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°, 1981-2006, Science Quality (8 Day Composite), Lon0360


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 (1 Day Composite), Lon0360


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


SST, Pathfinder Ver 5.2 (L3C), Day and Night, Global, 0.0417°, 1981-2012, Science Quality (Monthly Composite), Lon0360


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

Daytime measurements from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Version 5.2 L3-Collated (L3C) sea surface temperature. This netCDF-4 file contains sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. These data were created using Version 5.2 of the Pathfinder algorithm and the file is nearly but not completely compliant with the Global High-Resolution Sea Surface Temperature (GHRSST) Data Specifications V2.0 (GDS2).  The file does not encode time according to the GDS2 specifications, and the sses_bias and sses_standard_deviation variables are empty.  Full compliance with GDS2 specifications will be achieved in the future Pathfinder Version 6. These data were created as a partnership between the University of Miami and the US NOAA/National Oceanographic Data Center (NODC).

2014-02-11 Files downloaded from https://data.nodc.noaa.gov/pathfinder/Version5.2 to NOAA NMFS SWFSC ERD by erd.data@noaa.gov . Aggregated with reference times from the dates in the file names. Removed other, misleading time values from the file names and the data files. Removed empty sses_bias and sses_standard_deviation variables. Removed aerosol_dynamic_indicator because of incorrect add_offset and scale_factor in files from 1981 through 2000.

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)
dt_analysis (Deviation from Last SST Analysis (NCDC Daily OI), degree_C)
wind_speed (10m Wind Speed, m s-1)
sea_ice_fraction (1)
quality_level (SST Measurement Quality)
pathfinder_quality_level (Pathfinder SST Quality Flag)
l2p_flags


SST, Pathfinder Ver 5.2 (L3C), Day, Global, 0.0417°, 1981-2012, Science Quality (1 Day Composite), Lon0360


SST, Pathfinder Ver 5.2 (L3C), Day, Global, 0.0417°, 1981-2012, Science Quality (8 Day Composite)


SST, Pathfinder Ver 5.2 (L3C), Day, Global, 0.0417°, 1981-2012, Science Quality (8 Day Composite), Lon0360


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


SST, Pathfinder Ver 5.2 (L3C), Day, Global, 0.0417°, 1981-2012, Science Quality (Monthly Composite), Lon0360


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

Nighttime measurements from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Version 5.2 L3-Collated (L3C) sea surface temperature. This netCDF-4 file contains sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. These data were created using Version 5.2 of the Pathfinder algorithm and the file is nearly but not completely compliant with the Global High-Resolution Sea Surface Temperature (GHRSST) Data Specifications V2.0 (GDS2).  The file does not encode time according to the GDS2 specifications, and the sses_bias and sses_standard_deviation variables are empty.  Full compliance with GDS2 specifications will be achieved in the future Pathfinder Version 6. These data were created as a partnership between the University of Miami and the US NOAA/National Oceanographic Data Center (NODC).

2014-02-11 Files downloaded from https://data.nodc.noaa.gov/pathfinder/Version5.2 to NOAA NMFS SWFSC ERD by erd.data@noaa.gov . Aggregated with reference times from the dates in the file names. Removed other, misleading time values from the file names and the data files. Removed empty sses_bias and sses_standard_deviation variables. Fixed the incorrect add_offset and scale_factor for aerosol_dynamic_indicator in file from 1981 through 2000.

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)
dt_analysis (Deviation from Last SST Analysis (NCDC Daily OI), degree_C)
wind_speed (10m Wind Speed, m s-1)
sea_ice_fraction (1)
quality_level (SST Measurement Quality)
pathfinder_quality_level (Pathfinder SST Quality Flag)
l2p_flags


SST, Pathfinder Ver 5.2 (L3C), Night, Global, 0.0417°, 1981-2012, Science Quality (1 Day Composite), Lon0360


SST, Pathfinder Ver 5.2 (L3C), Night, Global, 0.0417°, 1981-2012, 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), Night, Global, 0.0417°, 1981-2012, Science Quality (8 Day Composite), Lon0360


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


SST, Pathfinder Ver 5.2 (L3C), Night, Global, 0.0417°, 1981-2012, Science Quality (Monthly Composite), Lon0360


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 (8 Day Composite), Lon0360


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), Day, Global, 0.0417°, 1981-present, Science Quality (Monthly Composite), Lon0360


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 (8 Day Composite), Lon0360


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, Pathfinder Ver 5.3 (L3C), Night, Global, 0.0417°, 1981-present, Science Quality (Monthly Composite), Lon0360


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (sst.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/coads/2degree/LTMs1950-1979/sst.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Sea Surface Temperature Monthly Long Term Mean at Surface, degree_C)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (sst.ltm). NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads2.5/2degree/enh/LTMs1950-1979/sst.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Sea Surface Temperature Monthly Long Term Mean at Surface, degree_C)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (sst.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/coads/2degree/enh/LTMs1950-1979/sst.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Sea Surface Temperature Monthly Long Term Mean at Surface, degree_C)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (sst.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads/2degree/LTMs1950-1979/sst.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Sea Surface Temperature Monthly Long Term Mean at Surface, degree_C)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (sst.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads/2degree/enh/LTMs1950-1979/sst.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Sea Surface Temperature Monthly Long Term Mean at Surface, degree_C)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (sst.ltm). NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads2.5/2degree/LTMs1950-1979/sst.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Sea Surface Temperature Monthly Long Term Mean at Surface, degree_C)


SSTANOM Advanced Very High Resolution Radiometer (AVHRR). NOAA National Environmental Satellite, Data, and Information Service (NESDIS) CoastWatch Caribbean and Gulf of Mexico (CWCGOM), NOAA Atlantic Oceanographic & Meteorological Laboratory (AOML) data from https://cwcgom.aoml.noaa.gov/thredds/dodsC/AVHRRSSTANOM/SSTANOM.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sstanomaly (sea surface temperature anomaly, degree_C)


St. Croix, U.S. Virgin Islands Coastal Digital Elevation Model (st croix 13 mhw 2014), 9.259259E-5°

St. Croix, U.S. Virgin Islands Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; 303-497-6826; 303-497-6513; 325 Broadway; Boulder; CO; 80305-3328; USA; ngdc.info@noaa.gov; custodian; DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; 303-497-6826; 303-497-6513; 325 Broadway; Boulder; CO; 80305-3328; USA; ngdc.info@noaa.gov; originator; NOAA NGDC, NESDIS, NOAA; originator


St. Thomas and St. John, U.S. Virgin Islands Coastal Digital Elevation Model, 9.259259E-5°

National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)


National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
Band1 (GDAL Band Number 1)


strait of juan de fuca 13 navd88 2015 (GDAL Band Number 1), 9.259259E-5°

GDAL Band Number 1. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1)


Strait of Juan de Fuca 36 sec Coastal Digital Elevation Model, 0.01°


Subset of NOAA/NCEI 1/4 Degree Daily Optimum Interpolation SST (OISST) Analysis, Version 2.1, 0.25°, 2020-present

Subset of NOAA/National Centers for Environmental Information (NCEI) 1/4 Degree Daily Optimum Interpolation Sea Surface Temperature (OISST) Analysis, Version 2.1. NOAAs 1/4-degree Daily Optimum Interpolation Sea Surface Temperature (OISST) (sometimes referred to as Reynolds SST, which however also refers to earlier products at different resolution), currently available as version v02r01, is created by interpolating and extrapolating SST observations from different sources, resulting in a smoothed complete field. The sources of data are satellite (Advanced Very High Resolution Radiometer (AVHRR)) and in situ platforms (i.e., ships and buoys), and the specific datasets employed may change over time. At the marginal ice zone, sea ice concentrations are used to generate proxy SSTs.  A preliminary version of this file is produced in near-real time (1-day latency), and then replaced with a final version after 2 weeks. Note that this is the AVHRR-ONLY DOISST, available from Oct 1981, but there is a companion DOISST product that includes microwave satellite data, available from June 2002. The present dataset has been modified by Atlantic OceanWatch to fit operational purposes.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Daily sea surface temperature, degree_C)
anom (Daily sea surface temperature anomalies, degree_C)


Surface CUrrents from a Diagnostic model (SCUD): Pacific

The SCUD data product is an estimate of upper-ocean velocities computed from a diagnostic model (Surface CUrrents from a Diagnostic model). This model makes daily estimates of ocean currents by combining geostrophic and Ekman currents. The estimate is computed through derived coefficients such that the results best match ocean drifting buoys. The currents therefore are a best-estimate of currents at 15 meters (drifting buoys are drogued at 15 meters). The dataset is intended to diagnose trajectories of a tracer floating near the surface such as marine debris, oil spills, etc. The data are provided on a 1/4-degree grid for the Pacific.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
u (sea water velocity: eastward component, meter second-1)
v (sea water velocity: northward component, meter second-1)

Pacific Islands Ocean Observing System (PacIOOS)


Surface CUrrents from a Diagnostic model (SCUD): Pacific, Lon+/-180


Synthetic temperature/salinity profiles for Hurricane EMILY., Preliminary, 0.5°, 2005

Synthetic temperature/salinity profiles for Hurricane EMILY. Quality Flag = Preliminary. This is an EXPERIMENTAL product

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
salinity (Sea Water Practical Salinity, PSU)
temperature (Sea Water Temperature, K)


Synthetic temperature/salinity profiles for Hurricane Rita., Preliminary, 0.5°, 2005

Synthetic temperature/salinity profiles for Hurricane Rita. Quality Flag = Preliminary. This is an EXPERIMENTAL product

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
salinity (Sea Water Practical Salinity, PSU)
temperature (Sea Water Temperature, K)


Synthetic temperature/salinity profiles for Hurricane Wilma., Preliminary, 0.5°, 2005

Synthetic temperature/salinity profiles for Hurricane Wilma. Quality Flag = Preliminary. This is an EXPERIMENTAL product

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
salinity (Sea Water Practical Salinity, PSU)
temperature (Sea Water Temperature, K)


Taholah, Washington Coastal Digital Elevation Model (taholah 13 mhw 2009), 9.259259E-5°

Taholah, Washington Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; NOAA NGDC, NESDIS, NOAA; Boulder; Colorado; publisher; NOAA NGDC, NESDIS, NOAA; originator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/512; Taholah, WA 1/3 arc-second Tsunami Inundation DEM; Download page for accessing DEM, metadata record and development report.; download; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/tsunami/inundation.html; NOAA Tsunami Inundation Gridding Project; Project web page.; information


Tampa Bay (G070) Bathymetric Digital Elevation Model (tampa bay G070 2017), 9.259259E-5°

Tampa Bay (G070) Bathymetric Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)


tampa bay 13 navd88 2014 (GDAL Band Number 1), 9.259259E-5°

GDAL Band Number 1. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [boundary]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [boundary]):
FSobc_in (free-surface inflow, nudging inverse time scale, second-1)
FSobc_out (free-surface outflow, nudging inverse time scale, second-1)
M2obc_in (2D momentum inflow, nudging inverse time scale, second-1)
M2obc_out (2D momentum outflow, nudging inverse time scale, second-1)
M3obc_in (3D momentum inflow, nudging inverse time scale, second-1)
M3obc_out (3D momentum outflow, nudging inverse time scale, second-1)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [boundary][tracer]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [boundary][tracer]):
Tobc_in (tracers inflow, nudging inverse time scale, second-1)
Tobc_out (tracers outflow, nudging inverse time scale, second-1)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [eta_psi][xi_psi]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [eta_psi][xi_psi]):
lon_psi (longitude of PSI-points, degrees_east)
lat_psi (latitude of PSI-points, degrees_north)
mask_psi (mask on PSI-points)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [eta_rho][xi_rho]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [eta_rho][xi_rho]):
lon_rho (longitude of RHO-points, degrees_east)
lat_rho (latitude of RHO-points, degrees_north)
h (time-independent bathymetry, meter)
f (Coriolis parameter, second-1)
pm (curvilinear coordinate metric in XI, meter-1)
pn (curvilinear coordinate metric in ETA, meter-1)
angle (angle between XI-axis and EAST, radians)
mask_rho (mask on RHO-points)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [eta_u][xi_u]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [eta_u][xi_u]):
lon_u (longitude of U-points, degrees_east)
lat_u (latitude of U-points, degrees_north)
mask_u (mask on U-points)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [eta_v][xi_v]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [eta_v][xi_v]):
lon_v (longitude of V-points, degrees_east)
lat_v (latitude of V-points, degrees_north)
mask_v (mask on V-points)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [s_rho]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [s_rho]):
Cs_r (S-coordinate stretching curves at RHO-points)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [s_w]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [s_w]):
Cs_w (S-coordinate stretching curves at W-points)


Tampa Bay Operational Forecast System (TBOFS): Forecast, Fields (Best Time Series) [tracer]

Tampa Bay Operational Forecast System (TBOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [tracer]):
nl_tnu2 (nonlinear model Laplacian mixing coefficient for tracers, meter2 second-1)
LtracerSponge (horizontal diffusivity sponge activation switch)
Akt_bak (background vertical mixing coefficient for tracers, meter2 second-1)
Tnudg (Tracers nudging/relaxation inverse time scale, day-1)
LtracerSrc (tracer point sources and sink activation switch)
LtracerCLM (tracer climatology processing switch)
LnudgeTCLM (tracer climatology nudging activation switch)


Tatitlek, Alaska Coastal Digital Elevation Model (tatitlek 815 mhhw 2011), 1.4814814E-4°

Tatitlek, Alaska Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; NOAA NGDC, NESDIS, NOAA; Boulder; Colorado; publisher; NOAA NGDC, NESDIS, NOAA; originator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/700; Tatitlek, AK 8/15 arc-second MHHW DEM; Download page for accessing DEM, metadata record, and development report; download


Sea surface temperature (SST) provides a measure of the surface ocean conditions, however no information about the subsurface ocean thermal structure (approximately the upper 50 m of the ocean) can be derived from SST alone. For instance, it is known that the oceanic skin temperature erodes when the sea surface is affected by strong winds, creating a well-mixed layer that can reach depths of several tens of meters. Moreover, warm ocean features, mainly anticyclonic rings and eddies, are characterized by a deepening of the isotherms towards their centers with a markedly different temperature and salinity structure than the surrounding waters. Several studies have shown that observations of sea surface height (SSH) are strongly correlated with the thermal structure of the upper ocean (e.g. Goni et al. 1996; Gilson et al. 1998; Mayer et al. 2001; Willis et al. 2004). Based in this virtually ubiquitous relationship, we developed a methodology to estimate fields of isotherm depth from the SHA fields derived from satellite observations.
 The Tropical Cyclone Heat Potential (TCHP), is defined as a measure of the integrated vertical temperature from the sea surface to the depth of the 26Â°C isotherm. This parameter is computed globally from the altimeter-derived vertical temperature profiles estimates in the upper ocean (Shay et al., 2000). Different methods have been developed to calculate this vertical thermal structure of the upper ocean.
 The Tropical Cyclone Heat Potential (TCHP) is made freely available by the Atlantic Oceanographic and Meteorological Laboratory (www.aoml.noaa.gov/phod/cyclone) and has been funded by the NASA and NOAA at different stages of the project.  The sea surface height and temperature products incorporated in the TCHP are supplied by CMEMS and Remote Sensing, USA (www.remss.com/tmi/) respectively.
 For technical questions, please contact Joaquin Trinanes (joaquin.trinanes@noaa.gov). For scientific questions, contact Gustavo Goni (gustavo.goni@noaa.gov).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Tropical_Cyclone_Heat_Potential (KJcm-2)
D26 (m)


Temperature, All Surface, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Daytime, 2006-present (Single Scan)

 NOAA CoastWatch provides surface temperature products derived from NOAA's Polar Operational Environmental Satellites (POES).  This data is provided at high resolution (0.0125 degrees) for the North Pacific Ocean.  Measurements are gathered by the Advanced Very High Resolution Radiometer (AVHRR) instrument, a multiband radiance sensor carried aboard the NOAA POES satellites. This product is provided before cloudmasking, and will contain sea surface temperature, land surface temperature, and cloud temperature data.

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


Temperature, All Surface, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Daytime, 2006-present (Single Scan), Lon+/-180


Temperature, All Surface, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Nighttime, 2006-present (Single Scan)


Temperature, All Surface, NOAA POES AVHRR, LAC, 0.0125 degrees, West US, Nighttime, 2006-present (Single Scan), Lon+/-180


National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
Band1 (GDAL Band Number 1)


Terrestrial Air Temperature and Precipitation: V4.01 (air.mon.mean.v501), 0.5°, 1900-2017

Terrestrial Air Temperature and Precipitation: V4.01 (air.mon.mean.v501)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (Monthly mean of surface temperature, degree_C)


Terrestrial Air Temperature and Precipitation: V4.01 (precip.mon.total.v501), 0.5°, 1900-2017

Terrestrial Air Temperature and Precipitation: V4.01 (precip.mon.total.v501)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Monthly total of precipitation, cm)


The GEBCO_2020 Grid, a continuous terrain model for oceans and land at 15 arc-second intervals

The GEBCO_2020 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals. The data in the GEBCO_2020 Grid should not be used for navigation or any purpose relating to safety at sea.

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


The GEBCO_2020 Grid, a continuous terrain model for oceans and land at 15 arc-second intervals, Lon0360


Tide Model (Barotropic) for the Pacific Ocean: Tidal Elevation

Barotropic tide model for the Pacific Ocean. The model is based on harmonics distributed by Oregon State University (OSU) and assimilates satellite altimetry data from TOPEX/Poseidon. It was generated using OSU Tidal Prediction Software (OTPS), modified locally by J. Potemra, using barotropic inverse tidal solutions from OSU. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ssh (tidal elevation, meters)

Pacific Islands Ocean Observing System (PacIOOS)


Tide Model (Barotropic) for the Pacific Ocean: Tidal Elevation, Lon+/-180


Tide Model (Barotropic) for the Pacific Ocean: Tidal Velocity

Barotropic tide model for the Pacific Ocean. The model is based on harmonics distributed by Oregon State University (OSU) and assimilates satellite altimetry data from TOPEX/Poseidon. It was generated using OSU Tidal Prediction Software (OTPS), modified locally by J. Potemra, using barotropic inverse tidal solutions from OSU. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Tide Model (Barotropic) for the Pacific Ocean: Tidal Velocity, Lon+/-180


Tide Model for the Big Island of Hawaii: Tidal Elevation

Tide model for the Big Island of Hawaii. The model is based on climatological stratification, but 64 harmonics are used to model the full-depth baroclinic tides. The model has been run at 1km resolution, hourly, through the end of 2025. Due to computing limitations, the model grid is divided into two pieces, one for the Northwestern main Hawaiian Islands (Kauai, Oahu, Maui) and the other for the Big Island. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ssh (tidal elevation, meters)


Tide Model for the Big Island of Hawaii: Tidal Velocity

Tide model for the Big Island of Hawaii. The model is based on climatological stratification, but 64 harmonics are used to model the full-depth baroclinic tides. The model has been run at 1km resolution, hourly, through the end of 2025. Due to computing limitations, the model grid is divided into two pieces, one for the Northwestern main Hawaiian Islands (Kauai, Oahu, Maui) and the other for the Big Island. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth_percent][latitude][longitude]):
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Tide Model for the Hawaiian Islands: Main NW Islands: Tidal Elevation

Tide model for the Hawaiian Islands. The model is based on climatological stratification, but 64 harmonics are used to model the full-depth baroclinic tides. The model has been run at 1km resolution, hourly, through the end of 2025. Due to computing limitations, the model grid is divided into two pieces, one for the Northwestern main Hawaiian Islands (Kauai, Oahu, Maui) and the other for the Big Island. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ssh (tidal elevation, meters)


Tide Model for the Hawaiian Islands: Main NW Islands: Tidal Velocity

Tide model for the Hawaiian Islands. The model is based on climatological stratification, but 64 harmonics are used to model the full-depth baroclinic tides. The model has been run at 1km resolution, hourly, through the end of 2025. Due to computing limitations, the model grid is divided into two pieces, one for the Northwestern main Hawaiian Islands (Kauai, Oahu, Maui) and the other for the Big Island. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use this output with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth_percent][latitude][longitude]):
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


tke.hl1.mon.ltm (Monthly NARR) [time][y][x], 0001

Monthly NARR (tke.hl1.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
tke (Long Term Monthly Mean Turbulent Kinetic Energy, J/kg)

National Centers for Environmental Prediction


Monthly NARR (tke.hl1.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (latitude coordinate, degrees_north)
lon (longitude coordinate, degrees_east)


tmp.0-10cm.mon.1981-2010.ltm (NCEP-NCAR Reanalysis 1), 0001

National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) Reanalysis 1. Data is from NCEP initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
tmp (Monthly Long Term Mean Temperature between 0-10 cm below ground level, degree_C)
valid_yr_count (count of non-missing values used in mean)


4x daily National Meteorological Center (NMC) reanalysis (1981). Data is from NMC initialized reanalysis
(4x/day).  It consists of T62 variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
tmp (Long Term Mean 4xDaily Temperature between 10-200 cm below ground level, degree_C)
valid_yr_count (count of non-missing values used in mean)


tmp.10-200cm.mon.1981-2010.ltm (NCEP-NCAR Reanalysis 1), 0001

National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) Reanalysis 1. Data is from NCEP initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
tmp (Monthly Long Term Mean Temperature between 10-200 cm below ground level, degree_C)
valid_yr_count (count of non-missing values used in mean)


tmp.300cm.mon.1981-2010.ltm (NCEP-NCAR Reanalysis 1), 0001

National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) Reanalysis 1. Data is from NCEP initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
tmp (Monthly Long Term Mean Temperature at 300 cm below ground level, degree_C)
valid_yr_count (count of non-missing values used in mean)


Toke Point, Washington Tsunami Forecast Grids for MOST Model (TokePointWA A), 0.02°

Toke Point, Washington Tsunami Forecast Grids for MOST Model. Pacific Marine Environmental Laboratory (PMEL) Forecast Model Grids provide bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a suite of numerical simulation codes capable of simulating three processes of tsunami evolution: generation, transoceanic propagation, and inundation of dry land. Tsunami waves are computationally propagated across a set of three nested grids (A, B, and C), each of which is successively finer in resolution, moving from offshore to onshore. Nearshore details are resolved to the point that model output can be directly compared with tide gauge observations and can provide estimates of wave arrival time, wave amplitude and simulation of wave inundation onto dry land.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
bathy (Grid Bathymetry, meters)

NOAA OAR PMEL Center for Tsunami Research


Toke Point, Washington Tsunami Forecast Grids for MOST Model (TokePointWA B), 0.0033333334°


Toke Point, Washington Tsunami Forecast Grids for MOST Model (TokePointWA C), 5.5555557E-4°


Tomales Bay (P110) Bathymetric Digital Elevation Model (tomales bay P110 2018), 9.259259E-5°

Tomales Bay (P110) Bathymetric Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)


Topography Grid (niue 3 isl 2016), 8.3333335E-4°

Topography Grid. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
z (Topography, m)


Topography, ETOPO1, 0.0166667 degrees, Global (longitude -180 to 180), (Ice Sheet Surface)

ETOPO1 is a 1 arc-minute global relief model of Earth's surface that integrates land topography and ocean bathymetry. It was built from numerous global and regional data sets. This is the 'Ice Surface' version, with the top of the Antarctic and Greenland ice sheets. The horizontal datum is WGS-84, the vertical datum is Mean Sea Level. Keywords: Bathymetry, Digital Elevation. This is the grid/node-registered version: the dataset's latitude and longitude values mark the centers of the cells.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
altitude (m)


Topography, ETOPO1, 0.0166667 degrees, Global (longitude 0 to 360), (Ice Sheet Surface)


Tutuila, American Samoa 1/3 arc-second Coastal Digital Elevation Model (tutuila 13 mhw 2013), 9.259259E-5°

Tutuila, American Samoa 1/3 arc-second Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)

NTHMP; originator; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/nthmp/nthmp.html; http:; National Tsunami Hazard Mitigation Program DEMs; Home page; information


U.S. Virgin Islands Coastal Digital Elevation Model (usvi 1 mhw 2014), 2.7777778E-4°

U.S. Virgin Islands Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; 303-497-6826; 303-497-6513; 325 Broadway; Boulder; CO; 80305-3328; USA; ngdc.info@noaa.gov; custodian; DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; 303-497-6826; 303-497-6513; 325 Broadway; Boulder; CO; 80305-3328; USA; ngdc.info@noaa.gov; originator; NOAA NGDC, NESDIS, NOAA; originator


uflx.sfc.mon.1981-2010.ltm (4x daily NMC reanalysis), 0001

4x daily National Meteorological Center (NMC) reanalysis. Data is from NMC initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uflx (Monthly Long Term Mean of Momentum Flux, U-Component, N/m^2)
valid_yr_count (count of non-missing values used in mean)


ugwd.sfc.mon.1981-2010.ltm (4x daily NMC reanalysis), 0001

4x daily National Meteorological Center (NMC) reanalysis. Data is from NMC initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ugwd (Monthly Long Term Mean of Zonal Gravity Wave Stress, N/m^2)
valid_yr_count (count of non-missing values used in mean)


ulwrf.ntat.mon.ltm (Monthly NARR) [time][y][x], 0001

Monthly NARR (ulwrf.ntat.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
ulwrf (Long Term Monthly Mean Upward Longwave Radiation Flux, W/m^2)

National Centers for Environmental Prediction


ulwrf.ntat.mon.ltm (Monthly NARR) [y][x]

Monthly NARR (ulwrf.ntat.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (latitude coordinate, degrees_north)
lon (longitude coordinate, degrees_east)


ulwrf.ntat.mon.mean (NARR Monthly Means) [time][y][x], 1979-present

NARR Monthly Means (ulwrf.ntat.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
ulwrf (Monthly Upward Longwave Radiation Flux, W/m^2)


ulwrf.ntat.mon.mean (NARR Monthly Means) [y][x]

NARR Monthly Means (ulwrf.ntat.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (Latitude, degrees_north)
lon (Longitude, degrees_east)


ulwrf.sfc.mon.1981-2010.ltm (4x daily NMC reanalysis), 0001

4x daily National Meteorological Center (NMC) reanalysis. Data is from NMC initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ulwrf (Monthly Long Term Mean of Upward Longwave Radiation Flux, W/m^2)
valid_yr_count (count of non-missing values used in mean)


ulwrf.sfc.mon.ltm (Monthly NARR) [time][y][x], 0001

Monthly NARR (ulwrf.sfc.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
ulwrf (Long Term Monthly Mean Upward Longwave Radiation Flux at Surface, W/m^2)


Monthly NARR (ulwrf.sfc.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (latitude coordinate, degrees_north)
lon (longitude coordinate, degrees_east)


National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
Band1 (GDAL Band Number 1)


Unalaska, Alaska Coastal Digital Elevation Model (unalaska 815 mhhw 2012), 1.4814814E-4°

Unalaska, Alaska Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
Band1 (GDAL Band Number 1, meters)

NTHMP; originator; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/nthmp/nthmp.html; http:; National Tsunami Hazard Mitigation Program DEMs; Home page; information


Unalaska, Alaska Tsunami Forecast Grids for MOST Model (UnalaskaAK A)

Unalaska, Alaska Tsunami Forecast Grids for MOST Model. Pacific Marine Environmental Laboratory (PMEL) Forecast Model Grids provide bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST is a suite of numerical simulation codes capable of simulating three processes of tsunami evolution: generation, transoceanic propagation, and inundation of dry land. Tsunami waves are computationally propagated across a set of three nested grids (A, B, and C), each of which is successively finer in resolution, moving from offshore to onshore. Nearshore details are resolved to the point that model output can be directly compared with tide gauge observations and can provide estimates of wave arrival time, wave amplitude and simulation of wave inundation onto dry land.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
bathy (Grid Bathymetry, meters)

NOAA OAR PMEL Center for Tsunami Research


Unalaska, Alaska Tsunami Forecast Grids for MOST Model (UnalaskaAK B), 0.005°


Unalaska, Alaska Tsunami Forecast Grids for MOST Model (UnalaskaAK C)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (upstr.ltm). NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads2.5/2degree/enh/LTMs1950-1979/upstr.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upstr (u-wind pseudoStress Monthly Long Term Mean at Surface, m^2/s^2)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (upstr.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/coads/2degree/enh/LTMs1950-1979/upstr.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upstr (u-wind pseudoStress Monthly Long Term Mean at Surface, m^2/s^2)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (upstr.ltm). NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads2.5/2degree/LTMs1950-1979/upstr.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upstr (u-wind pseudoStress Monthly Long Term Mean at Surface, m^2/s^2)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (upstr.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads/2degree/LTMs1950-1979/upstr.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upstr (u-wind pseudoStress Monthly Long Term Mean at Surface, m^2/s^2)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (upstr.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/coads/2degree/LTMs1950-1979/upstr.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upstr (u-wind pseudoStress Monthly Long Term Mean at Surface, m^2/s^2)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (upstr.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads/2degree/enh/LTMs1950-1979/upstr.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upstr (u-wind pseudoStress Monthly Long Term Mean at Surface, m^2/s^2)


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 21N 107W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 21N 107W, monthly, m^3/s/100m coastline)

NOAA/SWFSC Environmental Research Division


Upwelling Index, 21N 107W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 24N 113W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 24N 113W, monthly, m^3/s/100m coastline)


Upwelling Index, 24N 113W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 27N 116W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 27N 116W, monthly, m^3/s/100m coastline)


Upwelling Index, 27N 116W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 30N 119W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 30N 119W, monthly, m^3/s/100m coastline)


Upwelling Index, 30N 119W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 33N 119W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 33N 119W, monthly, m^3/s/100m coastline)


Upwelling Index, 33N 119W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 36N 122W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 36N 122W, monthly, m^3/s/100m coastline)


Upwelling Index, 36N 122W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 39N 125W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 39N 125W, monthly, m^3/s/100m coastline)


Upwelling Index, 39N 125W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 42N 125W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 42N 125W, monthly, m^3/s/100m coastline)


Upwelling Index, 42N 125W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 45N 125W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 45N 125W, monthly, m^3/s/100m coastline)

NOAA/SWFSC Environmental Research Division


Upwelling Index, 45N 125W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 48N 125W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 48N 125W, monthly, m^3/s/100m coastline)


Upwelling Index, 48N 125W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 51N 131W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 51N 131W, monthly, m^3/s/100m coastline)


Upwelling Index, 51N 131W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 54N 134W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 54N 134W, monthly, m^3/s/100m coastline)


Upwelling Index, 54N 134W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 57N 137W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 57N 137W, monthly, m^3/s/100m coastline)


Upwelling Index, 57N 137W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 60N 146W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 60N 146W, monthly, m^3/s/100m coastline)


Upwelling Index, 60N 146W, monthly, Lon+/-180


Upwelling index computed from FNMOC sea level pressure for 15 locations off the North American West Coast at each 3 degrees of latitude from 21N to 60N. The coastal Upwelling Index is an index of the strength of the wind forcing on the ocean which has been used in many studies of the effects of ocean variability on the reproductive and recruitment success of many fish and invertebrate species.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
upwelling_index (Upwelling Index, 60N 149W, monthly, m^3/s/100m coastline)
upwelling_index_anomaly (Upwelling Index Anomaly, 60N 149W, monthly, m^3/s/100m coastline)


Upwelling Index, 60N 149W, monthly, Lon+/-180


USDOC/NOAA/NESDIS ECDC USC Vibrio Risk Analysis (VIBRIO RISK CUMULATIVE), 0.05°, 2014-present

United States Department of Commerce (USDOC)/NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) ECDC USC Vibrio Risk Analysis. This is a collaborative project involving NOAA CoastWatch, the European Centre for Disease Prevention and Control ECDC and the Universidade de Santiago de Compostela

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


USDOC/NOAA/NESDIS ECDC USC Vibrio Risk Analysis FORECAST (VIBRIO RISK FORECAST), 0.05°, 2021-present

United States Department of Commerce (USDOC)/NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) ECDC USC Vibrio Risk Analysis FORECAST. This is a collaborative project involving NOAA CoastWatch, the European Centre for Disease Prevention and Control ECDC and the Universidade de Santiago de Compostela

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


USDOC/NOAA/NESDIS ECDC USC Vibrio Risk Analysis, 0.05°, 2013-present

This is a collaborative project involving NOAA CoastWatch, the European Centre for Disease Prevention and Control ECDC and the Universidade de Santiago de Compostela

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


USF Daily AFAI Fields (USF AFAI AOML), 2016-present

University of South Florida (USF) Daily AFAI Fields. AFAI: Alternate Floating Algae Index (in reflectance units) to detect ocean surface features such as Sargassum, green macroalgae, and cyanobacteria. AFAI is estimated by Chuanmin Hu (USF). AFAI is sensitive to detect subtle ocean surface features, but it saturates under sun glint, clouds, or thick aerosols. Reference: Hu, C., L. Feng, R. F. Hardy, and E. J. Hochberg (2015). Spectral and spatial requirements of remote measurements of pelagic Sargassum macro algae. Remote Sens. Environ. 167:229-246. doi:10.1016/j.rse.2015.05.022.
For technical questions, please contact Joaquin Trinanes (joaquin.trinanes@noaa.gov). For scientific questions, contact Chuanmin Hu (huc@usf.edu).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
AFAI (AFAI (Alternative Floating Algae Index))


USGS 10-m Digital Elevation Model (DEM): American Samoa: Ofu and Olosega

A 10-meter resolution land surface digital elevation model (DEM) for the Manua Islands of Ofu and Olosega in American Samoa from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "as_usgs_ofuolo_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): American Samoa: Tau

A 10-meter resolution land surface digital elevation model (DEM) for the Manua Island of Tau in American Samoa from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "as_usgs_tau_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): American Samoa: Tutuila

A 10-meter resolution land surface digital elevation model (DEM) for the island of Tutuila in American Samoa from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "as_usgs_tutaun_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): CNMI: Aguijan

A 10-meter resolution land surface digital elevation model (DEM) for the island of Aguijan in the Commonwealth of the Northern Mariana Islands (CNMI) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "mp_usgs_agu_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): CNMI: Rota

A 10-meter resolution land surface digital elevation model (DEM) for the island of Rota in the Commonwealth of the Northern Mariana Islands (CNMI) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "mp_usgs_rot_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): CNMI: Saipan

A 10-meter resolution land surface digital elevation model (DEM) for the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "mp_usgs_sai_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): CNMI: Tinian

A 10-meter resolution land surface digital elevation model (DEM) for the island of Tinian in the Commonwealth of the Northern Mariana Islands (CNMI) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "mp_usgs_tin_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): FSM: Chuuk

A 10-meter resolution land surface digital elevation model (DEM) for the islands of Chuuk in the Federated States of Micronesia (FSM) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "fm_usgs_chu_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): FSM: Kosrae

A 10-meter resolution land surface digital elevation model (DEM) for the island of Kosrae in the Federated States of Micronesia (FSM) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "fm_usgs_kos_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): FSM: Pohnpei

A 10-meter resolution land surface digital elevation model (DEM) for the island of Pohnpei in the Federated States of Micronesia (FSM) from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "fm_usgs_poh_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Guam

A 10-meter resolution land surface digital elevation model (DEM) for the island of Guam from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "gu_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Big Island

A 10-meter resolution land surface digital elevation model (DEM) for Big Island in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_bigi_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Kahoolawe

A 10-meter resolution land surface digital elevation model (DEM) for the island of Kahoolawe in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_kaho_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Kauai

A 10-meter resolution land surface digital elevation model (DEM) for the island of Kauai in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_kaua_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Lanai

A 10-meter resolution land surface digital elevation model (DEM) for the island of Lanai in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_lana_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Maui

A 10-meter resolution land surface digital elevation model (DEM) for the island of Maui in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_maui_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Molokai

A 10-meter resolution land surface digital elevation model (DEM) for the island of Molokai in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_molo_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Niihau

A 10-meter resolution land surface digital elevation model (DEM) for the island of Niihau in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_niih_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Hawaii: Oahu

A 10-meter resolution land surface digital elevation model (DEM) for the island of Oahu in Hawaii from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "hi_usgs_oahu_dem10m_hillshade" and "hi_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


USGS 10-m Digital Elevation Model (DEM): Palau

A 10-meter resolution land surface digital elevation model (DEM) for the islands of Palau from U.S. Geological Survey (USGS) 1/3 arc-second DEM quadrangles. For a grayscale hillshade image layer of this dataset, see "pw_usgs_all_dem10m_hillshade" in the distribution links listed in the metadata.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
elev (elevation, meters)


uswrf.ntat.mon.ltm (Monthly NARR) [time][y][x], 0001

Monthly NARR (uswrf.ntat.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
uswrf (Long Term Monthly Mean Upward Shortwave Radiation Flux, W/m^2)

National Centers for Environmental Prediction


uswrf.ntat.mon.ltm (Monthly NARR) [y][x]

Monthly NARR (uswrf.ntat.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (latitude coordinate, degrees_north)
lon (longitude coordinate, degrees_east)


uswrf.ntat.mon.mean (NARR Monthly Means) [time][y][x], 1979-present

NARR Monthly Means (uswrf.ntat.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
uswrf (Monthly Upward Shortwave Radiation Flux, W/m^2)


uswrf.ntat.mon.mean (NARR Monthly Means) [y][x]

NARR Monthly Means (uswrf.ntat.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (Latitude, degrees_north)
lon (Longitude, degrees_east)


uswrf.sfc.mon.1981-2010.ltm (NCEP-NCAR Reanalysis 1), 0001

National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) Reanalysis 1. Data is from NCEP initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uswrf (Monthly Long Term Mean Upward Solar Radiation Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


uswrf.sfc.mon.ltm (Monthly NARR) [time][y][x], 0001

Monthly NARR (uswrf.sfc.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
uswrf (Long Term Monthly Mean Upward Shortwave Radiation Flux at Surface, W/m^2)


Monthly NARR (uswrf.sfc.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (latitude coordinate, degrees_north)
lon (longitude coordinate, degrees_east)


uwnd.10m.day.ltm (Daily NARR) [time][y][x], 0001

Daily NARR (uwnd.10m.day.ltm). National Centers for Environmental Prediction data from https://psl.noaa.gov/thredds/dodsC/Datasets/NARR/Derived/monolevel/uwnd.10m.day.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
uwnd (Daily long term mean u-wind at 10 m: Smoothed, m/s)


Daily NARR (uwnd.10m.day.ltm). National Centers for Environmental Prediction data from https://psl.noaa.gov/thredds/dodsC/Datasets/NARR/Derived/monolevel/uwnd.10m.day.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (latitude coordinate, degrees_north)
lon (longitude coordinate, degrees_east)


uwnd.10m.mon.1981-2010.ltm (monthly mean u wind), 0001

monthly mean u wind. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of T62 variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (Monthly Long Term Mean of U-Wind, m/s)
valid_yr_count (count of non-missing values used in mean)


uwnd.10m.mon.ltm (Monthly NARR) [time][y][x], 0001

Monthly NARR (uwnd.10m.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
uwnd (Monthly Long Term Mean u-wind at 10 m, m/s)

National Centers for Environmental Prediction


Monthly NARR (uwnd.10m.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [y][x]):
lat (latitude coordinate, degrees_north)
lon (longitude coordinate, degrees_east)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (uwnd.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/coads/2degree/enh/LTMs1950-1979/uwnd.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind Monthly Long Term Mean at Surface, m/s)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (uwnd.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads/2degree/enh/LTMs1950-1979/uwnd.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind Monthly Long Term Mean at Surface, m/s)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (uwnd.ltm). NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads2.5/2degree/LTMs1950-1979/uwnd.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind Monthly Long Term Mean at Surface, m/s)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (uwnd.ltm). NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads2.5/2degree/enh/LTMs1950-1979/uwnd.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind Monthly Long Term Mean at Surface, m/s)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (uwnd.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/icoads/2degree/LTMs1950-1979/uwnd.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind Monthly Long Term Mean at Surface, m/s)


Comprehensive Ocean Atmosphere Data Set 1 (COADS1) (uwnd.ltm). NOAA International Comprehensive Ocean Atmosphere Data Set (ICOADS) data from https://psl.noaa.gov/thredds/dodsC/Datasets/coads/2degree/LTMs1950-1979/uwnd.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind Monthly Long Term Mean at Surface, m/s)


vbdsf.sfc.mon.1981-2010.ltm (NCEP-NCAR Reanalysis 1), 0001

National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) Reanalysis 1. Data is from NCEP initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vbdsf (Monthly Long Term Mean Visible Beam Downward Solar Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


vddsf.sfc.mon.1981-2010.ltm (NCEP-NCAR Reanalysis 1), 0001

National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) Reanalysis 1. Data is from NCEP initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vddsf (Monthly Long Term Mean Visible Diffuse Downward Solar Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


vflx.sfc.mon.1981-2010.ltm (4x daily NMC reanalysis), 0001

4x daily National Meteorological Center (NMC) reanalysis. Data is from NMC initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vflx (Monthly Long Term Mean of Momentum Flux, V-Component, N/m^2)
valid_yr_count (count of non-missing values used in mean)


vgwd.sfc.mon.1981-2010.ltm (4x daily NMC reanalysis), 0001

4x daily National Meteorological Center (NMC) reanalysis. Data is from NMC initialized reanalysis
(4x/day).  It consists of T42  variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vgwd (Monthly Long Term Mean of Meridional Gravity Wave Stress, N/m^2)
valid_yr_count (count of non-missing values used in mean)


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, R2018, 2012-present, 8-Day

R2018 version of Level-3 Standard Mapped Image (SMI), Global, 4km, Chlorophyll a, OCI Algorithm, 8-Day composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2017-12-12.)

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


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, R2018, 2012-present, 8-Day, Lon0360


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, R2018, 2012-present, Daily

R2018 version of Level-3 Standard Mapped Image (SMI), Global, 4km, Chlorophyll a, OCI Algorithm, Daily composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2017-12-12.)

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


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, R2018, 2012-present, Daily, Lon0360


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, R2018, 2012-present, Monthly

R2018 version of Level-3 Standard Mapped Image (SMI), Global, 4km, Chlorophyll a, OCI Algorithm, Monthly composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2017-12-12.)

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


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, R2018, 2012-present, Monthly, Lon0360


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, v2016, 2012-2017, 8-Day, DEPRECATED

THIS VERSION WAS DISCONTINUED on 2017-12-01. SEE THE NEW erdVH2018 DATASETS. Level-3 Standard Mapped Image (SMI), Global, 4km, Chlorophyll a, OCI Algorithm, 8-Day composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2016-04-01.)

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


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, v2016, 2012-2017, 8-Day, DEPRECATED, Lon0360


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, v2016, 2012-2017, Daily, DEPRECATED

THIS VERSION WAS DISCONTINUED on 2017-12-01. SEE THE NEW erdVH2018 DATASETS. Level-3 Standard Mapped Image (SMI), Global, 4km, Chlorophyll a, OCI Algorithm, Daily composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2016-04-01.)

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


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, v2016, 2012-2017, Daily, DEPRECATED, Lon0360


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, v2016, 2012-2017, Monthly, DEPRECATED

THIS VERSION WAS DISCONTINUED on 2017-12-01. SEE THE NEW erdVH2018 DATASETS. Level-3 Standard Mapped Image (SMI), Global, 4km, Chlorophyll a, OCI Algorithm, Monthly composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2016-04-01.)

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


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, Chlorophyll a, OCI Algorithm, v2016, 2012-2017, Monthly, DEPRECATED, Lon0360


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, K490, R2018, 2012-present, 8-Day

R2018 version of Level-3 Standard Mapped Image (SMI), Global, 4km, Diffuse Attenuation Coefficient K490, 8-Day composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2017-12-12.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
k490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m^-1)


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, K490, R2018, 2012-present, 8-Day, Lon0360


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, K490, R2018, 2012-present, Daily

R2018 version of Level-3 Standard Mapped Image (SMI), Global, 4km, Diffuse Attenuation Coefficient K490, Daily composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2017-12-12.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
k490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m^-1)


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, K490, R2018, 2012-present, Daily, Lon0360


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, K490, R2018, 2012-present, Monthly

R2018 of Level-3 Standard Mapped Image (SMI), Global, 4km, Diffuse Attenuation Coefficient K490, Monthly composite data from the Visible and Infrared Imager/Radiometer Suite (VIIRS), as processed by NASA GSFC Ocean Biology Processing Group (OBPG). VIIRS is a multi-disciplinary instrument that flies on the Suomi-NPP (National Polar-orbiting Partnership) satellite.  Suomi-NPP is the initial spacecraft in the JPSS (Joint Polar Satellite Systems) series of spacecraft. JPSS is our Nation's next generation polar-orbiting operational environmental satellite system. JPSS is a collaborative program between NOAA and its acquisition agent NASA. VIIRS is the successor to MODIS for Earth science data product generation. (This version of the VH data was first released on 2017-12-12.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
k490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m^-1)


VIIRSN, Suomi-NPP, Level-3 SMI, NASA, Global, 4km, K490, R2018, 2012-present, Monthly, Lon0360