In situ surface cloud measurement dataset from four cloud spectrometers during the Pallas Cloud Experiment (PaCE) 2022

Abstract. This data paper presents an overview of the cloud spectrometers deployed during the Pallas Cloud Experiment (PaCE) in autumn 2022, a coordinated measurement campaign in the Finnish subarctic that took place between 12 September and 15 December 2022. Four cloud spectrometers – the Cloud and Aerosol Spectrometer (CAS); the Forward Scattering Spectrometer Probe (FSSP-100); the Cloud Droplet Analyzer (CDA); and ICEMET – were operated as ground-based setups, providing high-resolution in-cloud measurements of droplet size distributions and key microphysical properties, such as number concentration (Nc), liquid water content (LWC), median volume diameter (MVD), and effective diameter (ED). The dataset is complemented by meteorological observations of temperature, humidity, wind speed, and visibility at a 1 min resolution. The measurements collected during PaCE 2022 offer valuable insights into aerosol–cloud interactions and cloud evolution in subarctic cloud systems. This dataset is suitable for researchers in cloud microphysics, atmospheric science, and climate modeling, as well as for instrument calibration and validation in future campaigns. The data can also be integrated with complementary concurrent in situ aerosol, remote sensing, UAV, and balloon-borne observations during PaCE 2022 to provide a more comprehensive understanding of cloud microphysics and atmospheric processes in the subarctic environment. The dataset is publicly available at https://doi.org/10.5281/zenodo.15045294 (Doulgeris et al., 2025).

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Publication Details

Journal
Earth system science data
Published
2025-11-26
DOI
https://doi.org/10.5194/essd-17-6497-2025
Primary Topic
Atmospheric aerosols and clouds
Type
article
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article

In situ surface cloud measurement dataset from four cloud spectrometers during the Pallas Cloud Experiment (PaCE) 2022

David Brus, Ville A. Kaikkonen, Anssi Mäkynen, Harri Juttula et al.
Earth system science data
Atmospheric aerosols and clouds
article

In situ surface cloud measurement dataset from four cloud spectrometers during the Pallas Cloud Experiment (PaCE) 2022

David Brus, Ville A. Kaikkonen, Anssi Mäkynen, Harri Juttula, Eero O. Molkoselkä, Konstantinos Doulgeris
article en

Abstract

Abstract. This data paper presents an overview of the cloud spectrometers deployed during the Pallas Cloud Experiment (PaCE) in autumn 2022, a coordinated measurement campaign in the Finnish subarctic that took place between 12 September and 15 December 2022. Four cloud spectrometers – the Cloud and Aerosol Spectrometer (CAS); the Forward Scattering Spectrometer Probe (FSSP-100); the Cloud Droplet Analyzer (CDA); and ICEMET – were operated as ground-based setups, providing high-resolution in-cloud measurements of droplet size distributions and key microphysical properties, such as number concentration (Nc), liquid water content (LWC), median volume diameter (MVD), and effective diameter (ED). The dataset is complemented by meteorological observations of temperature, humidity, wind speed, and visibility at a 1 min resolution. The measurements collected during PaCE 2022 offer valuable insights into aerosol–cloud interactions and cloud evolution in subarctic cloud systems. This dataset is suitable for researchers in cloud microphysics, atmospheric science, and climate modeling, as well as for instrument calibration and validation in future campaigns. The data can also be integrated with complementary concurrent in situ aerosol, remote sensing, UAV, and balloon-borne observations during PaCE 2022 to provide a more comprehensive understanding of cloud microphysics and atmospheric processes in the subarctic environment. The dataset is publicly available at https://doi.org/10.5281/zenodo.15045294 (Doulgeris et al., 2025).

Earth system science dataVol. 17(11)
Finnish Meteorological Institute (FI), Kajaani University of Applied Sciences (FI), University of Oulu (FI)
Openalex Percentile: Top 66%
Atmospheric aerosols and clouds
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