Development of PSC detection tools using IRF lidar data

• Main Author: Peláez Mercadal, Oriol
• Format: Bachelor Thesis
• Language: English
• Published: Luleå tekniska universitet, Institutionen för system- och rymdteknik 2020
• Subjects: atmospheric science; polar stratospheric clouds; lidar; data analysis; Earth and Related Environmental Sciences; Geovetenskap och miljövetenskap; Meteorology and Atmospheric Sciences; Meteorologi och atmosfärforskning; Kiruna; Northern Sweden
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-77953

Polar stratospheric clouds (PSCs) play a crucial role in ozone depletion mechanisms. Thus, their observations are important to understand their formation processes and active effects towards the atmosphere. The Swedish Institute of Space Physics (IRF) operates a lidar in their facilities in Kiruna, northern Sweden, in order to retrieve data from the atmosphere. A lidar, acronym of Light Detection and Ranging, is a device capable of obtaining atmospheric profiles of backscattering or extinction. It consists of a laser that is emitted up to the atmosphere with a specific polarisation. The gases and particles in the atmosphere bacskcatter the electromagnetic radiation of the light in different ways determined by their own properties. The backscattered radiation is collected by a telescope and stored, depending on the way it has been backscattered, by a series of filters and optical devices. The data gathered with the lidar can be used to analyse atmospheric profiles in order to find cloud data. Later, this data can be evaluated and processed in such a way that a classification can be done. Since there are multiple types of PSCs that exist, it is important to differentiate them considering each type has diverse properties and effects. This thesis provides tools developed with MATLAB code so clouds signals can be detected using an example data set, corresponding to one day. After detection, a methodology is applied so derived parameters can be obtained. These parameters will be used to compare the results with threshold values, useful for later classification. Classifying PSCs by type is convenient to understand their formation processes in a better way. It is also significant to observe the effect of every PSC type towards the local and global climatology. However, a deeper climatology study should be done after applying these processes to several data sets, so one day is not enough to derive a whole climate study. Alongside with the results, future work on the direction of this research is proposed in order to ...