  Depleting lake ice is a climate change indicator, just like sea-level rise or
glacial retreat. Monitoring Lake Ice Phenology (LIP) is useful because
long-term freezing and thawing patterns serve as sentinels to understand
regional and global climate change. We report a study for the Oberengadin
region of Switzerland, where several small- and medium-sized mountain lakes are
located. We observe the LIP events, such as freeze-up, break-up and ice cover
duration, across two decades (2000-2020) from optical satellite images. We
analyse the time series of MODIS imagery by estimating spatially resolved maps
of lake ice for these Alpine lakes with supervised machine learning. To train
the classifier we rely on reference data annotated manually based on webcam
images. From the ice maps, we derive long-term LIP trends. Since the webcam
data are only available for two winters, we cross-check our results against the
operational MODIS and VIIRS snow products. We find a change in complete freeze
duration of -0.76 and -0.89 days per annum for lakes Sils and Silvaplana,
respectively. Furthermore, we observe plausible correlations of the LIP trends
with climate data measured at nearby meteorological stations. We notice that
mean winter air temperature has a negative correlation with the freeze duration
and break-up events and a positive correlation with the freeze-up events.
Additionally, we observe a strong negative correlation of sunshine during the
winter months with the freeze duration and break-up events.
