Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Trends in Oceanography: More Data, More People, More Relevance J. Thomson* In 2025, the worldâs oceans will be largely unchanged from today. They may be more acidic, or warmer, but those will be minor shifts in comparison with the coincident evolution of society. Changes in oceanog- raphy, as a scientific discipline and as a commercial interest, will thus be driven by human factors. Three current trends are likely to continue: first, several areas of oceanography are becoming data-rich for the first time. Second, there are more people producing and consuming oceanographic knowledge. Third, oceanography has an expanding global relevance in studying the changing climate, and, possibly, in meeting some of the growing energy demands. More data Technology developments are giving oceanographers access to ever- increasing amounts of information; often well beyond what can be observed from a single ship or gained from direct calculation. The most prominent examples are the products from remote/autonomous sens- ing and from computational modeling. Both are the result of accelerated technologies, such as solid-state memory, lithium batteries, and multi- core processors, which are dramatically improving sampling via a mul- titude of platforms and are enabling models of realistic complexity. The resulting datasets and simulations are being used to test hypotheses and *âApplied Physics Laboratory, University of Washington 36
J. Thomson 37 advance science, as well as provide data products to a growing audience. The wealth of data is encouraging science that is more comprehensive, such that results from specific locations and conditions can now be placed within larger contexts. There are fundamental limitations to these new technologies, how- ever, and care must be taken to gather all the data necessary to answer a given set of scientific questions. Specifically, the oceans remain opaque to all forms of radiation, and thus satellite remote sensing remains a surface-biased tool. Computational models remain under-resolved in space and time, even with the rapid acceleration of processor speed. Thus, the conventional tools of oceanography (i.e., shipboard surveys, labora- tory experiments, and theoretical derivations) will remain important for assimilation into model results and new observing systems. As such, the infrastructure to teach conventional oceanography must be maintained. Fundamentally, the wealth of data from observing systems will only be useful in so much as the underlying processes can be understood. That will require focused experiments carefully designed by expert research- ersâpeople who are producers of scientific knowledge, not solely con- sumers of data products. More people There are more producers and consumers of oceanographic content every year. The number of trained oceanographers, measured by U.S. doctorates, is increasing at an annual rate of 10%. While this is promising as a solution to the influx of new data, it is daunting for the U.S. agencies tasked with funding oceanographic research. There is a real danger that high-risk, exploratory research will be shelved in favor of short-gain proj- ects with nearly guaranteed outcomes. Conversely, there is a tremendous opportunity to expand oceanography beyond the tradition of federal funding. Industrial and corporate partnerships may sprout as oceanic resources are explored and integrated into the global economy. Enhanced public and grassroots support may emerge as well. For example, as instrumentation costs become lower, a network of citizen observations, similar to the Meteorological Assimilation Data Ingest Sys- tem (MADIS) Mesonet for weather observations, will be possible by uti- lizing private vessels, docks, and facilities. Such projects would continue the progress towards a data-rich state, while attracting public interest. The pending launch of Google Ocean⢠(a similar geo-exploration software to the popular Google Earthâ¢) is an excellent example of such data-based outreach. In this way, âmore peopleâ may be expanded well beyond âmore doctoratesââand may be one of the most promising trends for oceanography.
38 OCEANOGRAPHY IN 2025 More relevance The oceans are now acknowledged as fundamental to the earth sys- tem and anthropogenic effects on that system. Given this new motivation and expanding datasets, several large science questions are ripe for study. For example, exchanges between the ocean and the atmosphere must be quantified to provide realistic input in Global Circulation Models (GCMs) and climate forecasts. One of the key quantities is energy, which is input via winds and tides and somehow dissipated via mixing and turbulence. This process is poorly understood on both local and global scales, yet is crucial to the dynamics of the overall system, as well as the accuracy of the GCMs. Furthermore, ocean energy is of practical interest as a potential power source; clearly, to understand the possible effects extracting power, the natural system must be better understood. Other basic topics, such as biophysical coupling and coastal evolu- tion, are poised for breakthroughs. While progress accrues in the basic science, predictive models in these areas are becoming valuable tools for resource management. Already, physical models of circulation, impressive in their richness of phenomena and fidelity to data, are being challenged to include biology at multiple scales. In well-tuned cases (which require data-rich backgrounds), the ability to reproduce coincident data shows great potential. The ability to predict future scenarios is enticing, but must always be constrained by observations and grounded in process. The next 16 years will mark only 10% of the time passed since the voyage of the H.M.S. Challenger (1872) and the naissance of oceanogra- phy. Surely, the curve is steeper now, and these next 16 years will witness more change than the first. The relevance is greater, the expectations are higher, and the pace is quicker. Yet to make real progress, empha- sis on the basic scientific methods and measurements of the previous years must prevail, even as data products and applications become more comprehensive.