SMART dataset

The following script exemplifies the access and usage of SMART data measured during EUREC4A. The Spectral Modular Airborne Radiation measurement sysTem (SMART) measures downward irradiances in the solar spectral range between 300 nm and 2200 nm.

More information on the dataset can be found in Stevens et al. (2019) and Wendisch et al. (2001). If you have questions or if you would like to use the data for a publication, please don’t hesitate to get in contact with the dataset authors as stated in the dataset attributes contact or author.

Get data

• To load the data we first load the EUREC4A meta data catalogue. More information on the catalog can be found here.

import eurec4a

cat = eurec4a.get_intake_catalog(use_ipfs="QmahMN2wgPauHYkkiTGoG2TpPBmj3p5FoYJAq9uE9iXT9N")
list(cat.HALO.SMART)

['spectral_irradiances']

• We can further specify a product and a flight and obtain the dataset using to_dask.

Note

Have a look at the attributes of the xarray dataset ds_smart for all relevant information on the dataset, such as author, contact, or citation infromation.

ds_smart = cat.HALO.SMART.spectral_irradiances['HALO-0205'].to_dask()
ds_smart

/usr/share/miniconda3/envs/how_to_eurec4a/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: 2MB
Dimensions:               (time: 32730)
Coordinates:
  * time                  (time) datetime64[ns] 262kB 2020-02-05T09:15:53 ......
Data variables:
    F_down_solar_wl_1238  (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    F_down_solar_wl_1638  (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    F_down_solar_wl_422   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    F_down_solar_wl_532   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    F_down_solar_wl_648   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    F_down_solar_wl_858   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    alt                   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    lat                   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    lon                   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    saa                   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
    sza                   (time) float32 131kB dask.array<chunksize=(32730,), meta=np.ndarray>
Attributes:
    Contact:              Andre Ehrlich, University Leipzig, a.ehrlich@uni-le...
    Research_Flight_Day:  2020/20/05
    Title:                Spectral downward irradiance measured by SMART duri...
    Version:              Revision 3 from 2021/01/24
    campaign:             EUREC4A
    comment 1:            BAHAMAS data was processed by DLR, contact Andreas ...
    platform:             HALO

xarray.Dataset

• Dimensions:
  • time: 32730
• Coordinates: (1)
  • time
    (time)
    datetime64[ns]
    2020-02-05T09:15:53 ... 2020-02-...

    long_name :

    time

    array(['2020-02-05T09:15:53.000000000', '2020-02-05T09:15:54.000000000',
           '2020-02-05T09:15:55.000000000', ..., '2020-02-05T18:21:20.000000000',
           '2020-02-05T18:21:21.000000000', '2020-02-05T18:21:22.000000000'],
          dtype='datetime64[ns]')

• Data variables: (11)
  • F_down_solar_wl_1238
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    comment :

    Corrected for aircraft movement, averaged for wavelength band +-5 nm

    long_name :

    Spectral downward solar irradiance (1238 nm) (SMART)

    units :

    W m-2 nm-1

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • F_down_solar_wl_1638
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    comment :

    Corrected for aircraft movement, averaged for wavelength band +-5 nm

    long_name :

    Spectral downward solar irradiance (1638 nm) (SMART)

    units :

    W m-2 nm-1

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • F_down_solar_wl_422
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    comment :

    Corrected for aircraft movement, averaged for wavelength band +-5 nm

    long_name :

    Spectral downward solar irradiance (422 nm) (SMART)

    units :

    W m-2 nm-1

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • F_down_solar_wl_532
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    comment :

    Corrected for aircraft movement, averaged for wavelength band +-5 nm

    long_name :

    Spectral downward solar irradiance (532 nm) (SMART)

    units :

    W m-2 nm-1

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • F_down_solar_wl_648
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    comment :

    Corrected for aircraft movement, averaged for wavelength band +-5 nm

    long_name :

    Spectral downward solar irradiance (648 nm) (SMART)

    units :

    W m-2 nm-1

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • F_down_solar_wl_858
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    comment :

    Corrected for aircraft movement, averaged for wavelength band +-5 nm

    long_name :

    Spectral downward solar irradiance (858 nm) (SMART)

    units :

    W m-2 nm-1

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • alt
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    long_name :

    altitude (WGS84 Datum/Elliptical, BAHAMAS)

    standard_name :

    altitude

    units :

    m

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • lat
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    long_name :

    latitude (WGS84 Datum/Latitude, BAHAMAS)

    standard_name :

    latitude

    units :

    degrees_north

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • lon
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    long_name :

    longitude (WGS84 Datum/Longitude, BAHAMAS)

    standard_name :

    longitude

    units :

    degree_east

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • saa
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    long_name :

    solar azimuth angle

    standard_name :

    solar_azimuth_angle

    units :

    degree

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • sza
    (time)
    float32
    dask.array<chunksize=(32730,), meta=np.ndarray>

    long_name :

    solar zenith angle

    standard_name :

    solar_zenith_angle

    units :

    degree

    Array Chunk Bytes 127.85 kiB 127.85 kiB Shape (32730,) (32730,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

• Indexes: (1)
  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2020-02-05 09:15:53', '2020-02-05 09:15:54',
                   '2020-02-05 09:15:55', '2020-02-05 09:15:56',
                   '2020-02-05 09:15:57', '2020-02-05 09:15:58',
                   '2020-02-05 09:15:59', '2020-02-05 09:16:00',
                   '2020-02-05 09:16:01', '2020-02-05 09:16:02',
                   ...
                   '2020-02-05 18:21:13', '2020-02-05 18:21:14',
                   '2020-02-05 18:21:15', '2020-02-05 18:21:16',
                   '2020-02-05 18:21:17', '2020-02-05 18:21:18',
                   '2020-02-05 18:21:19', '2020-02-05 18:21:20',
                   '2020-02-05 18:21:21', '2020-02-05 18:21:22'],
                  dtype='datetime64[ns]', name='time', length=32730, freq=None))

• Attributes: (7)

  Contact :

  Andre Ehrlich, University Leipzig, a.ehrlich@uni-leipzig.de or Kevin Wolf, University Leipzig, kevin.wolf@uni-leipzig.de

  Research_Flight_Day :

  2020/20/05

  Title :

  Spectral downward irradiance measured by SMART during EUREC4A

  Version :

  Revision 3 from 2021/01/24

  campaign :

  EUREC4A

  comment 1 :

  BAHAMAS data was processed by DLR, contact Andreas Giez

  platform :

  HALO

The available dataset includes irradiances for six selected wavelengths (422nm, 532nm, 648nm, 858nm, 1238nm, 1638nm). The full dataset is available on demand. Contact the dataset authors as stated in the dataset attributes contact.

First Quickplot of whole flight (one wavelength)

%matplotlib inline
import matplotlib.pyplot as plt
import pathlib
plt.style.use(pathlib.Path("./mplstyle/book"))

ds_smart.F_down_solar_wl_422.plot();

Load HALO flight phase information

All HALO flights were split up into flight phases or segments to allow for a precise selection in time and space of a circle or calibration pattern. For more information have a look at the respective github repository.

meta = eurec4a.get_flight_segments()

We select the flight phase we are interested in, e.g. the second circle on February 5 by it’s segment_id.

segments = {s["segment_id"]: {**s, "flight_id": flight["flight_id"]}
             for platform in meta.values()
             for flight in platform.values()
             for s in flight["segments"]
            }
seg = segments["HALO-0205_c2"]

We transfer the information from our flight segment selection to our radar and radiometer data in the xarray dataset.

ds_smart_selection = ds_smart.sel(time=slice(seg["start"], seg["end"]))

Plots

We plot the spectral irradiances from different wavelengths measured with SMART during the selected flight segment.

fig, ax = plt.subplots()
wl_list=[422,532,648,858,1238,1638]
for i in wl_list:
    ds_smart_selection[f'F_down_solar_wl_{i}'].plot(label =f'{i} nm')
ax.legend()
ax.set_ylabel('Spectral downward irradiance / Wm$^{-2}$nm$^{-1}$')
None