New insights on polar mesospheric cloud particle size distributions from a two-satellite common volume study
Journal article, 2021
The particle size distribution of Polar Mesospheric Clouds (PMC) is closely related to the fundamental processes of cloud formation and evolution. Still, despite substantial observational efforts, specific details about the particle size distribution have remained obscure. In this study, we aim at deriving more constraints on PMC size distributions by combining optical measurements from two satellite instruments observing a common PMC volume. We use a special set of 2D tomographic limb observations from the Optical Spectrograph and Infrared Imager System (OSIRIS) on the Odin satellite from 2010 to 2011 in the latitude range 78° N to 80° N and compare these to simultaneous PMC observations from the nadir-viewing Cloud Imaging and Particle Size (CIPS) instrument on the AIM satellite. A key goal is to find the assumption on the mathematical shape of the particle size distribution that should be applied to a vertically resolving limb-viewing instrument to reach consistent size results compared to the column-integrated ice distribution as seen by a nadir-viewing instrument. Our results demonstrate that viewing geometry and sampling volume of each instrument must be carefully considered and that the same size distribution assumption cannot simultaneously describe a column-integrated and a local height-resolved size distribution. In particular, applying the standard Gaussian assumption, used by many earlier PMC studies, to both limb and nadir observation leads to an overestimate of particle sizes seen by OSIRIS by about 10 nm as compared to CIPS. We show that the agreement can be improved if a Log-normal assumption with a broad distribution width around σ = 1.42 is adopted for OSIRIS. A reason for this broad distribution best describing the OSIRIS observations we suggest the large retrieval volume of the limb measurement. Gravity waves and other small-scale processes can cause horizontal variations and a co-existence of a wide range of particle populations in the sampling volume. Horizontal integration then leads to apparently much broader size distributions than encountered in a small horizontal sampling volume.
Polar mesospheric clouds
Remote sensing
Size distribution
Common volume study