New Technological Developments for Oceanographic Observations

Measurement is the foundation of any branch of science, and no less so in oceanography (Thorpe, 2009). Radical changes in early instruments that were largely mechanical, have been realized due to electronic, computing and data transmission advances. These advances produced new ways in oceans observing and monitoring which improve operational and forecasting oceanography to better understand the oceans. Operational forecasting of marine physical and biochemical state variables is now becoming an important tool for modern management and protection of the oceans and their living resources (Marcelli et al., 2007). Despite all these rapid advances in ocean measuring capabilities, the number of variables necessary to solve oceanographic problems is still big and increasing, generating a continuous gap between the available instruments and what we want to measure. In addition, the time and space scales of key processes span over ten orders of magnitude; to solve the risk of undersampling it is necessary to expand the rates of data acquisition, temporal coverage and spatial coverage. The recent advances in ocean monitoring system and new sampling strategies will going to face all these problems. This modern approach is based on the use of in situ autonomous sampling together with satellite observations, integrating SOOP (Ship Of Opportunity) monitoring programs. Moreover, programs like the Pan European Seadatanet (www.seadatanet.org) are set up to promote the use of common vocabularies in datasets in order to allow interoperability and data exchange.

[1]  Peter H. Wiebe,et al.  BIOMAPER-II: an integrated instrument platform for coupled biological and physical measurements in coastal and oceanic regimes , 2002 .

[2]  P. De Mey,et al.  The Mediterranean ocean forecasting system: first phase of implementation (1998–2001) , 2003 .

[3]  J. Aiken,et al.  The Undulating Oceanographic Recorder Mark 2 , 1981 .

[4]  Tommy D. Dickey,et al.  Interdisciplinary oceanographic observations: the wave of the future , 2005 .

[5]  W. Balch,et al.  Factors affecting the estimate of primary production from space , 1994 .

[6]  A. Grandi,et al.  The Mediterranean ocean Forecasting System , 2008 .

[7]  A. Di Maio,et al.  Di Maio, A , 2012 .

[8]  M. Borghini,et al.  Improved quality check procedures of XBT profiles in MFS-VOS , 2006 .

[9]  G. M. R. Manzella,et al.  Development of a new expendable probe for the study of pelagic ecosystems from voluntary observing ships , 2006 .

[10]  T. Antal,et al.  Measurement of phytoplankton photosynthesis rate using a pump-and-probe fluorometer , 2001 .

[11]  David W. Sims,et al.  Using continuous plankton recorder data , 2006 .

[12]  V. Piermattei,et al.  Analysis of mesoscale productivity processes in the Adriatic Sea: Comparison between data acquired by Sarago, a towed undulating vehicle, and CTD casts , 2006 .

[13]  P. Favali,et al.  Seafloor Observatory Science: a review , 2006 .

[14]  D. Antoine,et al.  Seasonal and interannual variability in algal biomass and primary production in the Mediterranean Sea, as derived from 4 years of SeaWiFS observations , 2004 .

[15]  Marina Tonani,et al.  Improved near real-time data management procedures for the Mediterranean ocean Forecasting System-Voluntary Observing Ship program , 2003 .

[16]  K. Mann,et al.  Dynamics of Marine Ecosystems , 1991 .

[17]  James E. Cloern,et al.  Trophic interactions and direct physical effects control phytoplankton biomass and production in an estuary , 1992 .