Radar and ground-level measurements collected during the POPE 2020 campaign at Princess Elisabeth Antarctica

This repository contain the datasets of radar and ground-level measurements collected in the vicinity of the Belgian research base Princess Elisabeth Antarctica (PEA).

The measurement campaign has been conducted by the Environmental Remote Sensing Laboratory (LTE) of the Scole Polytechnique Fédérale de Lausanne (EPFL), with the logistical support of the International Polar Foundation (IPF).

The datasets and their processing are described in the article “Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica”, by Alfonso Ferrone and Alexis Berne. The article was submitted to Earth System Science Data in August 2022, and is available at the following URL: https://doi.org/10.5194/essd-2022-295 .

Content of the archives
The datasets have been divided into compressed archives. Each of them contains a series of data files, all saved in NetCDF4 format.

The content of each archives is listed below.

- WProf.zip
This archive contains the radar variables collected by the W-band Doppler profiling cloud radar (WProf) deployed at PEA.
The liquid water path and integrated water vapor (retrieved thanks to the 89 GHz radiometer included in the instrument) has also been included in the files.

- MXPol_PPI.zip
This archive contains the polarimetric radar variables collected by the X-band Doppler dual-polarization scanning weather radar (MXPol) during the nearly-vertical PPI scans.

- MXPol_sector_scans_2019.zip
This archive contains the polarimetric radar variables collected by MXPol during the sector scans (PPI scans limited to a sector of the full azimuth circle) scans performed in December 2019. Sector scans collected in the following months have been stored separately, due to a limitation on the maximum number of files in input to the creation of the zip archive.

- MXPol_sector_scans_2020.zip
This archive contains the polarimetric radar variables collected by MXPol during the sector scans scans performed in January and February 2020.

- MXPol_hydrometeor_types.zip
This archive contains the polarimetric radar variables collected by MXPol during the RHI scans. The files also contain information on the proportion of hydrometeor classes and the dominant hydrometeor type computed from the measurements of MXPol.

- MRR_PRO_06.zip, MRR_PRO_22.zip, and MRR_PRO_23.zip
The three archives contain the radar variables collected by the K-band Doppler profiling radars (MRR-PRO) deployed in a transect across the mountain range south of PEA.

- aws_radiometers.zip
This archive contains the measurements collected by the Automated Weather Station (AWS) installed alongside each of the three MRR-PRO. The data from the two radiometers deployed at the MRR-PRO 06 site have also been included in the archive.

Content of the NetCDF4 files

A “short name” is associated to each variables in the NetCDF4 files. This section provides a list of all the relevant variables collected by each instruments, alongside their short name.

The following polarimetric variables are available for all the scans performed by MXPol, stored in the archives MXPol_PPI.zip, MXPol_hydrometeor_types.zip, MXPol_sector_scans_2019.zip, and MXPol_sector_scans_2020.zip:

– the horizontal reflectivity factors (ZH), identified in the files by the short name “Zh”;

– the vertical reflectivity factors (ZV), identified by the short name “Zv”;

– the differential reflectivity (ZDR), identified by the short name “Zdr”;

– the signal-to-noise ratio on the horizontal polarization channel (SNRH), identified by the short name “SNRh”;

– the signal-to-noise ratio on the vertical polarization channel (SNRV), identified by the short name “SNRv”;

– the mean Doppler radial velocity (V), identified by the short name “RVel”;

– the spectral width (SW), identified by the short name “Sw”;

– the total differential phase shift (ΨDP), identified by the short name “Psidp”;

– the differential phase shift (ΦDP), identified by the short name “Phidp”;

– the specific differential phase on propagation (KDP), identified by the short name “Kdp”;

– the co-polar correlation coefficient (ρhv), identified by the short name “Rhohv”.

The hydrometeor classification (Besic et al., 2016) and the retrieval of the proportion of each hydrometeor category in the radar volume (Besic et al., 2018) has been applied to all RHI scans of MXPol (archive MXPol_hydrometeor_types.zip), producing the following variables:

– the dominant hydrometeor type, identified by the short name “hydro”,

– the entropy computed by the classification algorithm, which provides an estimate of the confidence on the label assigned to the volume, identified by the short name “hydroclass_entropy”;

– the proportion of each hydrometeor type in the volume, stored in the variables “proportion_AG” (aggregates), “proportion_CR” (ice crystals), “proportion_LR” (light rain), “proportion_RP” (rimed particles), “proportion_RN” (rain), “proportion_VI” (vertically-aligned ice), “proportion_WS” (wet snow), “proportion_MH” (melting hail);

– the entropy computed by the demixing algorithm, identified by the short name “entropy”.

The following radar variables are available for all the profiles collected by WProf, stored in the archive WProf.zip:

– the equivalent reflectivity factor (Ze), identified in the files by the short name “Ze”

– the signal-to-noise ratio (SNR), identified in the files by the short name “SnR”;

– the mean Doppler radial velocity, identified in the files by the short name “Mean-velocity”;

– the spectral width, identified in the files by the short name “Spectral-width”;

– the skewness, identified in the files by the short name “Spectral-skewness”;

– the kurtosis, identified in the files by the short name “Spectral-kurtosis”;

– the noise level at each range gate gate, identified in the files by the short name “Noise_level”;

– the noise floor at each range gate gate, identified in the files by the short name “Noise_floor”.

The following retrievals (Billault-Roux et al., 2021) have been included in the WProf data files, stored in the archive WProf.zip:

– the Integrated Water Vapor (IWV), identified in the files by the short name “Integrated-water-vapor”;

– the Liquid Water Path (LWP), identified in the files by the short name “Liquid-water-path”.

The following atmospheric variables, recorded by the automated weather station integrated in the radar, have been included in the WProf data files, stored in the archive WProf.zip:

– the atmospheric pressure, identified in the files by the short name “Barometric-pressure”;

– the air temperature, identified in the files by the short name “Environment-temp”;

– the relative humidity with respect to liquid water, identified in the files by the short name “Rel-humidity”;

– the horizontal wind direction, identified in the files by the short name “Wind-direction”;

– the horizontal wind speed, identified in the files by the short name “Wind-speed”.

The following variables are available for all the profiles collected by the three MRR-PRO, stored in the archives MRR_PRO_06.zip, MRR_PRO_22.zip, and MRR_PRO_23.zip:

– the attenuated equivalent reflectivity factor (Zea), identified in the files by the short name “Zea”;

– the mean Doppler radial velocity, identified in the files by the short name “VEL”;

– the spectral width, identified in the files by the short name “SW”;

– the signal-to-noise ratio, identified in the files by the short name “SNR”;

– the noise level computed by ERUO (Ferrone et al., 2022) at each range gate gate, identified in the files by the short name “noise_level”;

– the noise floor computed by ERUO at each range gate gate, identified in the files by the short name “noise_floor”.

The following variables are available for all the measurements collected by the three weather stations, stored in the archive aws_radiometers.zip:

– the atmospheric pressure, identified in the files by the short name “pressure”;

– the air temperature, identified in the files by the short name “temperature”;

– the relative humidity with respect to liquid water, identified in the files by the short name “relative_humidity”;

– the horizontal wind direction, identified in the files by the short name “wind_speed”;

– the horizontal wind speed, identified in the files by the short name “wind_direction”.

The following variables are available for all the measurements collected by the pyrgeometer and pyranometer, stored in the archive aws_radiometers.zip::

– the total downwelling irradiance in the shortwave, identified in the files by the short name “shortwave_irradiance”;

– the total downwelling irradiance in the longwave, identified in the files by the short name “longwave_irradiance”.

References

Besic, N., Figueras i Venturra, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmospheric Measurement Techniques, 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, 2016.

Besic, N., Gehring, J., Praz, C., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Unraveling hydrometeor mixtures in polarimetric radar measurements, Atmospheric Measurement Techniques, 11, 4847–4866, https://doi.org/10.5194/amt-11-4847-2018, 2018

Billault-Roux, A.-C. and Berne, A.: Integrated water vapor and liquid water path retrieval using a single-channel radiometer, Atmospheric Measurement Techniques, 14, 2749–2769, https://doi.org/10.5194/amt-14-2749-2021, 2021

Ferrone, A., Billault-Roux, A.-C., and Berne, A.: ERUO: a spectral processing routine for the Micro Rain Radar PRO (MRR-PRO), Atmospheric Measurement Techniques, 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, 2022