Cloud micro- and macrophysical properties from ground-based remote sensing during the MOSAiC drift experiment

Area of Science:

• Atmospheric Science
• Arctic Climate Research
• Remote Sensing

Background:

• The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provided a unique platform for year-round Arctic observations.
• Understanding Arctic clouds is crucial due to their significant role in climate regulation.

Purpose of the Study:

• To establish a comprehensive dataset of cloud and aerosol properties using shipborne instrumentation during the MOSAiC expedition.
• To combine data from multiple instruments for a holistic view of cloud characteristics.

Main Methods:

• Operation of the shipborne OCEANET-Atmosphere facility, including a multiwavelength Raman lidar, microwave radiometer, and optical disdrometer.
• Integration of data from a US Atmospheric Radiation Measurement program cloud radar.
• Application of the Cloudnet methodology for processing and deriving cloud properties.
• Utilizing lidar-based low-level stratus retrieval for enhanced cloud detection.

Main Results:

• Generation of a year-round dataset of Arctic cloud properties with high spatiotemporal resolution (30s, 30m).
• Derivation of cloud properties including target classification, and liquid and ice microphysical properties.
• Combined lidar and cloud radar data provide comprehensive low- and high-altitude cloud observations.

Conclusions:

• The presented dataset offers valuable resources for research on Arctic cloud formation processes.
• The data can be used to investigate the radiative impact of clouds.
• This dataset is suitable for evaluating atmospheric model performance in the Arctic region.