Abstract
This project was focused on the intercomparison of Compact Raman Lidar (CRL) to dropsonde data and regional weather model outputs. During the summer of 2022, the main objective of this research was to better understand tropical cyclone (TC) development and the capabilities of this new airborne instrumentation in the TC environment. To do so, I programmed different functions on Python to statistically compare collocated measurements of the thermodynamic data from the CRL profiles to individual dropsondes. The purpose of this analysis was to provide guidance and refine measurement strategies to understand and potentially improve the collection of CRL data in tropical cyclone environments. However, the CRL was shown to have a particularly high temperature and moisture bias when compared to dropsondes. Furthermore, the instrument tends to overcompensate the amount of moisture near the aircraft and the levels of temperature near the surface, leading to question the quality of measurements being taken and the usefulness of the statistical comparisons being done with the dropsondes. Nonetheless, additional evaluation of the CRL could prove to benefit the scientific community as it is useful in performing tasks in which few instruments are able.