The Baltic Sea is a shallow, stratified, brackish water sea with several
subbasins. In this work, we analyzed CTD casts from HELCOM monitoring
data of the Baltic Sea, data from FMI's glider missions in 2016 and 2017
and profiles from FMI's Argo floats. We used clustering and machine
learning algorithms developed for time series analysis to classify
vertical profiles. We endeavored to classify profiles into classes with
similar shapes. Then, we defined whether it was possible to define the
depth of the upper mixed layer and possible halocline depth in each of
these classes. Our results show that time series classification
algorithm can cluster vertical profiles of CTD temperature and salinity
and classify them according to sea area and season.