MERRA2_monthly_2d_lnd_Nx
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/MERRA2_monthly_2d_lnd_Nx.yaml")
ds=cat.netcdf.read()Metadata
| title | MERRA2_monthly_2d_lnd_Nx |
| location | /shared/land/MERRA-2/MONTHLY/lnd |
| tags | reanalysis,global,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/MERRA2_monthly_2d_lnd_Nx.yaml |
| last updated | 2021-08-11 |
Dataset Contents
<xarray.Dataset>
Dimensions: (lat: 361, lon: 576, time: 492)
Coordinates:
* lat (lat) float64 -90.0 -89.5 -89.0 -88.5 ... 89.0 89.5 90.0
* lon (lon) float64 -180.0 -179.4 -178.8 ... 178.1 178.8 179.4
* time (time) int64 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0
Data variables:
BASEFLOW (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
ECHANGE (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
EVLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
EVPINTR (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
EVPSBLN (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
EVPSOIL (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
EVPTRNS (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
FRSAT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
FRSNO (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
FRUNST (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
FRWLT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
GHLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
GRN (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
GWETPROF (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
GWETROOT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
GWETTOP (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
LAI (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
LHLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
LWLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
PARDFLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
PARDRLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
PRECSNOLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
PRECTOTLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
PRMC (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
QINFIL (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
RUNOFF (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
RZMC (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SFMC (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SHLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SMLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SNODP (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SNOMAS (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SPLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SPSNOW (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SPWATR (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
SWLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TELAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TPSNOW (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TSAT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TSOIL1 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TSOIL2 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TSOIL3 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TSOIL4 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TSOIL5 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TSOIL6 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TSURF (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TUNST (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TWLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
TWLT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_BASEFLOW (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_ECHANGE (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_EVLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_EVPINTR (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_EVPSBLN (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_EVPSOIL (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_EVPTRNS (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_FRSAT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_FRSNO (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_FRUNST (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_FRWLT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_GHLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_GRN (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_GWETPROF (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_GWETROOT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_GWETTOP (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_LAI (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_LHLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_LWLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_PARDFLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_PARDRLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_PRECSNOLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_PRECTOTLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_PRMC (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_QINFIL (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_RUNOFF (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_RZMC (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SFMC (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SHLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SMLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SNODP (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SNOMAS (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SPLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SPSNOW (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SPWATR (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_SWLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TELAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TPSNOW (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TSAT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TSOIL1 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TSOIL2 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TSOIL3 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TSOIL4 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TSOIL5 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TSOIL6 (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TSURF (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TUNST (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TWLAND (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_TWLT (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Var_WCHANGE (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
WCHANGE (time, lat, lon) float32 dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
Attributes:
History: Wed Aug 11 19:56:56 2021: ncks -L 1 -O...
Filename: MERRA2_100.tavgM_2d_lnd_Nx.198001.nc4
Comment: GMAO filename: d5124_m2_jan79.tavg1_2d...
Conventions: CF-1
Institution: NASA Global Modeling and Assimilation ...
References: http://gmao.gsfc.nasa.gov
Format: NetCDF-4/HDF-5
SpatialCoverage: global
VersionID: 5.12.4
TemporalRange: 1980-01-01 -> 2016-12-31
identifier_product_doi_authority: http://dx.doi.org/
ShortName: M2TMNXLND
RangeBeginningDate: 1980-01-01
RangeEndingDate: 1980-01-31
GranuleID: MERRA2_100.tavgM_2d_lnd_Nx.198001.nc4
ProductionDateTime: Original file generated: Fri May 8 00...
LongName: MERRA2 tavg1_2d_lnd_Nx: 2d,1-Hourly,Ti...
Title: MERRA2 tavg1_2d_lnd_Nx: 2d,1-Hourly,Ti...
SouthernmostLatitude: -90.0
NorthernmostLatitude: 90.0
WesternmostLongitude: -180.0
EasternmostLongitude: 179.375
LatitudeResolution: 0.5
LongitudeResolution: 0.625
DataResolution: 0.5 x 0.625
Source: CVS tag: GEOSadas-5_12_4
Contact: http://gmao.gsfc.nasa.gov
identifier_product_doi: 10.5067/8S35XF81C28F
RangeBeginningTime: 00:00:00.000000
RangeEndingTime: 23:59:59.000000
NCO: netCDF Operators version 4.7.5 (Homepa...xarray.Dataset
- lat: 361
- lon: 576
- time: 492
- lat(lat)float64-90.0 -89.5 -89.0 ... 89.5 90.0
- long_name :
- latitude
- units :
- degrees_north
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
array([-90. , -89.5, -89. , ..., 89. , 89.5, 90. ])
- lon(lon)float64-180.0 -179.4 ... 178.8 179.4
- long_name :
- longitude
- units :
- degrees_east
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
array([-180. , -179.375, -178.75 , ..., 178.125, 178.75 , 179.375])
- time(time)int640 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0
- long_name :
- time
- time_increment :
- 60000
- begin_time :
- 3000
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
array([0, 0, 0, ..., 0, 0, 0])
- BASEFLOW(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- baseflow_flux
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - ECHANGE(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- rate_of_change_of_total_land_energy
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - EVLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Evaporation_land
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - EVPINTR(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- interception_loss_energy_flux
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - EVPSBLN(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- snow_ice_evaporation_energy_flux
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - EVPSOIL(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- baresoil_evap_energy_flux
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - EVPTRNS(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- transpiration_energy_flux
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - FRSAT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- fractional_area_of_saturated_zone
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - FRSNO(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- fractional_area_of_land_snowcover
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - FRUNST(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- fractional_area_of_unsaturated_zone
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - FRWLT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- fractional_area_of_wilting_zone
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - GHLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Ground_heating_land
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - GRN(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- greeness_fraction
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - GWETPROF(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- ave_prof_soil_moisture
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - GWETROOT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- root_zone_soil_wetness
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - GWETTOP(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- surface_soil_wetness
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - LAI(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- leaf_area_index
- units :
- 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - LHLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Latent_heat_flux_land
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - LWLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Net_longwave_land
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - PARDFLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- surface_downwelling_par_diffuse_flux
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - PARDRLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- surface_downwelling_par_beam_flux
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - PRECSNOLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- snowfall_land
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - PRECTOTLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Total_precipitation_land
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - PRMC(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- water_profile
- units :
- m-3 m-3
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - QINFIL(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Soil_water_infiltration_rate
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - RUNOFF(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- overland_runoff_including_throughflow
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - RZMC(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- water_root_zone
- units :
- m-3 m-3
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SFMC(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- water_surface_layer
- units :
- m-3 m-3
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SHLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Sensible_heat_flux_land
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SMLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Snowmelt_flux_land
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SNODP(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- snow_depth
- units :
- m
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SNOMAS(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Total_snow_storage_land
- units :
- kg m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SPLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- rate_of_spurious_land_energy_source
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SPSNOW(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- rate_of_spurious_snow_energy
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SPWATR(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- rate_of_spurious_land_water_source
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - SWLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Net_shortwave_land
- units :
- W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TELAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Total_energy_storage_land
- units :
- J m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TPSNOW(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- surface_temperature_of_snow
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TSAT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- surface_temperature_of_saturated_zone
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TSOIL1(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- soil_temperatures_layer_1
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TSOIL2(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- soil_temperatures_layer_2
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TSOIL3(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- soil_temperatures_layer_3
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TSOIL4(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- soil_temperatures_layer_4
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TSOIL5(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- soil_temperatures_layer_5
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TSOIL6(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- soil_temperatures_layer_6
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TSURF(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- surface_temperature_of_land_incl_snow
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TUNST(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- surface_temperature_of_unsaturated_zone
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TWLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Avail_water_storage_land
- units :
- kg m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - TWLT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- surface_temperature_of_wilted_zone
- units :
- K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_BASEFLOW(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_BASEFLOW
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_ECHANGE(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_ECHANGE
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_EVLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_EVLAND
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_EVPINTR(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_EVPINTR
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_EVPSBLN(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_EVPSBLN
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_EVPSOIL(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_EVPSOIL
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_EVPTRNS(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_EVPTRNS
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_FRSAT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_FRSAT
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_FRSNO(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_FRSNO
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_FRUNST(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_FRUNST
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_FRWLT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_FRWLT
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_GHLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_GHLAND
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_GRN(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_GRN
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_GWETPROF(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_GWETPROF
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_GWETROOT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_GWETROOT
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_GWETTOP(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_GWETTOP
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_LAI(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_LAI
- units :
- 1 1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_LHLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_LHLAND
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_LWLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_LWLAND
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_PARDFLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_PARDFLAND
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_PARDRLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_PARDRLAND
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_PRECSNOLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_PRECSNOLAND
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_PRECTOTLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_PRECTOTLAND
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_PRMC(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_PRMC
- units :
- m-3 m-3 m-3 m-3
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_QINFIL(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_QINFIL
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_RUNOFF(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_RUNOFF
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_RZMC(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_RZMC
- units :
- m-3 m-3 m-3 m-3
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SFMC(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SFMC
- units :
- m-3 m-3 m-3 m-3
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SHLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SHLAND
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SMLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SMLAND
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SNODP(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SNODP
- units :
- m m
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SNOMAS(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SNOMAS
- units :
- kg m-2 kg m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SPLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SPLAND
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SPSNOW(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SPSNOW
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SPWATR(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SPWATR
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_SWLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_SWLAND
- units :
- W m-2 W m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TELAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TELAND
- units :
- J m-2 J m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TPSNOW(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TPSNOW
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TSAT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TSAT
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TSOIL1(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TSOIL1
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TSOIL2(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TSOIL2
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TSOIL3(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TSOIL3
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TSOIL4(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TSOIL4
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TSOIL5(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TSOIL5
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TSOIL6(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TSOIL6
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TSURF(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TSURF
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TUNST(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TUNST
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TWLAND(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TWLAND
- units :
- kg m-2 kg m-2
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_TWLT(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_TWLT
- units :
- K K
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - Var_WCHANGE(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- Variance_of_WCHANGE
- units :
- kg m-2 s-1 kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray - WCHANGE(time, lat, lon)float32dask.array<chunksize=(1, 361, 576), meta=np.ndarray>
- long_name :
- rate_of_change_of_total_land_water
- units :
- kg m-2 s-1
- fmissing_value :
- 1000000000000000.0
- vmax :
- 1000000000000000.0
- vmin :
- -1000000000000000.0
- valid_range :
- [-1.e+15 1.e+15]
Array Chunk Bytes 409.22 MB 831.74 kB Shape (492, 361, 576) (1, 361, 576) Count 1476 Tasks 492 Chunks Type float32 numpy.ndarray
- History :
- Wed Aug 11 19:56:56 2021: ncks -L 1 -O MERRA2_100.tavgM_2d_lnd_Nx.198001.nc4 /shared/land/MERRA-2/MONTHLY/lnd/MERRA2_monthly_2d_lnd_Nx.198001.nc4 Original file generated: Fri May 8 00:04:50 2015 GMT
- Filename :
- MERRA2_100.tavgM_2d_lnd_Nx.198001.nc4
- Comment :
- GMAO filename: d5124_m2_jan79.tavg1_2d_lnd_Nx.monthly.198001.nc4
- Conventions :
- CF-1
- Institution :
- NASA Global Modeling and Assimilation Office
- References :
- http://gmao.gsfc.nasa.gov
- Format :
- NetCDF-4/HDF-5
- SpatialCoverage :
- global
- VersionID :
- 5.12.4
- TemporalRange :
- 1980-01-01 -> 2016-12-31
- identifier_product_doi_authority :
- http://dx.doi.org/
- ShortName :
- M2TMNXLND
- RangeBeginningDate :
- 1980-01-01
- RangeEndingDate :
- 1980-01-31
- GranuleID :
- MERRA2_100.tavgM_2d_lnd_Nx.198001.nc4
- ProductionDateTime :
- Original file generated: Fri May 8 00:04:50 2015 GMT
- LongName :
- MERRA2 tavg1_2d_lnd_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Land Surface Diagnostics Monthly Mean
- Title :
- MERRA2 tavg1_2d_lnd_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Land Surface Diagnostics Monthly Mean
- SouthernmostLatitude :
- -90.0
- NorthernmostLatitude :
- 90.0
- WesternmostLongitude :
- -180.0
- EasternmostLongitude :
- 179.375
- LatitudeResolution :
- 0.5
- LongitudeResolution :
- 0.625
- DataResolution :
- 0.5 x 0.625
- Source :
- CVS tag: GEOSadas-5_12_4
- Contact :
- http://gmao.gsfc.nasa.gov
- identifier_product_doi :
- 10.5067/8S35XF81C28F
- RangeBeginningTime :
- 00:00:00.000000
- RangeEndingTime :
- 23:59:59.000000
- NCO :
- netCDF Operators version 4.7.5 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)