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

0Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

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).

Cite

CITATION STYLE

APA

Doulgeris, K. M., Kaikkonen, V., Juttula, H., Molkoselkä, E., Mäkynen, A., & Brus, D. (2025). In situ surface cloud measurement dataset from four cloud spectrometers during the Pallas Cloud Experiment (PaCE) 2022. Earth System Science Data, 17(11), 6497–6506. https://doi.org/10.5194/essd-17-6497-2025

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free