soilw4_daily
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/soilw4_daily.yaml")
ds=cat.netcdf.read()
Metadata
title | soilw4_daily |
location | /project/CLIM751/data/daily/soilw4 |
tags | gridded, model, global, refcst, daily, soil_moisture, land |
catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/soilw4_daily.yaml |
last updated | 2016-08-29 |
Dataset Contents
xarray.Dataset
- ens: 5
- lat: 180
- lon: 360
- time: 12740
- lon(lon)float640.5 1.5 2.5 ... 357.5 358.5 359.5
- units :
- degrees_east
- long_name :
- Longitude
array([ 0.5, 1.5, 2.5, ..., 357.5, 358.5, 359.5])
- ens(ens)float641.0 2.0 3.0 4.0 5.0
- grads_dim :
- e
- long_name :
- Ensemble member
array([1., 2., 3., 4., 5.])
- lat(lat)float64-89.5 -88.5 -87.5 ... 88.5 89.5
- units :
- degrees_north
- long_name :
- Latitude
array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5, -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5, -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5, -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5, -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5, -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5, -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5, -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5, -9.5, -8.5, -7.5, -6.5, -5.5, -4.5, -3.5, -2.5, -1.5, -0.5, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5, 20.5, 21.5, 22.5, 23.5, 24.5, 25.5, 26.5, 27.5, 28.5, 29.5, 30.5, 31.5, 32.5, 33.5, 34.5, 35.5, 36.5, 37.5, 38.5, 39.5, 40.5, 41.5, 42.5, 43.5, 44.5, 45.5, 46.5, 47.5, 48.5, 49.5, 50.5, 51.5, 52.5, 53.5, 54.5, 55.5, 56.5, 57.5, 58.5, 59.5, 60.5, 61.5, 62.5, 63.5, 64.5, 65.5, 66.5, 67.5, 68.5, 69.5, 70.5, 71.5, 72.5, 73.5, 74.5, 75.5, 76.5, 77.5, 78.5, 79.5, 80.5, 81.5, 82.5, 83.5, 84.5, 85.5, 86.5, 87.5, 88.5, 89.5])
- time(time)datetime64[ns]1980-01-01 ... 2014-12-30
- long_name :
- Time
array(['1980-01-01T00:00:00.000000000', '1980-01-02T00:00:00.000000000', '1980-01-03T00:00:00.000000000', ..., '2014-12-28T00:00:00.000000000', '2014-12-29T00:00:00.000000000', '2014-12-30T00:00:00.000000000'], dtype='datetime64[ns]')
- soilw4(ens, time, lat, lon)float32dask.array<chunksize=(5, 91, 180, 360), meta=np.ndarray>
- units :
- fraction
- long_name :
- Volumetric Soil Moisture Content 100-200cm below ground
Array Chunk Bytes 16.51 GB 117.94 MB Shape (5, 12740, 180, 360) (5, 91, 180, 360) Count 420 Tasks 140 Chunks Type float32 numpy.ndarray