trmm_3b42rt

Near real time rainfall estimates from NASA's Tropical Rainfall Measuring Mission

Load in Python

from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/pangeo-data/pangeo-datastore/master/intake-catalogs/atmosphere.yaml") ds = cat["trmm_3b42rt"].to_dask()

Working with requester pays data

Several of the datasets within the cloud data catalog are contained in requester pays storage buckets. This means that a user requesting data must provide their own billing project (created and authenticated through Google Cloud Platform) to be billed for the charges associated with accessing a dataset. To set up an GCP billing project and use it for authentication in applications:

Metadata

url https://trmm.gsfc.nasa.gov/data_dir/data.html
tags ['precipitation', 'satellite']

Dataset Contents

Show/Hide data repr Show/Hide attributes
xarray.Dataset
    • lat: 480
    • lon: 1440
    • time: 41320
    • lat
      (lat)
      float64
      59.88 59.62 59.38 ... -59.62 -59.88
      array([ 59.875,  59.625,  59.375, ..., -59.375, -59.625, -59.875])
    • lon
      (lon)
      float64
      0.125 0.375 0.625 ... 359.6 359.9
      array([1.25000e-01, 3.75000e-01, 6.25000e-01, ..., 3.59375e+02, 3.59625e+02,
             3.59875e+02])
    • time
      (time)
      datetime64[ns]
      2000-03-01T12:00:00 ... 2014-04-22T09:00:00
      array(['2000-03-01T12:00:00.000000000', '2000-03-01T15:00:00.000000000',
             '2000-03-01T18:00:00.000000000', ..., '2014-04-22T03:00:00.000000000',
             '2014-04-22T06:00:00.000000000', '2014-04-22T09:00:00.000000000'],
            dtype='datetime64[ns]')
    • precipitation
      (time, lat, lon)
      float32
      dask.array<chunksize=(40, 480, 1440), meta=np.ndarray>
      Array Chunk
      Bytes 114.24 GB 110.59 MB
      Shape (41320, 480, 1440) (40, 480, 1440)
      Count 1034 Tasks 1033 Chunks
      Type float32 numpy.ndarray
      1440 480 41320