The NCAR airborne 94-ghz cloud radar: Calibration and data processing
The 94-GHz airborne HIAPER Cloud Radar (HCR) has been deployed in three major field campaigns, sampling clouds over the Pacific between California and Hawaii (2015), over the cold waters of the Southern Ocean (2018), and characterizing tropical convection in the Western Caribbean and Pacific waters...
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ftncar:oai:drupal-site.org:articles_24495 2024-04-14T08:20:01+00:00 The NCAR airborne 94-ghz cloud radar: Calibration and data processing Romatschke, Ulrike (author) Dixon, Michael (author) Tsai, Peisang (author) Loew, Eric (author) Vivekanandan, Jothiram (author) Emmett, Jonathan (author) Rilling, Robert (author) 2021-06-19 https://doi.org/10.3390/data6060066 en eng Data--Data--2306-5729 OTREC: NCAR HCR radar moments data. Version 3.2--10.26023/V9DJ-7T9J-PE0S articles:24495 doi:10.3390/data6060066 ark:/85065/d7qj7mqp Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. article Text 2021 ftncar https://doi.org/10.3390/data6060066 2024-03-21T18:00:26Z The 94-GHz airborne HIAPER Cloud Radar (HCR) has been deployed in three major field campaigns, sampling clouds over the Pacific between California and Hawaii (2015), over the cold waters of the Southern Ocean (2018), and characterizing tropical convection in the Western Caribbean and Pacific waters off Panama and Costa Rica (2019). An extensive set of quality assurance and quality control procedures were developed and applied to all collected data. Engineering measurements yielded calibration characteristics for the antenna, reflector, and radome, which were applied during flight, to produce the radar moments in real-time. Temperature changes in the instrument during flight affect the receiver gains, leading to some bias. Post project, we estimate the temperature-induced gain errors and apply gain corrections to improve the quality of the data. The reflectivity calibration is monitored by comparing sea surface cross-section measurements against theoretically calculated model values. These comparisons indicate that the HCR is calibrated to within 1–2 dB of the theory. A radar echo classification algorithm was developed to identify “cloud echo” and distinguish it from artifacts. Model reanalysis data and digital terrain elevation data were interpolated to the time-range grid of the radar data, to provide an environmental reference. Article in Journal/Newspaper Southern Ocean OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) Southern Ocean Pacific Data 6 6 66 |
institution |
Open Polar |
collection |
OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) |
op_collection_id |
ftncar |
language |
English |
description |
The 94-GHz airborne HIAPER Cloud Radar (HCR) has been deployed in three major field campaigns, sampling clouds over the Pacific between California and Hawaii (2015), over the cold waters of the Southern Ocean (2018), and characterizing tropical convection in the Western Caribbean and Pacific waters off Panama and Costa Rica (2019). An extensive set of quality assurance and quality control procedures were developed and applied to all collected data. Engineering measurements yielded calibration characteristics for the antenna, reflector, and radome, which were applied during flight, to produce the radar moments in real-time. Temperature changes in the instrument during flight affect the receiver gains, leading to some bias. Post project, we estimate the temperature-induced gain errors and apply gain corrections to improve the quality of the data. The reflectivity calibration is monitored by comparing sea surface cross-section measurements against theoretically calculated model values. These comparisons indicate that the HCR is calibrated to within 1–2 dB of the theory. A radar echo classification algorithm was developed to identify “cloud echo” and distinguish it from artifacts. Model reanalysis data and digital terrain elevation data were interpolated to the time-range grid of the radar data, to provide an environmental reference. |
author2 |
Romatschke, Ulrike (author) Dixon, Michael (author) Tsai, Peisang (author) Loew, Eric (author) Vivekanandan, Jothiram (author) Emmett, Jonathan (author) Rilling, Robert (author) |
format |
Article in Journal/Newspaper |
title |
The NCAR airborne 94-ghz cloud radar: Calibration and data processing |
spellingShingle |
The NCAR airborne 94-ghz cloud radar: Calibration and data processing |
title_short |
The NCAR airborne 94-ghz cloud radar: Calibration and data processing |
title_full |
The NCAR airborne 94-ghz cloud radar: Calibration and data processing |
title_fullStr |
The NCAR airborne 94-ghz cloud radar: Calibration and data processing |
title_full_unstemmed |
The NCAR airborne 94-ghz cloud radar: Calibration and data processing |
title_sort |
ncar airborne 94-ghz cloud radar: calibration and data processing |
publishDate |
2021 |
url |
https://doi.org/10.3390/data6060066 |
geographic |
Southern Ocean Pacific |
geographic_facet |
Southern Ocean Pacific |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_relation |
Data--Data--2306-5729 OTREC: NCAR HCR radar moments data. Version 3.2--10.26023/V9DJ-7T9J-PE0S articles:24495 doi:10.3390/data6060066 ark:/85065/d7qj7mqp |
op_rights |
Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
op_doi |
https://doi.org/10.3390/data6060066 |
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6 |
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6 |
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66 |
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1796298197952364544 |