Simone Cosoli

Validation of surface current measurements in the Northern Adriatic Sea from High-Frequency radars

Abstract The performances of a shore-based high-frequency (HF) radar network deployed along the coast of the Venice lagoon (northern Adriatic Sea) are discussed based on a comparison with a single bottom-mounted ADCP deployed in the shallow-water area offshore of the lagoon for a 40-day period in August–September 2005. The analyses, carried out using currents representative of the first meter for the HF radars and 2.5 m for the ADCP, gave rms differences of radial currents in the range of 8.7–14.7 cm s−1 (correlation 0.37– 0.82) for the ideal pattern and 8.4–20.5 cm s−1 (correlation 0.14–0.84) for the measured pattern. Good correlation was found between surface current vectors and moored data (scalar correlation up to R = 0.83, vector correlation ρ = 0.78, veering angle 6°). Comparison metrics were improved for the low-passed currents. Angular offsets ranged between +6° and +11°. Differences depended primarily on the geophysical variability within the water column. Bearing offsets also contributed because...

Surface circulation in the Gulf of Trieste (northern Adriatic Sea) from radar, model, and ADCP comparisons

[1] High resolution high frequency (HF) radar observations of surface currents in the Gulf of Trieste (GoT) are presented and compared to moored subsurface current measurements and to high-resolution simulations from the Northern Adriatic Princeton Ocean Model (NAPOM) oceanographic model. Dominant circulation modes of the GoT were resolved and numerical model capabilities in reconstructing them were assessed. The time frame covers March 2011 through October 2012. NAPOM reconstructs the dominant surface circulation features observed by the radar, such as the general basin-wide cyclonic circulation scheme and the coastal jet outflowing the GoT, but is in general less energetic than radar currents. Comparisons between radar, ADCP, and model currents suggest that the model underestimates originate within the low-frequency, diurnal, semidiurnal, and inertial bands, and that both radar and model currents do not reproduce the diurnal tidal ellipse structure observed by the moored current meter. However, radar-model results for the semidiurnal tides are spatially consistent. Using empirical orthogonal function (EOF) decomposition, the coherent spatial scales and corresponding temporal scales were extracted. Findings suggest that HF radar current observations complement model simulations in regions of enhanced topographic variability where variance of model currents at the surface is distorted by the effects of the sigma layer grid. On the contrary, model results complement radar observations in areas with poor radar coverage, and furthermore provide spatial and temporal continuity of ocean state forecasts.

A Real-Time and Offline Quality Control Methodology for SeaSonde High-Frequency Radar Currents

AbstractA near-real-time and offline quality control methodology for SeaSonde systems is proposed. It is applied on radial current maps and is based on the determination of the signal-to-noise ratio (SNR) values of the Doppler lines that contribute to the hourly radial current at each range-bearing (R, θ) pair, under the assumption that SNR is a proxy for radar data quality. The retrieval of the sequence of Doppler lines is performed through a minimization procedure that takes advantage of the statistical descriptors output in the short-term radial maps. The separation of the contributing Doppler velocities into valid observations and anomalous velocities is based on their spectral quality factor and on a range-dependent noise threshold derived from statistics (average and standard deviation) of the signal amplitudes in the tails of the Doppler spectra. The final product of the quality control procedure is a radial current map, in which Doppler velocities are weighted by their SNR values and their spectra...

Self-Organizing Maps-based ocean currents forecasting system

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.

Sensitivity of Self-Organizing Map surface current patterns to the use of radial vs. Cartesian input vectors measured by high-frequency radars

In this paper, the Self-Organizing Map (SOM) method was applied to the surface currents data obtained between February and November 2008 by a network of high-frequency (HF) radars in the northern Adriatic. The sensitivity of the derived SOM solutions was tested in respect to the change of coordinate system of the data introduced to the SOM. In one experiment the original radial data measurements were used, and in the other experiment the Cartesian (total) current vectors derived from original radar data were analyzed. Although the computation of SOM solutions was not a demanding task, comparing both neural lattices yielded the nondeterministic polynomial time (NP) problem for which is difficult to propose a solution that will be globally optimal. Thus, we suggested utilizing the greedy algorithm with underlying assumption of 1-to-1 mapping between lattices. The results suggested that such solution could be local, but not global optimum and that the latter assumption could lower the obtained correlations between the patterns. However, without the assumption of 1-to-1 mapping between lattices, correlation between the derived SOM patterns was quite high, indicating that SOM mapping introduced to the radial current vectors and subsequent transformation into Cartesian coordinate system does not significantly affect obtained patterns in comparison to the SOM mapping done on the derived Cartesian current vectors. The documented similarity corroborates the use of total current vectors in various oceanographic studies, as being representative derivative of original radial measurements. We analyzed high-frequency radar data in the northern Adriatic.Self-Organizing Map method has been applied to radial and Cartesian current vectors.Transformation to Cartesian vectors do not significantly affect the SOM patterns.

Sensitivity of HF radar-derived surface current self-organizing maps to various processing procedures and mesoscale wind forcing

We performed a number of sensitivity experiments by applying a mapping technique, self-organizing maps (SOM) method, to the surface current data measured by high-frequency (HF) radars in the northern Adriatic and surface winds modelled by two state-of-the-art mesoscale meteorological models, the Aladin (Aire Limitée Adaptation Dynamique Développement InterNational) and the Weather and Research Forecasting models. Surface current data used for the SOM training were collected during a period in which radar coverage was the highest: between February and November 2008. Different pre-processing techniques, such as removal of tides and low-pass filtering, were applied to the data in order to test the sensitivity of characteristic patterns and the connectivity between different SOM solutions. Topographic error did not exceed 15 %, indicating the applicability of the SOM method to the data. The largest difference has been obtained when comparing SOM patterns originating from unprocessed and low-pass filtered data. Introduction of modelled winds in joint SOM analyses stabilized the solutions, while sensitivity to wind forcing coming from the two different meteorological models was found to be small. Such a low sensitivity is considered to be favourable for creation of an operational ocean forecasting system based on neural networks, HF radar measurements and numerical weather prediction mesoscale models.

Marine sediments remotely unveil long-term climatic variability over Northern Italy

A deep understanding of natural decadal variability is pivotal to discuss recently observed climate trends. Paleoclimate proxies allow reconstructing natural variations before the instrumental period. Typically, regional-scale reconstructions depend on factors like dating, multi-proxy weighting and calibration, which may lead to non-robust reconstructions. Riverine records inherently integrate information about regional climate variability, partly overcoming the above mentioned limitation. The Po River provides major freshwater input to Eastern Mediterranean, as its catchment encompasses a large part of Northern Italy. Here, using historical discharge data and oceanographic measurements, we show that Po River discharge undergo robust decadal fluctuations that reach the Ionian Sea, ~1,000 km South of Po River delta, through propagating salinity anomalies. Based on this propagation, we use a high-resolution foraminiferal δ18O record from a sediment core in the Ionian Sea to reconstruct North Italian hydrological variability on millennial-scale for the first time. The reconstruction reveals highly significant decadal variability that persists over the last 2,000 years. Many reconstructed extremes correspond to documented catastrophic events. Our study provides the first millennial-scale reconstruction of the strength of decadal hydrological variability over Northern Italy. It paves the way to assess the persistence of large-scale circulation fingerprints on the North Italian climate.

Downscaling hydrodynamics features to depict causes of major productivity of Sicilian-Maltese area and implications for resource management

Chlorophyll-a (CHL-a) and sea surface temperature (SST) are generally accepted as proxies for water quality. They can be easily retrieved in a quasi-near real time mode through satellite remote sensing and, as such, they provide an overview of the water quality on a synoptic scale in open waters. Their distributions evolve in space and time in response to local and remote forcing, such as winds and currents, which however have much finer temporal and spatial scales than those resolvable by satellites in spite of recent advances in satellite remote-sensing techniques. Satellite data are often characterized by a moderate temporal resolution to adequately catch the actual sub-grid physical processes. Conventional pointwise measurements can resolve high-frequency motions such as tides or high-frequency wind-driven currents, however they are inadequate to resolve their spatial variability over wide areas. We show in this paper that a combined use of near-surface currents, available through High-Frequency (HF) radars, and satellite data (e.g., TERRA and AQUA/MODIS), can properly resolve the main oceanographic features in both coastal and open-sea regions, particularly at the coastal boundaries where satellite imageries fail, and are complementary tools to interpret ocean productivity and resource management in the Sicily Channel.

The Effect of the Leeuwin Current on Offshore Surface Gravity Waves in Southwest Western Australia

The knowledge of regional wave regimes is critical for coastal zone planning, protection, and management. In this study, the influence of the offshore current regime on surface gravity waves on the southwest Western Australian (SWWA) continental shelf was examined. This was achieved by coupling the three dimensional, free surface, terrain-following hydrodynamic Regional Ocean Modelling System (ROMS) and the third generation wave model Simulating WAves Nearshore (SWAN) using the Coupled Ocean-Atmosphere-WaveSediment Transport (COAWST) model. Different representative states of the Leeuwin Current (LC), a strong pole-ward flowing boundary current with a persistent eddy field along the SWWA shelf edge were simulated and used to investigate their influence on different large wave events. The coupled wave-current simulations were compared to wave only simulations, which represented scenarios in the absence of a background current field. Results showed that the LC and the eddy field significantly impact SWWA waves. Significant wave heights increased (decreased) when currents were opposing (aligning with) the incoming wave directions. During a fully developed LC system significant wave heights were altered by up to ±25% and wave directions by up to ±20°. The change in wave direction indicates that the LC may modify nearshore wave dynamics and consequently alter sediment patterns. Operational regional wave forecasts and hindcasts may give flawed predictions if wave-current interaction is not properly accounted for.

Operational data management procedures for the Australian Coastal Ocean Radar Network

The Australian Coastal Ocean Radar Network measures current, wave and wind parameters from an array of HF radar systems. A network of CODAR and WERA radars have been operating in Australia since 2007. This paper describes some data quality issues identified using the phased-array systems and the techniques in development in order to mitigate these factors: the optimal spatiotemporal spectral averaging schemes are determined using comparisons with a wave buoy and improvements in the quality of radar wave data are found; issues encountered since moving to the new ITU oceanographic radar frequency bands are described; the quality control procedures that have been applied to radar surface currents are discussed.