface temperature produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from the Visible and Infrared Imager/Radiometer Suite (VIIRS) NOAA-20 sensor. The data were processed by the Advanced Clear-Sky Processor for Oceans (ACSPO).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (degree_C)


Suspended Particulate Matter (Gap-filled DINEOF), NOAA S-NPP NOAA-20 VIIRS and Copernicus S-3A OLCI, Science Quality, Global 9km, 2018-recent, Daily

Visible and Infrared Imager/Radiometer Suite/Suomi-NPP and NOAA-20 (VIIRS) and Sentinel-3A OLCI DINEOF gap filled L4 data. NOAA National Environmental Satellite, Data, and Information Service (NESDIS) STAR data. Sentinel-3A courtesy of Copernicus Program

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
spm (Suspended Particulate Matter, mg l-1)


The purpose of this glider mission is to do cross canyon transects of Palmer Deep within the operating CODAR fields off of Anvers Island.  This multi-platform field study will investigate the impact of coastal physical processes (e.g. tides, currents, upwelling events, sea-ice) on Ad��lie penguin foraging ecology in the vicinity of Palmer Deep, off Anvers Island, WAP. Guided by real-time surface convergence and divergences based on remotely sensed surface current maps derived from a coastal network of High Frequency Radars (HFRs), a multidisciplinary research team will adaptively sample the distribution of phytoplankton and zooplankton, which influence Ad��lie penguin foraging ecology, to understand how local oceanographic processes structure the ecosystem.

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
conductivity (Sea Water Electrical Conductivity, S m-1)
conductivity_qc (conductivity Quality Flag)
density (Sea Water Density, kg m-3)
density_qc (density Quality Flag)
depth_qc (depth Quality Flag)
instrument_ctd (CTD Metadata, 1)
lat_qc (lat Quality Flag)
lat_uv (Depth-averaged Latitude, degrees_north)
lat_uv_qc (lat_uv Quality Flag)
lon_qc (lon Quality Flag)
lon_uv (Depth-averaged Longitude, degrees_east)
lon_uv_qc (lon_uv Quality Flag)
platform_meta (Platform Metadata, 1)
... (45 more variables)


The purpose of this glider mission is to do station keeping to resolve the time series of Palmer Deep within the operating CODAR fields off of Anvers Island.  This multi-platform field study will investigate the impact of coastal physical processes (e.g. tides, currents, upwelling events, sea-ice) on Ad�lie penguin foraging ecology in the vicinity of Palmer Deep, off Anvers Island, WAP. Guided by real-time surface convergence and divergences based on remotely sensed surface current maps derived from a coastal network of High Frequency Radars (HFRs), a multidisciplinary research team will adaptively sample the distribution of phytoplankton and zooplankton, which influence Ad�lie penguin foraging ecology, to understand how local oceanographic processes structure the ecosystem.

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
conductivity (Sea Water Electrical Conductivity, S m-1)
conductivity_qc (conductivity Quality Flag)
density (Sea Water Density, kg m-3)
density_qc (density Quality Flag)
depth_qc (depth Quality Flag)
instrument_ctd (CTD Metadata, 1)
lat_qc (lat Quality Flag)
lat_uv (Depth-averaged Latitude, degrees_north)
lat_uv_qc (lat_uv Quality Flag)
lon_qc (lon Quality Flag)
lon_uv (Depth-averaged Longitude, degrees_east)
lon_uv_qc (lon_uv Quality Flag)
... (46 more variables)


The goal of this project is to characterize the dynamics of a buoyant ocean front formed by meltwater along the Antarctic Peninsula.

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
bsipar_par (sci_bsipar_par, uE/m^2sec)
bsipar_timestamp (sci_bsipar_timestamp, seconds since 1970-01-01T00:00:00Z)
commanded_alt_time (c_alt_time, sec)
commanded_ballast_pumped (c_ballast_pumped, cc)
commanded_climb_target_depth (c_climb_target_depth, m)
commanded_dive_target_depth (c_dive_target_depth, m)
commanded_fin (c_fin, rad)
commanded_heading (c_heading, rad)
commanded_science_send_all (c_science_send_all, bool)
commanded_thruster_on (c_thruster_on, %)
commanded_weight_drop (c_weight_drop, bool)
commanded_wpt_lat (c_wpt_lat, lat)
commanded_wpt_lon (c_wpt_lon, lon)
commanded_wpt_x_lmc (c_wpt_x_lmc, m)
commanded_wpt_y_lmc (c_wpt_y_lmc, m)
conductivity (Sea Water Electrical Conductivity, S m-1)
crs (http://www.opengis.net/def/crs/EPSG/0/4326)
ctd41cp_timestamp (sci_ctd41cp_timestamp, seconds since 1970-01-01T00:00:00Z)
density (Sea Water Density, kg m-3)
... (137 more variables)


Shipboard observations of marine mammal distribution and habitat are expensive and logistically challenging to collect in Arctic waters.  Port facilities are minimal and access to appropriate vessels for spending extended periods of time at sea is extremely limited.  Autonomous platforms like gliders provide the capability to collect both oceanographic and passive acoustic data for far longer periods of time (weeks to months) and at significantly reduced costs than traditional shipboard or aerial surveys.  We have developed a system to record, detect, classify, and remotely report Arctic and sub-Arctic marine mammal calls in real time from Slocum ocean gliders based on the digital acoustic monitoring (DMON) instrument and the low-frequency detection and classification system (LFDCS). The system was successfully demonstrated for Arctic research during three AOOS-funded studies in the Chukchi Sea during September 2013 and 2014 and from 11 July – 8 September 2015. The joint acoustic-oceanographic data were used to examine the distribution, occurrence, and habitat of marine mammals using in-situ passive acoustic and oceanographic data collected by the glider, and to demonstrate the near real-time detection and reporting capability of the system.

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
conductivity (Sea Water Electrical Conductivity, S.m-1)
crs (http://www.opengis.net/def/crs/EPSG/0/4326)
density (Sea Water Density, kg.m-3)
instrument_ctd (CTD Metadata, 1)
lat_uv (Depth-averaged Latitude, degrees_north)
lon_uv (Depth-averaged Longitude, degrees_east)
platform_meta (Platform Metadata, 1)
... (36 more variables)

University of Alaska Fairbanks, College of Fisheries and Ocean Sciences


The purpose of this glider mission is to do along canyon transects of Palmer Deep within the operating CODAR fields off of Anvers Island.  This multi-platform field study will investigate the impact of coastal physical processes (e.g. tides, currents, upwelling events, sea-ice) on Ad��lie penguin foraging ecology in the vicinity of Palmer Deep, off Anvers Island, WAP. Guided by real-time surface convergence and divergences based on remotely sensed surface current maps derived from a coastal network of High Frequency Radars (HFRs), a multidisciplinary research team will adaptively sample the distribution of phytoplankton and zooplankton, which influence Ad��lie penguin foraging ecology, to understand how local oceanographic processes structure the ecosystem.

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
conductivity (Sea Water Electrical Conductivity, S m-1)
conductivity_qc (conductivity Quality Flag)
density (Sea Water Density, kg m-3)
density_qc (density Quality Flag)
depth_qc (depth Quality Flag)
instrument_ctd (CTD Metadata, 1)
lat_qc (lat Quality Flag)
lat_uv (Depth-averaged Latitude, degrees_north)
lat_uv_qc (lat_uv Quality Flag)
lon_qc (lon Quality Flag)
lon_uv (Depth-averaged Longitude, degrees_east)
lon_uv_qc (lon_uv Quality Flag)
platform_meta (Platform Metadata, 1)
... (45 more variables)


Shipboard observations of marine mammal distribution and habitat are expensive and logistically challenging to collect in Arctic waters.  Port facilities are minimal and access to appropriate vessels for spending extended periods of time at sea is extremely limited.  Autonomous platforms like gliders provide the capability to collect both oceanographic and passive acoustic data for far longer periods of time (weeks to months) and at significantly reduced costs than traditional shipboard or aerial surveys.  We have developed a system to record, detect, classify, and remotely report Arctic and sub-Arctic marine mammal calls in real time from Slocum ocean gliders based on the digital acoustic monitoring (DMON) instrument and the low-frequency detection and classification system (LFDCS). The system was successfully demonstrated for Arctic research during three AOOS-funded studies in the Chukchi Sea during September 2013 and 2014, 11 July – 8 September 2015, and from 10 July - 4 october 2016. The joint acoustic-oceanographic data were used to examine the distribution, occurrence, and habitat of marine mammals using in-situ passive acoustic and oceanographic data collected by the glider, and to demonstrate the near real-time detection and reporting capability of the system.

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
conductivity (Sea Water Electrical Conductivity, S.m-1)
crs (http://www.opengis.net/def/crs/EPSG/0/4326)
density (Sea Water Density, kg.m-3)
instrument_ctd (CTD Metadata, 1)
lat_uv (Depth-averaged Latitude, degrees_north)
lon_uv (Depth-averaged Longitude, degrees_east)
platform_meta (Platform Metadata, 1)
... (36 more variables)


UAF G191 Glider deployment in the North Pacific Ocean

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
conductivity (Sea Water Electrical Conductivity, S m-1)
crs (http://www.opengis.net/def/crs/EPSG/0/4326)
density (Sea Water Density, kg m-3)
instrument_ctd (CTD Metadata, 1)
lat_uv (Depth-averaged Latitude)
lon_uv (Depth-averaged Longitude)
platform_meta (Platform Metadata, 1)
precise_lat (Precise Latitude, degree_north)
precise_lon (Precise Longitude, degree_east)
precise_time (seconds since 1970-01-01T00:00:00Z)
pressure (Sea Water Pressure, bar)
qartod_conductivity_flat_line_flag (QARTOD Flat Line Test for sea_water_electrical_conductivity, 1)
qartod_conductivity_gross_range_flag (QARTOD Gross Range Test for sea_water_electrical_conductivity, 1)
qartod_conductivity_primary_flag (QARTOD Primary Flag for sea_water_electrical_conductivity, 1)
qartod_conductivity_rate_of_change_flag (QARTOD Rate of Change Test for sea_water_electrical_conductivity, 1)
qartod_conductivity_spike_flag (QARTOD Spike Test for sea_water_electrical_conductivity, 1)
qartod_density_flat_line_flag (QARTOD Flat Line Test for sea_water_density, 1)
qartod_density_gross_range_flag (QARTOD Gross Range Test for sea_water_density, 1)
qartod_density_primary_flag (QARTOD Primary Flag for sea_water_density, 1)
qartod_density_rate_of_change_flag (QARTOD Rate of Change Test for sea_water_density, 1)
... (24 more variables)

The University of Alaska Fairbanks College of Fisheries and Ocean Science


UAF G191 Glider deployment in the North Pacific Ocean (March 2021)

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
c_wpt_lat (lat)
c_wpt_lon (lon)
conductivity (Sea Water Electrical Conductivity, S.m-1)
crs (http://www.opengis.net/def/crs/EPSG/0/4326)
density (Sea Water Density, kg.m-3)
instrument_altimeter
instrument_altitude
instrument_ctd (CTD Metadata, 1)
instrument_dissolved_oxygen
instrument_fluorometer (Wetlabs FLNTUSLC Fluorometer)
instrument_gps
instrument_irradiance
instrument_radiance
lat_uv (Depth-averaged Latitude, degrees_north)
lon_uv (Depth-averaged Longitude, degrees_east)
m_altitude
m_ballast_pumped (cc)
m_battery (volts)
m_battpos (in)
m_coulomb_amphr_total (amp-hrs)
... (51 more variables)


UAF G191 Glider deployment in the North Pacific Ocean (April 2021)

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
c_wpt_lat (lat)
c_wpt_lon (lon)
conductivity (Sea Water Electrical Conductivity, S.m-1)
crs (http://www.opengis.net/def/crs/EPSG/0/4326)
density (Sea Water Density, kg.m-3)
instrument_altimeter
instrument_altitude
instrument_ctd (CTD Metadata, 1)
instrument_dissolved_oxygen
instrument_fluorometer (Wetlabs FLNTUSLC Fluorometer)
instrument_gps
instrument_irradiance
instrument_radiance
lat_uv (Depth-averaged Latitude, degrees_north)
lon_uv (Depth-averaged Longitude, degrees_east)
m_altitude
m_ballast_pumped (cc)
m_battery (volts)
m_battpos (in)
m_coulomb_amphr_total (amp-hrs)
... (51 more variables)


UAF G191 Glider deployment in the North Pacific Ocean (May 2022)

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
c_wpt_lat (lat)
c_wpt_lon (lon)
conductivity (Sea Water Electrical Conductivity, S.m-1)
crs (http://www.opengis.net/def/crs/EPSG/0/4326)
density (Sea Water Density, kg.m-3)
instrument_altimeter
instrument_altitude
instrument_ctd (CTD Metadata, 1)
instrument_dissolved_oxygen
instrument_fluorometer (Wetlabs FLNTUSLC Fluorometer)
instrument_gps
instrument_irradiance
instrument_radiance
lat_uv (Depth-averaged Latitude, degrees_north)
lon_uv (Depth-averaged Longitude, degrees_east)
m_altitude
m_ballast_pumped (cc)
m_battery (volts)
m_battpos (in)
m_coulomb_amphr_total (amp-hrs)
... (52 more variables)


This dataset contains measurements of temperature, conductivity, salinity, density, chlorophyll-a and CDOM fluorescence, Photosynthetically Active Radiation (PAR), Dissolved Oxygen and reception time and location from 180 kHz transmitters collected from a Teledyne Slocum autonomous underwater glider dataset gathered by University of Alaska Fairbanks as part of the Alaska Region Glider Missions Supporting an Ecosystem Approach to Fisheries Management project, funded by NOAA through the Integrated Ocean Observing System (IOOS) and the Alaska Ocean Observing System. The North Pacific Fisheries Management Council (NPFMC) establishes Alaska as a world leader in the Ecosystem Approach to Fisheries Management (EAFM) for maintaining sustainable fisheries (Zador et al., 2017). EAFM requires deep understanding of commercially and non-commercially important species’ biology, population status, and trends in addition to a holistic understanding of environmental drivers, trophic linkages, and many subtle complexities of ecosystem dynamics. A successful implementation of EAFM is based on timely information that guides an informed approach to setting fisheries harvest levels in the context of environmental conditions. Lack of timely ecosystem data is identified as a critical gap in the EAFM process. The purpose of this project is to apply gliders to the task of developing near-real-time indices of key physical and biological parameters that will inform the NPFMC decision-making process, and other marine and fisheries management related research activities.

cdm_data_type = TrajectoryProfile
VARIABLES:
trajectory (Trajectory Name)
wmo_id
profile_id
time (Profile Time, seconds since 1970-01-01T00:00:00Z)
latitude (Profile Latitude, degrees_north)
longitude (Profile Longitude, degrees_east)
depth (m)
c_wpt_lat (lat)
c_wpt_lon (lon)
conductivity (Sea Water Electrical Conductivity, S.m-1)
crs (http://www.opengis.net/def/crs/EPSG/0/4326)
... (68 more variables)


Wind Speed, monthly means, AFSC management regions

Timeseries of monthly sea surface temperature means for AFSC management regions generated from the NOAA/NCDC Blended Monthly Global Sea Surface Winds product. AFSC management regions are defined as:  North Bering Sea - Waters in the Bering Sea north of 58 N latitude;  South Bering Sea - Waters in the Bering Sea south of 58 N latitude;  Western Aleutians - Waters between 177 E and the limits of EEZ on east from south of 55 N to the EEZ that is south of the Aleutians Islands;  Central Aleutians - Waters between 177 W and 177 E from south of 55 N to the EEZ that is south of the Aleutians Islands;  Eastern Aleutians - Waters between 170 W and 177 W from south of 55 N to the EEZ that is south of the Aleutians Islands;  Western Gulf of Alaska - Waters between 159 W and 170 W from the Alaskan coast to the EEZ;  Central Gulf of Alaska - Waters between 147 W and 159 W from the Alaskan coast to the EEZ;  Eastern Gulf of Alaska - Waters between 132.667 W and 147 W from the Alaskan coast to the EEZ.

cdm_data_type = Other
VARIABLES:
time (Centered Time, seconds since 1970-01-01T00:00:00Z)
north_bering_wind (Wind Speed, North Bering Sea, m s-1)
south_bering_wind (Wind Speed, South Bering Sea, m s-1)
west_aleutians_wind (Wind Speed, West Aleutians, m s-1)
central_aleutians_wind (Wind Speed, Central Aleutians, m s-1)
east_aleutians_wind (Wind Speed, East Aleutians, m s-1)
west_gulf_wind (Wind Speed, West Gulf of Alaska, m s-1)
central_gulf_wind (Wind Speed, Central Gulf of Alaska, m s-1)
east_gulf_wind (Wind Speed, East Gulf of Alaska, m s-1)
north_bering_wind_stdev (Standard Deviation, North Bering Sea, m s-1)
south_bering_wind_stdev (Standard Deviation, South Bering Sea, m s-1)
west_aleutian_wind_stdev (Standard Deviation, West Aleutians, m s-1)
central_aleutian_wind_stdev (Standard Deviation, Central Aleutians, m s-1)
east_aleutians_wind_stdev (Standard Deviation, East Aleutians, m s-1)
west_gulf_wind_stdev (Standard Deviation, West Gulf of Alaska, m s-1)
central_gulf_wind_stdev (Standard Deviation, Central Gulf of Alaska, m s-1)
east_gulf_wind_stdev (Standard Deviation, East Gulf of Alaska, m s-1)
... (8 more variables)

NOAA/NMFS/SWFSC/ERD and NOAA/NESDIS/CoastWatch West Coast Node


Wind, All Metop ASCAT, 0.25°, Global, Near Real Time, 2013-present (Monthly), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instruments onboard all EUMETSAT's MetOp satellites.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is a monthly composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


Wind, Metop-B ASCAT, 0.25°, Global, Near Real Time, 2013-present (1 Day), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instrument onboard EUMETSAT's Metop-B satellite.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is a 1 day composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


Wind, Metop-B ASCAT, 0.25°, Global, Near Real Time, 2013-present (3 Day), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instrument onboard EUMETSAT's Metop-B satellite.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is a 3 day composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


Wind, Metop-B ASCAT, 0.25°, Global, Near Real Time, 2013-present (8 Day), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instrument onboard EUMETSAT's Metop-B satellite.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is an 8 day composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


Wind, Metop-B ASCAT, 0.25°, Global, Near Real Time, 2013-present (Monthly), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instrument onboard EUMETSAT's Metop-B satellite.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is a monthly composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


X- Experimental Ice/snow presence mean, standard deviation, and anomalies from US National Ice Center/NOAA NCEI Interactive Multisensor Snow and Ice Mapping System (IMS), 4km, 15-Day (2015-2020), Arctic

This dataset provides a 4km resolution ice and snow cover presence 15-day mean, standard deviation, and anomalies from 15-year baseline (2006-2020) over the Arctic, based on the U.S. National Ice Center Interactive Multisensor Snow and Ice Mapping System (IMS) data.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
IMS_mean (15-day mean probability of sea ice presence, 1)
IMS_stdev (15-day standard deviation of sea ice presence, 1)
IMS_anomaly (Mean anomaly, 1)

NOAA NESDIS CoatWatch, NMFS Southwest Fisheries Science Center


X- Experimental Sea Ice Classification, SAR Composite, Near Real-Time, 1km, North Pole, Daily

This file contains a composite of Synthetic Aperture Radar (SAR) derived sea ice classification covering the Arctic for a period of one day. The files are produced in SAROPS (SAR Operational Product System) by the Water Surface Conditions science team within the NOAA STAR Satellite Oceanography and Climatology Division. Data from the following C-Band SAR systems are included: Sentinel-1, RADARSAT-2, and RADARSAT Constellation Mission. Sea ice classification values represent concentration up to 80%, and greater than 80%. Daily coverage varies depending on SAR acquisitions.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
SIC (Classified sea ice concentration)


X- Experimental Sea ice drift data derived from the buoy data from the IABP, Daily Arctic

The sea ice drift dataset is derived daily from drifting buoys deployed on sea ice as part of the International Arctic Buoy Program (IABP).  It provides essential measurements of sea ice movement, including daily drift distance and direction.

cdm_data_type = Point
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
buoy_id
latitude (degrees_north)
longitude (degrees_east)
x (Easting of Pixel Centers, meter)
y (Northing of Pixel Centers, meter)
dx (horizontal (x-axis) component of the displacement, meter)
dy (vertical (y-axis) component of the displacement, meter)
distance (The great-circle distance: The measure of displacement on the shortest path between two geographic points along the Earth's surface, meter)
fwd_azimuth (angle or direction from the start position to the end position of buoy, measured clockwise from true north, degree)


X-experimental - Particulate Organic Carbon in Ocean Surface Water, MODIS, 9km, NASA SMI, Stramski 2022

Particulate Organic Carbon in Ocean Surface Water, MODIS Aqua, 9km, NASA Standard Mapped Image (SMI), Stramski 2022

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
poc (Particulate Organic Carbon, D. Stramski, 2022, mg m^-3)
poc_stdev (Standard Deviation for Particulate Organic Carbon, mg m^-3)
poc_var (Variance for Particulate Organic Carbon, mg m^-3)
poc_nobs (Number Particulate Organic Carbon of Observations, count)


X-experimental - Particulate Organic Carbon in Ocean Surface Water, SeaWiFS, 9km, NASA SMI, Stramski 2022

Particulate Organic Carbon in Ocean Surface Water, Sea-Wide Field-of-View Sensor (SeaWiFS), 9km, NASA Standard Mapped Image (SMI), Stramski 2022

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
poc (Particulate Organic Carbon, D. Stramski, 2022, mg m^-3)
poc_stdev (Standard Deviation for Particulate Organic Carbon, mg m^-3)
poc_var (Variance for Particulate Organic Carbon, mg m^-3)
poc_nobs (Number Particulate Organic Carbon of Observations, count)


X-experimental - Particulate Organic Carbon in Ocean Surface Water, VIIRS SNPP, 9km, NASA SMI, Stramski 2022

Particulate Organic Carbon in Ocean Surface Water, VIIRS SNPP, Level-3, NASA Standard Mapped Image (SMI), Stramski 2022

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
poc (Particulate Organic Carbon, D. Stramski, 2022, mg m^-3)
poc_stdev (Standard Deviation for Particulate Organic Carbon, mg m^-3)
poc_var (Variance for Particulate Organic Carbon, mg m^-3)
poc_nobs (Number Particulate Organic Carbon of Observations, count)


X-Experimental Chlorophyll, S-NPP VIIR, Alaska, Daily

Ocean color standard products include normalized water-leaving radiances, chlorophyll-a concentration, diffusive attenuation coefficient at 490 nm and diffusive attenuation coefficient of the photosynthetically available radiation (PAR).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll Concentration, OC3 Algorithm, mg m^-3)


X-Experimental Far Red Remote Sensing Reflectance (745nm 862nm), S-NPP VIIR, Alaska, Daily

Ocean color products include remote sensing reflectance at 745nm and 862nm, chlorophyll-a concentration, diffusive attenuation coefficient at 490 nm and diffusive attenuation coefficient of the photosynthetically available radiation (PAR).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_745 (Remove Sensing Reflectance 745nm, sr^-1)
Rrs_862 (Remove Sensing Reflectance 862nm, sr^-1)
par (Photosynthetically Available Radiation, sr^-1)
kd_490 (Diffuse Attenuation Coefficient at 490nm, m-1)
kd_par (Diffuse Attenuation Coefficient for PAR, m-1)


X-Experimental POC from NOAA S-NPP VIIRS Source Data

Particulate Organic Carbon in Ocean Surface Water, Sea-Wide Field-of-View Sensor (SeaWiFS), 9km, NASA Standard Mapped Image (SMI), Stramski 2022

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
poc (Particulate Organic Carbon, D. Stramski, 2022, mg m^-3)
Rrs_443 (Remote Sensing Reflectance at 443 nm, sr^-1)
Rrs_486 (Remote Sensing Reflectance at 486 nm, sr^-1)
Rrs_551 (Remote Sensing Reflectance at 551 nm, W m^-2 um^-1 sr^-1)
Rrs_510v (Virtual Remote Sensing Reflectance at 510 nm, W m^-2 um^-1 sr^-1)


X-Experimental Remote Sensing Reflectance, S-NPP VIIR, Alaska, Daily

Ocean color standard products include normalized water-leaving radiances, chlorophyll-a concentration, diffusive attenuation coefficient at 490 nm and diffusive attenuation coefficient of the photosynthetically available radiation (PAR).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_410 (SNPP Remote Sensing Reflectance at 410 nm, sr^-1)
Rrs_443 (Remove Sensing Reflectance 443nm, sr^-1)
Rrs_486 (Remove Sensing Reflectance 486nm, sr^-1)
Rrs_551 (Remove Sensing Reflectance 551nm, sr^-1)
Rrs_638 (Remove Sensing Reflectance 638nm)
Rrs_671 (Remove Sensing Reflectance 671nm, sr^-1)


Z-DEPRECATED - Sea Ice Concentration, NOAA/NSIDC Climate Data Record V3, Antarctic, 25km, Science Quality, 1978-2019, Daily

Alert: There is a newer version of this dataset. Please use Version 4 of the NSIDC Sea Ice Concentration CDR with ERDDAP ID:nsidcG02202v4sh1day. Link: https://polarwatch.noaa.gov/erddap/griddap/nsidcG02202v4sh1day.graph. Version 3 Summary: This data set provides a Climate Data Record (CDR) of sea ice concentration from passive microwave data. It provides a consistent, daily and monthly time series of sea ice concentrations from 09 July 1987 through the most recent processing for both the north and south polar regions. In addition, three other sea ice concentration products are included with the CDR that extend the sea ice measurements back to 26 October 1978. However, these three products are not included in the official CDR because processing the older data in a way that follows the standards of a CDR is not currently possible. All data are on a 25 km x 25 km grid. Variables containing standard deviation, quality flags, and projection information are also included.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][ygrid][xgrid]):
seaice_conc_cdr (NOAA/NSIDC Climate Data Record of Passive Microwave Daily Southern Hemisphere Sea Ice Concentration, 1)
stdev_of_seaice_conc_cdr (Passive Microwave Daily Southern Hemisphere Sea Ice Concentration Source Estimated Standard Deviation)
melt_onset_day_seaice_conc_cdr (Day of Snow Melt Onset Over Sea Ice, 1)
qa_of_seaice_conc_cdr (Passive Microwave Daily Southern Hemisphere Sea Ice Concentration QC flags)
goddard_merged_seaice_conc (Goddard Edited Climate Data Record of Passive Microwave Daily Southern Hemisphere Sea Ice Concentration, Goddard Edited, 1)
goddard_nt_seaice_conc (Passive Microwave Daily Southern Hemisphere Sea Ice Concentration by NASA Team algorithm with Goddard QC, 1)
goddard_bt_seaice_conc (Passive Microwave Daily Southern Hemisphere Sea Ice Concentration by Bootstrap algorithm with Goddard QC, 1)

NSIDC > National Snow and Ice Data Center, NOAA


Z-DEPRECATED - Sea Ice Concentration, NOAA/NSIDC Climate Data Record V3, Antarctic, 25km, Science Quality, 1978-2019, Monthly

Alert: There is a newer version of this dataset. Please use Version 4 of the NSIDC Sea Ice Concentration CDR with ERDDAP ID: nsidcG02202v4shmday. Link: https://polarwatch.noaa.gov/erddap/griddap/nsidcG02202v4shmday.graph. Version 3 Summary: This data set provides a passive microwave sea ice concentration climate data record (CDR) based on gridded brightness temperatures (TBs) from the Defense Meteorological Satellite Program (DMSP) series of passive microwave radiometers: the Special Sensor Microwave Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS). The sea ice concentration CDR is an estimate of sea ice concentration that is produced by combining concentration estimates from two algorithms developed at the NASA Goddard Space Flight Center (GSFC): the NASA Team algorithm and the Bootstrap algorithm. The individual algorithms are processed and combined at National Snow and Ice Data Center (NSIDC) using brightness temperature data from Remote Sensing Systems, Inc. (RSS).  This product is designed to provide a consistent time series of sea ice concentrations (the fraction, or percentage, of ocean area covered by sea ice) from 1987 to the present which spans the coverage of several passive microwave instruments. The data are gridded on the NSIDC polar stereographic grid with 25 x 25 km grid cells, and are available in Network Common Data Format (NetCDF) file format. Each file contains a variable with the CDR concentration values as well as variables that hold the input NASA Team and Bootstrap concentrations for reference and a merged NASA Team/Bootstrap version of the Goddard sea ice concentrations that spans 1978 to the present made available as a longer-term analog of the CDR concentrations. Variables containing standard deviation, quality flags, and projection information are also included. Data are available via FTP.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][ygrid][xgrid]):
seaice_conc_monthly_cdr (NOAA/NSIDC Climate Data Record of Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration, 1)
stdev_of_seaice_conc_monthly_cdr (Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration Source Estimated Standard Deviation)
melt_onset_day_seaice_conc_monthly_cdr (Monthly Day of Snow Melt Onset Over Sea Ice, 1)
qa_of_seaice_conc_monthly_cdr (Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration QC flags)
goddard_merged_seaice_conc_monthly (Goddard Edited Climate Data Record of Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration, Goddard Edited, 1)
goddard_nt_seaice_conc_monthly (Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration by NASA Team algorithm with Goddard QC, 1)
goddard_bt_seaice_conc_monthly (Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration by Bootstrap algorithm with Goddard QC, 1)


Z-DEPRECATED - Sea Ice Concentration, NOAA/NSIDC Climate Data Record V3, Arctic, 25km, Science Quality, 1978-2019, Daily

Alert: There is a newer version of this dataset. Please use Version 4 of the NSIDC Sea Ice Concentration CDR with ERDDAP ID: nsidcG02202v4nh1day. Link: https://polarwatch.noaa.gov/erddap/griddap/nsidcG02202v4nh1day.graph. Version 3 Summary: This data set NOAA/NSIDC Sea Ice Concentration CDR v3 (g02202) provides a passive microwave sea ice concentration climate data record (CDR) based on gridded brightness temperatures (TBs) from the Defense Meteorological Satellite Program (DMSP) series of passive microwave radiometers: the Special Sensor Microwave Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS). The sea ice concentration CDR is an estimate of sea ice concentration that is produced by combining concentration estimates from two algorithms developed at the NASA Goddard Space Flight Center (GSFC): the NASA Team algorithm and the Bootstrap algorithm. The individual algorithms are processed and combined at National Snow and Ice Data Center (NSIDC) using brightness temperature data from Remote Sensing Systems, Inc. (RSS).  This product is designed to provide a consistent time series of sea ice concentrations (the fraction, or percentage, of ocean area covered by sea ice) from 1987 to the present which spans the coverage of several passive microwave instruments. The data are gridded on the NSIDC polar stereographic grid with 25 x 25 km grid cells, and are available in Network Common Data Format (NetCDF) file format. Each file contains a variable with the CDR concentration values as well as variables that hold the input NASA Team and Bootstrap concentrations for reference and a merged NASA Team/Bootstrap version of the Goddard sea ice concentrations that spans 1978 to the present made available as a longer-term analog of the CDR concentrations. Variables containing standard deviation, quality flags, and projection information are also included. Data are available via FTP.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][ygrid][xgrid]):
seaice_conc_cdr (NOAA/NSIDC Climate Data Record of Passive Microwave Daily Northern Hemisphere Sea Ice Concentration, 1)
stdev_of_seaice_conc_cdr (Passive Microwave Daily Northern Hemisphere Sea Ice Concentration Source Estimated Standard Deviation)
melt_onset_day_seaice_conc_cdr (Day of Snow Melt Onset Over Sea Ice, 1)
qa_of_seaice_conc_cdr (Passive Microwave Daily Northern Hemisphere Sea Ice Concentration QC flags)
goddard_merged_seaice_conc (Goddard Edited Climate Data Record of Passive Microwave Daily Northern Hemisphere Sea Ice Concentration, Goddard Edited, 1)
goddard_nt_seaice_conc (Passive Microwave Daily Northern Hemisphere Sea Ice Concentration by NASA Team algorithm with Goddard QC, 1)
goddard_bt_seaice_conc (Passive Microwave Daily Northern Hemisphere Sea Ice Concentration by Bootstrap algorithm with Goddard QC, 1)


Z-DEPRECATED - Sea Ice Concentration, NOAA/NSIDC Climate Data Record V3, Arctic, 25km, Science Quality, 1978-2019, Monthly

Alert: There is a newer version of this dataset. Please use Version 4 of the NSIDC Sea Ice Concentration CDR with ERDDAP ID: nsidcG02202v4nhmday. Link: https://polarwatch.noaa.gov/erddap/griddap/nsidcG02202v4nhmday.graph. Version 3 Summary: This data set provides a Climate Data Record (CDR) of sea ice concentration from passive microwave data. It provides a consistent, daily and monthly time series of sea ice concentrations from 09 July 1987 through the most recent processing for both the north and south polar regions. In addition, three other sea ice concentration products are included with the CDR that extend the sea ice measurements back to 26 October 1978. However, these three products are not included in the official CDR because processing the older data in a way that follows the standards of a CDR is not currently possible. All data are on a 25 km x 25 km grid. Variables containing standard deviation, quality flags, and projection information are also included.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][ygrid][xgrid]):
seaice_conc_monthly_cdr (NOAA/NSIDC Climate Data Record of Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration, 1)
stdev_of_seaice_conc_monthly_cdr (Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration Source Estimated Standard Deviation)
melt_onset_day_seaice_conc_monthly_cdr (Monthly Day of Snow Melt Onset Over Sea Ice, 1)
qa_of_seaice_conc_monthly_cdr (Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration QC flags)
goddard_merged_seaice_conc_monthly (Goddard Edited Climate Data Record of Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration, Goddard Edited, 1)
goddard_nt_seaice_conc_monthly (Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration by NASA Team algorithm with Goddard QC, 1)
goddard_bt_seaice_conc_monthly (Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration by Bootstrap algorithm with Goddard QC, 1)


Z-DEPRECATED - Sea Ice Concentration, NOAA/NSIDC NRT Climate Data Record V1, Antarctic, 25km, Near Real-Time, 2016-Present, Monthly

Alert: There is a newer version of this dataset. Please use Version 2 of the NSIDC NRT Sea Ice Concentration CDR with ERDDAP ID: nsidcG10016v2shmday. Link: https://polarwatch.noaa.gov/erddap/griddap/nsidcG10016v2shmday.graph. Version 1 Summary: This data set provides a Climate Data Record (CDR) of sea ice concentration from passive microwave data. It provides a consistent, daily and monthly time series of sea ice concentrations from 09 July 1987 through the most recent processing for both the north and south polar regions. In addition, three other sea ice concentration products are included with the CDR that extend the sea ice measurements back to 26 October 1978. However, these three products are not included in the official CDR because processing the older data in a way that follows the standards of a CDR is not currently possible. All data are on a 25 km x 25 km grid. Variables containing standard deviation, quality flags, and projection information are also included.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][ygrid][xgrid]):
seaice_conc_monthly_cdr (NOAA/NSIDC Climate Data Record of Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration, 1)
stdev_of_seaice_conc_monthly_cdr (Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration Source Estimated Standard Deviation)
melt_onset_day_seaice_conc_monthly_cdr (Monthly Day of Snow Melt Onset Over Sea Ice, 1)
qa_of_seaice_conc_monthly_cdr (Passive Microwave Monthly Southern Hemisphere Sea Ice Concentration QC flags)


Z-DEPRECATED - Sea Ice Concentration, NOAA/NSIDC NRT Climate Data Record, Arctic, 25km, Near Real-Time, 2017-Present, Monthly

Alert: There is a newer version of this dataset. Please use Version 2 of the NSIDC NRT Sea Ice Concentration CDR with ERDDAP ID: nsidcG10016v2nhmday. Link: https://polarwatch.noaa.gov/erddap/griddap/nsidcG10016v2nhmday.graph. Version 1 Summary: This data set provides a Climate Data Record (CDR) of sea ice concentration from passive microwave data. It provides a consistent, daily and monthly time series of sea ice concentrations from 09 July 1987 through the most recent processing for both the north and south polar regions. In addition, three other sea ice concentration products are included with the CDR that extend the sea ice measurements back to 26 October 1978. However, these three products are not included in the official CDR because processing the older data in a way that follows the standards of a CDR is not currently possible. All data are on a 25 km x 25 km grid. Variables containing standard deviation, quality flags, and projection information are also included.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][ygrid][xgrid]):
seaice_conc_monthly_cdr (NOAA/NSIDC Climate Data Record of Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration, 1)
stdev_of_seaice_conc_monthly_cdr (Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration Source Estimated Standard Deviation)
melt_onset_day_seaice_conc_monthly_cdr (Monthly Day of Snow Melt Onset Over Sea Ice, 1)
qa_of_seaice_conc_monthly_cdr (Passive Microwave Monthly Northern Hemisphere Sea Ice Concentration QC flags)