A SCIENTIFIC APPROACH TO EMPLOY MONITORING AND MODELING TECHNIQUES FOR GLOBAL CHANGE AND TERRESTRIAL ECOSYSTEMS AND OTHER RELATED PROJECTS

The ultimate goal of understanding processes in the Earth's geophysica l/biogeochemical/climate system can be achieved by multi-disciplinary studies using global monitoring systems, regional networks and models merging scientific and technological issues. The Global Climate Observ ing System (GCOS) and its composite parts-Global Ocean Observing Syste m (GOOS) and Global Terrestrial Observing System (GTOS)-are on the age nda of current and subsequent international efforts. To outline scient ifically the construction of the systems, an approach is proposed that includes the following interrelated blocks: Climate/Biosphere Models, Observation Systems, Geoinformation Systems and Predictability Proble ms. The opportunity to unify these blocks in the general context of gl obal/regional change studies are determined by the proposed applicatio n of the information and thermodynamic properties of the entropy categ ory that reveals its dualism in the information content assessments fo r data of modelling/monitoring and in state parameter retrievals for n atural targets using multi-spectral remote sensing images. The Climate /Biosphere Models block is designed to highlight how global and region al change problems are drawn up in terms of models, data, and processe s for natural media (the atmosphere, hydrosphere, land surface, biosph ere). The Observation Systems block, linking modelling and monitoring quantities on various scales, serves to account for recommendations to optimization techniques based on certain criteria, value functions an d information content metrics. The recommendations are due to the nece ssity to improve or make cost-effective the systems which are planned within the EOS (Earth Observing System) and similar other programmes. The Geoinformation Systems (GIS) block gives an explanation to what ex tent GIS-technologies, databases and information systems can be unifie d with general principles of data processing, related algorithms and p rocedures. The Predictability Problems block enables one to understand what can be determined from temporal data set analyses and inter-annu al variability of multi-spectral satellite products and samples of gro und measurements. A mathematical functional, characterized by the sign al/noise ratio in a particular topic area, will elucidate how predicta ble is the effect of any anomalies in the Earth's global system. Anoth er functional, characterized by the ratio of biomass to temperature fo r the soil-vegetation system, both parameters being retrieved from reg ular satellite images, will give the scientific explanation of the sta bility category of the biosphere under natural and anthropogenic influ ences in the context of the overall problem of sustainable development . The approach is designed for elaborating a universal tool to study c ross-cutting themes of monitoring/modelling in GCTE and other projects concerning global and regional change.