Application of cloud particle sensor sondes for estimating the number concentration of cloud water droplets and liquid water content: case studies in the Arctic region

• Published in: Atmospheric Measurement Techniques
• Main Authors: J. Inoue, Y. Tobo, K. Sato, F. Taketani, M. Maturilli
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2021
• Subjects: Environmental engineering; TA170-171; Earthwork. Foundations; TA715-787; Arctic; Arctic Ocean; Svalbard; Ny-Ålesund; Norway; Ny Ålesund
• Online Access: https://doi.org/10.5194/amt-14-4971-2021; https://doaj.org/article/17bbb6e1e5db4cba94fc4785920dbb48

A cloud particle sensor (CPS) sonde is an observing system attached with a radiosonde sensor to observe the vertical structure of cloud properties. The signals obtained from CPS sondes are related to the phase, size, and number of cloud particles. The system offers economic advantages including human resource and simple operation costs compared with aircraft measurements and land-/satellite-based remote sensing. However, the observed information should be appropriately corrected because of several uncertainties. Here we made field experiments in the Arctic region by launching approximately 40 CPS sondes between 2018 and 2020. Using these data sets, a better practical correction method was proposed to exclude unreliable data, estimate the effective cloud water droplet radius, and determine a correction factor for the total cloud particle count. We apply this method to data obtained in October 2019 over the Arctic Ocean and March 2020 at Ny-Ålesund, Svalbard, Norway, to compare with a particle counter aboard a tethered balloon and liquid water content retrieved by a microwave radiometer. The estimated total particle count and liquid water content from the CPS sondes generally agree with those data. Although further development and validation of CPS sondes based on dedicated laboratory experiments would be required, the practical correction approach proposed here would offer better advantages in retrieving quantitative information on the vertical distribution of cloud microphysics under the condition of a lower number concentration.