the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Remote sensing measurements during PaCE 2022 campaign
Abstract. Continuous ground-based remote sensing measurements were conducted during the Pallas Cloud Experiment (PaCE) 2022 campaign. Remote sensing instruments, including two ceilometers (models CL31 and CL61, Vaisala Oyj), a Doppler cloud radar (model RPG-FMCW-94, RPG Radiometer Physics GmbH), and a Doppler wind lidar (model StreamLine XR, HALO Photonics), were deployed at Kenttärova, Finland, a measurement station that is part of the Pallas Atmosphere–Ecosystem Supersite. The instruments operated continuously throughout the entire campaign, with the exception of a few technical interruptions and brief maintenance periods. The PaCE 2022 remote sensing measurements provided vertical profiles of atmospheric targets with high temporal and vertical resolution, extending from the ground up to an altitude of 10–15 km depending on instrument. By combining the data from these instruments and a numerical weather prediction model, cloud micro- and macrophysical properties—such as ice water content, ice effective radius, and target classification—were retrieved using the Cloudnet methodology. The processed remote sensing data set complements the PaCE in situ measurements, providing valuable validation opportunities. The data set is available on the Cloudnet data portal at https://doi.org/10.60656/b3460d9d88d14fe6 (O’Connor and Hyvärinen, 2024).
- Preprint
(4327 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 06 Apr 2025)
-
RC1: 'Comment on essd-2024-605', Anonymous Referee #1, 25 Mar 2025
reply
Review of “Remote sensing measurements during PaCE 2022 campaign”
General comment: This study presents cloud remote sensing measurements and derived micro- and macrophysically properties from the PaCE 2022 campaign at the Kenttärova site in Finland. The manuscript is well-structured and clearly written and the dataset and software tools are available via open access.
These measurements provide a valuable contribution to the long-term atmospheric observation efforts within ACTRIS and the dataset is relevant for model evaluation and satellite validation efforts. The methodological implementation of the data collection, including multiple remote sensing instruments and the use of CloudnetPy processing and quality checks, ensures that the dataset is comprehensive and of high scientific value.
I recommend the manuscript for publication after minor comments have been addressed.
Minor comments:
Overall, I think, the presentation of the data set could benefit from validation and comparison to other measurements, e.g., collected during previous campaigns. This could help the user, for example, to assess the liquid water path retrieved by the cloud radar, as the standard Cloudnet instrumentation for this quantity is a microwave radiometer.
Also, an illustration of the VOODOO results would be helpful. The issue of missing liquid layers due to lidar attenuation is well known and VOODOO provides a valuable approach for the situations. Due to its still experimental stage, it would be good, to show and discuss the results of this method, for users inexperienced with VOODOO.
Specific comments:
Line 67: Change the sentence “...up to a height of 15 km height” to “...up to a height of 15 km” to avoid repetition.
Line 73: “attenuated backscatter cofficient” should be corrected to “attenuated backscatter coefficient.”
Line 163: Add a comma bevor “and higher-level derived synergetic geophysical products.”
Line 182: Change “according the FAIR principles” to “according to the FAIR principles.”
Citation: https://doi.org/10.5194/essd-2024-605-RC1
Data sets
Custom collection of categorize, categorize (Voodoo), classification, classification (Voodoo), Doppler lidar, and 12 other products from Kenttärova between 12 Sep and 15 Dec 2022 E. O'Connor and A. Hyvärinen https://doi.org/10.60656/b3460d9d88d14fe6
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
149 | 16 | 5 | 170 | 7 | 7 |
- HTML: 149
- PDF: 16
- XML: 5
- Total: 170
- BibTeX: 7
- EndNote: 7
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1