Aldo Drago

Use of the wavelet transform on hydro-meteorological data

Abstract The advantages of utilising wavelet analysis to study the dependence of sea level variability on meteorological parameters are demonstrated on data collected at a sea level station on the northwestern coast of Malta. The strength of the method lies in the fact that time information is conserved and signal variability can be resolved up to levels which would equivalently require a much longer data set with Fourier transform methods. The validity of the wavelet transform is verified in its potential to decompose and identify in detail the synoptic variability of a parameter, as well as to follow the inter-dependence of more parameters by a quantitative comparison based on a correlation of their wavelet expressions. The results of discrete wavelet analysis exhibit significant differences in the temporal development of the wavelet decompositions of residual sea level. This is even more evident in the air pressure field for which the variability is principally explained by wavelet decompositions corresponding to central frequencies of 0.56 and 0.28 cpd. The reduced activity in barometric pressure fluctuations during summer is particularly evident at these two decompositions. This work also furnishes a contribution to studies concerning the validity of the inverted barometer effect. The position and extent of the frequency range at which the local sea level variation can be approximated by the inverted barometer effect is found to depend on the amplitude of the air pressure fluctuations. During the stronger pressure variations, the inverted correlation to the sea level occurs at practically the full range of synoptic frequencies and even lower.

A first attempt at testing correlation between MODIS ocean colour data and in situ chlorophyll-a measurements within Maltese coastal waters

The study of spatio-temporal trends for key water quality parameters in the Maltese coastal waters is hindered by the lack of systematic observations spanning over the full domain and for sufficiently long time periods. Satellite data offers an alternative source of information, but requires ground truthing against in situ measurements. The aim of this study is to attempt the statistical comparison of MODIS ocean colour data, for a near-shore marine area off the north-east coastline of Malta, with in situ surface chlorophyll-a measurements, and to extract a twelve-month ocean colour data series for the same marine area. Peaks in surface chlorophyll-a concentration occurred in the January-February period, with lowest values being recorded during the early spring period. Log bias values indicate that the MODIS dataset under-estimates the surface chlorophyll-a values, whilst RMSD and r2 values suggest that the match-up between satellite and in situ values is only partly consistent.

Gap Filling of the CALYPSO HF Radar Sea Surface Current Data through Past Measurements and Satellite Wind Observations

High frequency (HF) radar installations are becoming essential components of operational real-time marine monitoring systems. The underlying technology is being further enhanced to fully exploit the potential of mapping sea surface currents and wave fields over wide areas with high spatial and temporal resolution, even in adverse meteo-marine conditions. Data applications are opening to many different sectors, reaching out beyond research and monitoring, targeting downstream services in support to key national and regional stakeholders. In the CALYPSO project, the HF radar system composed of CODAR SeaSonde stations installed in the Malta Channel is specifically serving to assist in the response against marine oil spills and to support search and rescue at sea. One key drawback concerns the sporadic inconsistency in the spatial coverage of radar data which is dictated by the sea state as well as by interference from unknown sources that may be competing with transmissions in the same frequency band. This work investigates the use of Machine Learning techniques to fill in missing data in a high resolution grid. Past radar data and wind vectors obtained from satellites are used to predict missing information and provide a more consistent dataset.

Defining the trophic status of Maltese (Central Mediterranean) coastal waters through the computation of water quality indices based on satellite data

ABSTRACT Farrugia, H.; Deidun, A.; Gauci, A., and Drago, A., 2016. Defining the trophic status of Maltese (Central Mediterranean) coastal waters through the computation of water quality indices based on satellite data. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 632–636. Coconut Creek (Florida), ISSN 0749-0208. The Maltese Islands have to comply with onerous EU legislation in order to protect the integrity of their water resources in a comprehensive manner. To date, operational monitoring of water quality parameters within the Maltese coastal waters is almost non-existent. This present study was carried out to compute and map values for the CSI023(+) and modified TRIX indices, using satellite and model data for the entire Maltese Fisheries Management Zone (FMZ); and to identify trends in such index values and relate these to anthropogenic activities, geolocation, bathymetry and seasonal factors. Temporal analyses of ocean colour and index values revealed the following seasonal trend, in decreasing order of value: winter, autumn, spring, and summer. Ocean colour and TRIX index values indicate that, overall, chlorophyll-a values for the 2002–2011 period and 2013–2014 period are consistent with those of oligotrophic, poorly productive waters, with a high water quality. CSI023(+) values for the 2002–2011 period indicated that the Maltese marine area shows a statistically insignificant trend of variation in chlorophyll-a values, possibly due to the low spatial resolution of the ocean colour dataset used. Statistical analyses shows that bathymetry and west/east geolocation have an influence on the trophic status of the Maltese FMZ. Water quality indices computation from satellite and model data enables the fulfilment of the mandatory, contemporary water quality monitoring requirements Malta has and enables the formulation of water quality management recommendations. This research can be integrated in an operational online system as a decision-making tool.