cprat.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]):
cprat (Monthly Long Term Mean Convective Precipitation Rate at surface, Kg/m^2/s)
valid_yr_count (count of non-missing values used in mean)


Craig and Klawock, Alaska 8/15 sec Coastal Digital Elevation Model, 1.4814814E-4°

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)


Craig, Alaska Coastal Digital Elevation Model (craig 13 mhw 2012), 9.259259E-5°

Craig, 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/3548; Craig, AK 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


Craig, Alaska Tsunami Forecast Grids for MOST Model (ChignikAK A)

Craig, 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


Craig, Alaska Tsunami Forecast Grids for MOST Model (ChignikAK B)


Craig, Alaska Tsunami Forecast Grids for MOST Model (ChignikAK C)


Craig, Alaska Tsunami Forecast Grids for MOST Model (CraigAK A), 0.033333335°


Craig, Alaska Tsunami Forecast Grids for MOST Model (CraigAK B), 0.0033333334°


Craig, Alaska Tsunami Forecast Grids for MOST Model (CraigAK C), 8.3333335E-4°


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

Monthly NARR (crain.mon.ltm). National Centers for Environmental Prediction data from https://psl.noaa.gov/thredds/dodsC/Datasets/NARR/Derived/monolevel/crain.mon.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
crain (Long Term Monthly Mean Categorical Rain at Surface, 1)


Monthly NARR (crain.mon.ltm). National Centers for Environmental Prediction data from https://psl.noaa.gov/thredds/dodsC/Datasets/NARR/Derived/monolevel/crain.mon.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)


created 05/2014 from data provided by JRA (icec.mon.ltm.1981-2010), 1.0°, 0001

created 05/2014 from data provided by Japanese Reanalysis (JRA) (icec.mon.ltm.1981-2010)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
icec (Long Term Mean Monthly Means of Global Ice Concentration, fr)
valid_yr_count (count of non-missing values used in mean)


created 05/2014 from data provided by JRA (icec.mon.mean), 1.0°, 1850-2019

created 05/2014 from data provided by Japanese Reanalysis (JRA) (icec.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
icec (Monthly Means of Global Ice Concentration, fr)


created 12/2013 from data provided by JRA (sst.mon.ltm.1981-2010), 1.0°, 0001

created 12/2013 from data provided by Japanese Reanalysis (JRA) (sst.mon.ltm.1981-2010)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Long Term Mean Monthly Means of Global Sea Surface Temperature, degree_C)
valid_yr_count (count of non-missing values used in mean)


created 12/2013 from data provided by JRA (sst.mon.mean), 1.0°, 1850-2019

created 12/2013 from data provided by Japanese Reanalysis (JRA) (sst.mon.mean)

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


Crescent City, California Coastal Digital Elevation Model (crescent city 13 mhw 2010), 9.259259E-5°

Crescent City, California 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/693; Crescent City, CA 1/3 arc-second MHW 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


Crescent City, California Coastal Digital Elevation Model (crescent city 13 navd88 2010), 9.259259E-5°

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/724; Crescent City, CA 1/3 arc-second NAVD 88 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


Crescent City, California Tsunami Forecast Grids for MOST Model (CrescentCityCA A), 0.02°

Crescent City, California 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


Crescent City, California Tsunami Forecast Grids for MOST Model (CrescentCityCA B), 0.0033333334°


Crescent City, California Tsunami Forecast Grids for MOST Model (CrescentCityCA C), 5.5555557E-4°


crm socal 1as vers2 (GDAL Band Number 1), 2.7777778E-4°

GDAL Band Number 1. National Geophysical Data Center (NGDC)'s 3 arc-second U.S. Coastal Relief Model (CRM) provides the first comprehensive view of the U.S. coastal zone, integrating offshore bathymetry with land topography into a seamless representation of the coast. The CRM spans the U.S. East and West Coasts, the northern coast of the Gulf of Mexico, Puerto Rico, and Hawaii, reaching out to, and in places even beyond, the continental slope. Bathymetric and topographic data sources include: NGDC's National Ocean Service (NOS) hydrographic surveys, multibeam bathymetry, and trackline bathymetry; the U.S. Geological Survey (United States Geological Survey (USGS)); and other federal government agencies and academic institutions.

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


crm socal 3as vers2 (GDAL Band Number 1), 8.3333335E-4°


CRU Combined Surface/Marine Air Temperature Climatology 1961-1990. (air.mon.ltm), 5.0°, 0001

Climatic Research Unit (CRU) Combined Surface/Marine Air Temperature Climatology 1961-1990. (air.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRU Combined Surface/Marine Air Temperature Monthly Climatology, degree_C)


CRUTEM4 Air Temperature Dataset (air.mon.anom), 5.0°, 1850-present

Climatic Research Unit CRUTEM4 Air Temperature Dataset. This dataset supersedes V3. NOAA Earth System Research Laboratory (ESRL) data from https://psl.noaa.gov/thredds/dodsC/Datasets/cru/crutem4/std/air.mon.anom.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRUTEM4: Surface Air Temperature Monthly Anomaly, degree_C)


Climatic Research Unit CRUTEM4 Air Temperature Dataset. This dataset supersedes V3. NOAA Earth System Research Laboratory (ESRL) data from https://psl.noaa.gov/thredds/dodsC/Datasets/cru/crutem4/var/air.mon.anom.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRUTEM4V: Surface Air Temperature Monthly Anomaly Variance Adjusted, degree_C)


CRUTEM4 Air Temperature Dataset (air.mon.anom.biased2.5), 5.0°, 1850-present

Climatic Research Unit CRUTEM4 Air Temperature Dataset. This dataset supersedes V3. NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/cru/crutem4/std/air.mon.anom.biased2.5.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRUTEM4: Surface Air Temperature Monthly 2.5 Bias Anomaly, degree_C)


CRUTEM4 Air Temperature Dataset (air.mon.anom.biased97.5), 5.0°, 1850-present

Climatic Research Unit CRUTEM4 Air Temperature Dataset. This dataset supersedes V3. NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/cru/crutem4/std/air.mon.anom.biased97.5.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRUTEM4: Surface Air Temperature Monthly 97.5 Bias Anomaly, degree_C)


CRUTEM4 Air Temperature Dataset (air.mon.anom.nobs), 5.0°, 1850-present

Climatic Research Unit CRUTEM4 Air Temperature Dataset. This dataset supersedes V3. NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/cru/crutem4/std/air.mon.anom.nobs.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRUTEM4: Surface Air Temperature Monthly Number of Observations, observations)


CRUTEM4 Air Temperature Dataset (air.mon.anom.samplingerror), 5.0°, 1850-present

Climatic Research Unit CRUTEM4 Air Temperature Dataset. This dataset supersedes V3. NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/cru/crutem4/std/air.mon.anom.samplingerror.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRUTEM4: Surface Air Temperature Monthly Sampling Error, degree_C)


CRUTEM4 Air Temperature Dataset (air.mon.anom.stationerror), 5.0°, 1850-present

Climatic Research Unit CRUTEM4 Air Temperature Dataset. This dataset supersedes V3. NOAA PSL data from https://psl.noaa.gov/thredds/dodsC/Datasets/cru/crutem4/std/air.mon.anom.stationerror.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRUTEM4: Surface Air Temperature Monthly Station Errors, degree_C)


CRUTEM4 Air Temperature Dataset (air.mon.mean), 5.0°, 1851-2018

Climatic Research Unit CRUTEM4 Air Temperature Dataset. This dataset supersedes V3. NOAA Earth System Research Laboratory (ESRL) data from https://psl.noaa.gov/thredds/dodsC/Datasets/cru/crutem4/std/air.mon.mean.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (CRUTEM4: Surface Air Temperature Monthly Anomaly, degree_C)


csdlf.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]):
csdlf (Monthly Long Term Mean of Clear Sky Downward Longwave Flux, W/m^2)
valid_yr_count (count of non-missing values used in mean)


csdsf.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]):
csdsf (Monthly Long Term Mean of Clear Sky Downward Solar Flux, W/m^2)
valid_yr_count (count of non-missing values used in mean)


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

Monthly NARR (csnow.mon.ltm). National Centers for Environmental Prediction data from https://psl.noaa.gov/thredds/dodsC/Datasets/NARR/Derived/monolevel/csnow.mon.ltm.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
csnow (Long Term Monthly Mean Categorical Snow at Surface, 1)


Monthly NARR (csnow.mon.ltm). National Centers for Environmental Prediction data from https://psl.noaa.gov/thredds/dodsC/Datasets/NARR/Derived/monolevel/csnow.mon.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)


csusf.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]):
csusf (Long Term Mean Monthly Mean of Clear Sky Upward Solar Flux, W/m^2)
valid_yr_count (count of non-missing values used in mean)


CT2007B.molefrac. NOAA Earth System Research Laboratory (ESRL) data from https://psl.noaa.gov/thredds/dodsC/Datasets/CarbonTracker/CT2007B.molefrac.nc.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
co2 (Mole Fraction Of Carbon Dioxide In Air, micromol mol-1)
pressure (Air Pressure, pascal)


Currents, Geostrophic, Aviso, 0.25 degrees, Global, 1992-2009 (Monthly Composite)

Aviso Zonal Geostrophic Current is inferred from Sea Surface Height Deviation, climatological dynamic height, and basic fluid mechanics.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
u_current (Eastward Sea Water Velocity, m s-1)
v_current (Northward Sea Water Velocity, m s-1)


Currents, Geostrophic, Aviso, 0.25 degrees, Global, 1992-2009 (Monthly Composite), Lon+/-180


Currents, Geostrophic, Aviso, 0.25 degrees, Global, 1992-2012 (1 Day Composite)


Currents, Geostrophic, Aviso, 0.25 degrees, Global, 1992-2012 (1 Day Composite), Lon+/-180


Currents, HF Radar, Alaska - North Slope, RTV, Near-Real Time, 2010-present, Hourly, 6km

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_radials (number of contributing radials, count)

Coastal Observing Research and Development Center, Scripps Institution of Oceanography


Currents, HF Radar, Alaska - North Slope, RTV, Near-Real Time, 2010-present, Hourly, 6km, Lon0360


Currents, HF Radar, Puerto Rico and the US Virgin Islands, RTV, Near-Real Time, 2012-present, Hourly, 2km

Surface ocean velocities estimated from HF-Radar are representative
of the upper 1.0 meters of the ocean.  The main objective of
near-real time processing is to produce the best product from
available data at the time of processing.  Radial velocity
measurements are obtained from individual radar sites through the
U.S. HF-Radar Network. Hourly radial data are processed by unweighted
least squares on a 2km resolution grid of the Puerto Rico and the
Virgin Islands to produce near real-time surface current maps.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, Puerto Rico and the US Virgin Islands, RTV, Near-Real Time, 2012-present, Hourly, 2km, Lon0360


Currents, HF Radar, Puerto Rico and the US Virgin Islands, RTV, Near-Real Time, 2012-present, Hourly, 6km

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, Puerto Rico and the US Virgin Islands, RTV, Near-Real Time, 2012-present, Hourly, 6km, Lon0360


Currents, HF Radar, US East Coast and Gulf of Mexico, RTV, Near-Real Time, 2012-present, Hourly, 1km

Surface ocean velocities estimated from HF-Radar are representative
of the upper 0.5 meters of the ocean.  The main objective of
near-real time processing is to produce the best product from
available data at the time of processing.  Radial velocity
measurements are obtained from individual radar sites through the
U.S. HF-Radar Network. Hourly radial data are processed by unweighted
least squares on a 1km resolution grid of the U.S. East and Gulf
Coast to produce near real-time surface current maps.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, US East Coast and Gulf of Mexico, RTV, Near-Real Time, 2012-present, Hourly, 1km, Lon0360


Currents, HF Radar, US East Coast and Gulf of Mexico, RTV, Near-Real Time, 2012-present, Hourly, 2km

Surface ocean velocities estimated from HF-Radar are representative
of the upper 1.0 meters of the ocean.  The main objective of
near-real time processing is to produce the best product from
available data at the time of processing.  Radial velocity
measurements are obtained from individual radar sites through the
U.S. HF-Radar Network. Hourly radial data are processed by unweighted
least squares on a 2km resolution grid of the U.S. East and Gulf
Coast to produce near real-time surface current maps.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, US East Coast and Gulf of Mexico, RTV, Near-Real Time, 2012-present, Hourly, 2km, Lon0360


Currents, HF Radar, US East Coast and Gulf of Mexico, RTV, Near-Real Time, 2012-present, Hourly, 6km

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, US East Coast and Gulf of Mexico, RTV, Near-Real Time, 2012-present, Hourly, 6km, Lon0360

Coastal Observing Research and Development Center, Scripps Institution of Oceanography


Currents, HF Radar, US Hawai'i State, RTV, Near-Real Time, 2012-present, Hourly, 1km

Surface ocean velocities estimated from HF-Radar are representative
of the upper 0.5 meters of the ocean.  The main objective of
near-real time processing is to produce the best product from
available data at the time of processing.  Radial velocity
measurements are obtained from individual radar sites through the
U.S. HF-Radar Network. Hourly radial data are processed by unweighted
least squares on a 1km resolution grid of the Hawaiian Islands to
produce near real-time surface current maps.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, US Hawai'i State, RTV, Near-Real Time, 2012-present, Hourly, 1km, Lon0360


Currents, HF Radar, US West Coast, RTV, Near-Real Time, 2012-present, Hourly, 1km

Surface ocean velocities estimated from HF-Radar are representative
of the upper 0.5 meters of the ocean.  The main objective of
near-real time processing is to produce the best product from
available data at the time of processing.  Radial velocity
measurements are obtained from individual radar sites through the
U.S. HF-Radar Network. Hourly radial data are processed by unweighted
least squares on a 1km resolution grid of the U.S. West Coast to
produce near real-time surface current maps.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, US West Coast, RTV, Near-Real Time, 2012-present, Hourly, 1km, Lon0360


Currents, HF Radar, US West Coast, RTV, Near-Real Time, 2012-present, Hourly, 2km

Surface ocean velocities estimated from HF-Radar are representative
of the upper 1.0 meters of the ocean.  The main objective of
near-real time processing is to produce the best product from
available data at the time of processing.  Radial velocity
measurements are obtained from individual radar sites through the
U.S. HF-Radar Network. Hourly radial data are processed by unweighted
least squares on a 2km resolution grid of the U.S. West Coast to
produce near real-time surface current maps.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, US West Coast, RTV, Near-Real Time, 2012-present, Hourly, 2km, Lon0360


Currents, HF Radar, US West Coast, RTV, Near-Real Time, 2012-present, Hourly, 500m

Surface ocean velocities estimated from HF-Radar are representative
of the upper 0.3 meters of the ocean.  The main objective of
near-real time processing is to produce the best product from
available data at the time of processing.  Radial velocity
measurements are obtained from individual radar sites through the
U.S. HF-Radar Network. Hourly radial data are processed by unweighted
least squares on a 500m resolution grid of the U.S. West Coast to
produce near real-time surface current maps.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, US West Coast, RTV, Near-Real Time, 2012-present, Hourly, 500m, Lon0360


Currents, HF Radar, US West Coast, RTV, Near-Real Time, 2012-present, Hourly, 6km

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
water_u (Surface Eastward Sea Water Velocity, m s-1)
water_v (Surface Northward Sea Water Velocity, m s-1)
DOPx (Longitudinal Dilution of Precision)
DOPy (Latitudinal Dilution of Precision)
hdop (horizontal dilution of precision)
number_of_sites (number of contributing radars, count)
number_of_radials (number of contributing radials, count)


Currents, HF Radar, US West Coast, RTV, Near-Real Time, 2012-present, Hourly, 6km, Lon0360


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1948)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
chi (Daily Mean Velocity Potential, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1949)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1950)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1951)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1952)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1953)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1954)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1955)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1956)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1957)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1958)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1959)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1960)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1961)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1962)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1963)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1964)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
chi (Daily Mean Velocity Potential, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1965)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1966)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1967)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1968)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1969)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1970)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1971)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1972)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1973)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1974)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1975)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1976)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1977)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1978)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1979)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1980)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
chi (Daily Mean Velocity Potential, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1981)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1982)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1983)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1984)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1985)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1986)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1987)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1988)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1989)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1990)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1991)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1992)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1993)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1994)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1995)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1996)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
chi (Daily Mean Velocity Potential, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1997)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1998)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.1999)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2000)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2001)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2002)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2003)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2004)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2005)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. 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][level][latitude][longitude]):
chi (Daily Mean Velocity Potential, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2006)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2007)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2008)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2009)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2010)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2011)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2012)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2013)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2014)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2015)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2016)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2017)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2018)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2019)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2020)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.2021)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. 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][level][latitude][longitude]):
chi (Daily Mean Velocity Potential, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (chi.day.ltm), 0001

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
chi (Daily Long Term Mean Velocity Potential<, m*m/s)
valid_yr_count (count of non-missing values used in mean)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1948)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
psi (Daily Mean Streamfunction, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1949)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1950)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1951)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1952)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1953)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1954)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1955)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1956)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1957)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1958)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1959)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1960)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1961)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1962)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1963)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1964)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
psi (Daily Mean Streamfunction, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1965)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1966)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1967)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1968)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1969)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1970)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1971)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1972)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1973)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1974)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1975)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1976)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1977)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1978)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1979)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1980)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
psi (Daily Mean Streamfunction, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1981)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1982)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1983)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1984)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1985)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1986)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1987)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1988)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1989)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1990)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1991)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1992)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1993)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1994)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1995)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1996)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
psi (Daily Mean Streamfunction, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1997)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1998)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.1999)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2000)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2001)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2002)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2003)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2004)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2005)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. 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][level][latitude][longitude]):
psi (Daily Mean Streamfunction, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2006)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2007)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2008)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2009)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2010)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2011)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2012)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2013)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2014)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2015)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2016)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2017)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2018)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2019)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2020)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.2021)

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. 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][level][latitude][longitude]):
psi (Daily Mean Streamfunction, m*m/s)


Daily averaged and put on grid 4x daily NCEP reanalysis (psi.day.ltm), 0001

Daily averaged and put on grid 4x daily National Centers for Environmental Prediction (NCEP) reanalysis. Data is from NCEP 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][level][latitude][longitude]):
psi (Daily Long Term Mean Streamfunction, m*m/s)
valid_yr_count (count of non-missing values used in mean)


Daily estimated MUR SST v4.1 Frontal edges, x_gradient, y_gradient and gradient magnitude, US West Coast, 2002-present

Front Edges estimated from daily Multi-scale Ultra-high Resolution (MUR) Sea Surface Temperature (SST) v4.1 files using the Python scikit-image canny algorithm with sigma = 10., and threshold values of .8 and .9, as well as the OpenCV algorithm findContours with a minimum length of 20. The SST x-gradient, y-gradient and gradient magnitude are also included

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
magnitude_gradient (Magnitude of SST Gradient)
edges (Frontal Edge)
x_gradient (East-West Gradient of SST)
y_gradient (North-South Gradient of SST)


Daily estimated MUR SST v4.1 Frontal edges, x_gradient, y_gradient and gradient magnitude, US West Coast, 2002-present, Lon0360


Daily Long Term Mean from NOAA interpolated OLR Dataset (olr.day.ltm), 2.5°, 0001

Daily Long Term Mean from NOAA interpolated Outgoing Longwave Radiation (OLR) Dataset. Calculated from Interpolated NOAA OLR daily data

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
olr (Long Term Mean Daily Mean OLR, W/m^2)


Daily Long Term Mean NARR (hgt.day.ltm) [time][level][y][x], 0001

Daily Long Term Mean NARR. Data is from North American Regional Reanalysis
(8x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
hgt (Daily Long Term Mean Geopotential Heights on Pressure Levels, m)

National Centers for Environmental Prediction


Daily Long Term Mean NARR (hgt.day.ltm) [y][x]

Daily Long Term Mean NARR. Data is from North American Regional Reanalysis
(8x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


Daily Long Term Mean NARR (omega.day.ltm) [time][level][y][x], 0001

Daily Long Term Mean NARR. Data is from North American Regional Reanalysis
(8x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
omega (Daily Long Term Mean Omega on Pressure Levels, Pascal/s)


Daily Long Term Mean NARR (omega.day.ltm) [y][x]


Daily Long Term Mean NARR (tke.day.ltm) [time][level][y][x], 0001

Daily Long Term Mean NARR. Data is from North American Regional Reanalysis
(8x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


Daily Long Term Mean NARR (tke.day.ltm) [y][x]


Daily Long Term Mean NARR (uwnd.day.ltm) [time][level][y][x], 0001

Daily Long Term Mean NARR. Data is from North American Regional Reanalysis
(8x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
uwnd (Daily Long Term Mean U-wind on Pressure Levels, m/s)


Daily Long Term Mean NARR (uwnd.day.ltm) [y][x]


Daily Long Term NARR (air.day.ltm) [time][level][y][x], 0001

Daily Long Term NARR. Data is from North American Regional Reanalysis
(8x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
air (Daily Long Term Mean Air Temperature on Pressure Levels, degK)


Daily Long Term NARR (air.day.ltm) [y][x]

Daily Long Term NARR. Data is from North American Regional Reanalysis
(8x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


daily ltm air from the NCEP Reanalysis (air.day.1981-2010.ltm), 2.5°, 0001

daily ltm air from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
air (mean Long Term Mean Daily Air temperature, degK)
valid_yr_count (count of non-missing values used in mean)


daily ltm air from the NCEP Reanalysis (air.day.ltm), 2.5°, 0001


daily ltm air.sig995 from the NCEP Reanalysis (air.day.ltm), 2.5°, 0001

daily ltm air.sig995 from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  These are the 0.9950 sigma level values.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (mean Long Term Mean Daily Air temperature, degK)
valid_yr_count (count of non-missing values used in mean)


daily ltm air.sig995 from the NCEP Reanalysis (air.sig995.day.ltm), 2.5°, 0001


daily ltm air.tropp from the NCEP Reanalysis (air.tropp.day.ltm), 2.5°, 0001

daily ltm air.tropp from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  These are the tropopause values.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (mean Long Term Mean Daily Air Temperature at Tropopause, degK)
valid_yr_count (count of non-missing values used in mean)


daily ltm csulf.ntat from the NCEP Reanalysis (csulf.ntat.day.ltm), 0001

daily ltm csulf.ntat from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


daily ltm csusf.ntat from the NCEP Reanalysis (csusf.ntat.day.ltm), 0001

daily ltm csusf.ntat from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


daily ltm dswrf.ntat from the NCEP Reanalysis (dswrf.ntat.day.ltm), 0001

daily ltm dswrf.ntat from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


daily ltm hgt from the NCEP Reanalysis (hgt.day.1981-2010.ltm), 2.5°, 0001

daily ltm hgt from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
hgt (mean Long Term Mean Daily Geopotential height, m)
valid_yr_count (count of non-missing values used in mean)


daily ltm hgt from the NCEP Reanalysis (hgt.day.ltm), 2.5°, 0001


daily ltm lftx from the NCEP Reanalysis (lftx.day.1981-2010.ltm), 2.5°, 0001

daily ltm lftx from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
lftx (mean Long Term Mean Daily Surface Lifted Index, degree_C)
valid_yr_count (count of non-missing values used in mean)


daily ltm lftx from the NCEP Reanalysis (lftx.day.ltm), 2.5°, 0001


daily ltm lftx4 from the NCEP Reanalysis (lftx4.day.1981-2010.ltm), 2.5°, 0001

daily ltm lftx4 from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
lftx4 (mean Long Term Mean Daily Best (4-layer) Lifted Index, degree_C)
valid_yr_count (count of non-missing values used in mean)


daily ltm omega from the NCEP Reanalysis (omega.day.1981-2010.ltm), 2.5°, 0001

daily ltm omega from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
omega (mean Long Term Mean Daily Omega, Pascal/s)
valid_yr_count (count of non-missing values used in mean)


daily ltm omega from the NCEP Reanalysis (omega.day.ltm), 2.5°, 0001

daily ltm omega from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
omega (mean Long Term Mean Daily omega, Pascal/s)
valid_yr_count (count of non-missing values used in mean)


daily ltm omega.sig995 from the NCEP Reanalysis (omega.sig995.day.ltm), 2.5°, 0001

daily ltm omega.sig995 from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  These are the 0.9950 sigma level values.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
omega (mean Long Term Mean Daily omega at sigma level 0.995, Pascal/s)
valid_yr_count (count of non-missing values used in mean)


daily ltm pottmp.sig995 from the NCEP Reanalysis (pottmp.sig995.day.ltm), 2.5°, 0001

daily ltm pottmp.sig995 from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  These are the 0.9950 sigma level values.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pottmp (mean Long Term Mean Daily Surface potential temperature, degree_C)
valid_yr_count (count of non-missing values used in mean)


daily ltm pr_wtr from the NCEP Reanalysis (pr wtr.day.ltm), 2.5°, 0001

daily ltm pr_wtr from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pr_wtr (mean Long Term Mean Daily Precipitable Water for entire atmosphere, kg/m^2)
valid_yr_count (count of non-missing values used in mean)


daily ltm pr_wtr from the NCEP Reanalysis (pr wtr.eatm.day.1981-2010.ltm), 2.5°, 0001


daily ltm pr_wtr from the NCEP Reanalysis (pr wtr.eatm.day.ltm), 2.5°, 0001


daily ltm pres from the NCEP Reanalysis (pres.day.1981-2010.ltm), 2.5°, 0001

daily ltm pres from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (mean Long Term Mean Daily Pressure at surface, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm pres from the NCEP Reanalysis (pres.day.ltm), 2.5°, 0001

daily ltm pres from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (mean Long Term Mean Daily Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm pres.hcb from the NCEP Reanalysis (pres.hcb.day.ltm), 0001

daily ltm pres.hcb from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (daily Long Term Mean mean High Cloud Bottom Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm pres.hct from the NCEP Reanalysis (pres.hct.day.ltm), 0001

daily ltm pres.hct from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (daily Long Term Mean mean High Cloud Top Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm pres.lcb from the NCEP Reanalysis (pres.lcb.day.ltm), 0001

daily ltm pres.lcb from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (daily Long Term Mean mean Low Cloud Bottom Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm pres.mcb from the NCEP Reanalysis (pres.mcb.day.ltm), 0001

daily ltm pres.mcb from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (daily Long Term Mean mean Middle Cloud Bottom Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm pres.mct from the NCEP Reanalysis (pres.mct.day.ltm), 0001

daily ltm pres.mct from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (daily Long Term Mean mean Middle Cloud Top Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm pres.tropp from the NCEP Reanalysis (pres.tropp.day.ltm), 2.5°, 0001

daily ltm pres.tropp from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  These are the tropopause values.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (mean Long Term Mean Daily Pressure at Tropopause, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm rhum from the NCEP Reanalysis (rhum.day.1981-2010.ltm), 2.5°, 0001

daily ltm rhum from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
rhum (mean Long Term Mean Daily relative humidity, percent)
valid_yr_count (count of non-missing values used in mean)


daily ltm rhum from the NCEP Reanalysis (rhum.day.ltm), 2.5°, 0001


daily ltm rhum.sig995 from the NCEP Reanalysis (rhum.day.ltm), 2.5°, 0001

daily ltm rhum.sig995 from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  These are the 0.9950 sigma level values.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (mean Long Term Mean Daily relative humidity, percent)
valid_yr_count (count of non-missing values used in mean)


daily ltm rhum.sig995 from the NCEP Reanalysis (rhum.sig995.day.ltm), 2.5°, 0001


daily ltm shum from the NCEP Reanalysis (shum.day.1981-2010.ltm), 2.5°, 0001

daily ltm shum from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
shum (mean Long Term Mean Daily specific humidity, kg/kg)
valid_yr_count (count of non-missing values used in mean)


daily ltm shum from the NCEP Reanalysis (shum.day.ltm), 2.5°, 0001


daily ltm slp from the NCEP Reanalysis (slp.day.1981-2010.ltm), 2.5°, 0001

daily ltm slp from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
slp (mean Long Term Mean Daily Sea Level Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily ltm slp from the NCEP Reanalysis (slp.day.ltm), 2.5°, 0001


daily ltm tcdc.daily from the NCEP Reanalysis (tcdc.eatm.day.ltm), 0001

daily ltm tcdc.daily from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
presssure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
tcdc (daily Long Term Mean mean Total cloud cover, percent)
valid_yr_count (count of non-missing values used in mean)


daily ltm ulwrf.ntat from the NCEP Reanalysis (ulwrf.ntat.day.ltm), 0001

daily ltm ulwrf.ntat from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


daily ltm uswrf.ntat from the NCEP Reanalysis (uswrf.ntat.day.ltm), 0001

daily ltm uswrf.ntat from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


daily ltm uwnd from the NCEP Reanalysis (uwnd.day.1981-2010.ltm), 2.5°, 0001

daily ltm uwnd from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


daily ltm uwnd from the NCEP Reanalysis (uwnd.day.ltm), 2.5°, 0001

daily ltm uwnd from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


daily ltm uwnd.sig995 from the NCEP Reanalysis (uwnd.day.ltm), 2.5°, 0001

daily ltm uwnd.sig995 from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  These are the 0.9950 sigma level values.

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


daily ltm uwnd.sig995 from the NCEP Reanalysis (uwnd.sig995.day.ltm), 2.5°, 0001


daily ltm vwnd from the NCEP Reanalysis (vwnd.day.1981-2010.ltm), 2.5°, 0001

daily ltm vwnd from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
vwnd (mean Long Term Mean Daily V wind, m/s)
valid_yr_count (count of non-missing values used in mean)


daily ltm vwnd from the NCEP Reanalysis (vwnd.day.ltm), 2.5°, 0001

daily ltm vwnd from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
vwnd (daily Long Term Mean mean v wind, m/s)
valid_yr_count (count of non-missing values used in mean)


daily ltm vwnd.sig995 from the NCEP Reanalysis (vwnd.day.ltm), 2.5°, 0001

daily ltm vwnd.sig995 from the National Centers for Environmental Prediction (NCEP) Reanalysis. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  These are the 0.9950 sigma level values.

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


daily ltm vwnd.sig995 from the NCEP Reanalysis (vwnd.sig995.day.ltm), 2.5°, 0001


Daily Mean Interpolated OLR (olr.day.mean) [time][lat][lon], 2.5°, 1974-present

Daily Mean Interpolated Outgoing Longwave Radiation (OLR). Data is interpolated in time and space from NOAA twice-daily OLR values and averaged to once daily

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
olr (Daily Mean OLR, W/m^2)


Daily Mean Interpolated OLR (olr.day.mean) [time][nmiss], 1974-present

Daily Mean Interpolated Outgoing Longwave Radiation (OLR). Data is interpolated in time and space from NOAA twice-daily OLR values and averaged to once daily

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][nmiss]):
info (Missing)


Daily NCEP/DOE Reanalysis 2 (air.day.ltm.1981-2010), 2.5°, 0001

Daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
air (Daily Long Term Mean Air Temperature on Pressure Levels, degK)
valid_yr_count (count of non-missing values used in mean)


daily NCEP/DOE Reanalysis 2 (hgt.day.ltm.1981-2010), 2.5°, 0001

daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
hgt (Daily Long Term Mean Geopotential Heights on Pressure Levels, m)
valid_yr_count (count of non-missing values used in mean)


Daily NCEP/DOE Reanalysis 2 (mslp.day.ltm.1981-2010), 2.5°, 0001

Daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  Data interpolated from model (sigma) surfaces to
a rectangular grid.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
mslp (Daily Long Term Mean Sea Level Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


Daily NCEP/DOE Reanalysis 2 (omega.day.ltm.1981-2010), 2.5°, 0001

Daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
omega (Daily Long Term Mean Omega on Pressure Levels, Pascal/s)
valid_yr_count (count of non-missing values used in mean)


Daily NCEP/DOE Reanalysis 2 (pr wtr.day.ltm.1981-2010), 2.5°, 0001

Daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  Data interpolated from model (sigma) surfaces to
a rectangular grid.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pr_wtr (Daily Long Term Mean Precipitable Water for Entire Atmosphere, kg/m^2)
valid_yr_count (count of non-missing values used in mean)


Daily NCEP/DOE Reanalysis 2 (pr wtr.eatm.mon.mean), 2.5°, 1979-present

Daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  Data interpolated from model (sigma) surfaces to
a rectangular grid.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pr_wtr (Monthly Precipitable Water for Entire Atmosphere, kg/m^2)


Daily NCEP/DOE Reanalysis 2 (pres.day.ltm.1981-2010), 2.5°, 0001

Daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  Data interpolated from model (sigma) surfaces to rectangular grid.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (Daily Long Term Mean Pressure at Surface, Pascals)
valid_yr_count (count of non-missing values used in mean)


daily NCEP/DOE Reanalysis 2 (rhum.day.ltm.1981-2010), 2.5°, 0001

daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
rhum (Daily Long Term Mean Relative Humidity on Pressure Levels, percent)
valid_yr_count (count of non-missing values used in mean)


Daily NCEP/DOE Reanalysis 2 (uwnd.day.ltm.1981-2010), 2.5°, 0001

Daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


Daily NCEP/DOE Reanalysis 2 (vwnd.day.ltm.1981-2010), 2.5°, 0001

Daily National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Reanalysis 2. Data is from
NCEP/DOE Atmosphere Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)
(4x/day).  It consists of most variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
vwnd (Daily Long Term Mean V-wind on Pressure Levels, m/s)
valid_yr_count (count of non-missing values used in mean)


daily NMC reanalysis (1981) (runof.sfc.day.1981-2010.ltm), 0001

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]):
runof (Accumulated Long Term Mean Daily Water Runoff at surface, kg/m^2)
valid_yr_count (count of non-missing values used in mean)


daily NMC reanalysis (1981) (runof.sfc.day.ltm), 0001

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]):
runof (Long Term Mean Monthly Mean of Water Runoff, kg/m^2)
valid_yr_count (count of non-missing values used in mean)


daily NMC reanalysis (1981) (tmax.2m.day.1981-2010.ltm), 0001

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]):
tmax (Daily Long Term Mean Maximum Temperature at 2 m, degK)
valid_yr_count (count of non-missing values used in mean)


daily NMC reanalysis (1981) (tmax.2m.day.ltm), 0001


daily NMC reanalysis (1981) (tmin.2m.day.1981-2010.ltm), 0001

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]):
tmin (Daily Long Term Mean Minimum Temperature at 2 m, degree_C)
valid_yr_count (count of non-missing values used in mean)


daily NMC reanalysis (1981) (tmin.2m.day.ltm), 0001


Daily-OI-V2, Interim, Data (Ship, Buoy, AMSR, AVHRR: NOAA19, METOP, NCEP-ice) [time], 2002-2011

Best time series, taking the data from the most recent run available. Aggregation filename pattern: amsr-avhrr-v2.*.nc

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time]):
time_run (run times for coordinate = time, seconds since 1970-01-01T00:00:00Z)
time_offset (offset hour from start of run for coordinate = time, seconds since 1970-01-01T00:00:00Z)


Daily-OI-V2, Interim, Data (Ship, Buoy, AMSR, AVHRR: NOAA19, METOP, NCEP-ice) [time][zlev][lat][lon], 0.25°, 2002-2011

Best time series, taking the data from the most recent run available. Aggregation filename pattern: amsr-avhrr-v2.*.nc

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][zlev][latitude][longitude]):
sst (Daily sea surface temperature, degree_C)
anom (Daily sea surface temperature anomalies, degree_C)
err (Estimated error standard deviation of analysed_sst, degree_C)
ice (Sea ice concentration, percent)


Daytona Beach, Florida Coastal Digital Elevation Model (daytona beach 13 mhw 2007), 9.259259E-5°

Daytona Beach, Florida 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/456; Daytona Beach, FL 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


Daytona Beach, Florida Tsunami Forecast Grids for MOST Model (DaytonaBeachFL A)

Daytona Beach, Florida 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


Daytona Beach, Florida Tsunami Forecast Grids for MOST Model (DaytonaBeachFL B), 0.0025°


Daytona Beach, Florida Tsunami Forecast Grids for MOST Model (DaytonaBeachFL C)


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)


Delaware Bay Operational Forecast System (DBOFS): Forecast, Fields (Best Time Series) [boundary]

Delaware Bay Operational Forecast System (DBOFS): 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)


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

Delaware Bay Operational Forecast System (DBOFS): 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)


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

Delaware Bay Operational Forecast System (DBOFS): 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)


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

Delaware Bay Operational Forecast System (DBOFS): 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)
rdrag2 (quadratic bottom drag coefficient)


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

Delaware Bay Operational Forecast System (DBOFS): 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)


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

Delaware Bay Operational Forecast System (DBOFS): 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)


Delaware Bay Operational Forecast System (DBOFS): Forecast, Fields (Best Time Series) [s_rho]

Delaware Bay Operational Forecast System (DBOFS): 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)


Delaware Bay Operational Forecast System (DBOFS): Forecast, Fields (Best Time Series) [s_w]

Delaware Bay Operational Forecast System (DBOFS): 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)


Delaware Bay Operational Forecast System (DBOFS): Forecast, Fields (Best Time Series) [tracer]

Delaware Bay Operational Forecast System (DBOFS): 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)


destin 13 navd88 2016 (GDAL Band Number 1), 9.25925E-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)


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (1 Day Composite)

NASA distributes Diffuse Attenuation Coefficient at 490 nm Wavelength data from NASA's Aqua satellite.  Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard the spacecraft.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
k490 (Diffuse Attenuation Coefficient K490, m-1)


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (1 Day Composite), Lon+/-180


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (14 Day Composite)


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (14 Day Composite), Lon+/-180


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (3 Day Composite)


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (3 Day Composite), Lon+/-180


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (8 Day Composite)


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (8 Day Composite), Lon+/-180


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (Monthly Composite)


Diffuse Attenuation Coef. K490, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (Monthly Composite), Lon+/-180


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite)

This dataset has monthly composites of Level 3, Standard Mapped Image, 4km, Diffuse Attenuation Coefficient at 490 nm Wavelength data from NASA's Aqua Spacecraft.  Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard the spacecraft. This is Science Quality data.  This is the August 2015 version of this dataset.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
k490 (Diffuse Attenuation Coefficient K490, m-1)


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite), Lon0360


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite)


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite), Lon0360


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite)


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite), Lon0360


Digital Elevation Model of Kauai, Hawaii, Integrating Bathymetric and Topographic Datasets, 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)

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/3550; Kauai, HI 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


Digital Elevation Model of Southeast Alaska, Integrating Bathymetric and Topographic Datasets, 7.4074074E-4°

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/715; Southeast Alaska, AK 8/3 arc-second MHHW DEM; Download page for accessing DEM, metadata record and development report.; download


Distance to Nearest Coastline: 0.01-Degree Grid

A global data set of distances from the nearest coastline. Negative distances represent locations over land (including land-locked bodies of water), while positive distances represent the ocean. NASA's Ocean Biology Processing Group (OBPG) generated this data set using the Generic Mapping Tools (GMT) software package. Distances were computed with GMT using its intermediate-resolution coastline and then gridded globally at a spatial resolution of 0.04 degrees. Bilinear interpolation was then applied to increase the spatial resolution to 0.01 degrees. There is an uncertainty of up to 1 km in the computed distance at any given point.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
dist (distance to nearest coastline, km)

NASA Ocean Biology Processing Group (OBPG)


Distance to Nearest Coastline: 0.01-Degree Grid, Lon0360


Distance to Nearest Coastline: 0.01-Degree Grid: Land

A global data set of land distances from the nearest coastline. NASA's Ocean Biology Processing Group (OBPG) generated this data set using the Generic Mapping Tools (GMT) software package. Distances were computed with GMT using its intermediate-resolution coastline and then gridded globally at a spatial resolution of 0.04 degrees. Bilinear interpolation was then applied to increase the spatial resolution to 0.01 degrees. There is an uncertainty of up to 1 km in the computed distance at any given point.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
dist (distance to nearest coastline, km)


Distance to Nearest Coastline: 0.01-Degree Grid: Land, Lon0360


Distance to Nearest Coastline: 0.01-Degree Grid: Ocean

A global data set of ocean distances from the nearest coastline. NASA's Ocean Biology Processing Group (OBPG) generated this data set using the Generic Mapping Tools (GMT) software package. Distances were computed with GMT using its intermediate-resolution coastline and then gridded globally at a spatial resolution of 0.04 degrees. Bilinear interpolation was then applied to increase the spatial resolution to 0.01 degrees. There is an uncertainty of up to 1 km in the computed distance at any given point.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
dist (distance to nearest coastline, km)


Distance to Nearest Coastline: 0.01-Degree Grid: Ocean, Lon0360


Distance to Nearest Coastline: 0.04-Degree Grid

A global data set of distances from the nearest coastline. Negative distances represent locations over land (including land-locked bodies of water), while positive distances represent the ocean. NASA's Ocean Biology Processing Group (OBPG) generated this data set using the Generic Mapping Tools (GMT) software package. Distances were computed with GMT using its intermediate-resolution coastline and then gridded globally at a spatial resolution of 0.04 degrees.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
dist (distance to nearest coastline, km)


Distance to Nearest Coastline: 0.04-Degree Grid, Lon0360


Distance to Nearest Coastline: 0.04-Degree Grid: Land

A global data set of land distances from the nearest coastline. NASA's Ocean Biology Processing Group (OBPG) generated this data set using the Generic Mapping Tools (GMT) software package. Distances were computed with GMT using its intermediate-resolution coastline and then gridded globally at a spatial resolution of 0.04 degrees.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
dist (distance to nearest coastline, km)


Distance to Nearest Coastline: 0.04-Degree Grid: Land, Lon0360


Distance to Nearest Coastline: 0.04-Degree Grid: Ocean

A global data set of ocean distances from the nearest coastline. NASA's Ocean Biology Processing Group (OBPG) generated this data set using the Generic Mapping Tools (GMT) software package. Distances were computed with GMT using its intermediate-resolution coastline and then gridded globally at a spatial resolution of 0.04 degrees.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
dist (distance to nearest coastline, km)


Distance to Nearest Coastline: 0.04-Degree Grid: Ocean, Lon0360

NASA Ocean Biology Processing Group (OBPG)


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

Monthly NARR (dlwrf.mon.ltm). National Centers for Environmental Prediction data from https://psl.noaa.gov/thredds/dodsC/Datasets/NARR/Derived/monolevel/dlwrf.mon.ltm.nc.das .

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


Monthly NARR (dlwrf.mon.ltm). National Centers for Environmental Prediction data from https://psl.noaa.gov/thredds/dodsC/Datasets/NARR/Derived/monolevel/dlwrf.mon.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)


dlwrf.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]):
dlwrf (Monthly Long Term Mean Downward Longwave Radiation Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)