A high resolution wind&wave forecast model chain for the Mediterranean and Adriatic Sea

DHI (Danish Hydraulic Institute) and HyMOLab (Hydrodynamics and Met-Ocean Laboratory of the Dept. of Engineering and Architecture of the University of Trieste) have undertaken a joint applied research project with the aim to develop a state-of-art wind-wave forecast service at mid resolution for the Mediterranean Sea and at very high resolution for the Adriatic Sea. Weather routing, civil protection, coastal engineering, oil&gas and renewable energy fields, the planning of operations at sea, ... are just few among the multiple potential applications of this service. The meteorological model used in this study is WRF-ARW, one of the most widely used state-of-the-art open-source non-hydrostatic model. Global Forecast System (GFS) dataset provides the boundary and initial conditions. MIKE21-Spectral Waves is used as wave model with resolution ranging from 0.1 to 0.03 approximately. The use of a local area meteorological model guarantees higher levels of resolution and accuracy in an area such as the Mediterranean Sea where the complex orography and coastline induce short-time/small-space weather scales. The model chain runs daily (or twice a day on demand) on the High Performance Computing (HPC) infrastructure of HyMOLab. The validation of the entire model chain and specifically the forecast data obtained for the sea state is continuously updated according to new available data from satellites and buoys. Anyway, a major verification of the performance of the model chain against historic data (hindcast) is almost mandatory. For this aim, we performed a multi-decade test obtaining very good statistical parameters for the entire model chain performance. In this context the hindcast dataset developed by DHI and HyMOLab consists of 35 years of hourly data for the period 1979-2013, with the same model chain. The CFSR d093.0 hourly dataset with a spatial resolution of 0.5 provides the boundary and initial conditions. The atmospheric and wave models performance is checked against six satellite datasets, missions Envisat, ERS-2, Geosat FO, Jason-1, Jason-2, Topex-Poseidon, using a moving window technique procedure. Wave data close to coast are compared with available data from more than 20 buoys. The paper describes the validation procedure adopted for the hindcasted data. Furthermore the forecast service is described too, with specific emphasis to the very high resolution adopted in the Adriatic Sea

Analysis of wave heights in Vado Ligure: a comparison using wind data and buoy data

The goal of the paper is to analyze the wave heights in Vado Ligure \u2013 Ligurian Sea obtained using different approaches. The original data of buoy were provided by Savona\u2019s Harbour Authorities. The procedure proposed utilizes the wind data on the land to evaluate the height of characteristic sea waves for particular meteorological condition

Analysis of possible pollution scenarios of risk in Vado Ligure harbour,

The goal of the paper is to analyze the possible pollution scenarios of risk in Vado Ligure \u2013 Ligurian Sea using wave heights data obtained from a local buoy. The original data of buoy were provided by Savona\u2019s Harbor Authorities for this research. The examined area present an extension of approximately 10 hectares, and the principal maritime structures are quays and piers. The realization of a new multipurpose platform with a surface over the sea of 250.000 m2 implies that this is an area of interest for environmental analysis taking into account the increasing of trade of dangerous goods. The area was defined in a detailed bathymetry with a grid of 5mx5m. The wave heights were available only for a short period not significant to support a statistical approach but to describe a possible ordinary conditions of sea waves. The analysis was curried out using the software of Danish Hydraulic Institute MIKE21 that allows to model starting from the boundary conditions over the examined area the hydro dynamic sea conditions and knowing the characteristic of polluted elements to evaluate the impact along the shore and in whole area. To simulate the diffusion of the polluted elements we have proposed different approach used in literature assuming different conditions of wind and current to evaluate the extension of the possible pollution and the value of its concentration. The different results obtained are then compared among them to define the worst condition of waves and winds in case of accident. The final goal is the production of maps of different risk scenario

A state-of-the-art met-ocean model chain for wind&wave hindcast over the Mediterranean and Black Seas: Implementation, Tuning and Validation Against Field Data

This work is currently being carried out at the Met-Ocean Laboratory (MOLab) of the Dept. of Engineering and Architecture of the University of Trieste [1] and at Danish Hydraulic Institute-Italia (DHI) with the aim to develop and validate a state-of-the-art model chain for medium resolution (0.10\ub0 approximately) wind and wave hindcast simulations over the Mediterranean and Black Seas, consisting of 30 years long hourly data, ready to be used for engineering and environmental applications or even to be used as input for local nested higher resolution simulations (of order of few kilometers or less). The meteorological model used is WRF-ARW [2,3,4], (one of) the most widely used state-of-the-art open-source non-hydrostatic model. The CFSR d093.0 dataset [5,6], hourly data with a spatial resolution of 0.5\ub0, is used as boundary and initial conditions. WWIII [7] and MIKE21 [8] are used as wave models with resolution ranging from 0.1\ub0 to 0.03\ub0 approximately. The paper will show the results of the preliminary validation tests, both wind and wave, carried out over an entire year, comparing the data of several field stations

A novel application of and an adaptable modeling approach to the management of toxic microalgal bloom events in coastal areas.

Harmful algal blooms have been increasing in frequency in recent years, and attention has shifted from describing to modeling and trying to predict these phenomena, since in many cases they pose a risk to human health and coastal activities. Predicting ecological phenomena is often time and resource consuming, since a large number of field collected data are required. We propose a novel approach that involves the use of modeled meteorological data as input features to predict the concentration of the toxic benthic dinoflagellate Ostreopsis cf. ovata in seawater. Ten meteorological features were used to train a Quantile Random Forests model, which was then validated using field collected concentration data over the course of a summer sampling season. The proposed model was able to accurately describe Ostreopsis abundance in the water column in response to meteorological variables. Furthermore, the predictive power of this model appears good, as indicated by the validation results, especially when the quantile for predictions is tuned to match management requirements. The Quantile Random Forests method was selected, as it allows for greater flexibility in the generated predictions, thus making this model suitable as a tool for coastal management. The application of this approach is novel, as no other models or tools that are adaptable to this degree are currently available. The model presented here was developed for a single species over a limited geographical extension, but its methodological basis appears flexible enough to be applied to the prediction of HABs in general and it could also be extended to the case of other ecological phenomena that are strongly dependent on meteorological drivers, that can be independently modeled and potentially globally available

Drones as tools for monitoring beach topography changes in the Ligurian Sea (NW Mediterranean)

The aim of this study was to evaluate topographic changes along a stretch of coastline in the Municipality of Borghetto Santo Spirito (Region of Liguria, Italy, north-western Mediterranean) by means of a remotely piloted aircraft system coupled with structure from motion and multi-view stereo techniques. This sector was surveyed three times over 5 months in the fall–winter of 2013–2014 (1 November 2013, 4 December 2013, 17 March 2014) to obtain digital elevation models and orthophotos of the beach. Changes in beach topography associated with storm action and human activities were assessed in terms of gain/loss of sediments and shifting of the wet–dry boundary defining the shoreline. Between the first and second surveys, the study area was hit by two storms (10–11 November 2013 and 21–22 November 2013) with waves approaching from the E–NNE, causing a shoreline retreat which, in some sectors, reached 7 m. Between the second and third surveys, by contrast, four storms (25–27 December 2013, 5–6 January 2014, 17–18 January 2014 and 6–10 February 2014) with waves propagating from the SE produced a general advancement of the shoreline (up to ~5 m) by deposition of sediments along some parts of the beach. The data also reflect changes in beach topography due to human activity during the 2013 fall season, when private beach managers quarried ~178 m3 of sediments on the emerged beach near the shoreline to accumulate them landwards. The results show that drones can be used for regular beach monitoring activities, and that they can provide new insights into the processes related to natural and/or human-related topographic beach changes

Study of wave runup using numerical models and low-altitude aerial photogrammetry: A tool for coastal management

Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research