Temporal variations of zooplankton biomass in the Ligurian Sea inferred from long time series of ADCP data

Abstract. Three years of 300 kHz acoustic doppler current profiler data collected in the central Ligurian Sea are analysed to investigate the variability of the zooplankton biomass and the diel vertical migration in the upper thermocline. After a pre-processing phase aimed at avoiding the slant range attenuation, hourly volume backscattering strength time series are obtained. Despite the lack of concurrent net samples collection, different migration patterns are identified and their temporal variability examined by means of time–frequency analysis. The effect of changes in the environmental condition is also investigated. The highest zooplankton biomasses are observed in April–May just after the peak of surface primary production in March–April. The main migration pattern found here points to a "nocturnal" migration, with zooplankton organisms occurring deeper in the water column during the day and shallower at night. Also, twilight migration is highlighted during this study. The largest migrations are recorded in November–December, corresponding to lowest backscattering strength values and they are likely attributable to larger and more active organisms (i.e. euphausiids and mesopelagic fish). The results suggest further applications of the available historical acoustic doppler current profiler time series

Upper layer current variability in the Central Ligurian Sea

Abstract. Long-time series of surface currents and meteorological parameters were analysed to estimate the variability of the upper layer circulation and the response to the local winds. Current meter data were collected by an upward-looking RDI Sentinel 300 kHz ADCP deployed in the Central Ligurian Sea (43°47.77' N; 9°02.85' E) near the meteo-oceanographic buoy ODAS Italia 1 for more than eight months, from 13th of September 2003 to 24th of May 2004. The ADCP sampled the upper 50 m of water column at 8 m vertical resolution and 1 h time interval; surface marine and atmospheric hourly averaged data were provided by the buoy. Currents in the sampled layer were mainly barotropic, directed North-West in accordance with the general circulation of the area, and had a mean velocity of about 18 cm/s and hourly mean peaks up to 80 cm/s. Most of the observed variability in the upper thermocline was determined by inertial currents and mesoscale activity due to the presence of the Ligurian Front. Local wind had a minor role in the near-surface circulation but induced internal waves propagating downward in the water column

Introducing temporal correlation in rainfall and wind prediction from underwater noise

While in the past the prediction of wind and rainfall from underwater noise was performed using empirical equations fed with very few spectral bins and fitted to the data, it has recently been shown that regression performed using supervised machine learning techniques can benefit from the simultaneous use of all spectral bins, at the cost of increased complexity. However, both empirical equations and machine learning regressors perform the prediction using only the acoustic information collected at the time when one wants to know the wind speed or the rainfall intensity. At most, averages are made between spectra measured at subsequent times (spectral compounding) or between predictions obtained at subsequent times (prediction compounding). In this article, it is proposed to exploit the temporal correlation inherent in the phenomena being predicted, as has already been done in methods that forecast wind and rainfall from their values (and sometimes those of other meteorological quantities) in the recent past. A special architecture of recurrent neural networks, the long shortterm memory, is used along with a data set composed of about 16 months of underwater noise measurements (acquired every 10 min, simultaneously with wind and rain measurements above the sea surface) to demonstrate that the introduction of temporal correlation brings significant advantages, improving the accuracy and reducing the problems met in the widely adopted memoryless prediction performed by random forest regression. Working with samples acquired at 10-min intervals, the best performance is obtained by including three noise spectra for wind prediction and six spectra for rainfall prediction

Mediterranean Forecasting System: forecast and analysis assessment through skill scores

Abstract. This paper describes the first evaluation of the quality of the forecast and analyses produced at the basin scale by the Mediterranean ocean Forecasting System (MFS) (http://gnoo.bo.ingv.it/mfs). The system produces short-term ocean forecasts for the following ten days. Analyses are produced weekly using a daily assimilation cycle. The analyses are compared with independent data from buoys, where available, and with the assimilated data before the data are inserted. In this work we have considered 53 ten days forecasts produced from 16 August 2005 to 15 August 2006. The forecast skill is evaluated by means of root mean square error (rmse) differences, bias and anomaly correlations at different depths for temperature and salinity, computing differences between forecast and analysis, analysis and persistence and forecast and persistence. The Skill Score (SS) is defined as the ratio of the rmse of the difference between analysis and forecast and the rmse of the difference between analysis and persistence. The SS shows that at 5 and 30 m the forecast is always better than the persistence, but at 300 m it can be worse than persistence for the first days of the forecast. This result may be related to flow adjustments introduced by the data assimilation scheme. The monthly variability of SS shows that when the system variability is high, the values of SS are higher, therefore the forecast has higher skill than persistence. We give evidence that the error growth in the surface layers is controlled by the atmospheric forcing inaccuracies, while at depth the forecast error can be interpreted as due to the data insertion procedure. The data, both in situ and satellite, are not homogeneously distributed in the basin; therefore, the quality of the analyses may be different in different areas of the basin

Mediterranean Forecasting System: forecast and analysis assessment through skill scores

This paper describes the first evaluation of the quality of the forecast and analyses produced at the basin scale by the Mediterranean ocean Forecasting System (MFS) (http://gnoo.bo.ingv.it/mfs). The system produces short-term ocean forecasts for the following ten days. Analyses are produced weekly using a daily assimilation cycle. The analyses are compared with independent data from buoys, where available, and with the assimilated data before the data are inserted. In this work we have considered 53 ten days forecasts produced from 16 August 2005 to 15 August 2006. The forecast skill is evaluated by means of root mean square error (rmse) differences, bias and anomaly correlations at different depths for temperature and salinity, computing differences between forecast and analysis, analysis and persistence and forecast and persistence. The Skill Score (SS) is defined as the ratio of the rmse of the difference between analysis and forecast and the rmse of the difference between analysis and persistence. The SS shows that at 5 and 30m the forecast is always better than the persistence, but at 300m it can be worse than persistence for the first days of the forecast. This result may be related to flow adjustments introduced by the data assimilation scheme. The monthly variability of SS shows that when the system variability is high, the values of SS are higher, therefore the forecast has higher skill than persistence. We give evidence that the error growth in the surface layers is controlled by the atmospheric forcing inaccuracies, while at depth the forecast error can be interpreted as due to the data insertion procedure. The data, both in situ and satellite, are not homogeneously distributed in the basin; therefore, the quality of the analyses may be different in different areas of the basin

Operational evaluation of the Mediterranean Monitoring and Forecasting Centre products: implementation and results

A web-based validation platform has been developed at the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for the Near Real Time validation of the MyOcean-Mediterranean Monitoring and Forecasting Centre products (Med-MFC). A network for the collection of the in-situ observations, the nested sub-basin forecasting systems model data (provided by the partners of the Mediterranean Operational Oceanography Network, MOON) and the Sea Surface Temperature (SST) satellite data has been developed and is updated every day with the new available data. The network collects temperature, salinity, currents and sea level data. The validation of the biogeochemical forecast products is done by use of ocean colour satellite data produced for the Mediterranean Sea. All the data are organized in an ad hoc database interfaced with a dedicated software which allows interactive visualizations and statistics (CalVal SW). This tool allows to evaluate NRT products by comparison with independent observations for the first time. The heterogeneous distribution and the scarcity of moored observations reflect with large areas uncovered with measurements. Nevertheless, the evaluation of the forecast at the locations of observations could be very useful to discover sub-regions where the model performances can be improved, thus yielding an important complement to the basin-mean statistics regularly calculated for the Mediterranean MFC products using semi-independent observations

Sistema per l'acquisizione e la trasmissione dei dati della stazione mareografica MENFOR

Il presente documento descrive i componenti e le funzionalità del sistema realizzato per l’acquisizione e la trasmissione dei dati della stazione mareografica MENFOR sviluppata nell’ambito del progetto “Sviluppo di una stazione portuale per la previsione dei flussi di marea meteorologica, finalizzata a costituire un servizio per la sicurezza della navigazione e per la protezione dei natanti nel Golfo della Spezia” supportato dal programma PRAI-FESR della Regione Liguria. Il sistema qui descritto è stato realizzato con il contributo di tutti gli Enti coinvolti

Evaluating LoRaWAN connectivity in a marine scenario

The growing need for interoperability among the different oceanic monitoring systems to deliver services able to answer the requirements of stakeholders and end-users led to the development of a low-cost machine-to-machine communication system able to guarantee data reliability over marine paths. In this framework, an experimental evaluation of the performance of long-range (LoRa) technology in a fully operational marine scenario has been proposed. In-situ tests were carried out exploiting the availability of (i) a passenger vessel and (ii) a research vessel operating in the Ligurian basin (North-Western Mediterranean Sea) both hosting end-nodes, and (iii) gateways positioned on mountains and hills in the inland areas. Packet loss ratio, packet reception rate, received signal strength indicator, signal to noise, and expected signal power ratio were chosen as metrics in line of sight and not the line of sight conditions. The reliability of Long Range Wide Area Network (LoRaWAN) transmission over the sea has been demonstrated up to more than 110 km in a free space scenario and for more than 20 km in a coastal urban environment

Observed development of the vertical structure of the marine boundary layer during the LASIE experiment in the Ligurian Sea

In the marine environment, complete datasets describing the surface layer and the vertical structure of the Marine Atmospheric Boundary Layer (MABL), through its entire depth, are less frequent than over land, due to the high cost of measuring campaigns. During the seven days of the Ligurian Air-Sea Interaction Experiment (LASIE), organized by the NATO Undersea Research Centre (NURC) in the Mediterranean Sea, extensive in situ and remote sensing measurements were collected from instruments placed on a spar buoy and a ship. Standard surface meteorological measurements were collected by meteorological sensors mounted on the buoy ODAS Italia1 located in the centre of the Gulf of Genoa. The evolution of the height (<I>z<sub>i</sub></I>) of the MABL was monitored using radiosondes and a ceilometer on board of the N/O Urania. <br><br> Here, we present the database and an uncommon case study of the evolution of the vertical structure of the MABL, observed by two independent measuring systems: the ceilometer and radiosondes. Following the changes of surface flow conditions, in a sequence of onshore – offshore – onshore wind direction shifting episodes, during the mid part of the campaign, the overall structure of the MABL changed. Warm and dry air from land advected over a colder sea, induced a stably stratified Internal Boundary Layer (IBL) and a consequent change in the structure of the vertical profiles of potential temperature and relative humidity