Backscatter Cloud Probe with Polarization Detection
This dataset contains the processed and raw data collected with the Backscatter Cloud Probe with Polarization Detection during the HALO-AC³ campaign in March and April 2022 with the Polar 6 Aircraft out of Longyearbyen, Svalbard. The dataset contains two kinds of data. Data to which no inversion pro...
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Format: | Dataset |
Language: | English |
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PANGAEA
2023
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Online Access: | https://doi.pangaea.de/10.1594/PANGAEA.963614 https://doi.org/10.1594/PANGAEA.963614 |
id |
ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.963614 |
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record_format |
openpolar |
institution |
Open Polar |
collection |
PANGAEA - Data Publisher for Earth & Environmental Science |
op_collection_id |
ftpangaea |
language |
English |
topic |
AC Aircraft Arctic Backscatter Cloud Probe with Polarization Detection BCPD Date/Time of event Event label HALO - (AC)3 HALO-(AC)³ HALO-AC3_20220320_P6_RF01 HALO-AC3_20220322_P6_RF02 HALO-AC3_20220326_P6_RF04 HALO-AC3_20220328_P6_RF05 HALO-AC3_20220329_P6_RF06 HALO-AC3_20220330_P6_RF07 HALO-AC3_20220401_P6_RF08 HALO-AC3_20220404_P6_RF09 HALO-AC3_20220405_P6_RF10 HALO-AC3_20220408_P6_RF11 HALO-AC3_20220409_P6_RF12 HALO-AC3_20220410_P6_RF13 mixed-phase clouds netCDF file netCDF file (File Size) P6_231_HALO_2022_2203200401 P6_231_HALO_2022_2203220501 P6_231_HALO_2022_2203260702 P6_231_HALO_2022_2203280801 P6_231_HALO_2022_2203290901 P6_231_HALO_2022_2203301001 P6_231_HALO_2022_2204011101 P6_231_HALO_2022_2204041201 P6_231_HALO_2022_2204051301 P6_231_HALO_2022_2204081401 P6_231_HALO_2022_2204091501 P6_231_HALO_2022_2204101601 P6-231_HALO_2022 Particle size distributions Phase differentiation POLAR 6 Polarimetric Radar Observations meet Atmospheric Modelling (PROM) - Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes SPP2115_PROM Svalbard |
spellingShingle |
AC Aircraft Arctic Backscatter Cloud Probe with Polarization Detection BCPD Date/Time of event Event label HALO - (AC)3 HALO-(AC)³ HALO-AC3_20220320_P6_RF01 HALO-AC3_20220322_P6_RF02 HALO-AC3_20220326_P6_RF04 HALO-AC3_20220328_P6_RF05 HALO-AC3_20220329_P6_RF06 HALO-AC3_20220330_P6_RF07 HALO-AC3_20220401_P6_RF08 HALO-AC3_20220404_P6_RF09 HALO-AC3_20220405_P6_RF10 HALO-AC3_20220408_P6_RF11 HALO-AC3_20220409_P6_RF12 HALO-AC3_20220410_P6_RF13 mixed-phase clouds netCDF file netCDF file (File Size) P6_231_HALO_2022_2203200401 P6_231_HALO_2022_2203220501 P6_231_HALO_2022_2203260702 P6_231_HALO_2022_2203280801 P6_231_HALO_2022_2203290901 P6_231_HALO_2022_2203301001 P6_231_HALO_2022_2204011101 P6_231_HALO_2022_2204041201 P6_231_HALO_2022_2204051301 P6_231_HALO_2022_2204081401 P6_231_HALO_2022_2204091501 P6_231_HALO_2022_2204101601 P6-231_HALO_2022 Particle size distributions Phase differentiation POLAR 6 Polarimetric Radar Observations meet Atmospheric Modelling (PROM) - Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes SPP2115_PROM Svalbard Lucke, Johannes Moser, Manuel De La Torre Castro, Elena Mayer, Johanna Voigt, Christiane Backscatter Cloud Probe with Polarization Detection |
topic_facet |
AC Aircraft Arctic Backscatter Cloud Probe with Polarization Detection BCPD Date/Time of event Event label HALO - (AC)3 HALO-(AC)³ HALO-AC3_20220320_P6_RF01 HALO-AC3_20220322_P6_RF02 HALO-AC3_20220326_P6_RF04 HALO-AC3_20220328_P6_RF05 HALO-AC3_20220329_P6_RF06 HALO-AC3_20220330_P6_RF07 HALO-AC3_20220401_P6_RF08 HALO-AC3_20220404_P6_RF09 HALO-AC3_20220405_P6_RF10 HALO-AC3_20220408_P6_RF11 HALO-AC3_20220409_P6_RF12 HALO-AC3_20220410_P6_RF13 mixed-phase clouds netCDF file netCDF file (File Size) P6_231_HALO_2022_2203200401 P6_231_HALO_2022_2203220501 P6_231_HALO_2022_2203260702 P6_231_HALO_2022_2203280801 P6_231_HALO_2022_2203290901 P6_231_HALO_2022_2203301001 P6_231_HALO_2022_2204011101 P6_231_HALO_2022_2204041201 P6_231_HALO_2022_2204051301 P6_231_HALO_2022_2204081401 P6_231_HALO_2022_2204091501 P6_231_HALO_2022_2204101601 P6-231_HALO_2022 Particle size distributions Phase differentiation POLAR 6 Polarimetric Radar Observations meet Atmospheric Modelling (PROM) - Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes SPP2115_PROM Svalbard |
description |
This dataset contains the processed and raw data collected with the Backscatter Cloud Probe with Polarization Detection during the HALO-AC³ campaign in March and April 2022 with the Polar 6 Aircraft out of Longyearbyen, Svalbard. The dataset contains two kinds of data. Data to which no inversion procedure has been applied and data to which the inversion procedure has been applied. The inversion procedure is applied to account for an uneven intensity of the laser beam across the sample area and resulting undersizing effects. The inversion procedure has been discussed in Lucke et al. (2023) (doi.org/10.4271/2023-01-1485) and Beswick et al. (2014) (doi.org/10.5194/amt-7-1443-2014). All quantities which carry the suffix inv are based on the inverted data, all other properties are not. It should be noted, that the necessity of the inversion procedure remains unclear (see the previously mentioned publications). The inversion procedure could only be applied when more than 2000 particles were present over a 5 second interval. When this was not the case, the inverted data are 9999.999. The inverted data are therefore also computed from a 5s rolling average. The measurements of the BCPD are likely severely influenced by inertial separation effects, due to the proximity of the BCPD sample area to the fuselage (approx. 3cm). When ice particles are present, shattering occurs on the fuselage and artificially increases the ice number concentration. The number of ice and liquid particles listed in this data set can be useful for assessing the presence of ice and liquid particles. To estimate the number of liquid and ice particles more than 100 particles are required over a 5s interval. When this is not the case, the data are 9999.999. The number of ice and liquid particles were computed as rolling averages over 5s intervals. The sample area in case no inversion procedure is applied is 0.273 square millimeters. |
format |
Dataset |
author |
Lucke, Johannes Moser, Manuel De La Torre Castro, Elena Mayer, Johanna Voigt, Christiane |
author_facet |
Lucke, Johannes Moser, Manuel De La Torre Castro, Elena Mayer, Johanna Voigt, Christiane |
author_sort |
Lucke, Johannes |
title |
Backscatter Cloud Probe with Polarization Detection |
title_short |
Backscatter Cloud Probe with Polarization Detection |
title_full |
Backscatter Cloud Probe with Polarization Detection |
title_fullStr |
Backscatter Cloud Probe with Polarization Detection |
title_full_unstemmed |
Backscatter Cloud Probe with Polarization Detection |
title_sort |
backscatter cloud probe with polarization detection |
publisher |
PANGAEA |
publishDate |
2023 |
url |
https://doi.pangaea.de/10.1594/PANGAEA.963614 https://doi.org/10.1594/PANGAEA.963614 |
op_coverage |
MEDIAN LATITUDE: 78.239504 * MEDIAN LONGITUDE: 15.106434 * SOUTH-BOUND LATITUDE: 78.091476 * WEST-BOUND LONGITUDE: 6.004681 * NORTH-BOUND LATITUDE: 78.246003 * EAST-BOUND LONGITUDE: 15.503320 * DATE/TIME START: 2022-03-20T10:39:14 * DATE/TIME END: 2022-04-10T14:13:58 |
long_lat |
ENVELOPE(6.004681,15.503320,78.246003,78.091476) |
geographic |
Arctic Svalbard Longyearbyen |
geographic_facet |
Arctic Svalbard Longyearbyen |
genre |
Arctic Longyearbyen Svalbard |
genre_facet |
Arctic Longyearbyen Svalbard |
op_relation |
Beswick, K; Baumgardner, Darrel; Gallagher, Martin W; Volz-Thomas, A; Nedelec, P; Wang, K-Y; Lance, S (2014): The backscatter cloud probe – a compact low-profile autonomous optical spectrometer. Atmospheric Measurement Techniques, 7(5), 1443-1457, https://doi.org/10.5194/amt-7-1443-2014 Herber, Andreas; Borrmann, Stephan; Bozem, Heiko; Clemen, Hans-Christian; De La Torre Castro, Elena; Dupuy, Regis; Eppers, Oliver; Gourbeyre, Christophe; Grawe, Sarah; Hartmann, Jörg; Henning, Silvia; Hoor, Peter; Jourdan, Olivier; Jurányi, Zsófia; Lucke, Johannes; Lüpkes, Christof; Mayer, Johanna; Mertes, Stephan; Michaelis, Janosch; Mioche, Guillaume; Moser, Manuel; Schäfer, Jonas; Schneider, Johannes; Stratmann, Frank; Tatzelt, Christian; Tuch, Thomas; Voigt, Christiane; Wetzel, Bruno: Collection of data sources from the Polar 6 research aircraft for the HALO-(AC)³ field campaign, March/April 2022. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.968884 Lucke, Johannes; Jurkat, Tina; Baumgardner, Darrel; Kalinka, Frank; Moser, Manuel; De La Torre Castro, Elena; Voigt, Christiane (2023): Characterization of Atmospheric Icing Conditions during the HALO-(AC) 3 Campaign with the Nevzorov Probe and the Backscatter Cloud Probe with Polarization Detection. International Conference on Icing of Aircraft, Engines, and Structures, Technical Paper, 2023-01-1485, https://doi.org/10.4271/2023-01-1485 https://doi.pangaea.de/10.1594/PANGAEA.963614 https://doi.org/10.1594/PANGAEA.963614 |
op_rights |
CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1594/PANGAEA.96361410.5194/amt-7-1443-201410.4271/2023-01-1485 |
_version_ |
1802641878871441408 |
spelling |
ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.963614 2024-06-23T07:50:56+00:00 Backscatter Cloud Probe with Polarization Detection Lucke, Johannes Moser, Manuel De La Torre Castro, Elena Mayer, Johanna Voigt, Christiane MEDIAN LATITUDE: 78.239504 * MEDIAN LONGITUDE: 15.106434 * SOUTH-BOUND LATITUDE: 78.091476 * WEST-BOUND LONGITUDE: 6.004681 * NORTH-BOUND LATITUDE: 78.246003 * EAST-BOUND LONGITUDE: 15.503320 * DATE/TIME START: 2022-03-20T10:39:14 * DATE/TIME END: 2022-04-10T14:13:58 2023 text/tab-separated-values, 12 data points https://doi.pangaea.de/10.1594/PANGAEA.963614 https://doi.org/10.1594/PANGAEA.963614 en eng PANGAEA Beswick, K; Baumgardner, Darrel; Gallagher, Martin W; Volz-Thomas, A; Nedelec, P; Wang, K-Y; Lance, S (2014): The backscatter cloud probe – a compact low-profile autonomous optical spectrometer. Atmospheric Measurement Techniques, 7(5), 1443-1457, https://doi.org/10.5194/amt-7-1443-2014 Herber, Andreas; Borrmann, Stephan; Bozem, Heiko; Clemen, Hans-Christian; De La Torre Castro, Elena; Dupuy, Regis; Eppers, Oliver; Gourbeyre, Christophe; Grawe, Sarah; Hartmann, Jörg; Henning, Silvia; Hoor, Peter; Jourdan, Olivier; Jurányi, Zsófia; Lucke, Johannes; Lüpkes, Christof; Mayer, Johanna; Mertes, Stephan; Michaelis, Janosch; Mioche, Guillaume; Moser, Manuel; Schäfer, Jonas; Schneider, Johannes; Stratmann, Frank; Tatzelt, Christian; Tuch, Thomas; Voigt, Christiane; Wetzel, Bruno: Collection of data sources from the Polar 6 research aircraft for the HALO-(AC)³ field campaign, March/April 2022. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.968884 Lucke, Johannes; Jurkat, Tina; Baumgardner, Darrel; Kalinka, Frank; Moser, Manuel; De La Torre Castro, Elena; Voigt, Christiane (2023): Characterization of Atmospheric Icing Conditions during the HALO-(AC) 3 Campaign with the Nevzorov Probe and the Backscatter Cloud Probe with Polarization Detection. International Conference on Icing of Aircraft, Engines, and Structures, Technical Paper, 2023-01-1485, https://doi.org/10.4271/2023-01-1485 https://doi.pangaea.de/10.1594/PANGAEA.963614 https://doi.org/10.1594/PANGAEA.963614 CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess AC Aircraft Arctic Backscatter Cloud Probe with Polarization Detection BCPD Date/Time of event Event label HALO - (AC)3 HALO-(AC)³ HALO-AC3_20220320_P6_RF01 HALO-AC3_20220322_P6_RF02 HALO-AC3_20220326_P6_RF04 HALO-AC3_20220328_P6_RF05 HALO-AC3_20220329_P6_RF06 HALO-AC3_20220330_P6_RF07 HALO-AC3_20220401_P6_RF08 HALO-AC3_20220404_P6_RF09 HALO-AC3_20220405_P6_RF10 HALO-AC3_20220408_P6_RF11 HALO-AC3_20220409_P6_RF12 HALO-AC3_20220410_P6_RF13 mixed-phase clouds netCDF file netCDF file (File Size) P6_231_HALO_2022_2203200401 P6_231_HALO_2022_2203220501 P6_231_HALO_2022_2203260702 P6_231_HALO_2022_2203280801 P6_231_HALO_2022_2203290901 P6_231_HALO_2022_2203301001 P6_231_HALO_2022_2204011101 P6_231_HALO_2022_2204041201 P6_231_HALO_2022_2204051301 P6_231_HALO_2022_2204081401 P6_231_HALO_2022_2204091501 P6_231_HALO_2022_2204101601 P6-231_HALO_2022 Particle size distributions Phase differentiation POLAR 6 Polarimetric Radar Observations meet Atmospheric Modelling (PROM) - Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes SPP2115_PROM Svalbard Dataset 2023 ftpangaea https://doi.org/10.1594/PANGAEA.96361410.5194/amt-7-1443-201410.4271/2023-01-1485 2024-06-12T14:17:12Z This dataset contains the processed and raw data collected with the Backscatter Cloud Probe with Polarization Detection during the HALO-AC³ campaign in March and April 2022 with the Polar 6 Aircraft out of Longyearbyen, Svalbard. The dataset contains two kinds of data. Data to which no inversion procedure has been applied and data to which the inversion procedure has been applied. The inversion procedure is applied to account for an uneven intensity of the laser beam across the sample area and resulting undersizing effects. The inversion procedure has been discussed in Lucke et al. (2023) (doi.org/10.4271/2023-01-1485) and Beswick et al. (2014) (doi.org/10.5194/amt-7-1443-2014). All quantities which carry the suffix inv are based on the inverted data, all other properties are not. It should be noted, that the necessity of the inversion procedure remains unclear (see the previously mentioned publications). The inversion procedure could only be applied when more than 2000 particles were present over a 5 second interval. When this was not the case, the inverted data are 9999.999. The inverted data are therefore also computed from a 5s rolling average. The measurements of the BCPD are likely severely influenced by inertial separation effects, due to the proximity of the BCPD sample area to the fuselage (approx. 3cm). When ice particles are present, shattering occurs on the fuselage and artificially increases the ice number concentration. The number of ice and liquid particles listed in this data set can be useful for assessing the presence of ice and liquid particles. To estimate the number of liquid and ice particles more than 100 particles are required over a 5s interval. When this is not the case, the data are 9999.999. The number of ice and liquid particles were computed as rolling averages over 5s intervals. The sample area in case no inversion procedure is applied is 0.273 square millimeters. Dataset Arctic Longyearbyen Svalbard PANGAEA - Data Publisher for Earth & Environmental Science Arctic Svalbard Longyearbyen ENVELOPE(6.004681,15.503320,78.246003,78.091476) |