Data Assimilation within the Advanced Circulation (ADCIRC) Modeling Framework for Hurricane Storm Surge Forecasting

Abstract

Accurate, real-time forecasting of coastal inundation due to hurricanes and tropical storms is a challenging computational problem requiring high-fidelity forward models of currents and water levels driven by hurricane-force winds. Despite best efforts in computational modeling there will always be uncertainty in storm surge forecasts. In recent years, there has been significant instrumentation located along the coastal United States for the purpose of collecting data-specifically wind, water levels, and wave heights-during these extreme events. This type of data, if available in real time, could be used in a data assimilation framework to improve hurricane storm surge forecasts. In this paper a data assimilation methodology for storm surge forecasting based on the use of ensemble Kalman filters and the advanced circulation (ADCIRC) storm surge model is described. The singular evolutive interpolated Kalman (SEIK) filter has been shown to be effective at producing accurate results for ocean models using small ensemble sizes initialized by an empirical orthogonal function analysis. The SEIK filter is applied to the ADCIRC model to improve storm surge forecasting, particularly in capturing maximum water levels (high water marks) and the timing of the surge. Two test cases of data obtained from hindcast studies of Hurricanes Ike and Katrina are presented. It is shown that a modified SEIK filter with an inflation factor improves the accuracy of coarse-resolution forecasts of storm surge resulting from hurricanes. Furthermore, the SEIK filter requires only modest computational resources to obtain more accurate forecasts of storm surge in a constrained time window where forecasters must interact with emergency responders.

Meso-scale Simulation of Typhoon Generated Storm Surge: Methodology and Shanghai Case Study

“…Unlike most past studies, a meso-scale study not only meets the spatial requirements of numerical models, but also does not require much cost for computation. Previous studies on the storm surge were usually conducted at national or local levels (Dietrich et al, 2011a;Butler et al, 2012). In China, most of these studies tended to emphasize the significance of numerical modelling of storm surge and risk analysis either for the 25 coastline on a large spatial scale (>100 km in length) (Zheng, 2010;Tan et al, 2011;Yin, 2011) or for the small scale coastal area (1 -1000m in length) with fine resolution simulation (Zhang et al, 2006;Xie, 2010;Xie et al, 2010;Ye, 2011).…”

“…Fritz et al (2010) simulated the storm surge occurring in the Arabian Sea with a spatial resolution range of 1 -80 km. Due to the high risk of storm surge, there were also many studies conducted in Louisiana, USA (Westerink et al, 2008;Wamsley et al, 2009;Sheng et al, 2010;Butler et al, 2012) and the 20 Gulf of Mexico area (Dietrich et al, 2011a;Dietrich et al, 2011b;Dietrich et al, 2012). Cheung et al (2003) also analysed the emergency plan for Hawaii based on storm surge simulations.…”

A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

“…In all the experiments, we set the standard deviation of the measurement noise of the hindcast data to produce an assumed 95% confidence interval of 60.01 m, as in Butler et al (2012). It should be noted that we expect that there can be large errors in absolute terms between the coarse model forecasts and the hindcast study due to the dissipation of water elevations across large elements.…”

“…There is also the ensemble adjustment Kalman filter (EAKF; see, e.g., , which was developed under the umbrella of the Data Assimilation Research Testbed (DART) at the National Center for Atmospheric Research (NCAR). Many other ensemble-based Kalman filters have been developed using similar strategies, for example, Cohn and Todling (1996), Verlaan and Heemink (1997), Zupanski (2005), Beezley and Mandel (2008), Luo and Moroz (2009), and Luo and Hoteit (2012 to name but a few.…”

“…Specific to storm surge modeling resulting from hurricanes, the SEIK filter was recently applied to the shortrange forecasting problem using the extensively validated ADCIRC model (Butler et al 2012;Altaf et al 2013). This particular problem exhibits unique fast-evolving dynamics.…”