Surface current patterns in the northern Adriatic extracted from high-frequency radar data using self-organizing map analysis

Abstract

[1] A network of high-frequency (HF) radars was installed in the northern Adriatic in the second half of 2007, aimed to measure surface currents in the framework of the North Adriatic Surface Current Mapping (NASCUM) project. This study includes a detailed analysis of current measurements from February to August 2008, a period in which three radars were simultaneously operational. Current patterns and temporal evolutions of different physical processes were extracted by using self-organizing map (SOM) analysis. The analysis focused on subtidal frequency band and extracted 12 different circulation patterns on a 4 × 3 rectangular SOM grid. The SOM was also applied on a joint data set that included contemporaneous surface wind data obtained from the operational hydrostatic mesoscale meteorological model ALADIN/HR. The strongest currents were recorded during energetic bora episodes, being recognized by several current patterns and having the characteristic downwind flow with magnitudes exceeding 35 cm/s at some grid points. Another characteristic wind, the sirocco, was represented by three current patterns, while the remaining current structures were attributed to weak winds and the residual thermohaline circulation. A strong resemblance has been found between SOM patterns extracted from HF radar data only and from combined HF radar and wind data sets, revealing the predominant wind influence to the surface circulation structures and their temporal changes in the northern Adriatic. These results show the SOM analysis being a valuable tool for extracting characteristic surface current patterns and forcing functions.Citation: Mihanović, H., S. Cosoli, I. Vilibić, D. Ivanković, V. Dadić, and M. Gačić (2011), Surface current patterns in the northern Adriatic extracted from high-frequency radar data using self-organizing map analysis,

Mapping underwater sound noise and assessing its sources by using a self-organizing maps method

“…Furthermore, the results acknowledge qualitative contribution of non-anthropogenic sources such as sea surface agitation and wave-breaking along the shorelines (Manasseh et al, 2006;Cho and Choi, 2010) on the background noise in the sea. The results therefore demonstrates a capacity of the joint neural network analysis to extract the connections between the variables of different types, already found in other oceanographic studies (Ramji et al, 2009;Mihanović et al, 2011;.…”

Mapping of oceanographic properties along a middle Adriatic transect using Self-Organising Maps

“…This study also supports applications of the SOM method utilizing smaller datasets and series (e.g., Lee and Lwiza, 2008), in addition to large data set applications, which are available via remote sensing and modelling. Another advantage of the method is its capacity to integrally treat different types of data, such as the physical and chemical data used in our study, or jointly analyse the data connected with a functional relationship (e.g., ocean currents and current generating winds, Mihanovi c et al, 2011). This broadens its possible applications to a variety of ocean problems and processes (from atmosphere and oceanography to marine biology and fisheries, or a combination), where relationships between variables and quantities are necessary to properly assess and manage ocean states and resources.…”

“…The SOM was recently introduced to Adriatic oceanography as a useful tool for classifying patterns of different oceanographic parameters (Solidoro et al, 2007;Vilibi c et al, 2011;Mihanovi c et al, 2011;Rako et al, 2013;Kova c et al, 2014). In addition, SOM has been widely used in the global oceanographic community (Liu et al, 2006;Liu and Weisberg, 2011).…”

Report of the Croatian Committee of Geodesy and Geophysics on activities carried out between 2011 and 2014

“…HF radars were used to map the surface currents in the northern and middle Adriatic. Mihanović et al (2011) studied current measurements in the northern Adriatic from February to August 2009. Current patterns and temporal evolutions of different physical processes were extracted by using Self-Organizing Maps (SOM) analysis based on neural networks approach.…”