Best NAM Hawaii Time Series [time][pressure_difference_layer5][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][pressure_difference_layer5][y][x]):
Pressure_pressure_difference_layer (Pressure @ Level at specified pressure difference from ground to level layer, Pa)
Specific_humidity_pressure_difference_layer (Specific humidity @ Level at specified pressure difference from ground to level layer, kg/kg)
Temperature_pressure_difference_layer (Temperature @ Level at specified pressure difference from ground to level layer, K)
Relative_humidity_pressure_difference_layer (Relative humidity @ Level at specified pressure difference from ground to level layer, percent)
u_component_of_wind_pressure_difference_layer (u-component of wind @ Level at specified pressure difference from ground to level layer, m/s)
v_component_of_wind_pressure_difference_layer (v-component of wind @ Level at specified pressure difference from ground to level layer, m/s)


Best NAM Hawaii Time Series [time][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
Momentum_flux_u_component_surface (Momentum flux, u-component @ Ground or water surface, N.m-2)
Momentum_flux_v_component_surface (Momentum flux, v-component @ Ground or water surface, N.m-2)
Downward_Short_Wave_Radiation_Flux_surface (Downward Short-Wave Radiation Flux @ Ground or water surface, W.m-2)
Downward_Long_Wave_Radp_Flux_surface (Downward Long-Wave Rad. Flux @ Ground or water surface, W.m-2)
Pressure_grid_scale_cloud_bottom (Pressure @ Grid scale cloud bottom level, Pa)
Pressure_grid_scale_cloud_top (Pressure @ Grid scale cloud top level, Pa)
Vertical_Speed_Shear_tropopause (Vertical Speed Shear @ Tropopause, s-1)
Ventilation_Rate_planetary_boundary (Ventilation Rate @ Planetary Boundary Layer, m2.s-1)
MSLP_Eta_model_reduction_msl (MSLP (Eta model reduction) @ Mean sea level, Pa)
Wind_speed_gust_surface (Wind speed (gust) @ Ground or water surface, m/s)
Categorical_Rain_surface (Categorical Rain @ Ground or water surface, Code table 4.222)
Maximum_Snow_Albedo_surface (Maximum Snow Albedo @ Ground or water surface, percent)
Lightning_surface (Lightning @ Ground or water surface, non-dim)
Specific_humidity_surface (Specific humidity @ Ground or water surface, kg/kg)
Pressure_surface (Pressure @ Ground or water surface, Pa)
Ice_cover_surface (Ice cover @ Ground or water surface)
Land_cover_0_sea_1_land_surface (Land cover (0 = sea, 1 = land) @ Ground or water surface)
Soil_type_surface (Soil type @ Ground or water surface, (Code table 4.213))
Water_temperature_surface (Water temperature @ Ground or water surface, K)
Temperature_surface (Temperature @ Ground or water surface, K)
Visibility_surface (Visibility @ Ground or water surface, m)
Albedo_surface (Albedo @ Ground or water surface, percent)
Surface_roughness_surface (Surface roughness @ Ground or water surface, m)
Haines_index_surface (Haines index @ Ground or water surface)
Vegetation_surface (Vegetation @ Ground or water surface, percent)
Geopotential_height_surface (Geopotential height @ Ground or water surface, gpm)
... (81 more variables)


Best NAM Puerto Rico Time Series [time], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time]):
reftime (GRIB reference time, seconds since 1970-01-01T00:00:00Z)


Best NAM Puerto Rico Time Series [time][altitude_above_msl][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][y][x]):
Temperature_altitude_above_msl (Temperature @ Specific altitude above mean sea level, K)
u_component_of_wind_altitude_above_msl (u-component of wind @ Specific altitude above mean sea level, m/s)
v_component_of_wind_altitude_above_msl (v-component of wind @ Specific altitude above mean sea level, m/s)


Best NAM Puerto Rico Time Series [time][depth_below_surface][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][y][x]):
Soil_temperature_depth_below_surface (Soil temperature @ Depth below land surface, K)


Best NAM Puerto Rico Time Series [time][depth_below_surface_layer2][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][y][x]):
Moisture_Availability_depth_below_surface_layer (Moisture Availability @ Depth below land surface layer, percent)


Best NAM Puerto Rico Time Series [time][hybrid1][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][hybrid1][y][x]):
u_component_of_wind_hybrid (u-component of wind @ Hybrid level, m/s)
v_component_of_wind_hybrid (v-component of wind @ Hybrid level, m/s)
Turbulent_kinetic_energy_hybrid (Turbulent kinetic energy @ Hybrid level, J/kg)


Best NAM Puerto Rico Time Series [time][hybrid][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][hybrid][y][x]):
Total_Condensate_hybrid (Total Condensate @ Hybrid level, kg.kg-1)
Reflectivity_hybrid (Reflectivity @ Hybrid level, dB)
Cloud_mixing_ratio_hybrid (Cloud mixing ratio @ Hybrid level, kg/kg)
Rain_mixing_ratio_hybrid (Rain mixing ratio @ Hybrid level, kg/kg)
Snow_mixing_ratio_hybrid (Snow mixing ratio @ Hybrid level, kg/kg)
Cloud_ice_hybrid (Cloud ice @ Hybrid level, kg.m-2)
Pressure_hybrid (Pressure @ Hybrid level, Pa)
Specific_humidity_hybrid (Specific humidity @ Hybrid level, kg/kg)
Temperature_hybrid (Temperature @ Hybrid level, K)
Relative_humidity_hybrid (Relative humidity @ Hybrid level, percent)
Geopotential_height_hybrid (Geopotential height @ Hybrid level, gpm)
Vertical_velocity_pressure_hybrid (Vertical velocity (pressure) @ Hybrid level, Pa/s)
Blackadars_Mixing_Length_Scale_hybrid (Blackadars Mixing Length Scale @ Hybrid level, m)
Rime_Factor_hybrid (Rime Factor @ Hybrid level, non-dim)


Best NAM Puerto Rico Time Series [time][isobaric2][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][isobaric2][y][x]):
Specific_humidity_isobaric (Specific humidity @ Isobaric surface, kg/kg)
Temperature_isobaric (Temperature @ Isobaric surface, K)
Relative_humidity_isobaric (Relative humidity @ Isobaric surface, percent)
u_component_of_wind_isobaric (u-component of wind @ Isobaric surface, m/s)
v_component_of_wind_isobaric (v-component of wind @ Isobaric surface, m/s)
Geopotential_height_isobaric (Geopotential height @ Isobaric surface, gpm)
Vertical_velocity_pressure_isobaric (Vertical velocity (pressure) @ Isobaric surface, Pa/s)
Vertical_velocity_geometric_isobaric (Vertical velocity (geometric) @ Isobaric surface, m/s)


Best NAM Puerto Rico Time Series [time][pressure_difference_layer1][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][pressure_difference_layer1][y][x]):
Best_4_layer_Lifted_Index_pressure_difference_layer (Best (4 layer) Lifted Index @ Level at specified pressure difference from ground to level layer, K)


Best NAM Puerto Rico Time Series [time][pressure_difference_layer3][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][pressure_difference_layer3][y][x]):
Pressure_of_level_from_which_parcel_was_lifted_pressure_difference_layer (Pressure of level from which parcel was lifted @ Level at specified pressure difference from ground to level layer, Pa)


Best NAM Puerto Rico Time Series [time][pressure_difference_layer4][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][pressure_difference_layer4][y][x]):
Parcel_lifted_index_to_500_hPa_pressure_difference_layer (Parcel lifted index (to 500 hPa) @ Level at specified pressure difference from ground to level layer, K)
Potential_temperature_pressure_difference_layer (Potential temperature @ Level at specified pressure difference from ground to level layer, K)
Precipitable_water_pressure_difference_layer (Precipitable water @ Level at specified pressure difference from ground to level layer, kg.m-2)
Dewpoint_temperature_pressure_difference_layer (Dewpoint temperature @ Level at specified pressure difference from ground to level layer, K)
Horizontal_Moisture_Divergence_pressure_difference_layer (Horizontal Moisture Divergence @ Level at specified pressure difference from ground to level layer, kg.kg-1.s-1)


Best NAM Puerto Rico Time Series [time][pressure_difference_layer5][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][pressure_difference_layer5][y][x]):
Pressure_pressure_difference_layer (Pressure @ Level at specified pressure difference from ground to level layer, Pa)
Specific_humidity_pressure_difference_layer (Specific humidity @ Level at specified pressure difference from ground to level layer, kg/kg)
Temperature_pressure_difference_layer (Temperature @ Level at specified pressure difference from ground to level layer, K)
Relative_humidity_pressure_difference_layer (Relative humidity @ Level at specified pressure difference from ground to level layer, percent)
u_component_of_wind_pressure_difference_layer (u-component of wind @ Level at specified pressure difference from ground to level layer, m/s)
v_component_of_wind_pressure_difference_layer (v-component of wind @ Level at specified pressure difference from ground to level layer, m/s)


Best NAM Puerto Rico Time Series [time][y][x], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
Momentum_flux_u_component_surface (Momentum flux, u-component @ Ground or water surface, N.m-2)
Momentum_flux_v_component_surface (Momentum flux, v-component @ Ground or water surface, N.m-2)
Downward_Short_Wave_Radiation_Flux_surface (Downward Short-Wave Radiation Flux @ Ground or water surface, W.m-2)
Downward_Long_Wave_Radp_Flux_surface (Downward Long-Wave Rad. Flux @ Ground or water surface, W.m-2)
Pressure_grid_scale_cloud_bottom (Pressure @ Grid scale cloud bottom level, Pa)
Pressure_grid_scale_cloud_top (Pressure @ Grid scale cloud top level, Pa)
Vertical_Speed_Shear_tropopause (Vertical Speed Shear @ Tropopause, s-1)
Ventilation_Rate_planetary_boundary (Ventilation Rate @ Planetary Boundary Layer, m2.s-1)
MSLP_Eta_model_reduction_msl (MSLP (Eta model reduction) @ Mean sea level, Pa)
Wind_speed_gust_surface (Wind speed (gust) @ Ground or water surface, m/s)
Categorical_Rain_surface (Categorical Rain @ Ground or water surface, Code table 4.222)
Maximum_Snow_Albedo_surface (Maximum Snow Albedo @ Ground or water surface, percent)
Lightning_surface (Lightning @ Ground or water surface, non-dim)
Specific_humidity_surface (Specific humidity @ Ground or water surface, kg/kg)
Pressure_surface (Pressure @ Ground or water surface, Pa)
Ice_cover_surface (Ice cover @ Ground or water surface)
Land_cover_0_sea_1_land_surface (Land cover (0 = sea, 1 = land) @ Ground or water surface)
Soil_type_surface (Soil type @ Ground or water surface, (Code table 4.213))
Water_temperature_surface (Water temperature @ Ground or water surface, K)
Temperature_surface (Temperature @ Ground or water surface, K)
Visibility_surface (Visibility @ Ground or water surface, m)
Albedo_surface (Albedo @ Ground or water surface, percent)
Surface_roughness_surface (Surface roughness @ Ground or water surface, m)
Haines_index_surface (Haines index @ Ground or water surface)
Vegetation_surface (Vegetation @ Ground or water surface, percent)
Geopotential_height_surface (Geopotential height @ Ground or water surface, gpm)
... (81 more variables)


Best NWPS PHI Time Series [time], 2021-present

Single time dimension: for each forecast time, use GRIB record with smallest offset from reference time

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time]):
reftime (GRIB reference time, seconds since 1970-01-01T00:00:00Z)


Best NWPS TBW Time Series [time], 2021-present


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
bgrun (Long Term Monthly Mean Subsurface Runoff (baseflow), kg/m^2)


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


Biloxi, Mississippi Coastal Digital Elevation Model (biloxi 13 mhw 2007), 9.259259E-5°

Biloxi, Mississippi 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/241; Biloxi, MS 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


Biologically Effective Upwelling Transport Index (BEUTI), Daily

The Coastal Upwelling Transport Index (CUTI, pronounced "cutie") and the Biologically Effective Upwelling Transport Index (BEUTI; pronounced "beauty") are two new upwelling indices that leverage state-of-the-art ocean models as well as satellite and in situ data to improve upon historically available upwelling indices for the U.S. west coast. CUTI provides estimates of vertical transport near the coast (i.e., upwelling/downwelling). It was developed as a more accurate alternative to the previously available "Bakun Index". BEUTI provides estimates of vertical nitrate flux near the coast (i.e., the amount of nitrate upwelled/downwelled), which may be more relevant than upwelling strength when considering some biological responses.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude]):
BEUTI (Biologically Effective Upwelling Transport Index (vertical nitrate flux), mmol m-1 s-1)

NOAA/SWFSC Environmental Research Division


Biologically Effective Upwelling Transport Index (BEUTI), Monthly


Biscayne Bay (S200) Bathymetric Digital Elevation Model (biscayne bay S200 2018), 9.259259E-5°

Biscayne Bay (S200) 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)


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

Monthly NARR (bmixl.hl1.mon.ltm)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
bmixl (Long Term Monthly Mean Blackadar's Mixing Length Scale, m)


Monthly NARR (bmixl.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)


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)


BOSZ Wave-Driven Sea Level Rise Inundation: West Maui

A new modeling approach was implemented here to simulate wave-induced coastal inundation. Using the Boussinesq Ocean and Surf Zone (BOSZ) phase-resolving model, we produced simulations of inundation depth over land for selected combinations of swell amplitudes and directions under different water levels (WLs) that are controlled by the astronomical tides, long-period anomalies (hereafter, will be referred to as background WL), and long-term sea level rise (SLR). The simulations represent three scenarios: (i) Minimum Wave Flooding (minimal swell and high background WL); (ii) Annual High Wave Flooding (large swell and high background WL), and; (iii) Maximum Wave Flooding (largest swell and highest background WL). Simulations for the above three scenarios are repeated for the following SLR projections: 0.0 m; 0.3 m (1 ft); 0.6 m (2 ft); 1.0 m (3.3 ft), and; 2.0 m (6.6 ft). Modeling was carried out over a high-resolution two-dimensional digital elevation model (DEM) that was created by blending the following DEM grids: (i) Lidar data from a 2013 survey by USACE (cloud data with resolution on the order of meters), plus Lidar data from a 2000 survey by USACE (cloud data with resolution on the order of meters; used only to fill certain data gaps found in the 2013 Lidar survey), and; (ii) multibeam bathymetry data from the Hawaii Mapping Research Group (50-m resolution). Results are gridded at 5-m resolution and span the coastline of West Maui, Hawaii.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [longitude][latitude]):
flood_m1a (flood depth: combined minimum swell, WL 0.4m, SLR 0.0m, meters)
flood_m1b (flood depth: combined minimum swell, WL 0.4m, SLR 0.3m, meters)
flood_m1c (flood depth: combined minimum swell, WL 0.4m, SLR 0.6m, meters)
flood_m1d (flood depth: combined minimum swell, WL 0.4m, SLR 1.0m, meters)
flood_m1e (flood depth: combined minimum swell, WL 0.4m, SLR 2.0m, meters)
flood_m2a (flood depth: combined annual high swell, WL 0.4m, SLR 0.0m, meters)
flood_m2b (flood depth: combined annual high swell, WL 0.4m, SLR 0.3m, meters)
flood_m2c (flood depth: combined annual high swell, WL 0.4m, SLR 0.6m, meters)
flood_m2d (flood depth: combined annual high swell, WL 0.4m, SLR 1.0m, meters)
flood_m2e (flood depth: combined annual high swell, WL 0.4m, SLR 2.0m, meters)
flood_m3a (flood depth: combined maximum swell, WL 0.9m, SLR 0.0m, meters)
flood_m3b (flood depth: combined maximum swell, WL 0.9m, SLR 0.3m, meters)
flood_m3c (flood depth: combined maximum swell, WL 0.9m, SLR 0.6m, meters)
... (52 more variables)

Pacific Islands Ocean Observing System (PacIOOS)


British Columbia 3 arc-second Bathymetric Digital Elevation Model (british columbia 3 msl 2013), 8.3333335E-4°

British Columbia 3 arc-second 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)

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


British Columbia, Canada 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


British Columbia, Canada Tsunami Forecast Grids for MOST Model (BritishColumbia A)

British Columbia, Canada 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)


British Columbia, Canada Tsunami Forecast Grids for MOST Model (BritishColumbia B)


C-HARM v1 1-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2018-2022

The C-HARM model generates nowcast and forecasts of the probability of Pseudo-nitzschia concentrations of in excess of 10,000 cells/L in California and Southern Oregon coastal water. Gap-filled chlorophyll a, 488nm reflectance, and 555nm reflectance fields are included in the dataset. Inputs for the model include near real-time satellite observations of ocean color and Regional Ocean Modeling System (ROMS) model nowcast and forecast of surface salinity, sea surface temperature, and surface currents

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pseudo_nitzschia (Probability of Pseudo-nitzschia > 10,000 cells/L , 1)
particulate_domoic (Probability of Particulate Domoic Acid > 500 nanograms/L, 1)
cellular_domoic (Probability of Cellular Domoic Acid > 10 picograms/cell, 1)
chla_filled (Chlorophyll fields filled with DINEOF, mg m^-3)
r555_filled (555nm reflectance fields filled with DINEOF, sr^-1)
r488_filled (488nm reflectance fields filled with DINEOF, sr^-1)


C-HARM v1 1-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2018-2022, Lon+/-180


C-HARM v1 2-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2018-2022


C-HARM v1 2-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2018-2022, Lon+/-180


C-HARM v1 Nowcast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2018-2022


C-HARM v1 Nowcast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2018-2022, Lon+/-180


C-HARM v1, 3-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2018-2022


C-HARM v1, 3-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2018-2022, Lon+/-180


C-HARM v2 1-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2022-present

The C-HARM model generates nowcast and forecasts of the probability of Pseudo-nitzschia concentrations of in excess of 10,000 cells/L, the probability of particulate domoic acid > 500 nanograms/L, and the probability of cellular domoic acid > 10 picograms/cell in California and Southern Oregon coastal water. Inputs for the model include near real-time satellite observations gap-filled chlorophyll a, 486nm reflectance, and 551nm reflectance fields from the S-NPP NOAA VIIRS sensor plus nowcast and forecast data of surface salinity, sea surface temperature, and surface currents from WCOFS ROMS. The chlorophyll a, reflectance, temperature, and surface current fields are included in the dataset

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pseudo_nitzschia (Probability of Pseudo-nitzschia > 10,000 cells/L , 1)
cellular_domoic (Probability of Cellular Domoic Acid > 10 picograms/cell, 1)
particulate_domoic (Probability of Particulate Domoic Acid > 500 nanograms/L, 1)
chla_filled (S-NPP NOAA VIIRS Chlorophyll Fields Filled with DINEOF, mg m^-3)
rrs486_filled (S-NPP NOAA VIIRS 486nm Reflectance Fields Filled with DINEOF, sr^-1)
rrs551_filled (S-NPP NOAA VIIRS 551nm Reflectance Fields Filled with DINEOF, sr^-1)


C-HARM v2 1-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2022-present, Lon+/-180


C-HARM v2 2-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2022-present


C-HARM v2 2-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2022-present, Lon+/-180


C-HARM v2 3-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2022-present


C-HARM v2 3-Day Forecast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2022-present, Lon+/-180


C-HARM v2 Nowcast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2022-present


C-HARM v2 Nowcast, Pseudo-nitzschia, cellular domoic acid, and particular domoic acid probability, California and Southern Oregon coast, 2022-present, Lon+/-180


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

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


Cape Hatteras, North Carolina Coastal Digital Elevation Model (cape hatteras 13 mhw 2006), 9.259259E-5°

Cape Hatteras, North Carolina 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/296; Cape Hatteras, NC 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


Cape Hatteras, North Carolina Tsunami Forecast Grids for MOST Model (CapeHatterasNC A)

Cape Hatteras, North Carolina 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


Cape Hatteras, North Carolina Tsunami Forecast Grids for MOST Model (CapeHatterasNC B)


Cape Hatteras, North Carolina Tsunami Forecast Grids for MOST Model (CapeHatterasNC C)


Carbontracker CT2009 Fluxes (ct flux) [date], 2000-2001

Carbontracker CT2009 Fluxes. NOAA Earth System Research Laboratory (ESRL) data from https://data.pmel.noaa.gov/pmel/thredds/dodsC/ct_flux.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time]):
decimal_date (years)


Carbontracker CT2009 Fluxes (ct flux) [date][calendar_components], 2000-2001

Carbontracker CT2009 Fluxes. NOAA Earth System Research Laboratory (ESRL) data from https://data.pmel.noaa.gov/pmel/thredds/dodsC/ct_flux.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][calendar_components]):
date_components (integer components of UTC date)


Carbontracker CT2009 Fluxes (ct flux) [date][lat][lon], 1.0°, 2000-2001

Carbontracker CT2009 Fluxes. NOAA Earth System Research Laboratory (ESRL) data from https://data.pmel.noaa.gov/pmel/thredds/dodsC/ct_flux.das .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
fossil_imposed (imposed surface CO2 flux due to fossil fuel burning, mol m-2 s-1)
bio_flux_optimized (optimized surface CO2 flux due to terrestrial biosphere exchange, mol m-2 s-1)
ocean_flux_optimized (optimized surface CO2 flux due to air-sea exchange, mol m-2 s-1)
fire_flux_imposed (imposed surface CO2 flux due to fire emissions, mol m-2 s-1)


Casco Bay (N100) Bathymetric Digital Elevation Model (casco bay N100 2018), 9.259259E-5°

Casco Bay (N100) 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)


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
ccond (Long Term Monthly Mean Canopy Conductance at Surface, m/s)


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


CDC DERIVED NOAA OI SST V2 (sst.day.ltm), 1.0°, 0001

CDC DERIVED NOAA OI SST V2. Data is derived from NOAA Optimum Interpolation Sea Surface Temperature (OISST) V2

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


cdcon.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]):
cdcon (Long Term Monthly Mean Mean of Convective Cloud Cover at Entire Atmosphere Considered as a Single Layer, percent)


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)


cdlyr.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]):
cdlyr (Long Term Monthly Mean Mean of Non-Convective Cloud Cover at Entire Atmosphere Considered as a Single Layer, percent)


Central California Coastal Digital Elevation Model (central california 1 mhw 2010), 2.7777778E-4°

Central 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/739; Central California 1 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


Central California Coastal Digital Elevation Model (central california 1 navd88 2010), 2.7777778E-4°

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; NOAA NGDC, NESDIS, NOAA; Boulder; Colorado; publisher; NOAA NGDC, NESDIS, NOAA; originator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/665; Central California 1 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


Central Florida 1/3 arc-second MHW 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)

NCTR; NCTR; information; collaborator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/5230; Central Florida 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


Central Florida 1/3 arc-second NAVD 88 Coastal Digital Elevation Model, 9.259259E-5°

NCTR; NCTR; information; collaborator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/5167; Central Florida 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


central oregon 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)


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


cfnsf.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]):
cfnsf (Monthly Long Term Mean Cloud Forcing Net Solar Flux at Surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


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

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

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


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


Charleston Harbor (S080) Bathymetric Digital Elevation Model (charleston harbor S080 2017), 9.259259E-5°

Charleston Harbor (S080) 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)


Charlotte Amalie, Virgin Islands Tsunami Forecast Grids for MOST Model (CharlotteAmalieVI A)

Charlotte Amalie, Virgin Islands 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


Charlotte Amalie, Virgin Islands Tsunami Forecast Grids for MOST Model (CharlotteAmalieVI B), 5.5555557E-4°


Charlotte Amalie, Virgin Islands Tsunami Forecast Grids for MOST Model (CharlotteAmalieVI C), 0.0033333334°


Charlotte Harbor (G050) Bathymetric Digital Elevation Model (charlotte harbor G050 2018), 9.259259E-5°

Charlotte Harbor (G050) 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)


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

Chenega, 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/702; Chenega, AK 8/15 arc-second MHHW DEM; Download page for accessing DEM, metadata record, and development report.; download


Chesapeake Bay (M130) Bathymetric Digital Elevation Model (chesapeake bay M130 2017), 9.259259E-5°

Chesapeake Bay (M130) 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]):
z (meters)


Chignik, Alaska 1 arc-second Coastal Digital Elevation Model (chignik 1 mhhw 2014), 2.7777778E-4°

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

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

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


Chignik, Alaska 1/3 arc-second Coastal Digital Elevation Model (chignik 13 mhhw 2014), 9.259259E-5°

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

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


chiniak 815 mhhw 2015 (GDAL Band Number 1), 1.4814814E-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)


CHIRPS Version 2.0, Precipitation, Global, 0.05°, 5-Day, 1981-present

This dataset has 5-day (pentad) averages of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), which is quasi-global rainfall data set. Spanning 50°S-50°N (and all longitudes) and ranging from 1981 to near-present, CHIRPS incorporates our in-house climatology, CHPclim, 0.05° resolution satellite imagery, and in-situ station data to create a gridded rainfall time series for trend analysis and seasonal drought monitoring. Since 1999, USGS and CHC scientists (supported by funding from USAID, NASA, and NOAA) have developed techniques for producing rainfall maps, especially in areas where surface data is sparse. Estimating rainfall variations in space and time is a key aspect of drought early warning and environmental monitoring. See https://www.nature.com/articles/sdata201566 . See the FAQ at https://wiki.chc.ucsb.edu/CHIRPS_FAQ .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Precipitation, mm/(5days))


CHIRPS Version 2.0, Precipitation, Global, 0.05°, 5-Day, 1981-present, Lon0360


CHIRPS Version 2.0, Precipitation, Global, 0.05°, Annual, 1981-present

This dataset has annual averages of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), which is quasi-global rainfall data set. Spanning 50°S-50°N (and all longitudes) and ranging from 1981 to near-present, CHIRPS incorporates our in-house climatology, CHPclim, 0.05° resolution satellite imagery, and in-situ station data to create a gridded rainfall time series for trend analysis and seasonal drought monitoring. Since 1999, USGS and CHC scientists (supported by funding from USAID, NASA, and NOAA) have developed techniques for producing rainfall maps, especially in areas where surface data is sparse. Estimating rainfall variations in space and time is a key aspect of drought early warning and environmental monitoring. See https://www.nature.com/articles/sdata201566 . See the FAQ at https://wiki.chc.ucsb.edu/CHIRPS_FAQ .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Precipitation, mm/year)


CHIRPS Version 2.0, Precipitation, Global, 0.05°, Annual, 1981-present, Lon0360


CHIRPS Version 2.0, Precipitation, Global, 0.05°, Daily, 1981-present

This dataset has 1-day (daily) averages of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), which is quasi-global rainfall data set. Spanning 50°S-50°N (and all longitudes) and ranging from 1981 to near-present, CHIRPS incorporates our in-house climatology, CHPclim, 0.05° resolution satellite imagery, and in-situ station data to create a gridded rainfall time series for trend analysis and seasonal drought monitoring. Since 1999, USGS and CHC scientists (supported by funding from USAID, NASA, and NOAA) have developed techniques for producing rainfall maps, especially in areas where surface data is sparse. Estimating rainfall variations in space and time is a key aspect of drought early warning and environmental monitoring. See https://www.nature.com/articles/sdata201566 . See the FAQ at https://wiki.chc.ucsb.edu/CHIRPS_FAQ .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Precipitation, mm/day)


CHIRPS Version 2.0, Precipitation, Global, 0.05°, Daily, 1981-present, Lon0360


CHIRPS Version 2.0, Precipitation, Global, 0.05°, Monthly, 1981-present

This dataset has monthly averages of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), which is quasi-global rainfall data set. Spanning 50°S-50°N (and all longitudes) and ranging from 1981 to near-present, CHIRPS incorporates our in-house climatology, CHPclim, 0.05° resolution satellite imagery, and in-situ station data to create a gridded rainfall time series for trend analysis and seasonal drought monitoring. Since 1999, USGS and CHC scientists (supported by funding from USAID, NASA, and NOAA) have developed techniques for producing rainfall maps, especially in areas where surface data is sparse. Estimating rainfall variations in space and time is a key aspect of drought early warning and environmental monitoring. See https://www.nature.com/articles/sdata201566 . See the FAQ at https://wiki.chc.ucsb.edu/CHIRPS_FAQ .

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
precip (Precipitation, mm/month)


CHIRPS Version 2.0, Precipitation, Global, 0.05°, Monthly, 1981-present, Lon0360


Chlorophyll a, North Pacific, NOAA VIIRS, 750m resolution, 2015-present (1 Day Composite)

NOAA CoastWatch distributes L3 level chlorophyll a concentration data derived from measurements take by the VIIRS sensor (Visible Infrared Imaging Radiometer Suite) aboard the Suomi-NPP satellite. Chlorophyll values were calculated using NOAA-MSL12 NRT processing with LAND+CLDICE+HIGLINT+HISATZEN+HISOLZEN masking.

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


Chlorophyll a, North Pacific, NOAA VIIRS, 750m resolution, 2015-present (1 Day Composite), Lon0360


Chlorophyll a, North Pacific, NOAA VIIRS, 750m resolution, 2015-present (3 Day Composite)


Chlorophyll a, North Pacific, NOAA VIIRS, 750m resolution, 2015-present (3 Day Composite), Lon0360


Chlorophyll a, North Pacific, NOAA VIIRS, 750m resolution, 2015-present (8 Day Composite)


Chlorophyll a, North Pacific, NOAA VIIRS, 750m resolution, 2015-present (8 Day Composite), Lon0360


Chlorophyll a, North Pacific, NOAA VIIRS, 750m resolution, 2015-present (Monthly Composite)


Chlorophyll a, North Pacific, NOAA VIIRS, 750m resolution, 2015-present (Monthly Composite), Lon0360


Chlorophyll-a Deviation, Orbview-2 SeaWiFS, 0.0125°, West US, 1998-2009 (8 Day Composite) DEPRECATED

NOAA CoastWatch distributes chlorophyll-a concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on the Orbview-2 satellite.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chl_dev (Deviation of Chlorophyll Concentration In Sea Water, mg m-3)


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (1 Day Composite)

NOAA CoastWatch distributes chlorophyll-a concentration data from NASA's Aqua Spacecraft.  Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard the spacecraft.  The algorithm currently used in processing the water leaving radiance to chlorophyll concentration has not yet been accepted as science quality.  In addition, assumptions are made in the atmospheric correction in order to provide the data in a timely manner.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chlorophyll (Concentration Of Chlorophyll In Sea Water, mg m-3)


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (1 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (14 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (14 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (3 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (3 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (8 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (8 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (Monthly Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.0125°, West US, EXPERIMENTAL, 2002-present (Monthly Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (1 Day Composite)

NOAA CoastWatch distributes chlorophyll-a concentration data from NASA's Aqua Spacecraft.  Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard the spacecraft.  The algorithm currently used in processing the water leaving radiance to chlorophyll concentration has not yet been accepted as science quality.  In addition, assumptions are made in the atmospheric correction in order to provide the data in a timely manner.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chlorophyll (Chlorophyll Concentration in Sea Water, mg m-3)


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (1 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (14 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (14 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (3 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (3 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (8 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (8 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (Monthly Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2006-present, EXPERIMENTAL (Monthly Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2013-present, EXPERIMENTAL (5 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, 0.025 degrees, Pacific Ocean, 2013-present, EXPERIMENTAL (5 Day Composite), Lon+/-180


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite)

This dataset has Level 3, Standard Mapped Image, 4km, chlorophyll-a concentration 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]):
chlorophyll (Mean Chlorophyll a Concentration, mg m-3)


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite), Lon0360


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite), Lon0360


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite)


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite), Lon0360


Chlorophyll-a, Orbview-2 SeaWiFS, 0.0125°, West US, 1998-2009 (1 Day Composite) DEPRECATED

NOAA CoastWatch distributes chlorophyll-a concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on the Orbview-2 satellite.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chlorophyll (Concentration Of Chlorophyll In Sea Water, mg m-3)


Chlorophyll-a, Orbview-2 SeaWiFS, 0.0125°, West US, 1998-2009 (3 Day Composite) DEPRECATED


Chlorophyll-a, Orbview-2 SeaWiFS, 0.0125°, West US, 1998-2009 (8 Day Composite) DEPRECATED


Chlorophyll-a, Orbview-2 SeaWiFS, 0.0125°, West US, 2006-2009 (14 Day Composite) DEPRECATED


Chlorophyll-a, Orbview-2 SeaWiFS, 0.0125°, West US, 2009-2009 (Single Scan) DEPRECATED


Chlorophyll-a, Orbview-2 SeaWiFS, 0.1°, Global, 1997-2010 (8 Day Composite) DEPRECATED

THIS VERSION IS DEPRECATED. SEE THE NEW R2018.0 VERSION IN erdSW2018chla8day. (Feb 2018)
NASA GSFC Ocean Color Web distributes science-quality chlorophyll-a concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on the Orbview-2 satellite.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chlorophyll (Concentration Of Chlorophyll In Sea Water, mg m-3)


Chlorophyll-a, Orbview-2 SeaWiFS, 0.1°, Global, 1997-2010 (Monthly Composite) DEPRECATED

THIS VERSION IS DEPRECATED. SEE THE NEW R2018.0 VERSION IN erdSW2018chla1day. (Feb 2018)
NASA GSFC Ocean Color Web distributes science-quality chlorophyll-a concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on the Orbview-2 satellite.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chlorophyll (Concentration Of Chlorophyll In Sea Water, mg m-3)


Chlorophyll-a, Orbview-2 SeaWiFS, R2014.0, 0.1°, Global, 1997-2010 (1 Day Composite) DEPRECATED

THIS VERSION IS DEPRECATED. SEE THE NEW R2018.0 VERSION IN erdSW2018chla1day. (Feb 2018)

NASA GSFC Ocean Color Web distributes science-quality chlorophyll-a
concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS)
on the Orbview-2 satellite. This version is the 2014.0 Reprocessing (R2014.0).

The SeaWiFS instrument was launched by Orbital Sciences Corporation on the
OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from
September 1997 until the end of mission in December 2010. SeaWiFS had 8
spectral bands from 412 to 865 nm. It collected global data at 4 km
resolution, and local data (limited onboard storage and direct broadcast)
at 1 km. The mission and sensor were optimized for ocean color measurements,
with a local noon (descending) equator crossing time orbit, fore-and-aft
tilt capability, full dynamic range, and low polarization sensitivity.

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


Chlorophyll-a, Orbview-2 SeaWiFS, R2014.0, 0.1°, Global, 1997-2010 (1 Day Composite) DEPRECATED, Lon0360


Chlorophyll-a, Orbview-2 SeaWiFS, R2014.0, 0.1°, Global, 1997-2010 (8 Day Composite) DEPRECATED

THIS VERSION IS DEPRECATED. SEE THE NEW R2018.0 VERSION IN erdSW2018chla8day. (Feb 2018)

NASA GSFC Ocean Color Web distributes science-quality chlorophyll-a
concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS)
on the Orbview-2 satellite. This version is the 2014.0 Reprocessing (R2014.0).

The SeaWiFS instrument was launched by Orbital Sciences Corporation on the
OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from
September 1997 until the end of mission in December 2010. SeaWiFS had 8
spectral bands from 412 to 865 nm. It collected global data at 4 km
resolution, and local data (limited onboard storage and direct broadcast)
at 1 km. The mission and sensor were optimized for ocean color measurements,
with a local noon (descending) equator crossing time orbit, fore-and-aft
tilt capability, full dynamic range, and low polarization sensitivity.

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


Chlorophyll-a, Orbview-2 SeaWiFS, R2014.0, 0.1°, Global, 1997-2010 (8 Day Composite) DEPRECATED, Lon0360


Chlorophyll-a, Orbview-2 SeaWiFS, R2014.0, 0.1°, Global, 1997-2010 (Monthly Composite) DEPRECATED

THIS VERSION IS DEPRECATED. SEE THE NEW R2018.0 VERSION IN erdSW2018chlamday. (Feb 2018)

NASA GSFC Ocean Color Web distributes science-quality chlorophyll-a
concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS)
on the Orbview-2 satellite. This version is the 2014.0 Reprocessing (R2014.0).

The SeaWiFS instrument was launched by Orbital Sciences Corporation on the
OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from
September 1997 until the end of mission in December 2010. SeaWiFS had 8
spectral bands from 412 to 865 nm. It collected global data at 4 km
resolution, and local data (limited onboard storage and direct broadcast)
at 1 km. The mission and sensor were optimized for ocean color measurements,
with a local noon (descending) equator crossing time orbit, fore-and-aft
tilt capability, full dynamic range, and low polarization sensitivity.

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


Chlorophyll-a, Orbview-2 SeaWiFS, R2014.0, 0.1°, Global, 1997-2010 (Monthly Composite) DEPRECATED, Lon0360


Chlorophyll-a, Orbview-2 SeaWiFS, R2018.0, 0.1°, Global, 1997-2010 (1 Day Composite)

NASA GSFC Ocean Color Web distributes science-quality chlorophyll-a
concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS)
on the Orbview-2 satellite. This version is the 2018.0 Reprocessing (R2018.0). https://oceancolor.gsfc.nasa.gov/reprocessing/r2018/seawifs/

The SeaWiFS instrument was launched by Orbital Sciences Corporation on the
OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from
September 1997 until the end of mission in December 2010. SeaWiFS had 8
spectral bands from 412 to 865 nm. It collected global data at 4 km
resolution, and local data (limited onboard storage and direct broadcast)
at 1 km. The mission and sensor were optimized for ocean color measurements,
with a local noon (descending) equator crossing time orbit, fore-and-aft
tilt capability, full dynamic range, and low polarization sensitivity.

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


Chlorophyll-a, Orbview-2 SeaWiFS, R2018.0, 0.1°, Global, 1997-2010 (1 Day Composite), Lon0360


Chlorophyll-a, Orbview-2 SeaWiFS, R2018.0, 0.1°, Global, 1997-2010 (8 Day Composite)

NASA GSFC Ocean Color Web distributes science-quality chlorophyll-a
concentration data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS)
on the Orbview-2 satellite. This version is the 2018.0 Reprocessing (R2018.0).
https://oceancolor.gsfc.nasa.gov/reprocessing/r2018/seawifs/

The SeaWiFS instrument was launched by Orbital Sciences Corporation on the
OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from
September 1997 until the end of mission in December 2010. SeaWiFS had 8
spectral bands from 412 to 865 nm. It collected global data at 4 km
resolution, and local data (limited onboard storage and direct broadcast)
at 1 km. The mission and sensor were optimized for ocean color measurements,
with a local noon (descending) equator crossing time orbit, fore-and-aft
tilt capability, full dynamic range, and low polarization sensitivity.

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


Chlorophyll-a, Orbview-2 SeaWiFS, R2018.0, 0.1°, Global, 1997-2010 (8 Day Composite), Lon0360


Chlorophyll-a, Orbview-2 SeaWiFS, R2018.0, 0.1°, Global, 1997-2010 (Monthly Composite)


Chlorophyll-a, Orbview-2 SeaWiFS, R2018.0, 0.1°, Global, 1997-2010 (Monthly Composite), Lon0360


Choctawhatchee Bay (G120) Bathymetric Digital Elevation Model (choctawhatchee bay G120 2018), 9.25925E-5°

Choctawhatchee Bay (G120) 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)


Christiansted, Virgin Islands Tsunami Forecast Grids for MOST Model (ChristianstedVI A)

Christiansted, Virgin Islands 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


Christiansted, Virgin Islands Tsunami Forecast Grids for MOST Model (ChristianstedVI B), 0.0011111111°


Christiansted, Virgin Islands Tsunami Forecast Grids for MOST Model (ChristianstedVI C)


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2010-2013 (Monthly Composite)

MODIS data is used to develop an index of the amount of chromophoric dissolved organic material (CDOM) in the surface waters.  CDOM absorbs heavily in the blue wavelengths and thus can skew many derived products, especially in coastal waters.  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]):
cdom (Chromophoric Dissolved Organic Material, 1)


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2010-2013 (Monthly Composite), Lon+/-180


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2012-2015 (14 Day Composite)


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2012-2015 (14 Day Composite), Lon+/-180


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2012-2015 (3 Day Composite)


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2012-2015 (3 Day Composite), Lon+/-180


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2012-2015 (8 Day Composite)


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2012-2015 (8 Day Composite), Lon+/-180


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2012-2016 (1 Day Composite)


Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.0125°, West US, 2012-2016 (1 Day Composite), Lon+/-180


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

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

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


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


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
cldc (Cloudiness Monthly Long Term Mean at Surface, okta)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
cldc (Cloudiness Monthly Long Term Mean at Surface, okta)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
cldc (Cloudiness Monthly Long Term Mean at Surface, okta)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
cldc (Cloudiness Monthly Long Term Mean at Surface, okta)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
cldc (Cloudiness Monthly Long Term Mean at Surface, okta)


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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
cldc (Cloudiness Monthly Long Term Mean at Surface, okta)


Cloudmask, CLAVR-1, NOAA POES AVHRR, 0.0125 degrees, West US, 2007-present, Daytime (Single Scan)

 The CLAVR-1 cloudmask (Stowe, 1999) is used to cloudmask AVHRR high resolution sea surface temperature products.  The cloudmask runs a series of tests on each surface temperature pixel to determine whether the pixel is contaminated by cloud cover.  Users may evaluate which specific tests in the cloudmask returned positive cloud presence results by examining the value of the cloudmask.  This value corresponds to an 8 bit binary number which details which tests flagged the pixel as a cloudy pixel.  See https://coastwatch.pfeg.noaa.gov/info/CLAVR.html for more information regarding the specific tests used in the cloudmask.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
cloudmask (Daytime Cloud Mask, 8 bits, encoded)


Cloudmask, CLAVR-1, NOAA POES AVHRR, 0.0125 degrees, West US, 2007-present, Daytime (Single Scan), Lon+/-180


Cloudmask, CLAVR-1, NOAA POES AVHRR, 0.0125 degrees, West US, 2007-present, Nighttime (Single Scan)

 The CLAVR-1 cloudmask (Stowe, 1999) is used to cloudmask AVHRR high resolution sea surface temperature products.  The cloudmask runs a series of tests on each surface temperature pixel to determine whether the pixel is contaminated by cloud cover.  Users may evaluate which specific tests in the cloudmask returned positive cloud presence results by examining the value of the cloudmask.  This value corresponds to an 8 bit binary number which details which tests flagged the pixel as a cloudy pixel.  See https://coastwatch.pfeg.noaa.gov/info/CLAVR.html for more information regarding the specific tests used in the cloudmask.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
cloudmask (Nighttime Cloud Mask, 8 bits, encoded)


Cloudmask, CLAVR-1, NOAA POES AVHRR, 0.0125 degrees, West US, 2007-present, Nighttime (Single Scan), Lon+/-180


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
cnwat (Long Term Monthly Mean Plant Canopy Water at Surface, kg/m^2)


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


COADS Surface Marine Observations (1854-1993), 2.0°

Comprehensive Ocean Atmosphere Data Set (COADS) Surface Marine Observations (1854-1993)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
AIR (Air Temperature, deg C)
CLDC (Cloudiness, okta)
LFLX (Latent Heat Parameter, grams/kg m/s)
NAIR (Number of air obs)
NCLDC (Number of cldc obs)
NLFLX (Number of lflx obs)
NRHUM (Number of rhum obs)
NSFLX (Number of sflx obs)
NSHUM (Number of shum obs)
NSLP (Number of slp obs)
NSST (Number of sst obs)
NUSTR (Number of ustr obs)
NUWND (Number of uwnd obs)
NVSTR (Number of vstr obs)
NVWND (Number of vwnd obs)
NWSPD (Number of wspd obs)
RHUM (Relative Humidity, percent)
SFLX (Sensible Heat Parameter, deg C m/s)
SHUM (Specific Humidity, gm/kg)
SLP (Sea Level Pressure, mb)
SST (Sea Surface Temperature, deg C)
USTR (Zonal Pseudostress, m**/s**2)
UWND (Zonal Wind, m/s)
VSTR (Meridional Pseudostress, m**/s**2)
VWND (Meridional Wind, m/s)
WSPD (Wind Speed, m/s)


Coastal Upwelling Transport Index (CUTI), Daily

The Coastal Upwelling Transport Index (CUTI, pronounced "cutie") and the Biologically Effective Upwelling Transport Index (BEUTI; pronounced "beauty") are two new upwelling indices that leverage state-of-the-art ocean models as well as satellite and in situ data to improve upon historically available upwelling indices for the U.S. west coast. CUTI provides estimates of vertical transport near the coast (i.e., upwelling/downwelling). It was developed as a more accurate alternative to the previously available "Bakun Index". BEUTI provides estimates of vertical nitrate flux near the coast (i.e., the amount of nitrate upwelled/downwelled), which may be more relevant than upwelling strength when considering some biological responses.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude]):
CUTI (Coastal Upwelling Transport Index (vertical volume transport), m2 s-1)

NOAA/SWFSC Environmental Research Division


Coastal Upwelling Transport Index (CUTI), Monthly


COBE SST Analysis (sst.mon.ltm.1981-2010), 1.0°, 0001

COBE Sea Surface Temperature Analysis. recent values (w/i last year) may change as dataset is updated. It is a monitoring dataset.

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


COBE SST Analysis (sst.mon.ltm.1991-2020), 1.0°, 0001


COBE SST Analysis (sst.mon.mean), 1.0°, 1891-present

COBE Sea Surface Temperature Analysis. recent values (w/i last year) may change as dataset is updated. It is a monitoring dataset.

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


Cold Bay, Alaska 8 arc-second Coastal Digital Elevation Model (cold bay 8 mhhw 2013), 0.0022222223°

Cold Bay, Alaska 8 arc-second Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

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

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


Cold Bay, Alaska 8/15 arc-second Coastal Digital Elevation Model (cold bay 815 mhhw 2013), 1.4814814E-4°

Cold Bay, Alaska 8/15 arc-second Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

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


Cold Bay, Alaska 8/3 arc-second Coastal Digital Elevation Model (cold bay 83 mhhw 2013), 7.4074074E-4°

Cold Bay, Alaska 8/3 arc-second Coastal Digital Elevation Model. National Centers for Environmental Information (NCEI) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. DEMs are used for coastal process modeling (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness.

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


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)


Cordova, Alaska Coastal Digital Elevation Model (cordova 13 mhw 2010), 9.259259E-5°

Cordova, 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/256; Cordova, AK 1/3 arc-second Tsunami Inundation DEM; Download page for accessing DEM, metadata record and development report.; download; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/tsunami/inundation.html; NOAA Tsunami Inundation Gridding Project; Project web page.; information


Cordova, Alaska Coastal Digital Elevation Model (cordova 3 mhw 2010), 8.3333335E-4°

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; NOAA NGDC, NESDIS, NOAA; Boulder; Colorado; publisher; NOAA NGDC, NESDIS, NOAA; originator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/696; Cordova, AK 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


Cordova, Alaska Coastal Digital Elevation Model (cordova 815 mhhw 2009), 1.4814814E-4°

Cordova, 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]):
z (Topography (m), 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/640; Cordova, AK 8/15 arc-second MHHW DEM; Download page for accessing DEM, metadata record and development report.; download


Cordova, Alaska Tsunami Forecast Grids for MOST Model (CordovaAK A)

Cordova, 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


Cordova, Alaska Tsunami Forecast Grids for MOST Model (CordovaAK B)


Cordova, Alaska Tsunami Forecast Grids for MOST Model (CordovaAK C)


Corpus Christi Bay (G310) Bathymetric Digital Elevation Model (corpus christi bay G310 2018), 9.259259E-5°

Corpus Christi Bay (G310) 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)


Corpus Christi, Texas Coastal Digital Elevation Model (corpus christi 13 mhw 2007), 9.259259E-5°

Corpus Christi, Texas 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/401; Corpus Christi, TX 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


Data file is obtained from Climate Prediction Center (CPC)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
land (Land-sea Mask)


Data file is obtained from Climate Prediction Center (CPC)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
landperc (Percent of grid that is land, percent)


CPC Merged Analysis of Precipitation (excludes NCEP Reanalysis) (precip.mon.ltm), 2.5°, 0001

Climate Prediction Center (CPC) Merged Analysis of Precipitation (excludes National Centers for Environmental Prediction (NCEP) Reanalysis) (precip.mon.ltm)

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


CPC Merged Analysis of Precipitation (excludes NCEP Reanalysis) (precip.mon.ltm.1991-2020), 2.5°, 0001

Climate Prediction Center (CPC) Merged Analysis of Precipitation (excludes National Centers for Environmental Prediction (NCEP) Reanalysis) (precip.mon.ltm.1991-2020)

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


CPC Merged Analysis of Precipitation (excludes NCEP Reanalysis) (precip.mon.mean), 2.5°, 1979-present

Climate Prediction Center (CPC) Merged Analysis of Precipitation (excludes National Centers for Environmental Prediction (NCEP) Reanalysis) (precip.mon.mean)

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)


CPC Merged Analysis of Precipitation (includes NCEP Reanalysis) (precip.mon.ltm), 2.5°, 0001

Climate Prediction Center (CPC) Merged Analysis of Precipitation (includes National Centers for Environmental Prediction (NCEP) Reanalysis) (precip.mon.ltm)

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


CPC Merged Analysis of Precipitation (includes NCEP Reanalysis) (precip.mon.ltm.1991-2020), 2.5°, 0001

Climate Prediction Center (CPC) Merged Analysis of Precipitation (includes National Centers for Environmental Prediction (NCEP) Reanalysis) (precip.mon.ltm.1991-2020)

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


CPC Merged Analysis of Precipitation (includes NCEP Reanalysis) (precip.mon.mean), 2.5°, 1979-present

Climate Prediction Center (CPC) Merged Analysis of Precipitation (includes National Centers for Environmental Prediction (NCEP) Reanalysis) (precip.mon.mean)

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)


CPC Merged Analysis of Precipitation Pentad data (excludes NCEP Reanalysis I), 2.5°, 1979-2016

Climate Prediction Center (CPC) Merged Analysis of Precipitation Pentad data (excludes National Centers for Environmental Prediction (NCEP) Reanalysis I) (precip.pentad.mean)

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


CPC Merged Analysis of Precipitation Pentad data (includes NCEP Reanalysis I), 2.5°, 1979-2016

Climate Prediction Center (CPC) Merged Analysis of Precipitation Pentad data (includes National Centers for Environmental Prediction (NCEP) Reanalysis I) (precip.pentad.mean)

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


CPC Merged Analysis of Precipitation Pentad RT data (excludes NCEP Reanalysis I), 2.5°, 2000-present

Climate Prediction Center (CPC) Merged Analysis of Precipitation Pentad RT data (excludes National Centers for Environmental Prediction (NCEP) Reanalysis I) (precip.pentad.mean.rt)

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


CPC Soil Moisture (soilw.mon.ltm.v2), 0.5°, 0001

Climate Prediction Center (CPC) Soil Moisture (soilw.mon.ltm.v2)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
soilw (Model-Calculated Long Term Monthly Mean Soil Moisture, mm)
valid_yr_count (count of non-missing values used in mean)


CPC Soil Moisture (soilw.mon.mean), 0.5°, 1948-present

Climate Prediction Center (CPC) Soil Moisture (soilw.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
soilw (Model-Calculated Monthly Mean Soil Moisture, mm)


CPC Soil Moisture (soilw.mon.mean.v2), 0.5°, 1948-present

Climate Prediction Center (CPC) Soil Moisture (soilw.mon.mean.v2)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
soilw (Model-Calculated Monthly Mean Soil Moisture, mm)