Denis Cutajar

Which is the Best Predictor of Sea Temperature: Satellite, Model or Data Logger Values? A Case Study from the Maltese Islands (Central Mediterranean)

ABSTRACT Deidun, A.; Gauci, A.; Azzopardi, J.; Cutajar, D., and Drago, A., 2016. Which is the best predictor of sea temperature: satellite, model or data logger values? A case study from the Maltese Islands (Central Mediterranean) In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), XC Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 627–631. Coconut Creek (Florida), ISSN 0749-0208. Water temperature data loggers were deployed at six different depths along a mooring line within Maltese coastal waters. A one-year timeseries of water column temperature data recorded by the same loggers over the September 2012- September 2013 period were compared, through the computation of Pearson correlation factor values, against satellite measures of the SST and against OPA (Ocean Parallelise) model values for the equivalent water depths. Results indicate that satellite-derived SST values are a good estimate of the water column temperature throughout the entire infralittoral zone during the winter and spring seasons, when the thermocline has not yet been established, whilst the degree of convergence between the two sets of values declines sharply during the summer and autumn seasons and extended only up to a depth of 8m and 10m, respectively. OPA model water temperature values for the various column depths give similar results when confronted against data logger values. Although the absolute thickness of the surface warm layer cant be established, one can conclude that this layer is relatively thicker in autumn than in summer.

A monitoring and control prototype for the SKA low frequency aperture array

A monitoring and control system is being developed for the Aperture Array Verificaton System (AAVS) prototype of the Low Frequency Aperture Array (LFAA) component of the Squatre Kilometer Array (SKA). This software system will have to continuously monitor hundreds of thousands of antennas; schedule, run and monitor observations; control the data flow within the element and outwards; and provide the operational and diagnostic utilities for the system. This paper will describe the various elements of the software stack and the integration with the TANGO control system framework.

The low frequency receivers for SKA 1-low: Design and verification

The initial phase of the Square Kilometre Array (SKA) [1] is represented by a −10% instrument and construction should start in 2018. SKA 1-Low, a sparse Aperture Array (AA) covering the frequency range 50 to 350 MHz, will be part of this. This instrument will consist of 512 stations, each hosting 256 antennas creating a total of 131,072 antennas. A first verification system towards SKA 1-Low, Aperture Array Verification System 1 (AAVSl), is being deployed and validated in 2017.