Development of a Dynamic Linear Model Procedure for Quantifying Long-term Trends in Atmospheric Time Series
With satellite remote sensing instruments, global data records of various atmospheric species, spanning considerable periods of time, have been produced. These data provide insight into atmospheric processes and the evolution of our atmosphere. Statistical analysis on them is essential. One thing in particular that we often wish to know about is the long-term trend in a species concentration on the order of decades. This is important because it allows us to monitor changes in our atmosphere. Changes that can be traced back to human activity, giving us feedback on how we are affecting the atmosphere, or changes from natural phenomena, such as volcanic eruptions. In this thesis, a statistical procedure is developed for modelling atmospheric remote sensing data records, with particular emphasis placed on the ability to extract accurate and informative information about the long-term trend. Procedures operating on the same principals have been used in the past for time series analysis in general. For example, on economic time series, as well as on atmospheric remote sensing data records, or just any atmospheric data. In this thesis, we show the theory behind the procedure in detail as well as describe how to implement and use it in practice. This is done with the intent of making the rather complicated procedure more accessible so that it can become more adopted by scientists working with atmospheric remote sensing data if desired, and compared to current methods for obtaining long-term trends. For an example application of this procedure, we apply it to a stratospheric ozone data record that extends from 1984 to present (2019). Ozone is a species that is of considerable interest since we know without a doubt that the changing chlorine situation in the atmosphere due to human activity has a significant effect on it, and because of its importance in absorbing ultraviolet radiation, which can seriously harm life on the Earth. The results we give paint a detailed picture of the long-term trends in stratospheric ozone concentration in the 65ºS to 65ºN latitude region.
Dynamic, Linear, Model, Atmosphere, Time, Series, Trends, Ozone
Master of Science (M.Sc.)
Physics and Engineering Physics