Algorithmic recognition of anomalous time intervals in sea-level observations

Аннотация

The problem of the algorithmic recognition of anomalous time intervals in the time series of the sea-level observations conducted by the Russian Tsunami Warning Survey (RTWS) is considered. The normal and anomalous sea-level observations are described. The polyharmonic models describing the sea-level fluctuations on the short time intervals are constructed, and sea-level forecasting based on these models is suggested. The algorithm for the recognition of anomalous time intervals is developed and its work is tested on the real RTWS data.