Jiajia Liu has completed his MSc at the age of 25 years from University of Southern Denmark and have worked for National Ocean Technology Center for 11 years as an engineer, being in charge of ocean observation system integration technology. He has been involved in 15 national and international ocean research projects and published 10 academic papers in reputed journals as well as acquired 4 national patents of invention and new utility model. He has been serving as committee member of ISO/TC8/SC13(Ocean Observation International Standard).
China has launched achievements integration of ocean energy resource exploration and selection project since 2012. It is aimed at advanced analyzing and researching the spatial and temporal distribution characteristic and transformation law of ocean energy in key zones with the datasets and atlases of marine renewable energy as the achievements of earlier related projects, and carrying out a special research on comprehensive evaluation of development and utilization. In order to visualize the historical and simulated data and exhibit to customers as a display window, the exhibition platform for displaying achievements of ocean energy resource exploration and selection is the emphasis of this project. Foundation database, being used for data storage of historical and simulated data of wave energy, tidal-current energy and tidal energy, is combined with the exhibition platform to display visual data on the application software based on WebGIS. The exhibition platform software can be divided into 6 modules by functions: data entry, map display, historical data browse and output, data simulation and forecast, report and chart generation, system administration. The exhibition platform has been built up in National Ocean Technology Center of China. Past 10 years’ achievement of ocean energy resource exploration and selection in key zones of China has been inputting to the foundation database, which is serving for the achievement
Balla Maggero has been a Research Meteorologist at the Institute of Meteorological Training & Research and the Kenya Meteorological Service since 1993 where he studies marine physics with focus on Indian Ocean, geophysical fluid dynamics, interaction of the near surface and deep sea; meso-scale climate events, boundary-layer fluxes, marine boundary-layer clouds, numerical modeling and data assimilation in marine science including 4 years in the field.
Accurate estimation of four dimensional interdisciplinary fields in the ocean is essential for modern ocean research. In most applications, the continuous time evolution of three dimensional synoptic realizations over a large regional domain with (sub) mesoscale resolution are required for biogeophysical, chemical, and acoustical state variables. There are many couplings and interactions among these fields which provide both challenges and opportunities for the use of interdisciplinary techniques. Field estimation in the ocean is complex and data sets are generally sparse compared to requirements. This is for the most part due to the presence of a large range of interactive space and time scales associated with the wide variety of oceanic phenomena. The coastal ocean is particularly challenging because of multiple forcings, complex geometries, and boundary interactions. An efficient and generally applicable coastal ocean prediction system must take into account the wide variety of coastal phenomena (currents, waves, tides, etc.) and forcings (buoyancy, wind, external) which occur over the multiplicity of time and space scales. The observational network will generally consist of a mix of platforms and sensors with real time telemetry deployed in nested domains of increasing resolutions. The set of coupled interdisciplinary models for assimilating the data will have compatible two-way nested computational domains. Prediction systems should accelerate scientific research progress in the multiscale intermittent ocean and important practical application areas include management of the multiuse coastal zone and naval and marine operations. The advances in oceanic numerical models and data assimilation schemes of the last decade have given rise to interdisciplinary Ocean Observing and Prediction Systems that are used in operational settings. The next generation of such systems will advance the interaction between simulation and measurement to a new level where the forecast application changes its runtime behavior to adapt to new measurements. Importantly, the data assimilation community is starting to recognize the importance of this adaptation, from the correction of model biases to the multi-model data assimilation and automated evolution of model structures as a function of model-data misfits. Physical and biogeochemical ocean dynamics can be highly intermittent and variable, and involve multiple interactive scales in 2-D feedbacks. In general, the oceanic fields, processes and interactions that matter thus vary in time and space. These processes are importantly dominated by strong sporadic events that are erratic on spatiotemporal scale. Understanding non-linear dynamics specification of actual events and identifying important additional as yet unknowns provides a framework for realistic representation and prediction of the interdisciplinary coastal ocean. For efficient forecasting, the structures and parameters of models must evolve and respond dynamically to new data added into the executing prediction system. The conceptual basis of this adaptive modeling and corresponding computational scheme is the subject of this presentation.