Towards a Climatology of Polar Stratospheric Cloudsbased on observation with the IRF lidar

• Main Author: Willbrink, Oliver
• Format: Bachelor Thesis
• Language: English
• Published: Luleå tekniska universitet, Rymdteknik 2021
• Subjects: Meteorology and Atmospheric Sciences; Meteorologi och atmosfärforskning; Kiruna; Northern Sweden
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-88433

The effect that the Polar stratospheric clouds (PSCs) have on the destruction of ozone in the polar vortex is well known. The study of these clouds is therefore highly relevant and important. A tool that can be used to gather parameters needed to describe the PSC is a lidar (Light Detection and Ranging). The Swedish Institute of Space Physics (IRF) uses such a lidar to observe PSCs above Kiruna in northern Sweden. The lidar works by emitting polarised light and then collecting the scattered light. Knowing the time between when the light was emitted and the backscattered light was collected one can then determine at which altitude the scattering happened. The time and the backscattered light can then be used to derive the useful parameters needed to create a climatology of the PSCs. When creating a climatology, the different types of PSCs (type Ia, Ib and II) have to be classified. Each of the different types is classified by looking at the PSCs parallel and perpendicular backscatter ratio as well as the depolarisation ratio. The classification can then be used to understand the formation and composition of the cloud. To process the data gathered from the lidar a script in MATLAB is developed. The script is automatically going through the data and pinpointing the boundaries and interpolate the data, then using this to calculate the backscatter and depolarisation ratio. The script runs for all the available IRF observations between 2008 and 2018. The ratios and boundaries calculated from all the observations are then used to create a climatology. Comparing the climatology to the climatology by Blum et. al \cite{Psct} shows similar results. Future work should be done on the MATLAB program to inprove finding parameters from observation where the data includes more noise than the program can currently handle. This enables the retrieval of more trusty parameters and a more precise climatology.