During this period, over one third of all papers published in these journals concerned time series forecasting. We also review highly influential works on time series forecasting that have been published elsewhere during this period. Enormous progress has been made in many areas, but we find that there are a large number of topics in need of further development. We conclude with comments on possible future research directions in this field.

Hydrological extremes in coastal areas in the Netherlands often result from a combination of anomalous (but not necessarily extreme) conditions: storm surges preventing the ability to discharge water to the open sea, and local precipitation generating excessive water levels in the inland area. A near-flooding event in January 2012 occurred due to such a combination of (mild) extreme weather conditions, by which free discharge of excessive water was not possible for five consecutive tidal periods. An ensemble of regional climate model simulations (covering 800 years of simulation data for current climate conditions) is used to demonstrate that the combined occurrence of the heavy precipitation and storm surge in this area is physically related. Joint probability distributions of the events are generated from the model ensemble, and compared to distributions of randomized variables, removing the potential correlation. A clear difference is seen. An inland water model is linked to the meteorological simulations, to analyze the statistics of extreme water levels and its relationship to the driving forces. The role of the correlation between storm surge and heavy precipitation increases with inland water level up to a certain value, but its role decreases at the higher water levels when tidal characteristics become increasingly important. The case study illustrates the types of analyzes needed to assess the impact of compounding events, and shows the importance of coupling a realistic impact model (expressing the inland water level) for deriving useful statistics from the model simulations.

AIC, dynamic factor analysis, Kalman filter, Markovian state-space model, nonstationarity, SBIC,

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