The International Workshop on Wave Hindcasting and Forecasting and the Coastal Hazards Symposium

Following the 13th International Workshop on Wave Hindcasting and Forecasting and 4th Coastal Hazards Symposium in October 2013 in Banff, Canada, a topical collection has appeared in recent issues of Ocean Dynamics. Here we give a brief overview of the history of the conference since its inception in 1986 and of the progress made in the fields of wind-generated ocean waves and the modelling of coastal hazards before we summarize the main results of the papers that have appeared in the topical collection

Synoptic multi-variable multi-glider study

Analysis and report of sustained multi-glider deployments, providing detailed methodology of the deployment strategy, piloting, and calibration process. The analysis will deliver methods for the synoptic interpretation of all ocean variables over multiple timescales

Storm surge climatology report

Any increase in flood frequency or severity due to sea level rise or changes in storminess would adversely impact society. It is crucial to understand the physical drivers of extreme storm surges to have confidence in the datasets used for extreme sea level statistics. We will refine and improve methods to the estimation of extreme sea levels around Europe and more widely. We will do so by developing a comprehensive world picture of storm surge distribution (including extremes) for both tropical and extra-tropical cyclones. We will apply statistical methods to both tide gauge data and multi-decadal runs of numerical models. We will advance the development of a consistent global storm surge climatology, building on the work of the IOC/WMO JCOMM Expert Team for Waves and Coastal Hazards [D8.1] [NOC

Using remotely sensed data to modify wind forcing in operational storm surge forecasting

Storm surges are abnormal coastal sea level events caused by meteorological conditions such as tropical cyclones. They have the potential to cause widespread loss of life and financial damage and have done so on many occasions in the past. Accurate and timely forecasts are necessary to help mitigate the risks posed by these events. Operational forecasting models use discretisations of the governing equations for fluid flow to model the sea surface, which is then forced by surface stresses derived from a model wind and pressure fields. The wind fields are typically idealised and generated parametrically. In this study, wind field datasets derived from remotely sensed data are used to modify the model parametric wind forcing and investigate potential improvement to operational forecasting. We examine two methods for using analysis wind fields derived from remotely sensed observations of three hurricanes. Our first method simply replaces the parametric wind fields with its corresponding analysis wind field for a period of time. Our second method does this also but takes it further by attempting to use some of the information present in the analysis wind field to estimate future wind fields. We find that our methods do yield some forecast improvement, most notably for our second method where we get improvements of up to 0.29 m on average. Importantly, the spatial structure of the surge is changed in some places such that locations that were previously forecast small surges had their water levels increased. These results were validated by tide gauge data

Data assmilation tests using NISE10 Storm Surge Model

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Observations and modelling of the western Irish Sea gyre.

Observations from 1995 and 1996 described the seasonal evolution of the threedimensional density field in the western Irish Sea. A cold, dense pool flanked by strong nearbed density gradients was present from May until October. Temperature had the dominant effect on density from June onwards. The trajectories of 55 satellite-tracked drifters defmed the full spatial extent of the cyclonic circulation that is the western Irish Sea gyre. Several distinct recirculation paths were observed and drifter speeds were in good agreement with geostrophic calculations based on the observed density field. The existence of such organised, baroclinic flows in shelf seas demands that coastal ocean models should reproduce their dynamics correctly, if the models are to be useful as environmental management tools. One such model, ECOMsi, was applied to the study area and results from seasonal simulations were compared with the observations. A new technique was developed to perform quantitative comparisons between modelled and observed flow fields. The model successfully reproduced the three-dimensional temperature structure throughout the seasonal simulations, and also predicted the cyclonic, near-surface residual circulation of the gyre. The model demonstrated conclusively that the gyre is density-driven and revealed the same recirculation paths that were visible in the drifter tracks. The vertical structure of the modelled density-driven flow confirmed the geostrophic nature of the currents and emphasised the important dynamical role of sharp density gradients near the bed (bottom fronts). A quantitative comparison of different model runs identified the critical parameterisations and forcing quantities for this application. An accurate specification of air temperature over the sea region was required for the model to achieve the correct timing of the stratification breakdown. During this phase, convective cooling at the surface was seen to be as important as the mixing by autumnal winds in eroding the density structure. The possibility of a seasonal reversal in density-driven flow along the east coast of Ireland was also identified. A new interaction between the wind and the density field, which could defme where the strongest currents in the gyre are to be found, is described. The model is now considered to be sufficiently well tested to use in a predictive capacity and for biological transport studies. This work highlights the benefits that can be obtained using high quality spatial and temporal field observations in the critical testing of numerical models, and furthermore suggests that shelf seas are the perfect location for such tests to be performed

A reassessment of the UK operational surge forecasting procedure

This report is a summary of the Met Office surge forecasting procedure for the UK, and some investigations into possible sources of error. The forecast is based on the "non-tidal residual", the difference of two model runs with and without weather effects, linearly added to the "astronomical prediction" from local tide gauge harmonics. This method is exposed to several errors. Here we do not attempt to quantify errors in the model or weather forcing, but we show how errors can arise in the harmonic analysis and due to the double counting of weather-related tides. The executive summary, validation guidelines and recommendations have been prepared jointly with the Met Office

Uncertainty quantification of landslide generated waves using gaussian process emulation and variance-based sensitivity analysis

Simulations of landslide generated waves (LGWs) are prone to high levels of uncertainty. Here we present a probabilistic sensitivity analysis of an LGW model. The LGW model was realised through a smooth particle hydrodynamics (SPH) simulator, which is capable of modelling fluids with complex rheologies and includes flexible boundary conditions. This LGW model has parameters defining the landslide, including its rheology, that contribute to uncertainty in the simulated wave characteristics. Given the computational expense of this simulator, we made use of the extensive uncertainty quantification functionality of the Dakota toolkit to train a Gaussian process emulator (GPE) using a dataset derived from SPH simulations. Using the emulator we conducted a variance-based decomposition to quantify how much each input parameter to the SPH simulation contributed to the uncertainty in the simulated wave characteristics. Our results indicate that the landslide’s volume and initial submergence depth contribute the most to uncertainty in the wave characteristics, while the landslide rheological parameters have a much smaller influence. When estimated run-up is used as the indicator for LGW hazard, the slope angle of the shore being inundated is shown to be an additional influential parameter. This study facilitates probabilistic hazard analysis of LGWs, because it reveals which source characteristics contribute most to uncertainty in terms of how hazardous a wave will be, thereby allowing computational resources to be focused on better understanding that uncertainty