Panama City, Florida Coastal Digital Elevation Model (panama city 13 mhw 2010), 9.259259E-5°

Panama City, 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]):
z (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/686; Panama City, FL 1/3 arc-second VDatum DEM; Download page for accessing MHW DEM, metadata record and development report.; download; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/vdatum/vdatum.html; NOAA VDatum DEM Project; Project web page.; information


Panama City, Florida Coastal Digital Elevation Model (panama city 13 navd88 2010), 9.259259E-5°

Panama City, 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/684; Panama City, FL 1/3 arc-second VDatum DEM; Download page for accessing NAVD 88 DEM, metadata record and development report.; download; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/vdatum/vdatum.html; NOAA VDatum DEM Project; Project web page.; information


Pearl Harbor, Hawaii Tsunami Forecast Grids for MOST Model (PearlHarborHI A)

Pearl Harbor, Hawaii 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


Pearl Harbor, Hawaii Tsunami Forecast Grids for MOST Model (PearlHarborHI B), 0.005°


Pearl Harbor, Hawaii Tsunami Forecast Grids for MOST Model (PearlHarborHI 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)


pensacola 13 navd88 2015 (GDAL Band Number 1), 9.259259E-5°

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

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


Pensacola Bay (G130) Bathymetric Digital Elevation Model (pensacola bay G130 2018), 9.259259E-5°

Pensacola Bay (G130) Bathymetric Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

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


Perdido Bay (G140) Bathymetric Digital Elevation Model (perdido bay G140 2018), 9.259259E-5°

Perdido Bay (G140) Bathymetric Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

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


Perryville and Ivanof Bay, Alaska 1/3 arc-second Coastal Digital Elevation Model, 9.259259E-5°

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

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

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


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pevap (Long Term Monthly Mean accumulated potential evaporation at Surface, kg/m^2)


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


pevpr.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]):
pevpr (Monthly Long Term Mean of Potential Evaporation Rate, W/m^2)
valid_yr_count (count of non-missing values used in mean)


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (1 Day Composite)

MODIS measures photosynthetically available radiation that may be used to mode primary productivity.  THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for scientific evaluation by professional marine scientists.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
par (Photosynthetically Available Radiation, Einsteins m-2 d-1)


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (1 Day Composite), Lon+/-180


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (14 Day Composite)


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (14 Day Composite), Lon+/-180


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (3 Day Composite)


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (3 Day Composite), Lon+/-180


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (8 Day Composite)


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (8 Day Composite), Lon+/-180


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (Monthly Composite)


Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.0125°, West US, 2002-present (Monthly Composite), Lon+/-180


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite)

This dataset has Level 3, Standard Mapped Image, 4km, photosynthetically available radiation (PAR) 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]):
par (Photosynthetically Available Radiation, R. Frouin, einstein m-2 day-1)


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite), Lon0360


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite)


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite), Lon0360


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite)


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite), Lon0360


Physical data collected from Seaglider SG609 during North Atlantic 2014 deployed on 2014-07-19 [profile]

SG609 North Atlantic 2014. Atlantic Oceanographic Meteorlogical Laboratory,
National Oceanographic Atmospheric Administration
Miami, Florida data from https://cwcgom.aoml.noaa.gov/thredds/dodsC/GLIDERS/SG609.nc.das .

cdm_data_type = Trajectory
VARIABLES (all of which use the dimensions [profile]):
year
profile_time (Time, seconds since 1970-01-01T00:00:00Z)
start_time (seconds since 1970-01-01T00:00:00Z)
start_longitude (Latitude, degrees_east)
start_latitude (Latitude, degrees_north)
month
longitude (degrees_east)
latitude (degrees_north)
hour
end_time (seconds since 1970-01-01T00:00:00Z)
end_longitude (Longitude, degrees_east)
end_latitude (Longitude, degrees_north)
dive_number
depth_avg_curr_north (Northward Sea Water Velocity, m/s)
depth_avg_curr_east (Eastward Sea Water Velocity, m/s)
dd
date


Physical data collected from Seaglider SG609 during North Atlantic 2014 deployed on 2014-07-19 [profile][depth]

SG609 North Atlantic 2014. Atlantic Oceanographic Meteorlogical Laboratory,
National Oceanographic Atmospheric Administration
Miami, Florida data from https://cwcgom.aoml.noaa.gov/thredds/dodsC/GLIDERS/SG609.nc.das .

cdm_data_type = Trajectory
VARIABLES (all of which use the dimensions [profile][depth]):
theta (Sea Water Potential Temperature, degree_C)
temperature_raw (degree_C)
temperature (Sea Water Temperature, degree_C)
sound_velocity (Speed Of Sound In Sea Water, m/s)
sigma_theta (Sea Water Sigma Theta, g/m^3)
sigma_t (Sea Water Sigma T, g/m^3)
salinity_raw (Sea Water Practical Salinity, PSU)
salinity (Sea Water Practical Salinity, PSU)
pressure (Sea Water Pressure, dbar)
longitude_gsm (degrees_east)
log_gps_time (seconds since 1970-01-01T00:00:00Z)
latitude_gsm (degrees_north)
dissolved_oxygen_sat (Mole Concentration Of Dissolved Molecular Oxygen In Sea Water, micromoles/kg)
density (Sea Water Density, g/m^3)
ctd_time (seconds since 1970-01-01T00:00:00Z)
ctd_depth (Depth, meters)
conductivity_raw (Sea Water Electrical Conductivity, S/m)
conductivity (Sea Water Electrical Conductivity, S/m)
bin_time (seconds since 1970-01-01T00:00:00Z)


Physical data collected from Seaglider SG610 during North Atlantic 2014 deployed on 2014-07-15 [profile]

SG610 North Atlantic 2014. Atlantic Oceanographic Meteorlogical Laboratory,
National Oceanographic Atmospheric Administration
Miami, Florida data from https://cwcgom.aoml.noaa.gov/thredds/dodsC/GLIDERS/SG610.nc.das .

cdm_data_type = Trajectory
VARIABLES (all of which use the dimensions [profile]):
year
profile_time (Time, seconds since 1970-01-01T00:00:00Z)
start_time (seconds since 1970-01-01T00:00:00Z)
start_longitude (Latitude, degrees_east)
start_latitude (Latitude, degrees_north)
month
longitude (degrees_east)
latitude (degrees_north)
hour
end_time (seconds since 1970-01-01T00:00:00Z)
end_longitude (Longitude, degrees_east)
end_latitude (Longitude, degrees_north)
dive_number
depth_avg_curr_north (Northward Sea Water Velocity, m/s)
depth_avg_curr_east (Eastward Sea Water Velocity, m/s)
dd
date


Physical data collected from Seaglider SG610 during North Atlantic 2014 deployed on 2014-07-15 [profile][depth]

SG610 North Atlantic 2014. Atlantic Oceanographic Meteorlogical Laboratory,
National Oceanographic Atmospheric Administration
Miami, Florida data from https://cwcgom.aoml.noaa.gov/thredds/dodsC/GLIDERS/SG610.nc.das .

cdm_data_type = Trajectory
VARIABLES (all of which use the dimensions [profile][depth]):
theta (Sea Water Potential Temperature, degree_C)
temperature_raw (degree_C)
temperature (Sea Water Temperature, degree_C)
sound_velocity (Speed Of Sound In Sea Water, m/s)
sigma_theta (Sea Water Sigma Theta, g/m^3)
sigma_t (Sea Water Sigma T, g/m^3)
salinity_raw (Sea Water Practical Salinity, PSU)
salinity (Sea Water Practical Salinity, PSU)
pressure (Sea Water Pressure, dbar)
longitude_gsm (degrees_east)
log_gps_time (seconds since 1970-01-01T00:00:00Z)
latitude_gsm (degrees_north)
dissolved_oxygen_sat (Mole Concentration Of Dissolved Molecular Oxygen In Sea Water, micromoles/kg)
density (Sea Water Density, g/m^3)
ctd_time (seconds since 1970-01-01T00:00:00Z)
ctd_depth (Depth, meters)
conductivity_raw (Sea Water Electrical Conductivity, S/m)
conductivity (Sea Water Electrical Conductivity, S/m)
bin_time (seconds since 1970-01-01T00:00:00Z)


Point Reyes, California Tsunami Forecast Grids for MOST Model (PointReyesCA A)

Point Reyes, 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


Point Reyes, California Tsunami Forecast Grids for MOST Model (PointReyesCA B)


Point Reyes, California Tsunami Forecast Grids for MOST Model (PointReyesCA C)


Ponce, Puerto Rico Tsunami Forecast Grids for MOST Model (PoncePR A)

Ponce, Puerto Rico 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)


Ponce, Puerto Rico Tsunami Forecast Grids for MOST Model (PoncePR B)


Ponce, Puerto Rico Tsunami Forecast Grids for MOST Model (PoncePR C)


port alberni 13 navd88 2016 (GDAL Band Number 1), 9.259259E-5°

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

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


Port Alexander Alaska Coastal Digital Elevation Model (port alexander 13 mhw 2011), 9.259E-5°

Port Alexander 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


Port Alexander, 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)


Port Alexander, Alaska 8/45 sec Coastal Digital Elevation Model, 4.938272E-5°


Port Alexander, Alaska Tsunami Forecast Grids for MOST Model (PortAlexanderAK A), 0.025°

Port Alexander, 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


Port Alexander, Alaska Tsunami Forecast Grids for MOST Model (PortAlexanderAK B), 0.005°


Port Alexander, Alaska Tsunami Forecast Grids for MOST Model (PortAlexanderAK C)


Port Angeles, Washington Tsunami Forecast Grids for MOST Model (PortAngelesWA A), 0.02°

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

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


Port Angeles, Washington Tsunami Forecast Grids for MOST Model (PortAngelesWA B)


Port Angeles, Washington Tsunami Forecast Grids for MOST Model (PortAngelesWA C)


port ensenada 3 mhw 2006 (GDAL Band Number 1), 8.3333335E-4°

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)


Port Graham and Nanwalek, Alaska 8/15 sec Coastal Digital Elevation Model, 1.4814814E-4°


port lions 815 mhhw 2016 (GDAL Band Number 1), 1.4814814E-4°


Port Orford, Oregon Coastal Digital Elevation Model (port orford 13 mhw 2008), 9.259259E-5°

Port Orford, Oregon 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/410; Port Orford, OR 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


Port Orford, Oregon Tsunami Forecast Grids for MOST Model (PortOrfordOR A), 0.02°

Port Orford, Oregon 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)


Port Orford, Oregon Tsunami Forecast Grids for MOST Model (PortOrfordOR B)

NOAA OAR PMEL Center for Tsunami Research


Port Orford, Oregon Tsunami Forecast Grids for MOST Model (PortOrfordOR C)


Port San Luis, California Coastal Digital Elevation Model (port san luis 13 mhw 2011), 9.259259E-5°

Port San Luis, 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/1841; Port San Luis, CA 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


Port San Luis, California Coastal Digital Elevation Model (port san luis 13 navd88 2011), 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/3164; Port San Luis, CA 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


Port San Luis, California Tsunami Forecast Grids for MOST Model (PortSanLuisCA A)

Port San Luis, 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)


Port San Luis, California Tsunami Forecast Grids for MOST Model (PortSanLuisCA B), 0.005°


Port San Luis, California Tsunami Forecast Grids for MOST Model (PortSanLuisCA C)


Port Townsend, Washington Coastal Digital Elevation Model (port townsend 13 mhw 2011), 9.259259E-5°

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

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

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; NOAA NGDC, NESDIS, NOAA; Boulder; Colorado; publisher; NOAA NGDC, NESDIS, NOAA; originator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/366; Port Townsend, WA 1/3 arc-second Tsunami Inundation DEM; Download page for accessing DEM, metadata record and development report.; download; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/tsunami/inundation.html; NOAA Tsunami Inundation Gridding Project; Project web page.; information


Port Townsend, Washington Coastal Digital Elevation Model (port townsend 13 navd88 2011), 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/1786; Port Townsend, WA 1/3 arc-second Tsunami Inundation DEM; Download page for accessing DEM, metadata record and development report.; download; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/tsunami/inundation.html; NOAA Tsunami Inundation Gridding Project; Project web page.; information


Portland, Maine Coastal Digital Elevation Model (portland 13 mhw 2008), 9.259259E-5°

Portland, Maine 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/606; Portland, ME 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


Portland, Maine Tsunami Forecast Grids for MOST Model (PortlandME A)

Portland, Maine 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


Portland, Maine Tsunami Forecast Grids for MOST Model (PortlandME B)


Portland, Maine Tsunami Forecast Grids for MOST Model (PortlandME C)


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

Monthly NARR (pottmp.hl1.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pottmp (Long Term Monthly Mean Potential Temperature, K)

National Centers for Environmental Prediction


pottmp.hl1.mon.ltm (Monthly NARR) [y][x]

Monthly NARR (pottmp.hl1.mon.ltm)

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


pottmp.hl1.mon.mean (NARR Monthly Means) [time][y][x], 1979-present

NARR Monthly Means (pottmp.hl1.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pottmp (Monthly Potential Temperature, K)


pottmp.hl1.mon.mean (NARR Monthly Means) [y][x]

NARR Monthly Means (pottmp.hl1.mon.mean)

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


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

Monthly NARR (pottmp.sfc.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pottmp (Long Term Monthly Mean potential temperature at Surface, degK)


pottmp.sfc.mon.ltm (Monthly NARR) [y][x]

Monthly NARR (pottmp.sfc.mon.ltm)

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


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

NARR Monthly Means (pottmp.sfc.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pottmp (Monthly potential temperature at Surface, degK)


pottmp.sfc.mon.mean (NARR Monthly Means) [y][x]

NARR Monthly Means (pottmp.sfc.mon.mean)

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


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

Monthly 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][y][x]):
pr_wtr (Long Term Monthly Mean Precipitable Water for entire atmosphere, kg/m^2)

National Centers for Environmental Prediction


Monthly 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)


prate.day.ltm (Daily NARR) [time][y][x], 0001

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
prate (Daily long term mean precipitation rate at Surface: Smoothed, kg/m^2/s)


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

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


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
prate (Monthly Long Term Mean precipitation rate at Surface, kg/m^2/s)


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


prate.sfc.gauss.day.ltm.1981-2010 (Daily NCEP/DOE Reanalysis 2), 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 gaussian grid.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
prate (Daily Long Term Mean of Precipitation Rate at Surface, Kg/m^2/s)
valid_yr_count (count of non-missing values used in mean)


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


Precipitation Reconstruction (PREC): 2.5x2.5 (precip.mon.anom), 1948-present

Precipitation Reconstruction (PREC): 2.5x2.5 (precip.mon.anom)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)


Precipitation Reconstruction over Land (PREC/L) 2.5x2.5: Number of Gauges, 1948-present

Precipitation Reconstruction over Land (PREC/L) 2.5x2.5: Number of Gauges (precip.mon.number gauges.2.5x2.5)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Number of Gauges in Grid Cell for Average Monthly Rate of Precipitation, 1)


Precipitation Reconstruction over Land (PREC/L): 0.5x0.5 (precip.mon.1981-2010.ltm.0.5x0.5), 0001

Precipitation Reconstruction over Land (PREC/L): 0.5x0.5 (precip.mon.1981-2010.ltm.0.5x0.5)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Long Term Mean Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)
valid_yr_count (count of non-missing values used in mean)


Precipitation Reconstruction over Land (PREC/L): 0.5x0.5 (precip.mon.ltm.0.5x0.5), 0001

Precipitation Reconstruction over Land (PREC/L): 0.5x0.5 (precip.mon.ltm.0.5x0.5)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Long Term Mean Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)
valid_yr_count (count of non-missing values used in mean)


Precipitation Reconstruction over Land (PREC/L): 0.5x0.5 (precip.mon.mean.0.5x0.5), 1948-2012

Precipitation Reconstruction over Land (PREC/L): 0.5x0.5 (precip.mon.mean.0.5x0.5)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)


Precipitation Reconstruction over Land (PREC/L): 0.5x0.5: Number of Gauges, 1948-2012

Precipitation Reconstruction over Land (PREC/L): 0.5x0.5: Number of Gauges (precip.mon.number gauges.0.5x0.5)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Number of Gauges in Grid Cell for Average Monthly Rate of Precipitation, 1)


Precipitation Reconstruction over Land (PREC/L): 1.0x1.0 (precip.mon.1981-2010.ltm.1x1), 0001

Precipitation Reconstruction over Land (PREC/L): 1.0x1.0 (precip.mon.1981-2010.ltm.1x1)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Average Long Term Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)
valid_yr_count (count of non-missing values used in mean)


Precipitation Reconstruction over Land (PREC/L): 1.0x1.0 (precip.mon.1991-2020.ltm.1x1), 0001

Precipitation Reconstruction over Land (PREC/L): 1.0x1.0 (precip.mon.1991-2020.ltm.1x1)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Long Term Mean Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)
valid_yr_count (count of non-missing values used in mean)


Precipitation Reconstruction over Land (PREC/L): 1.0x1.0 (precip.mon.ltm.1x1), 0001

Precipitation Reconstruction over Land (PREC/L): 1.0x1.0 (precip.mon.ltm.1x1)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Long Term Mean Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)
valid_yr_count (count of non-missing values used in mean)


Precipitation Reconstruction over Land (PREC/L): 1.0x1.0 (precip.mon.mean.1x1), 1948-present

Precipitation Reconstruction over Land (PREC/L): 1.0x1.0 (precip.mon.mean.1x1)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)


Precipitation Reconstruction over Land (PREC/L): 1.0x1.0: Number of Gauges, 1948-present

Precipitation Reconstruction over Land (PREC/L): 1.0x1.0: Number of Gauges (precip.mon.number gauges.1x1)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Number of Gauges in Grid Cell for Average Monthly Rate of Precipitation, 1)


Precipitation Reconstruction over Land (PREC/L): 2.5x2.5 (precip.mon.ltm.2.5x2.5), 0001

Precipitation Reconstruction over Land (PREC/L): 2.5x2.5 (precip.mon.ltm.2.5x2.5)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Long Term Mean Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)
valid_yr_count (count of non-missing values used in mean)


Precipitation Reconstruction over Land (PREC/L): 2.5x2.5 (precip.mon.mean.2.5x2.5), 1948-present

Precipitation Reconstruction over Land (PREC/L): 2.5x2.5 (precip.mon.mean.2.5x2.5)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Average Monthly Rate of Precipitation, seconds since 1970-01-01T00:00:00Z)


pres.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]):
pres (Monthly Long Term Mean Surface Pressure, Pascals)
valid_yr_count (count of non-missing values used in mean)


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

Monthly NARR (pres.sfc.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pres (Monthly pressure at Surface, Pa)

National Centers for Environmental Prediction


Monthly NARR (pres.sfc.mon.ltm)

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


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

Monthly NARR (pres.tropo.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pres (Long Term Monthly Mean Tropopause Pressure, Pa)


pres.tropo.mon.ltm (Monthly NARR) [y][x]

Monthly NARR (pres.tropo.mon.ltm)

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


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

NARR Monthly Means (pres.tropo.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pres (Monthly Tropopause Pressure, Pa)


pres.tropo.mon.mean (NARR Monthly Means) [y][x]

NARR Monthly Means (pres.tropo.mon.mean)

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


Primary Productivity, Aqua MODIS, NPP, Global, 2003-present, EXPERIMENTAL (1 Day Composite)

calculates vertically integrated primary productivity using the Behrenfield - Falkowski method and satellite-based measurements of Chlorophyll a, incident visible surface irradiance, and sea surface temperature.  see (Behrenfield and Falkowski, L&O 1997).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
productivity (Net Primary Productivity Of Carbon, mg C m-2 day-1)


Primary Productivity, Aqua MODIS, NPP, Global, 2003-present, EXPERIMENTAL (1 Day Composite), Lon0360


Primary Productivity, Aqua MODIS, NPP, Global, 2003-present, EXPERIMENTAL (3 Day Composite)

calculates the composite of vertically integrated primary productivity one day files that use the Behrenfield - Falkowski method and satellite-based measurements of Chlorophyll a, incident visible surface irradiance, and sea surface temperature.  see (Behrenfield and Falkowski, L&O 1997).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
productivity (Net Primary Productivity Of Carbon, mg C m-2 day-1)
nobs (Number of observations in composite, count)


Primary Productivity, Aqua MODIS, NPP, Global, 2003-present, EXPERIMENTAL (3 Day Composite), Lon0360


Primary Productivity, Aqua MODIS, NPP, Global, 2003-present, EXPERIMENTAL (8 Day Composite)


Primary Productivity, Aqua MODIS, NPP, Global, 2003-present, EXPERIMENTAL (8 Day Composite), Lon0360


Primary Productivity, Aqua MODIS, NPP, Global, 2003-present, EXPERIMENTAL (Monthly Composite)

calculates the composite of vertically integrated primary productivity one day files that use the Behrenfield - Falkowski method and satellite-based measurements of Chlorophyll a, incident visible surface irradiance, and sea surface temperature.  see (Behrenfield and Falkowski, L&O 1997).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
productivity (Net Primary Productivity Of Carbon, mg C m-2 day-1)


Primary Productivity, Aqua MODIS, NPP, Global, 2003-present, EXPERIMENTAL (Monthly Composite), Lon0360


Prince William Sound, Alaska Coastal Digital Elevation Model (prince william sound 8 mhhw 2009), 0.0022222223°

Prince William Sound, 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/638; Prince William Sound, AK 8 arc-second MHHW DEM; Download page for accessing DEM, metadata record and development report.; download


Prince William Sound, Alaska Coastal Digital Elevation Model, 7.4074074E-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]):
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/735; Prince William Sound, AK 8/3 arc-second MHHW DEM; Download page for accessing DEM, metadata record and development report.; download


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
prmsl (Long Term Monthly Mean Pressure at Mean Sea Level, Pa)


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


Puget Sound 1/3 arc-second MHW Coastal Digital Elevation Model (puget sound 13 mhw 2014), 9.259259E-5°

Puget Sound 1/3 arc-second MHW 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)


Puget Sound 1/3 arc-second NAVD 88 Coastal Digital Elevation Model (puget sound 13 navd88 2014), 9.259259E-5°

Puget Sound 1/3 arc-second NAVD 88 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)


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)


quflux.day.ltm (Daily NARR) [time][y][x], 0001

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

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


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

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


qvflux.day.ltm (Daily NARR) [time][y][x], 0001

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

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


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

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


rarotonga 1 isl 2016 (GDAL Band Number 1), 2.7777778E-4°

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)


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
rcsol (Long Term Monthly Mean Soil Moisture Parameter Canopy Conductance at Surface, 1)


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


Regional Ocean Modeling System (ROMS): Guam: 2-D Variables

Regional Ocean Modeling System (ROMS) 6-day, 3-hourly forecast for the region surrounding Guam and parts of the Commonwealth of the Northern Mariana Islands (CNMI) at approximately 2-km resolution. Boundary conditions provided by the wider ROMS model for the region surrounding the Western North Pacific (roms_mari) at approximately 4-km resolution. Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding Guam and parts of the Commonwealth of the Northern Mariana Islands (CNMI) (wrf_guam) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)

Pacific Islands Ocean Observing System (PacIOOS)


Regional Ocean Modeling System (ROMS): Guam: 3-D Variables

Regional Ocean Modeling System (ROMS) 6-day, 3-hourly forecast for the region surrounding Guam and parts of the Commonwealth of the Northern Mariana Islands (CNMI) at approximately 2-km resolution. Boundary conditions provided by the wider ROMS model for the region surrounding the Western North Pacific (roms_mari) at approximately 4-km resolution. Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding Guam and parts of the Commonwealth of the Northern Mariana Islands (CNMI) (wrf_guam) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: 2-D Variables

Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: 3-D Variables

Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Data Assimilating: 2-D Variables

Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Data Assimilating: 3-D Variables

Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Reanalysis: 2-D Variables

Regional Ocean Modeling System (ROMS) 3-hourly data assimilating reanalysis for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Reanalysis: 3-D Variables

Regional Ocean Modeling System (ROMS) 3-hourly data assimilating reanalysis for the region surrounding the main Hawaiian Islands at approximately 4-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the main Hawaiian Islands (wrf_hi) at approximately 6-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Oahu South Shore: 2-D Variables

Regional Ocean Modeling System (ROMS) 3-day, 3-hourly forecast for the region surrounding the south shore of the island of Oahu at approximately 200-m resolution. Boundary conditions provided by the wider ROMS model for the region surrounding the island of Oahu (roms_hiog) at approximately 1-km resolution. Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the island of Oahu (wrf_oa) at approximately 1.5-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)

Pacific Islands Ocean Observing System (PacIOOS)


Regional Ocean Modeling System (ROMS): Oahu South Shore: 3-D Variables

Regional Ocean Modeling System (ROMS) 3-day, 3-hourly forecast for the region surrounding the south shore of the island of Oahu at approximately 200-m resolution. Boundary conditions provided by the wider ROMS model for the region surrounding the island of Oahu (roms_hiog) at approximately 1-km resolution. Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the island of Oahu (wrf_oa) at approximately 1.5-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; surface currents from PacIOOS high-frequency radios (HFR); and in-situ water temperature and salinity profiles from ARGO floats and ocean glider autonomous underwater vehicles (AUV). While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Samoa: 2-D Variables

Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the islands of Samoa at approximately 3-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the islands of Samoa (wrf_samoa) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Samoa: 3-D Variables

Regional Ocean Modeling System (ROMS) 7-day, 3-hourly forecast for the region surrounding the islands of Samoa at approximately 3-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the islands of Samoa (wrf_samoa) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast) before forecasts are run. Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Regional Ocean Modeling System (ROMS): Samoa: Data Assimilating: 2-D Variables

Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the islands of Samoa at approximately 3-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the islands of Samoa (wrf_samoa) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
zeta (free-surface, meter)


Regional Ocean Modeling System (ROMS): Samoa: Data Assimilating: 3-D Variables

Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the islands of Samoa at approximately 3-km resolution. Boundary conditions provided by the global, 1/12-degree (~9-km) HYbrid Coordinate Ocean Model (HYCOM). Atmospheric forcing generated by the Weather Research and Forecasting (WRF) model for the region surrounding the islands of Samoa (wrf_samoa) at approximately 3-km resolution. Tide forcing uses the Oregon State University (OSU) Tidal Prediction Software (OTPS) TOPEX/Poseidon global inverse solution (TPXO) to derive barotropic tidal elevation and velocity. Data are assimilated over the previous 3 days using all available observations to improve the model estimate of current ocean state (its nowcast). Assimilated observations may include satellite-based sea surface temperatures from MODIS, AVHRR, or OSTIA; satellite-based sea surface height from AVISO; and in-situ water temperature and salinity profiles from ARGO floats. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. As such, please use these data with the caution appropriate for any ocean related activity.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
temp (potential temperature, Celsius)
salt (salinity, 1e-3)
u (u-velocity component, meter second-1)
v (v-velocity component, meter second-1)


Relative Bycatch:Target Catch Probability Product (daily), EcoCast Project

The Relative Bycatch:Target Catch Probability Product is produced using a data-driven, multi-species predictive habitat modelling framework. First, boosted regression tree models were fit to determine the habitat preferences of the target species, broadbill swordfish (Xiphias gladius), and three bycatch-sensitive species that interact with the California drift gillnet fishery (leatherback sea turtle (Dermochelys coricea), blue shark (Prionace glauca), California sea lion (Zalophus californianus)). Then, individual species weightings were set to reflect the level of bycatch and management concern for each species. Prediction layers for each species were then combined into a single surface by multiplying the layer by the species weighting, summing the layers, and then re-calculating the range of values in the final predictive surface from -1 (low catch & high bycatch probabilities) to 1 (high catch & low bycatch probabilities).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ecocast (EcoCast Relative Bycatch-Target Catch Probability Product, 1)


Relative Bycatch:Target Catch Probability Product (daily), EcoCast Project, Lon0360


rhum.2m.mon.ltm (Monthly NARR) [time][y][x], 0001

Monthly NARR (rhum.2m.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
rhum (Long Term Monthly Mean Relative Humidity at 2m, percent)

National Centers for Environmental Prediction


Monthly NARR (rhum.2m.mon.ltm)

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


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Relative Humidity Monthly Long Term Mean at Surface, percent)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Relative Humidity Monthly Long Term Mean at Surface, percent)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Relative Humidity Monthly Long Term Mean at Surface, percent)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Relative Humidity Monthly Long Term Mean at Surface, percent)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Relative Humidity Monthly Long Term Mean at Surface, percent)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Relative Humidity Monthly Long Term Mean at Surface, percent)


RTOFS Forecast, 2D, 3-Hourly Prognostic, Global, Latest Model Run, today - today+8days

The global operational Real-Time Ocean Forecast System (Global RTOFS) at the NOAA National Centers for Environmental Prediction is based on an eddy resolving 1/12° global HYCOM (HYbrid Coordinates Ocean Model) and is part of a larger national backbone capability of ocean modeling at the National Weather Service in a strong partnership with the US Navy.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][latitude][longitude]):
sst (Sea Surface Temperature, degree_C)
sss (Sea Water Practical Salinity, PSU)
u_velocity (Eastward Sea Water Velocity, m s-1)
v_velocity (Northward Sea Water Velocity, m s-1)


RTOFS Forecast, 2D, 3-Hourly Prognostic, Global, Latest Model Run, today - today+8days, Lon+/-180


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


Saco Bay (N110) Bathymetric Digital Elevation Model (saco bay N110 2018), 9.259259E-5°

Saco Bay (N110) Bathymetric Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

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


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)


San Diego Bay (P020) Bathymetric Digital Elevation Model (san diego bay P020 2017), 9.259259E-5°

San Diego Bay (P020) Bathymetric Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

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


San Diego, California Coastal Digital Elevation Model (san diego 13 mhw 2012), 9.259259E-5°

San Diego, 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/3543; San Diego, 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


San Diego, California Coastal Digital Elevation Model (san diego 13 navd88 2012), 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/3542; San Diego, 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


San Diego, California Tsunami Forecast Grids for MOST Model (SanDiegoCA A)

San Diego, 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


San Diego, California Tsunami Forecast Grids for MOST Model (SanDiegoCA B)


San Diego, California Tsunami Forecast Grids for MOST Model (SanDiegoCA C)


San Francisco Bay (P090) Bathymetric Digital Elevation Model (san francisco bay P090 2018), 9.259259E-5°

San Francisco Bay (P090) Bathymetric Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

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


San Francisco Bay, California Coastal Digital Elevation Model (san francisco 13 mhw 2010), 9.259259E-5°

San Francisco Bay, 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/417; San Francisco Bay, 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


San Francisco Bay, California Coastal Digital Elevation Model (san francisco 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/741; San Francisco Bay, 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


San Francisco, California Tsunami Forecast Grids for MOST Model (SanFranciscoCA A), 0.008333334°

San Francisco, 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)


San Francisco, California Tsunami Forecast Grids for MOST Model (SanFranciscoCA B), 0.0016666666°


San Francisco, California Tsunami Forecast Grids for MOST Model (SanFranciscoCA C)


san juan 19 prvd02 2015 (GDAL Band Number 1), 3.0864E-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)


San Juan, Puerto Rico Tsunami Forecast Grids for MOST Model (SanJuanPR A)

San Juan, Puerto Rico 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


San Juan, Puerto Rico Tsunami Forecast Grids for MOST Model (SanJuanPR B)


San Juan, Puerto Rico Tsunami Forecast Grids for MOST Model (SanJuanPR C)