ERA5 daily precipitation

import earthkit.plots as ekp
import earthkit.data as ekd
import earthkit.transforms as ekt

data = ekd.from_source("sample", "era5-precip-reading.nc")

ds = data.to_xarray()
ds

<xarray.Dataset> Size: 9kB
Dimensions:     (valid_time: 744)
Coordinates:
  * valid_time  (valid_time) datetime64[ns] 6kB 2025-08-01 ... 2025-08-31T23:...
    latitude    float64 8B ...
    longitude   float64 8B ...
Data variables:
    tp          (valid_time) float32 3kB ...
Attributes:
    Conventions:             CF-1.7
    GRIB_centre:             ecmf
    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts
    GRIB_edition:            1
    GRIB_subCentre:          0
    history:                 2024-09-02T04:48 GRIB to CDM+CF via cfgrib-0.9.1...
    institution:             European Centre for Medium-Range Weather Forecasts

xarray.Dataset

• Dimensions:
  • valid_time: 744
• Coordinates: (3)
  • valid_time
    (valid_time)
    datetime64[ns]
    2025-08-01 ... 2025-08-31T23:00:00

    array(['2025-08-01T00:00:00.000000000', '2025-08-01T01:00:00.000000000',
           '2025-08-01T02:00:00.000000000', ..., '2025-08-31T21:00:00.000000000',
           '2025-08-31T22:00:00.000000000', '2025-08-31T23:00:00.000000000'],
          shape=(744,), dtype='datetime64[ns]')

  • latitude
    ()
    float64
    ...

    long_name :

    latitude

    standard_name :

    latitude

    stored_direction :

    decreasing

    units :

    degrees_north

    [1 values with dtype=float64]

  • longitude
    ()
    float64
    ...

    long_name :

    longitude

    standard_name :

    longitude

    units :

    degrees_east

    [1 values with dtype=float64]

• Data variables: (1)
  • tp
    (valid_time)
    float32
    ...

    GRIB_NV :

    0

    GRIB_Nx :

    1440

    GRIB_Ny :

    721

    GRIB_cfName :

    unknown

    GRIB_cfVarName :

    tp

    GRIB_dataType :

    fc

    GRIB_gridDefinitionDescription :

    Latitude/Longitude Grid

    GRIB_gridType :

    regular_ll

    GRIB_iDirectionIncrementInDegrees :

    0.25

    GRIB_iScansNegatively :

    0

    GRIB_jDirectionIncrementInDegrees :

    0.25

    GRIB_jPointsAreConsecutive :

    0

    GRIB_jScansPositively :

    0

    GRIB_latitudeOfFirstGridPointInDegrees :

    90.0

    GRIB_latitudeOfLastGridPointInDegrees :

    -90.0

    GRIB_longitudeOfFirstGridPointInDegrees :

    0.0

    GRIB_longitudeOfLastGridPointInDegrees :

    359.75

    GRIB_missingValue :

    3.4028234663852886e+38

    GRIB_name :

    Total precipitation

    GRIB_numberOfPoints :

    1038240

    GRIB_paramId :

    228

    GRIB_shortName :

    tp

    GRIB_stepType :

    accum

    GRIB_stepUnits :

    1

    GRIB_totalNumber :

    0

    GRIB_typeOfLevel :

    surface

    GRIB_units :

    m

    long_name :

    Total precipitation

    standard_name :

    unknown

    units :

    m

    [744 values with dtype=float32]

• Attributes: (7)

  Conventions :

  CF-1.7

  GRIB_centre :

  ecmf

  GRIB_centreDescription :

  European Centre for Medium-Range Weather Forecasts

  GRIB_edition :

  1

  GRIB_subCentre :

  0

  history :

  2024-09-02T04:48 GRIB to CDM+CF via cfgrib-0.9.10.4/ecCodes-2.26.0 with {"source": "../../../../../admp-scratch/data/arco-job-76964210-9c34-4488-a458-d3511cc8a37a-inputs/pre-reanalysis_era5_single_levels-sfc:1-sst-20150131-000000.grib", "filter_by_keys": {}, "encode_cf": ["parameter", "time", "geography", "vertical"]}

  institution :

  European Centre for Medium-Range Weather Forecasts

import numpy as np

daily = ekt.temporal.daily_mean(ds)
daily = daily.assign_coords(valid_time=daily.valid_time + np.timedelta64(12, "h"))

ekp.timeseries.bar(
    daily,
    color="#99ccff",
    title="ERA5 daily {variable_name} at {latitude:%Lt} {longitude:%Ln} ({location:%c}, {location:%C})",
    xticks={
        "frequency": "D",
        "format": "%-d",
        "highlight": {"weekday": "sunday"},
        "highlight_color": "pink",
        "period": True,
    },
    xlabel="August 2025",
    yunits="mm",
).show()