Multi-scale Ultra-high Resolution (MUR) SST Analysis fv04.1, Global, 0.01°, 2002-present, Monthly

A monthly mean Sea Surface Temperature (SST) product created by NOAA NMFS SWFSC ERD based on the daily, global, Multi-scale, Ultra-high Resolution (MUR) Sea Surface Temperature (SST) 1-km data set, Version 4.1, which is produced at the NASA Jet Propulsion Laboratory (JPL) under the NASA MEaSUREs program. For details of the source dataset, see https://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4-GLOB-v4.1 . The source dataset is part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Sea Surface Temperature Monthly Mean, degree_C)
nobs (Number of Observations)
mask (Sea/Land Field Composite Mask)

NOAA ERD and CoastWatch West Coast Regional Node


Multi-scale Ultra-high Resolution (MUR) SST Analysis fv04.1, Global, 0.01°, 2002-present, Monthly, Lon0360


Multi-scale Ultra-high Resolution (MUR) SST Daily Climatology 2003-2014, fv04.1, Global, 0.01°

This JPL MUR SST daily climatology v4.1 (2003-2014) is from  ftp://mariana.jpl.nasa.gov/mur_sst/tmchin/seasonal/ and is based on the Jet Propulsion Laboratory's (JPL) Multi-scale Ultra-high Resolution (MUR), merged, multi-sensor L4 v4.1 Foundation SST analysis product (part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [dayOfYear][latitude][longitude]):
mean_sst (2003-2014 Climatological Mean Sea Surface Temperature, degree_C)
standard_deviation (standard deviation of mean_sst, degree_C)

NOAA NMFS SWFSC ERD and NOAA NESDIS CoastWatch WCRN


Multi-scale Ultra-high Resolution (MUR) SST Daily Climatology 2003-2014, fv04.1, Global, 0.01°, Lon0360


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)


Myrtle Beach, South Carolina Coastal Digital Elevation Model (myrtle beach 1 mhw 2006), 2.7777778E-4°

Myrtle Beach, South 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/601; Myrtle Beach, SC 1 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


Myrtle Beach, South Carolina Coastal Digital Elevation Model (myrtle beach 13 mhw 2006), 9.259259E-5°

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; NOAA NGDC, NESDIS, NOAA; Boulder; Colorado; publisher; NOAA NGDC, NESDIS, NOAA; originator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/300; Myrtle Beach, SC 1/3 arc-second Tsunami Innundation 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


Myrtle Beach, South Carolina Tsunami Forecast Grids for MOST Model (MyrtleBeachSC A), 0.02°

Myrtle Beach, South 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


Myrtle Beach, South Carolina Tsunami Forecast Grids for MOST Model (MyrtleBeachSC B), 0.0025°


Myrtle Beach, South Carolina Tsunami Forecast Grids for MOST Model (MyrtleBeachSC C), 8.3333335E-4°


Nantucket, Massachusetts Coastal Digital Elevation Model (nantucket 13 mhw 2008), 9.259259E-5°

Nantucket, Massachusetts 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/385; Nantucket, MA 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


Nantucket, Massachusetts Tsunami Forecast Grids for MOST Model (NantucketMA A)

Nantucket, Massachusetts 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)


Nantucket, Massachusetts Tsunami Forecast Grids for MOST Model (NantucketMA B)


Nantucket, Massachusetts Tsunami Forecast Grids for MOST Model (NantucketMA C)


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

NARR Monthly Means (acpcp.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
acpcp (Monthly accumulated convective precipitation at Surface, kg/m^2)

National Centers for Environmental Prediction


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

NARR Monthly Means (acpcp.mon.mean)

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


NARR Monthly Means (air.2m.mon.mean) [time][y][x], 1979-present

NARR Monthly Means (air.2m.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
air (Monthly Air Temperature at 2 m, K)


NARR Monthly Means (air.2m.mon.mean) [y][x]

NARR Monthly Means (air.2m.mon.mean)

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


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

NARR Monthly Means (air.mon.mean)

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


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

NARR Monthly Means (air.mon.mean)

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


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

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

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


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

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

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


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

NARR Monthly Means (albedo.mon.mean)

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

National Centers for Environmental Prediction


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

NARR Monthly Means (albedo.mon.mean)

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


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

NARR Monthly Means (apcp.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
apcp (Monthly accumulated total precipitation at Surface, kg/m^2)


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

NARR Monthly Means (apcp.mon.mean)

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


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

NARR Monthly Means (bgrun.mon.mean)

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


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

NARR Monthly Means (bgrun.mon.mean)

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


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

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

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


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

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

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


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

NARR Monthly Means (cape.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
cape (Monthly Convective Available Potential Energy at Surface, J/kg)

National Centers for Environmental Prediction


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

NARR Monthly Means (cape.mon.mean)

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


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

NARR Monthly Means (ccond.mon.mean)

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


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

NARR Monthly Means (ccond.mon.mean)

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


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

NARR Monthly Means (cdcon.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
cdcon (Monthly Mean of Convective Cloud Cover at Entire Atmosphere Considered as a Single Layer, percent)


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

NARR Monthly Means (cdcon.mon.mean)

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


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

NARR Monthly Means (cdlyr.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
cdlyr (Monthly Mean of Non-Convective Cloud Cover at Entire Atmosphere Considered as a Single Layer, percent)


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

NARR Monthly Means (cdlyr.mon.mean)

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


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

NARR Monthly Means (cfrzr.mon.mean)

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

National Centers for Environmental Prediction


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

NARR Monthly Means (cfrzr.mon.mean)

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


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

NARR Monthly Means (cicep.mon.mean)

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


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

NARR Monthly Means (cicep.mon.mean)

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


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

NARR Monthly Means (cin.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
cin (Monthly Convective Inhibition at Surface, J/kg)


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

NARR Monthly Means (cin.mon.mean)

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


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

NARR Monthly Means (cnwat.mon.mean)

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


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

NARR Monthly Means (cnwat.mon.mean)

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


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

NARR Monthly Means (crain.mon.mean)

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

National Centers for Environmental Prediction


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

NARR Monthly Means (crain.mon.mean)

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


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

NARR Monthly Means (csnow.mon.mean)

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


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

NARR Monthly Means (csnow.mon.mean)

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


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

NARR Monthly Means (dlwrf.mon.mean)

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


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

NARR Monthly Means (dlwrf.mon.mean)

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


NARR Monthly Means (dpt.2m.mon.mean) [time][y][x], 1979-present

NARR Monthly Means (dpt.2m.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
dpt (Monthly Dew Point Temperature at 2m, K)


NARR Monthly Means (dpt.2m.mon.mean) [y][x]

NARR Monthly Means (dpt.2m.mon.mean)

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


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

NARR Monthly Means (dswrf.mon.mean)

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

National Centers for Environmental Prediction


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

NARR Monthly Means (dswrf.mon.mean)

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


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

NARR Monthly Means (evap.mon.mean)

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


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

NARR Monthly Means (evap.mon.mean)

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


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

NARR Monthly Means (gflux.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
gflux (Monthly Ground Heat Flux at Surface, W/m^2)


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

NARR Monthly Means (gflux.mon.mean)

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


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

NARR Monthly Means (hcdc.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
hcdc (Monthly High Cloud Area Fraction, percent)


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

NARR Monthly Means (hcdc.mon.mean)

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


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

NARR Monthly Means (hgt.mon.mean)

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

National Centers for Environmental Prediction


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

NARR Monthly Means (hgt.mon.mean)

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


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
hgt (Monthly Geopotential Height, m)


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

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

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


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

NARR Monthly Means (hlcy.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
hlcy (Monthly Storm Relative Helicity, m^2/s^2)


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

NARR Monthly Means (hlcy.mon.mean)

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


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

NARR Monthly Means (hpbl.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
hpbl (Monthly Planetary Boundary Layer Height, m)


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

NARR Monthly Means (hpbl.mon.mean)

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


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

NARR Monthly Means (lcdc.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
lcdc (Monthly Low Cloud Area Fraction, percent)

National Centers for Environmental Prediction


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

NARR Monthly Means (lcdc.mon.mean)

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


NARR Monthly Means (lftx4.mon.mean) [time][y][x], 1979-present

NARR Monthly Means (lftx4.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
lftx4 (Monthly Best (4-layer) Lifted Index, degK)


NARR Monthly Means (lftx4.mon.mean) [y][x]

NARR Monthly Means (lftx4.mon.mean)

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


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

NARR Monthly Means (lhtfl.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
lhtfl (Monthly Latent Heat Flux at Surface, W/m^2)


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

NARR Monthly Means (lhtfl.mon.mean)

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


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

NARR Monthly Means (mcdc.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
mcdc (Monthly Medium Cloud Area Fraction, percent)


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

NARR Monthly Means (mcdc.mon.mean)

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


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
mconv (Monthly Horizontal Moisture Divergence, kg/kg/s)

National Centers for Environmental Prediction


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

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

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


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

NARR Monthly Means (mslet.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
mslet (Monthly Mean Sea Level (ETA model) Pressure, Pa)


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

NARR Monthly Means (mslet.mon.mean)

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


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

NARR Monthly Means (mstav.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
mstav (Monthly Moisture Availability, percent)


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

NARR Monthly Means (mstav.mon.mean)

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


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

NARR Monthly Means (omega.mon.mean)

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


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

NARR Monthly Means (omega.mon.mean)

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


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

NARR Monthly Means (pevap.mon.mean)

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

National Centers for Environmental Prediction


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

NARR Monthly Means (pevap.mon.mean)

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


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

NARR Monthly Means (pr wtr.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
pr_wtr (Monthly Precipitable Water for entire atmosphere, kg/m^2)


NARR Monthly Means (pr wtr.mon.mean) [y][x]

NARR Monthly Means (pr wtr.mon.mean)

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


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

NARR Monthly Means (prate.mon.mean)

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


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

NARR Monthly Means (prate.mon.mean)

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


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

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

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


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

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

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


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

NARR Monthly Means (prmsl.mon.mean)

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

National Centers for Environmental Prediction


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

NARR Monthly Means (prmsl.mon.mean)

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


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

NARR Monthly Means (rcq.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
rcq (Monthly Humidity Parameter Canopy Conductance at Surface, 1)


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

NARR Monthly Means (rcq.mon.mean)

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


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

NARR Monthly Means (rcs.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
rcs (Monthly Solar Parameter Canopy Conductance at Surface, 1)


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

NARR Monthly Means (rcs.mon.mean)

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


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

NARR Monthly Means (rcsol.mon.mean)

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


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

NARR Monthly Means (rcsol.mon.mean)

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


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

NARR Monthly Means (rct.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
rct (Monthly Temperature Parameter Canopy Conductance at Surface, 1)

National Centers for Environmental Prediction


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

NARR Monthly Means (rct.mon.mean)

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


NARR Monthly Means (rhum.2m.mon.mean) [time][y][x], 1979-present

NARR Monthly Means (rhum.2m.mon.mean)

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


NARR Monthly Means (rhum.2m.mon.mean) [y][x]

NARR Monthly Means (rhum.2m.mon.mean)

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


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

NARR Monthly Means (shtfl.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
shtfl (Monthly Sensible Heat Flux at Surface, W/m^2)


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

NARR Monthly Means (shtfl.mon.mean)

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


NARR Monthly Means (shum.2m.mon.mean) [time][y][x], 1979-present

NARR Monthly Means (shum.2m.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
shum (Monthly Specific Humidity at 2m, kg/kg)


NARR Monthly Means (shum.2m.mon.mean) [y][x]

NARR Monthly Means (shum.2m.mon.mean)

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


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

NARR Monthly Means (shum.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
shum (Monthly Specific Humidity on Pressure Levels, kg/kg)

National Centers for Environmental Prediction


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

NARR Monthly Means (shum.mon.mean)

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


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

NARR Monthly Means (snod.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
snod (Monthly Snow Depth at Surface, m)


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

NARR Monthly Means (snod.mon.mean)

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


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

NARR Monthly Means (snohf.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
snohf (Monthly Snow Phase-change Heat at Surface, W/m^2)


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

NARR Monthly Means (snohf.mon.mean)

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


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

NARR Monthly Means (snom.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
snom (Monthly Snow Melt, kg/m^2)


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

NARR Monthly Means (snom.mon.mean)

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


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

NARR Monthly Means (snowc.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
snowc (Monthly Snow Cover at Surface, 1)

National Centers for Environmental Prediction


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

NARR Monthly Means (snowc.mon.mean)

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


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

NARR Monthly Means (soill.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
soill (Monthly Liquid Volumetric Soil Moisture (non-frozen) Fraction, 1)


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

NARR Monthly Means (soill.mon.mean)

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


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

NARR Monthly Means (soilm.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
soilm (Monthly Soil Moisture Content, kg/m^2)


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

NARR Monthly Means (soilm.mon.mean)

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


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

NARR Monthly Means (soilw.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
soilw (Monthly Volumetric Soil Moisture (frozen + liquid) Fraction, 1)


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

NARR Monthly Means (soilw.mon.mean)

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


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

NARR Monthly Means (ssrun.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
ssrun (Monthly Surface Runoff (non-infiltrating), kg/m^2)

National Centers for Environmental Prediction


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

NARR Monthly Means (ssrun.mon.mean)

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


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

NARR Monthly Means (tcdc.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
tcdc (Monthly Forecast of Total Cloud Cover at Entire Atmosphere Considered as a Single Layer, percent)


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

NARR Monthly Means (tcdc.mon.mean)

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


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

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

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


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

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

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


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

NARR Monthly Means (tke.mon.mean)

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


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

NARR Monthly Means (tke.mon.mean)

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


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

NARR Monthly Means (tsoil.mon.mean)

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

National Centers for Environmental Prediction


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

NARR Monthly Means (tsoil.mon.mean)

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


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

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

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


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

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

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


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

NARR Monthly Means (ustm.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
ustm (Monthly U-component of Storm Motion, m/s)


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

NARR Monthly Means (ustm.mon.mean)

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


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

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

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


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

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

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


NARR Monthly Means (uwnd.10m.mon.mean) [time][y][x], 1979-present

NARR Monthly Means (uwnd.10m.mon.mean)

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

National Centers for Environmental Prediction


NARR Monthly Means (uwnd.10m.mon.mean) [y][x]

NARR Monthly Means (uwnd.10m.mon.mean)

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


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

NARR Monthly Means (uwnd.mon.mean)

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


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

NARR Monthly Means (uwnd.mon.mean)

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


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

NARR Monthly Means (veg.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
veg (Monthly vegetation at Surface, percent)


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

NARR Monthly Means (veg.mon.mean)

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


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

NARR Monthly Means (vis.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
vis (Monthly Visibility, m)


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

NARR Monthly Means (vis.mon.mean)

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


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

NARR Monthly Means (vstm.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
vstm (Monthly V-component of Storm Motion, m/s)

National Centers for Environmental Prediction


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

NARR Monthly Means (vstm.mon.mean)

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


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

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

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
vvel (Monthly Pressure Vertical Velocity, Pa/s)


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

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

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


NARR Monthly Means (vwnd.10m.mon.mean) [time][y][x], 1979-present

NARR Monthly Means (vwnd.10m.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
vwnd (Monthly v-wind at 10 m, m/s)


NARR Monthly Means (vwnd.10m.mon.mean) [y][x]

NARR Monthly Means (vwnd.10m.mon.mean)

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


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

NARR Monthly Means (vwnd.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][level][y][x]):
vwnd (Monthly V-wind on Pressure Levels, m/s)


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

NARR Monthly Means (vwnd.mon.mean)

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


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

NARR Monthly Means (wcconv.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
wcconv (Monthly Water Condensate Flux Convergence Accumulation at Entire Atmosphere Considered as a Single Layer, kg/m^2)

National Centers for Environmental Prediction


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

NARR Monthly Means (wcconv.mon.mean)

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


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

NARR Monthly Means (wcinc.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
wcinc (Monthly Water Condensate Added by Precip. Assimilation Accumulation at Entire Atmosphere Considered as a Single Layer, kg/m^2)


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

NARR Monthly Means (wcinc.mon.mean)

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


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

NARR Monthly Means (wcuflx.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
wcuflx (Monthly Water Condensate Zonal Flux Accumulation at Entire Atmosphere Considered as a Single Layer, kg/m)


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

NARR Monthly Means (wcuflx.mon.mean)

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


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

NARR Monthly Means (wcvflx.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
wcvflx (Monthly Water Condensate Meridional Flux Accumulation at Entire Atmosphere Considered as a Single Layer, kg/m)


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

NARR Monthly Means (wcvflx.mon.mean)

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


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

NARR Monthly Means (weasd.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
weasd (Monthly Accumulated Snow at Surface, kg/m^2)

National Centers for Environmental Prediction


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

NARR Monthly Means (weasd.mon.mean)

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


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

NARR Monthly Means (wvconv.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
wvconv (Monthly Water Vapor Flux Convergence Accumulation at Entire Atmosphere Considered as a Single Layer, kg/m^2)


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

NARR Monthly Means (wvconv.mon.mean)

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


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

NARR Monthly Means (wvinc.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
wvinc (Monthly Water Vapor Added by Precip. Assimilation Accumulation at Entire Atmosphere Considered as a Single Layer, kg/m^2)


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

NARR Monthly Means (wvinc.mon.mean)

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


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

NARR Monthly Means (wvuflx.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
wvuflx (Monthly Water Vapor Zonal Flux Accumulation at Entire Atmosphere Considered as a Single Layer, kg/m)


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

NARR Monthly Means (wvuflx.mon.mean)

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


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

NARR Monthly Means (wvvflx.mon.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
wvvflx (Monthly Water Vapor Meridional Flux Accumulation at Entire Atmosphere Considered as a Single Layer, kg/m)

National Centers for Environmental Prediction


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

NARR Monthly Means (wvvflx.mon.mean)

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


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 10 m Wind

Navy Global Environmental Model (NAVGEM) is a global numerical weather prediction computer model. It replaced NOGAPS as the prime model in the middle of February 2013 at the Navy Fleet Numerical Meteorology and Oceanography Center (FNMOC) Weather model synoptic site. [Wikipedia]

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
wnd_ucmp_height_above_ground (Eastward Wind, m s-1)
wnd_vcmp_height_above_ground (Northward Wind, m s-1)


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 10 m Wind, Lon+/-180


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 20 m Wind


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 20 m Wind, Lon+/-180


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 500 hPa Height

Navy Global Environmental Model (NAVGEM) is a global numerical weather prediction computer model. It replaced NOGAPS as the prime model in the middle of February 2013 at the Navy Fleet Numerical Meteorology and Oceanography Center (FNMOC) Weather model synoptic site. [Wikipedia]

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][isobaric][latitude][longitude]):
geop_ht_isobaric (Geopotential Height (500 hPa), gpm)


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 500 hPa Height, Lon+/-180


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, Pressure MSL

Navy Global Environmental Model (NAVGEM) is a global numerical weather prediction computer model. It replaced NOGAPS as the prime model in the middle of February 2013 at the Navy Fleet Numerical Meteorology and Oceanography Center (FNMOC) Weather model synoptic site. [Wikipedia]

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres_reduced_msl (Pressure (adjusted to Mean Sea Level), hPa)


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, Pressure MSL, Lon+/-180


Navy Global Environmental Model (NAVGEM), 1 degree, 2013-present, 10 m Wind


Navy Global Environmental Model (NAVGEM), 1 degree, 2013-present, 10 m Wind, Lon+/-180


Navy Global Environmental Model (NAVGEM), 1 degree, 2013-present, 20 m Wind


Navy Global Environmental Model (NAVGEM), 1 degree, 2013-present, 20 m Wind, Lon+/-180


Navy Global Environmental Model (NAVGEM), 1 degree, 2013-present, 500 hPa Height


Navy Global Environmental Model (NAVGEM), 1 degree, 2013-present, 500 hPa Height, Lon+/-180


Navy Global Environmental Model (NAVGEM), 1 degree, 2013-present, Pressure MSL


Navy Global Environmental Model (NAVGEM), 1 degree, 2013-present, Pressure MSL, Lon+/-180


Nawiliwili, Hawaii Tsunami Forecast Grids for MOST Model (NawiliwiliHI A)

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

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

NOAA OAR PMEL Center for Tsunami Research


Nawiliwili, Hawaii Tsunami Forecast Grids for MOST Model (NawiliwiliHI B)


Nawiliwili, Hawaii Tsunami Forecast Grids for MOST Model (NawiliwiliHI C)


nbdsf.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]):
nbdsf (Monthly Long Term Mean Near IR Beam Downward Solar Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


NCEP North American Regional Reanalysis Data (hgt.sfc) [time][y][x], 1800

National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis Data. data is from NCEP NARR  (8x/day)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
hgt (Surface Geopotential Height, m)


NCEP North American Regional Reanalysis Data (hgt.sfc) [y][x]

National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis Data. data is from NCEP NARR  (8x/day)

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


NCEP North American Regional Reanalysis Data (land) [time][y][x], 1979

National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis Data. data is from NCEP NARR  (8x/day)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][y][x]):
land (time-invariant Land-sea Mask, 1)


NCEP North American Regional Reanalysis Data (land) [y][x]


NCEP Real-time Marine (air.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (air.mean)

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


NCEP Real-time Marine (air.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (air.nobs)

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


NCEP Real-time Marine (cldc.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (cldc.mean)

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


NCEP Real-time Marine (cldc.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (cldc.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
cldc (Cloudiness Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (lflx.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (lflx.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
lflx (Latent Heat Parameter Monthly Mean at Surface, grams/kg m/s)


NCEP Real-time Marine (lflx.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (lflx.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
lflx (Latent Heat Parameter Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (rhum.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (rhum.mean)

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


NCEP Real-time Marine (rhum.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (rhum.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Relative Humidity Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (sflx.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (sflx.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sflx (Sensible Heat Parameter Monthly Mean at Surface, degC m/s)


NCEP Real-time Marine (sflx.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (sflx.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sflx (Sensible Heat Parameter Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (shum.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (shum.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
shum (Specific Humidity Monthly Mean at Surface, g/kg)


NCEP Real-time Marine (shum.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (shum.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
shum (Specific Humidity Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (slp.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (slp.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
slp (Sea Level Pressure Monthly Mean at Surface, mb)


NCEP Real-time Marine (slp.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (slp.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
slp (Sea Level Pressure Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (sst.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (sst.mean)

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


NCEP Real-time Marine (sst.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (sst.nobs)

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


NCEP Real-time Marine (ustr.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (ustr.mean)

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


NCEP Real-time Marine (ustr.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (ustr.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
ustr (u-wind Stress Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (uwnd.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (uwnd.mean)

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


NCEP Real-time Marine (uwnd.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (uwnd.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (vstr.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (vstr.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vstr (v-wind Stress Monthly Mean at Surface, m^2/s^2)


NCEP Real-time Marine (vstr.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (vstr.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vstr (v-wind Stress Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (vwnd.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (vwnd.mean)

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


NCEP Real-time Marine (vwnd.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (vwnd.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vwnd (v-wind Monthly Number of Observations at Surface, observations)


NCEP Real-time Marine (wspd.mean), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (wspd.mean)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
wspd (Scalar Wind Monthly Mean at Surface, m/s)


NCEP Real-time Marine (wspd.nobs), 2.0°, 1991-2011

National Centers for Environmental Prediction (NCEP) Real-time Marine (wspd.nobs)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
wspd (Scalar Wind Monthly Number of Observations at Surface, observations)


NCEP Reanalysis Diurnal Cycle Surface Air Temperature (airsfcapr.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface Air Temperature. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (Diurnal Cycle Anomaly of Air Temperature for April, degree_C)


NCEP Reanalysis Diurnal Cycle Surface Air Temperature (airsfcjan.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface Air Temperature. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (Diurnal Cycle Anomaly of Air Temperature for January, degree_C)


NCEP Reanalysis Diurnal Cycle Surface Air Temperature (airsfcjul.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface Air Temperature. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (Diurnal Cycle Anomaly of Air Temperature for July, degree_C)


NCEP Reanalysis Diurnal Cycle Surface Air Temperature (airsfcoct.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface Air Temperature. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (Diurnal Cycle Anomaly of Air Temperature for October, degree_C)


NCEP Reanalysis Diurnal Cycle Surface Pressure (presapr.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface Pressure. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (Diurnal Cycle Anomaly of Surface Pressure for April, millibars)


NCEP Reanalysis Diurnal Cycle Surface Pressure (presjan.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface Pressure. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (Diurnal Cycle Anomaly of Surface Pressure for January, millibars)


NCEP Reanalysis Diurnal Cycle Surface Pressure (presjul.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface Pressure. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (Diurnal Cycle Anomaly of Surface Pressure for July, millibars)


NCEP Reanalysis Diurnal Cycle Surface Pressure (presoct.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface Pressure. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (Diurnal Cycle Anomaly of Surface Pressure for October, millibars)


NCEP Reanalysis Diurnal Cycle Surface u-wind (uwndsfcapr.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface u-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (Diurnal Cycle Anomaly of U-Wind for April, m/s)


NCEP Reanalysis Diurnal Cycle Surface u-wind (uwndsfcjan.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface u-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (Diurnal Cycle Anomaly of U-Wind for January, m/s)


NCEP Reanalysis Diurnal Cycle Surface u-wind (uwndsfcjul.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface u-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (Diurnal Cycle Anomaly of U-Wind for July, m/s)


NCEP Reanalysis Diurnal Cycle Surface u-wind (uwndsfcoct.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface u-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (Diurnal Cycle Anomaly of U-Wind for October, m/s)


NCEP Reanalysis Diurnal Cycle Surface v-wind (vwndsfcapr.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface v-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vwnd (Diurnal Cycle Anomaly of V-Wind for April, m/s)


NCEP Reanalysis Diurnal Cycle Surface v-wind (vwndsfcjan.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface v-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vwnd (Diurnal Cycle Anomaly of V-Wind for January, m/s)


NCEP Reanalysis Diurnal Cycle Surface v-wind (vwndsfcjul.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface v-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vwnd (Diurnal Cycle Anomaly of V-Wind for July, m/s)


NCEP Reanalysis Diurnal Cycle Surface v-wind (vwndsfcoct.mon.dailyanom), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis Diurnal Cycle Surface v-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
vwnd (Diurnal Cycle Anomaly of V-Wind for October, m/s)


NCEP Reanalysis monthly intraseasonal std (pres.mon.intra.std), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis monthly intraseasonal std. Data is derived form NCEP/National Center for Atmospheric Research (NCAR) Reanalysis I dataset

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres (Monthly Intraseasonal Standard Deviation, millibars)


NCEP Reanalysis monthly mean 10 m wind speed (wspd.10m.mon.1981-2010.ltm), 0001

National Centers for Environmental Prediction (NCEP) Reanalysis monthly mean 10 m wind speed. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of T62 variables interpolated to
pressure surfaces from model (sigma) surfaces.

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


NCEP Reanalysis monthly mean 10 m wind speed (wspd.10m.mon.ltm), 0001

National Centers for Environmental Prediction (NCEP) Reanalysis monthly mean 10 m wind speed. Data is from National Meteorological Center (NMC) initialized reanalysis
(4x/day).  It consists of T62 variables interpolated to
pressure surfaces from model (sigma) surfaces.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
wspd (Long Term Mean Monthly Mean of 10m Wind Speed from daily wind speed (from daily vector winds), m/s)
valid_yr_count (count of non-missing values used in mean)


NCEP Reanalysis monthly mean surface relative humidity (rhum.mon.ltm), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis monthly mean surface relative humidity. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Long Term Mean Monthly Mean Relative Humidity at sigma level 0.995, percent)
valid_yr_count (count of non-missing values used in mean)


NCEP Reanalysis monthly mean surface relative humidity (rhum.sig995.mon.1981-2010.ltm), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis monthly mean surface relative humidity. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rhum (Monthly Long Term Mean Relative Humidity at sigma level 0.995, percent)
valid_yr_count (count of non-missing values used in mean)


NCEP Reanalysis monthly mean surface relative humidity (rhum.sig995.mon.ltm), 2.5°, 0001


NCEP Reanalysis monthly mean surface u-wind (thickness 1000500.mon.ltm), 2.5°, 0001

National Centers for Environmental Prediction (NCEP) Reanalysis monthly mean surface u-wind. Data from NCEP initialized reanalysis (4x/day).  These are the 0.9950 sigma level values

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


NCEP Reanalysis monthly mean surface u-wind (thickness 500200.mon.1981-2010.ltm), 2.5°, 0001


NCEP Reanalysis monthly mean surface u-wind (thickness 500200.mon.ltm), 2.5°, 0001


NCEP-NCAR Reanalysis 1 (cfnsf.sfc.mon.ltm), 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 (Long Term Mean Monthly Mean Cloud Forcing Net Solar Flux at Surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


NCEP-NCAR Reanalysis 1 (cprat.sfc.mon.ltm), 0001

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

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


NCEP-NCAR Reanalysis 1 (dswrf.sfc.mon.ltm), 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]):
dswrf (Long Term Mean Monthly Mean Downward Solar Radiation Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


NCEP-NCAR Reanalysis 1 (icec.sfc.mon.ltm), 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]):
icec (Long Term Mean Monthly Mean Ice Concentration at surface)
valid_yr_count (count of non-missing values used in mean)


NCEP-NCAR Reanalysis 1 (nbdsf.mon.ltm), 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]):
nbdsf (Long Term Mean Monthly Mean Near IR Beam Downward Solar Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


NCEP-NCAR Reanalysis 1 (nbdsf.sfc.mon.ltm), 0001


NCEP-NCAR Reanalysis 1 (nddsf.sfc.mon.ltm), 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]):
nddsf (Long Term Mean Monthly Mean Near IR Diffuse Downward Solar Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


NCEP-NCAR Reanalysis 1 (pres.sfc.mon.ltm), 0001

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

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


NCEP-NCAR Reanalysis 1 (sfcr.sfc.mon.ltm), 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]):
sfcr (Long Term Mean Monthly Mean Surface Roughness, m)
valid_yr_count (count of non-missing values used in mean)


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

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

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


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

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

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


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

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

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


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

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

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


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

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

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


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

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

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


The NCEP/NCAR Reanalysis 1 project is using a state-of-the-art analysis/forecast system to perform data assimilation using past data from 1948 to the present.  Data is from NMC initialized reanalysis (4x/day).  See the PROBLEMS LIST at https://www.esrl.noaa.gov/psd/data/reanalysis/problems.shtml

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
air (mean Daily Air temperature at sigma level 995, degK)
lftx (mean Daily Surface Lifted Index, degK)
lftx4 (mean Daily Best (4-layer) Lifted Index, degK)
omega (mean Daily omega at sigma level 0.995, Pascal/s)
pottmp (mean Daily potential temperature at sigma level 995, degK)
pr_wtr (mean Daily Precipitable Water for entire atmosphere, kg/m^2)
pres (mean Daily Pressure at surface, Pascals)
rhum (mean Daily relative humidity at sigma level 995, percent)
slp (mean Daily Sea Level Pressure, Pascals)
uwnd (mean Daily u-wind at sigma level 995, m/s)
vwnd (mean Daily v wind at sigma level 995, m/s)


NCEP/NCAR Reanalysis (1948-present), Lon+/-180


nddsf.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]):
nddsf (Monthly Long Term Mean Near IR Diffuse Downward Solar Flux at surface, W/m^2)
valid_yr_count (count of non-missing values used in mean)


Neah Bay, Washington Tsunami Forecast Grids for MOST Model (NeahBayWA A), 0.02°

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

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

NOAA OAR PMEL Center for Tsunami Research


Neah Bay, Washington Tsunami Forecast Grids for MOST Model (NeahBayWA B)


Neah Bay, Washington Tsunami Forecast Grids for MOST Model (NeahBayWA C)


Near Real Time 3 Day MODIS AQUA K490 Fields (AQUA K490 GULF 3D), 2019-present

Near Real Time 3 Day Moderate Resolution Imaging Spectroradiometer (MODIS) AQUA K490 Fields (AQUA K490 GULF 3D)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
K490 (K490 - Diffuse Attenuation Coefficient at 490 nm, m-1)


Near Real Time 3 Day MODIS AQUA Rrs667 Fields (AQUA RRS667 GULF 3D), 2019-present

Near Real Time 3 Day Moderate Resolution Imaging Spectroradiometer (MODIS) AQUA Rrs667 Fields (AQUA RRS667 GULF 3D)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs667 (Rrs667 - Remote Sensing Reflectance at 667 nm, sr-1)


Near Real Time 3 Day MODIS TERRA K490 Fields (TERRA K490 GULF 3D), 2012

Near Real Time 3 Day Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA K490 Fields (TERRA K490 GULF 3D)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
K490 (K490 - Diffuse Attenuation Coefficient at 490 nm, m-1)


Near Real Time 3 Day MODIS TERRA Rrs667 Fields (TERRA RRS667 GULF 3D), 2012

Near Real Time 3 Day Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA Rrs667 Fields (TERRA RRS667 GULF 3D)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs667 (Rrs667 - Remote Sensing Reflectance at 667 nm, sr-1)


Near Real Time Dynamic Topography (CW AOML PHOD DYNT), 0.2°, 2006-present

Near Real Time Dynamic Topography (CoastWatch (CW) Atlantic Oceanographic & Meteorological Laboratory (AOML) Physical Oceanography Division (PHOD) DYNT)

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


Near Real Time Geostrophic Currents

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


Near Real Time Geostrophic Currents (OCEAN GEOSTROPHIC CURRENTS), 0.19999999°, 2016-present

Near Real Time Geostrophic Currents (OCEAN GEOSTROPHIC CURRENTS)

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


Near Real Time Geostrophic Currents, Lon0360


Near Real Time MCI Fields (MCI GULF) (kk1), 2012

Near Real Time Maximum Chlorophyll Index (MCI) Fields (MCI GULF)

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


Near Real Time MODIS AQUA Rrs667 Fields (AQUA RRS667 GULF), 2019-present

Near Real Time Moderate Resolution Imaging Spectroradiometer (MODIS) AQUA Rrs667 Fields (AQUA RRS667 GULF)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs667 (Rrs667 - Remote Sensing Reflectance at 667 nm, sr-1)


Near Real Time MODIS TERRA K490 Fields (TERRA K490 GULF), 2014

Near Real Time Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA K490 Fields (TERRA K490 GULF)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
K490 (K490 - Diffuse Attenuation Coefficient at 490 nm, m-1)


Near Real Time MODIS TERRA Rrs667 Fields (TERRA RRS667 GULF), 2012

Near Real Time Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA Rrs667 Fields (TERRA RRS667 GULF)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs667 (Rrs667 - Remote Sensing Reflectance at 667 nm, sr-1)


NEOWAVE Regional Tsunami Model: Guam: Agana and Tumon Bays

Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE) regional tsunami model for adjacent Agana and Tumon Bays along the northwest shore of the island of Guam, categorized by earthquake magnitude and subduction zone. Offshore data are gridded at approximately 90-m resolution while in-harbor data are approximately 9-m resolution. Includes offshore surge and current based on maximum considered tsunamis as well as in-harbor hazard maps of surge, drawdown, and current for hypothetical advisory and warning-level tsunamis from potential sources at the Mariana, Nankai, Philippine, and New Guinea subduction zones. Data are referenced to the WGS84 coordinate system, and the vertical datum is mean sea level (MSL). This shock-capturing, dispersive wave model computes tsunami generation, propagation, and inundation for complex flow patterns in shelf and reef environments. It has been validated with analytical, laboratory, and field benchmarks and is approved by the National Tsunami Hazard Mitigation Program. These hazard maps cover tsunamis only; other potential hazards such as wind waves and swells would be additive to the surge, drawdown, and current described by these data.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
current_event01 (current from East Philippines Mw 8.0, meters second-1)
current_event02 (current from East Philippines Mw 8.2, meters second-1)
current_event03 (current from East Philippines Mw 8.4, meters second-1)
current_event04 (current from Mariana Mw 7.8, meters second-1)
current_event05 (current from Mariana Mw 8.0, meters second-1)
current_event06 (current from Mariana Mw 8.2, meters second-1)
current_event07 (current from Nankai Mw 8.3, meters second-1)
current_event08 (current from Nankai Mw 8.5, meters second-1)
current_event09 (current from Nankai Mw 8.7, meters second-1)
current_event10 (current from New Guinea Mw 8.4, meters second-1)
current_event11 (current from New Guinea Mw 8.6, meters second-1)
current_event12 (current from New Guinea Mw 8.8, meters second-1)
drawdown_event01 (drawdown from East Philippines Mw 8.0, meters)
drawdown_event02 (drawdown from East Philippines Mw 8.2, meters)
drawdown_event03 (drawdown from East Philippines Mw 8.4, meters)
... (21 more variables)

Pacific Islands Ocean Observing System (PacIOOS)


NEOWAVE Regional Tsunami Model: Guam: Agat Bay

Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE) regional tsunami model for Agat Bay along the southwest shore of the island of Guam, categorized by earthquake magnitude and subduction zone. Includes nearshore hazard maps of surge, drawdown, and current for hypothetical advisory and warning-level tsunamis from potential sources at the Mariana, Nankai, Philippine, and New Guinea subduction zones. Data are gridded at approximately 20-m resolution referenced to the WGS84 coordinate system and use a vertical datum of mean sea level (MSL). This shock-capturing, dispersive wave model computes tsunami generation, propagation, and inundation for complex flow patterns in shelf and reef environments. It has been validated with analytical, laboratory, and field benchmarks and is approved by the National Tsunami Hazard Mitigation Program. These hazard maps cover tsunamis only; other potential hazards such as wind waves and swells would be additive to the surge, drawdown, and current described by these data.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
current_event01 (current from East Philippines Mw 7.6, meters second-1)
current_event02 (current from East Philippines Mw 7.7, meters second-1)
current_event03 (current from East Philippines Mw 7.8, meters second-1)
current_event04 (current from East Philippines Mw 7.9, meters second-1)
current_event05 (current from East Philippines Mw 8.0, meters second-1)
current_event06 (current from East Philippines Mw 8.1, meters second-1)
current_event07 (current from East Philippines Mw 8.2, meters second-1)
current_event08 (current from East Philippines Mw 8.3, meters second-1)
current_event09 (current from East Philippines Mw 8.4, meters second-1)
current_event10 (current from East Philippines Mw 8.5, meters second-1)
current_event11 (current from Mariana Mw 7.2, meters second-1)
current_event12 (current from Mariana Mw 7.3, meters second-1)
current_event13 (current from Mariana Mw 7.4, meters second-1)
current_event14 (current from Mariana Mw 7.5, meters second-1)
current_event15 (current from Mariana Mw 7.6, meters second-1)
current_event16 (current from Mariana Mw 7.7, meters second-1)
current_event17 (current from Mariana Mw 7.8, meters second-1)
... (124 more variables)


NEOWAVE Regional Tsunami Model: Guam: Agat Marina

Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE) regional tsunami model for Agat Marina along the southwest shore of the island of Guam, categorized by earthquake magnitude and subduction zone. Includes nearshore hazard maps of surge, drawdown, and current for hypothetical advisory and warning-level tsunamis from potential sources at the Mariana, Nankai, Philippine, and New Guinea subduction zones. Data are gridded at approximately 5-m resolution referenced to the WGS84 coordinate system and use a vertical datum of mean sea level (MSL). This shock-capturing, dispersive wave model computes tsunami generation, propagation, and inundation for complex flow patterns in shelf and reef environments. It has been validated with analytical, laboratory, and field benchmarks and is approved by the National Tsunami Hazard Mitigation Program. These hazard maps cover tsunamis only; other potential hazards such as wind waves and swells would be additive to the surge, drawdown, and current described by these data.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
current_event01 (current from East Philippines Mw 7.6, meters second-1)
current_event02 (current from East Philippines Mw 7.7, meters second-1)
current_event03 (current from East Philippines Mw 7.8, meters second-1)
current_event04 (current from East Philippines Mw 7.9, meters second-1)
current_event05 (current from East Philippines Mw 8.0, meters second-1)
current_event06 (current from East Philippines Mw 8.1, meters second-1)
current_event07 (current from East Philippines Mw 8.2, meters second-1)
current_event08 (current from East Philippines Mw 8.3, meters second-1)
current_event09 (current from East Philippines Mw 8.4, meters second-1)
current_event10 (current from East Philippines Mw 8.5, meters second-1)
current_event11 (current from Mariana Mw 7.2, meters second-1)
current_event12 (current from Mariana Mw 7.3, meters second-1)
current_event13 (current from Mariana Mw 7.4, meters second-1)
current_event14 (current from Mariana Mw 7.5, meters second-1)
current_event15 (current from Mariana Mw 7.6, meters second-1)
current_event16 (current from Mariana Mw 7.7, meters second-1)
current_event17 (current from Mariana Mw 7.8, meters second-1)
... (124 more variables)


NEOWAVE Regional Tsunami Model: Guam: Apra Harbor

Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE) regional tsunami model for Apra Harbor on the island of Guam, categorized by earthquake magnitude and subduction zone. Offshore data are gridded at approximately 90-m resolution while in-harbor data are approximately 9-m resolution. Includes offshore surge and current based on maximum considered tsunamis as well as in-harbor hazard maps of surge, drawdown, and current for hypothetical advisory and warning-level tsunamis from potential sources at the Mariana, Nankai, Philippine, and New Guinea subduction zones. Data are referenced to the WGS84 coordinate system, and the vertical datum is mean sea level (MSL). This shock-capturing, dispersive wave model computes tsunami generation, propagation, and inundation for complex flow patterns in shelf and reef environments. It has been validated with analytical, laboratory, and field benchmarks and is approved by the National Tsunami Hazard Mitigation Program. These hazard maps cover tsunamis only; other potential hazards such as wind waves and swells would be additive to the surge, drawdown, and current described by these data.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
current_event01 (current from East Philippines Mw 8.1, meters second-1)
current_event02 (current from East Philippines Mw 8.3, meters second-1)
current_event03 (current from East Philippines Mw 8.5, meters second-1)
current_event04 (current from Mariana Mw 7.6, meters second-1)
current_event05 (current from Mariana Mw 7.8, meters second-1)
current_event06 (current from Mariana Mw 8.0, meters second-1)
current_event07 (current from Nankai Mw 8.3, meters second-1)
current_event08 (current from Nankai Mw 8.5, meters second-1)
current_event09 (current from Nankai Mw 8.7, meters second-1)
current_event10 (current from New Guinea Mw 8.4, meters second-1)
current_event11 (current from New Guinea Mw 8.6, meters second-1)
current_event12 (current from New Guinea Mw 8.8, meters second-1)
drawdown_event01 (drawdown from East Philippines Mw 8.1, meters)
drawdown_event02 (drawdown from East Philippines Mw 8.3, meters)
drawdown_event03 (drawdown from East Philippines Mw 8.5, meters)
drawdown_event04 (drawdown from Mariana Mw 7.6, meters)
... (20 more variables)


NETCDF/20211202_AQUA (CHLOR MODIS AQUA) (CHLOR A), 2020-present

NETCDF/20211202_AQUA (CHLOR Moderate Resolution Imaging Spectroradiometer (MODIS) AQUA)

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


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)


New Orleans, Louisiana Coastal Digital Elevation Model (new orleans 13 mhw 2010), 9.259259E-5°

New Orleans, Louisiana 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/682; New Orleans, LA 1/3 arc-second MHW DEM; Download page for accessing DEM, metadata record and development report.; download; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/vdatum/vdatum.html; NOAA VDatum DEM Project; Project web page.; information


New Orleans, Louisiana Coastal Digital Elevation Model (new orleans 13 navd88 2010), 9.259259E-5°

DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA; publisher; NOAA NGDC, NESDIS, NOAA; Boulder; Colorado; publisher; NOAA NGDC, NESDIS, NOAA; originator; Citation URL; https://www.ngdc.noaa.gov/dem/squareCellGrid/download/728; New Orleans, LA 1/3 arc-second NAVD 88 DEM; Download page for accessing DEM, metadata record and development report.; download; Citation URL; https://www.ngdc.noaa.gov/mgg/inundation/vdatum/vdatum.html; NOAA VDatum DEM Project; Project web page.; information


New York and New Jersey Operational Forecast System (NYOFS): Forecast, Fields [ny][nx]

New York and New Jersey Operational Forecast System (NYOFS): Forecast - Fields. Best time series, taking the data from the most recent run available.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [ny][nx]):
lon (Longitude, degrees_east)
lat (Latitude, degrees_north)
mask (Land Mask, nondimensional)
depth (Bathymetry, m)


Newport, Oregon Tsunami Forecast Grids for MOST Model (NewportOR A), 0.01°

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

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

NOAA OAR PMEL Center for Tsunami Research


Newport, Oregon Tsunami Forecast Grids for MOST Model (NewportOR B), 0.001667°


Newport, Oregon Tsunami Forecast Grids for MOST Model (NewportOR C)