Coordination of global ocean observatories within the international framework: JCOMM and OceanSITES

Abstract

To improve the accuracy of local forecasts and other services as well as climate prediction, a global view of ocean behaviour is essential; hence, a global ocean observing system, consisting of the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> networks; continuous satellite missions; data and assimilation subsystems; and system management and product delivery. To meet this need, the world community called for the Global Ocean Observing System (GOOS) at the United Nations Conference on Environment and Development. It is being developed by nations working together through its main sponsors, the Intergovernmental Oceanographic Commission (IOC), World Meteorological Organization (WMO), United Nations Environment Programme (UNEP), and International Council for Science (ICSU). GOOS, as a sustained, coordinated international mechanism, is conceived as a system for gathering oceans/seas data as well as a system for processing such data to enable the generation of beneficial, analytical and prognostic environmental information services. GOOS also includes the research and development on which such services depend for their improvement. The climate component of GOOS is the ocean component of the Global Climate Observing System (GCOS). In that context, GOOS meets the needs of the UN Framework Convention on Climate Change (UNFCCC) by providing ocean data to underpin forecasts of changes in climate. By providing the local user with an accurate regional framework, GOOS helps to improve predictability. It complements, but not replaces, the collection of data and application of models for specific local application. GOOS is to meet the demands of operational oceanography, but also includes sustained observations needed for research (e.g., on climate variability), and it stimulates research needed to improve observations and forecasts. design for a sustained global observing network: priorities and challenges The productive design of the global observing network presupposes an excellent scientific basis of knowledge which can be used to specify the time and space scales of observations needed for each process and variable to be predicted. It also should connote consistent development in scientific/research requirements and operational applications