ea_moda_fc
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/ea_moda_fc.yaml")
ds=cat.netcdf.read()
Metadata
title | ea_moda_fc |
location | /reanalysis/land/ERA5/monthly |
tags | global,reanalysis,monthly |
catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/ea_moda_fc.yaml |
last updated | 2021-03-07 |
Dataset Contents
<xarray.Dataset> Dimensions: (latitude: 523, longitude: 1280, time: 504) Coordinates: * latitude (latitude) float32 87.25959 86.97859 ... -59.15688 -59.43791 * longitude (longitude) float32 -168.75 -168.46875 ... 190.68774 190.969 * time (time) int64 692496 693240 693912 ... 1058472 1059216 1059936 Data variables: blh (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> cbh (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> d2m (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> fal (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> flsr (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> fsr (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> mcpr (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> mer (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> mper (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> mror (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> msdrswrf (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> msdwlwrf (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> msdwswrf (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> mslhf (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> msnlwrf (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> msnswrf (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> msr (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> msshf (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> mtpr (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> mvimd (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> rsn (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> sd (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> si10 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> skt (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> sst (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> stl1 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> stl2 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> stl3 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> stl4 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> swvl1 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> swvl2 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> swvl3 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> swvl4 (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> t2m (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> tcc (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> tcwv (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> tsn (time, latitude, longitude) float32 dask.array<chunksize=(12, 523, 1280), meta=np.ndarray> Attributes: Conventions: CF-1.6 history: Sat Feb 20 15:17:39 2021: ncks -4 -O -L 1 /scratch/rd/napd/... NCO: netCDF Operators version 4.9.2 (Homepage = http://nco.sf.ne...
xarray.Dataset
- latitude: 523
- longitude: 1280
- time: 504
- latitude(latitude)float3287.25959 86.97859 ... -59.43791
- units :
- degrees_north
- long_name :
- latitude
array([ 87.25959 , 86.97859 , 86.697586, ..., -58.87585 , -59.15688 , -59.43791 ], dtype=float32)
- longitude(longitude)float32-168.75 -168.46875 ... 190.969
- units :
- degrees_east
- long_name :
- longitude
array([-168.75 , -168.46875, -168.1875 , ..., 190.4065 , 190.68774, 190.969 ], dtype=float32)
- time(time)int64692496 693240 ... 1059216 1059936
- units :
- hours since 1900-01-01 00:00:00.0
- long_name :
- time
- calendar :
- gregorian
array([ 692496, 693240, 693912, ..., 1058472, 1059216, 1059936])
- blh(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m
- long_name :
- Boundary layer height
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - cbh(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m
- long_name :
- Cloud base height
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - d2m(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- 2 metre dewpoint temperature
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - fal(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- (0 - 1)
- long_name :
- Forecast albedo
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - flsr(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- ~
- long_name :
- Forecast logarithm of surface roughness for heat
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - fsr(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m
- long_name :
- Forecast surface roughness
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - mcpr(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-2 s**-1
- long_name :
- Mean convective precipitation rate
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - mer(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-2 s**-1
- long_name :
- Mean evaporation rate
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - mper(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-2 s**-1
- long_name :
- Mean potential evaporation rate
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - mror(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-2 s**-1
- long_name :
- Mean runoff rate
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - msdrswrf(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- W m**-2
- long_name :
- Mean surface direct short-wave radiation flux
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - msdwlwrf(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- W m**-2
- long_name :
- Mean surface downward long-wave radiation flux
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - msdwswrf(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- W m**-2
- long_name :
- Mean surface downward short-wave radiation flux
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - mslhf(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- W m**-2
- long_name :
- Mean surface latent heat flux
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - msnlwrf(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- W m**-2
- long_name :
- Mean surface net long-wave radiation flux
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - msnswrf(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- W m**-2
- long_name :
- Mean surface net short-wave radiation flux
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - msr(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-2 s**-1
- long_name :
- Mean snowfall rate
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - msshf(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- W m**-2
- long_name :
- Mean surface sensible heat flux
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - mtpr(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-2 s**-1
- long_name :
- Mean total precipitation rate
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - mvimd(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-2 s**-1
- long_name :
- Mean vertically integrated moisture divergence
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - rsn(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-3
- long_name :
- Snow density
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - sd(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m of water equivalent
- long_name :
- Snow depth
- standard_name :
- lwe_thickness_of_surface_snow_amount
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - si10(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m s**-1
- long_name :
- 10 metre wind speed
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - skt(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- Skin temperature
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - sst(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- Sea surface temperature
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - stl1(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- Soil temperature level 1
- standard_name :
- surface_temperature
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - stl2(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- Soil temperature level 2
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - stl3(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- Soil temperature level 3
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - stl4(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- Soil temperature level 4
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - swvl1(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m**3 m**-3
- long_name :
- Volumetric soil water layer 1
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - swvl2(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m**3 m**-3
- long_name :
- Volumetric soil water layer 2
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - swvl3(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m**3 m**-3
- long_name :
- Volumetric soil water layer 3
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - swvl4(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- m**3 m**-3
- long_name :
- Volumetric soil water layer 4
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - t2m(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- 2 metre temperature
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - tcc(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- (0 - 1)
- long_name :
- Total cloud cover
- standard_name :
- cloud_area_fraction
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - tcwv(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- kg m**-2
- long_name :
- Total column water vapour
- standard_name :
- lwe_thickness_of_atmosphere_mass_content_of_water_vapor
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray - tsn(time, latitude, longitude)float32dask.array<chunksize=(12, 523, 1280), meta=np.ndarray>
- units :
- K
- long_name :
- Temperature of snow layer
- standard_name :
- temperature_in_surface_snow
Array Chunk Bytes 1.35 GB 32.13 MB Shape (504, 523, 1280) (12, 523, 1280) Count 126 Tasks 42 Chunks Type float32 numpy.ndarray
- Conventions :
- CF-1.6
- history :
- Sat Feb 20 15:17:39 2021: ncks -4 -O -L 1 /scratch/rd/napd/monthly/ea_moda_fc_1979.nc /scratch/rd/napd/monthly/ea_moda_fc_1979.nc4 2021-02-20 15:17:26 GMT by grib_to_netcdf-2.19.1: grib_to_netcdf -D NC_FLOAT -u time -o /scratch/rd/napd/monthly/ea_moda_fc_1979.nc /scratch/rd/napd/monthly/ea_moda_fc_1979.grb
- NCO :
- netCDF Operators version 4.9.2 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)