Verification of WAQUA/DCSMv5’s operational water level probability forecasts
toon extra info.
|Utrecht [etc.] : Universiteit Utrecht [etc.]|
|Toelichting (Engels)||Rising sea levels due to climate change pose a serious threat to countries where much of the economic activity is close to the coast or below sea level. In the Netherlands, most political and economical centres are situated in low-lying areas. Accurate storm surge forecasts are of paramount importance, as extreme high waters are expected due to rising meas sea levels as a result of climate change. In fact, forecasts up to 2 days ahead serve as guidance for local authorities and for optimal management of the storm surge barriers. In addition, forecasts up to 10 days ahead are beneficial for the preparation for severe storm surge events. Recently, there has been a growing demand from the forecasts end-users for uncertainty information and the extension of the forecast horizon. To fulfill this demand, the Integrated Forecasting System (IFS), developed by the European Centre for Medium range Weather Forecasts (ECMWF), has been used to generate storm surge probability forecasts. These storm surge forecasts with input from ECMWF-IFS runs for 10 years already, which opens the possibility for forecast verification and robust statistics. As a result, this research performed a verification study to quantify the quality of these issued storm surge probability forecasts for three locations along the Dutch coast. In general, the forecasts with positive surges were of good quality with Brier skill scores > 0.5 for lead-times < 48h and Brier skill scores > 0.4 for lead-times between 48h and 84h. This holds true for all three locations. Furthermore, forecasts are skillful till 5-7 days ahead. In addition, winter forecasts are more skillful than summer forecasts and high-tide forecasts have higher skill than low-tide forecasts. Next to this, this research proved that the current bias correction and calibration applied to the forecasts is not suitable and sub-optimal. In fact, the yearly ensemble’s bias with respect to the observations needs to be considered as a dynamic variable instead of a static one. Therefore, the revision of both the bias correction and the calibration should be considered in the future to improve forecast quality.|
Koninklijk Nederlands Meteorologisch Instituut (KNMI)