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Laboratorio Analisi & Integrazione Dati Satellitari Oceanografici

Referente: Dr. Salvatore Marullo
salvatore.marullo@enea.it

Tel: +39-06-9400 5867

Fig. 1. (a) Relation between "in situ" MBR and CM used to derive the new coefficients for the MedOC4 algorithm. Different optical data sources are highlighted with different colours and symbols. MedOC4 functional form is superimposed. (b) MedOC4-derived chlorophyll versus CM. The 1:1 (continuous line) 1:2 (bottom dashed line) and 2:1 (top dashed line) lines are also plotted. From Volpe et al. 2007
Ocean Color: bio-optical algorithms for Chlorophyll
The quantification of the spatial and time variability of phytoplankton biomass and biological activity is among the main scopes of ocean color observation missions.
Starting from the beginning of this millennium field activity and ocean color data analysis in The Mediterranean Sea raised the question of why the global algorithms overestimate chlorophyll-a concentration in the Mediterranean Sea. In fact the analysis of bio-optical measurements revealed a systematic overestimation of chlorophyll-a concentration by NASA global algorithms. For this reason, we introduced a new algorithm, retrieved by fitting a Mediterranean bio-optical data set with an OC2-like functional forms. The DORMA (D'ORtenzio - MARullo) algorithm was the result of this first attempt (D'Ortenzio et. al., 2002). This first algorithm was refined in the following years using a larger set of in situ bio-optical measurements (Volpe et al., 2007) producing the MedOC4 (Fig. 1). This activity was conducted in the framework of the NASA SYMPLEX project (Synoptic Mesoscale Plankton Experiment) also funded by ASI in collaboration with the GOS group of ISAC-CNR.

Ocean Color: Coastal Oceanography
Ocean Color application for coastal oceanography have been developed in the framework of the ADRICOSM NERES and ADRICOSM STAR projects. The objective was to study of the impact of the river outflow and the evolution of the estuarine area on the marine environment in the areas of the Neretva river (fig. 2) and Montenegro Coastal area (Fig. 3).
Further developments of this activity will be done in the framework of an incoming project founded by the Italian Space Agency (CoastSat). A new proposal to develop a procedure to estimate the Phytoplankton Size Classes (PSC) distribution from satellite ocean color data will be submitted to EU by the end of this year (2010).

Oil Spill detection:
ENEA participates to the Italian Space Agency project PRIMI (PRogetto pilota Inquinamento Marino da Idrocarburi) contributing to forecast and analysis of the Tyrrhenian Sea Circulation (UTMEA Section of ENEA) and to the field activity (PRIMI cruise August 2009) with lidar measurements to detect oil spills observed by satellite.

Sea Surface Temperature and diurnal cycle:
The increasing quality of Sea Surface Temperature derived from satellite measurements has now reached such levels that its diurnal cycle cannot be considered any more as geophysical noise.
The knowledge of the SST diurnal cycle contribute to all those ocean applications that include air-sea interaction processes and is important for assimilation in ocean forecasting schemas either when the model do not fully include the physics of the daily temperature variation of the upper warm-layer or when this variability is requested with enough precision to reproduce usual to extreme diurnal warming events.
Moreover, if the foundation SST (i.e. the temperature at the base of the diurnal thermocline) is the ideal measure to construct consistent time series of regional to global SST maps for climate time series, it is necessary to estimate diurnal warming at the ocean surface and remove it from daytime SST retrievals. This will contribute to reduce the geophysical noise due to the diurnal cycle and the bias due to the uneven distribution of the valid SST retrieval during the day.
We participate to the GHRSST-PP Diurnal Variability Working Group (DVWG) of GHRSST (Group for High-Resolution Sea Surface Temperature) and to European Research Network for Estimation from Space of Surface Temperature (ERNESST).
Our goal is to develop a new approach that combine high time frequency satellite data, mainly from geostationary satellites but non only, and MyOcean Operational Ocean Forecasting Models products to generate level 4 hourly maps of sea surface temperature resolving the diurnal variations and including extreme diurnal warming events. Preliminary results are already available (see fig. 4).

Fig 2. . Interannual variability of the monthly aCDOM(300 nm) in the Neretva area


Fig 3. Ocean Color parameters derived from SeaWiFs off of the Montenegro coasts (March 4th 2004)


Fig. 4. SST reconstruction of a diurnal warming event in the Mediterranean Sea. The method uses SEVIRI SST data as input of an adapted optimal interpolation schema that also uses ocean general circulation model (OGCM) analysis (OPA) as first guess.


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References:

  • Measuring the oceans from space: the principles and methods of satellite oceanography, Ian Stuart Robinson, Springer, 2004 - 669 pages
  • Oceanography from Space, Vittorio Barale, Springer, 2010 - 374 pagine
  • Validation of empirical SeaWiFS algorithms for chlorophyll-a retrieval in the Mediterranean Sea A case study for oligotrophic seas, D'Ortenzio et al. Remote Sensing of Environment 82 (2002) 79-94, 2002
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