Radiation

Instrumentation

The BCO is equipped with a solar and terrestrial radiation measurement station, comprised of 4 radiation sensors attached to a SOLYS2 sun tracker. The instruments were installed on 2015-03-30.

More specifically, the apparatus sits on the top of the BCO container, \(4.5\,\mathrm{m}\) above the ground, or \(21.5\,\mathrm{m}\) above mean sea level

The 4 sensors are as follows:

• shaded pyranometer mounted on table of sun tracker for diffuse radiation (CMP21 by Kipp and Zonen),

• non-shaded pyranometer mounted on table of sun tracker for diffuse radiation (CMP21 by Kipp and Zonen),

  pyranometers measure solar irradiance from a hemispherical field of view diffuse radiation is the portion of incoming shortwave (SW) radiation due to atmospheric scattering

• shaded pyrgeometer mounted on table of sun tracker for longwave (LW) radiation (CGR4 by Kipp and Zonen)

• pyrheliometer mounted on the side of the sun tracker (CPH1 by Kipp and Zonen) points directly into the sun.

Two sets of 4 sensors are used and exchanged simultaneously approximately every two years.

• Set 1: CMP21 #140337, CMP21 #140356, CGR4 #140034 (replaced by 220446), CHP1 #140059 (replaced by 160388)

• Set 2: CMP21 #160654, CMP21 #160653, CGR4 #150139, CHP1 #160388

The calibration is done by the DWD in Lindenberg, and the solar irradiance (\(\mathrm{W} \mathrm{m}^{-2}\)), the raw voltages, the sensitivities, and the housing temperatures of each of the 4 sensors are available.

Data Availability

Housekeeping data is available as .zarr files in the catalog as:

• BCO.radiation_c1 (2015-03-30 to 2015-10-14)

• BCO.radiation_c2 (2015-10-15 to present)

And a level 2 product is being tested and can be found under the catalog entry BCO.radiation_l2 (2015-03-30 to present).

import intake

cat = intake.open_catalog("https://tcodata.mpimet.mpg.de/catalog.yaml")
ds_rad = cat.BCO.radiation_l2.to_dask()
ds_rad

/builds/tco/bco/docs/.venv/lib/python3.12/site-packages/intake_xarray/base.py:21: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.
  'dims': dict(self._ds.dims),

<xarray.Dataset> Size: 88MB
Dimensions:     (time: 3665382)
Coordinates:
    alt         float64 8B ...
    lat         float64 8B ...
    lon         float64 8B ...
  * time        (time) datetime64[ns] 29MB 2015-03-30T15:17:40 ... 2015-10-13...
Data variables:
    LWD_diff    (time) float32 15MB dask.array<chunksize=(262144,), meta=np.ndarray>
    SWD_diff    (time) float32 15MB dask.array<chunksize=(262144,), meta=np.ndarray>
    SWD_dir     (time) float32 15MB dask.array<chunksize=(262144,), meta=np.ndarray>
    SWD_global  (time) float32 15MB dask.array<chunksize=(262144,), meta=np.ndarray>
Attributes:
    Conventions:           CF-1.12
    _logical_cutoff_date:  2015-10-14T00:00:00Z
    bcoproc_version:       0.0.0.post1564.dev0+f62cdee
    featureType:           timeSeries
    institution:           Max Planck Institute for Meteorology, Hamburg
    license:               CC0-1.0
    location:              The Barbados Cloud Observatory (BCO), Deebles Poin...
    platform:              BCO
    source:                Kipp & Zonen CMP21 (shaded and un-shaded) pyranome...
    summary:               This dataset contains measurements of downwelling ...
    title:                 Radiation data from BCO (Level 2)
    tool_versions:         {"Python": "3.11.2 (main, Apr 28 2025, 14:11:48) [...

xarray.Dataset

• Dimensions:
  • time: 3665382
• Coordinates: (4)
  • alt
    ()
    float64
    ...

    long_name :

    height above mean sea level

    standard_name :

    altitude

    units :

    m

    [1 values with dtype=float64]

  • lat
    ()
    float64
    ...

    long_name :

    north latitude

    units :

    degree_north

    valid_max :

    90.0

    valid_min :

    -90.0

    [1 values with dtype=float64]

  • lon
    ()
    float64
    ...

    long_name :

    east longitude

    units :

    degree_east

    valid_max :

    180.0

    valid_min :

    -180.0

    [1 values with dtype=float64]

  • time
    (time)
    datetime64[ns]
    2015-03-30T15:17:40 ... 2015-10-...

    axis :

    T

    standard_name :

    time

    units_metadata :

    leap_seconds: utc

    array(['2015-03-30T15:17:40.000000000', '2015-03-30T15:17:50.000000000',
           '2015-03-30T15:18:00.000000000', ..., '2015-10-13T23:59:57.000000000',
           '2015-10-13T23:59:58.000000000', '2015-10-13T23:59:59.000000000'],
          shape=(3665382,), dtype='datetime64[ns]')

• Data variables: (4)
  • LWD_diff
    (time)
    float32
    dask.array<chunksize=(262144,), meta=np.ndarray>

    long_name :

    Longwave downwelling diffuse radiation

    standard_name :

    surface_downwelling_longwave_flux_in_air

    units :

    W m-2

    Array Chunk Bytes 13.98 MiB 1.00 MiB Shape (3665382,) (262144,) Dask graph 14 chunks in 2 graph layers Data type float32 numpy.ndarray

  • SWD_diff
    (time)
    float32
    dask.array<chunksize=(262144,), meta=np.ndarray>

    long_name :

    Shortwave downwelling diffuse radiation

    standard_name :

    surface_diffuse_downwelling_shortwave_flux_in_air

    units :

    W m-2

    Array Chunk Bytes 13.98 MiB 1.00 MiB Shape (3665382,) (262144,) Dask graph 14 chunks in 2 graph layers Data type float32 numpy.ndarray

  • SWD_dir
    (time)
    float32
    dask.array<chunksize=(262144,), meta=np.ndarray>

    long_name :

    Shortwave downwelling direct radiation

    standard_name :

    surface_direct_downwelling_shortwave_flux_in_air

    units :

    W m-2

    Array Chunk Bytes 13.98 MiB 1.00 MiB Shape (3665382,) (262144,) Dask graph 14 chunks in 2 graph layers Data type float32 numpy.ndarray

  • SWD_global
    (time)
    float32
    dask.array<chunksize=(262144,), meta=np.ndarray>

    long_name :

    Shortwave downwelling global radiation

    standard_name :

    surface_downwelling_shortwave_flux_in_air

    units :

    W m-2

    Array Chunk Bytes 13.98 MiB 1.00 MiB Shape (3665382,) (262144,) Dask graph 14 chunks in 2 graph layers Data type float32 numpy.ndarray

• Indexes: (1)
  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2015-03-30 15:17:40', '2015-03-30 15:17:50',
                   '2015-03-30 15:18:00', '2015-03-30 15:18:10',
                   '2015-03-30 15:18:20', '2015-03-30 15:18:30',
                   '2015-03-30 15:18:40', '2015-03-30 15:18:50',
                   '2015-03-30 15:19:00', '2015-03-30 15:19:10',
                   ...
                   '2015-10-13 23:59:50', '2015-10-13 23:59:51',
                   '2015-10-13 23:59:52', '2015-10-13 23:59:53',
                   '2015-10-13 23:59:54', '2015-10-13 23:59:55',
                   '2015-10-13 23:59:56', '2015-10-13 23:59:57',
                   '2015-10-13 23:59:58', '2015-10-13 23:59:59'],
                  dtype='datetime64[ns]', name='time', length=3665382, freq=None))

• Attributes: (12)

  Conventions :

  CF-1.12

  _logical_cutoff_date :

  2015-10-14T00:00:00Z

  bcoproc_version :

  0.0.0.post1564.dev0+f62cdee

  featureType :

  timeSeries

  institution :

  Max Planck Institute for Meteorology, Hamburg

  license :

  CC0-1.0

  location :

  The Barbados Cloud Observatory (BCO), Deebles Point, Barbados, West Indies

  platform :

  BCO

  source :

  Kipp & Zonen CMP21 (shaded and un-shaded) pyranometer, CGR4 (shaded) pyrgeometer, CHP1 pyrheliometer

  summary :

  This dataset contains measurements of downwelling shortwave and longwave radiation measurements from sensors mounted on the table of a SOLYS2 sun tracker at the BCO. This level 2 dataset contains data marked as `ok` in the level 1 data.

  title :

  Radiation data from BCO (Level 2)

  tool_versions :

  {"Python": "3.11.2 (main, Apr 28 2025, 14:11:48) [GCC 12.2.0]", "xarray": "2025.4.0", "tzdata": "2025.2", "locket": "1.0.0", "pendulum": "3.1.0", "propcache": "0.3.1", "packaging": "25.0", "cloudpickle": "3.1.1", "idna": "3.10", "dask": "2025.4.1", "yarl": "1.20.0", "ruff": "0.13.0", "frozenlist": "1.6.0", "click": "8.1.8", "aiohttp": "3.11.18", "certifi": "2025.4.26", "jinja2": "3.1.6", "pytz": "2025.2", "attrs": "25.3.0", "pluggy": "1.5.0", "pytest": "8.3.5", "bcologs": "0.0.0.post1564.dev0+f62cdee", "importlib_metadata": "8.7.0", "pandas": "2.2.3", "zipp": "3.21.0", "datarecords": "0.0.0.post1564.dev0+f62cdee", "aiohappyeyeballs": "2.6.1", "iniconfig": "2.1.0", "python-dateutil": "2.9.0.post0", "netcdf4": "1.7.2", "MarkupSafe": "3.0.3", "pyyaml": "6.0.2", "cftime": "1.6.4.post1", "six": "1.17.0", "numpy": "2.2.5", "partd": "1.4.2", "toolz": "1.0.0", "aiosignal": "1.3.2", "fsspec": "2025.3.2", "multidict": "6.4.3", "bcoproc": "0.0.0.post1564.dev0+f62cdee"}

Sample Plot

import matplotlib.pylab as plt
import pandas as pd
import xarray as xr
from pvlib.location import Location

cat = intake.open_catalog("https://tcodata.mpimet.mpg.de/catalog.yaml")
ds_rad = cat.BCO.radiation_l2.to_dask()

# select a few days of interest
subset = ds_rad.sel(time=slice("2015-07-03", "2015-07-05"))

# get clear sky calculated radiation for reference
lat, lon, alt = float(subset.lat), float(subset.lon), float(subset.alt)
bco = Location(lat, lon, 'UTC', alt, name = 'bco')
times = pd.to_datetime(subset.coords['time'].values)
cs = bco.get_clearsky(times).to_xarray().rename({'index': 'time'})
ds_cs = xr.merge([subset, cs])

# plot observed SW vs calculated clear-sky
ds_cs.SWD_global.plot(label='SW from non-shaded pyranometer')
ds_cs.ghi.plot(label='Clear-sky')
plt.legend(loc='upper left')
plt.ylabel('Solar Irradiance [W/m²]')
plt.title('BCO SW radiation vs. clear-sky calculated')

/builds/tco/bco/docs/.venv/lib/python3.12/site-packages/intake_xarray/base.py:21: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.
  'dims': dict(self._ds.dims),

Text(0.5, 1.0, 'BCO SW radiation vs. clear-sky calculated')