The Atlantic Meridional Overturning Circulation (AMOC) plays a significant role in the global climate system, and its behavior in a warming climate is a matter of significant concern. The AMOC is thought to be driven largely by ocean heat loss in the subpolar North Atlantic Ocean, but recent research increasingly emphasizes the importance of the Arctic Mediterranean for the AMOC. In turn, the AMOC may influence the Arctic heat budget through its impact on poleward heat transport. Hence, understanding the processes that link the AMOC and the Arctic is critical for our ability to project how both may evolve in a warming climate. In this paper we review some of the recent research that is shaping our thinking about the AMOC and its two-way interactions with the Arctic.
Simulations of ocean currents using numerical circulation models are becoming increasingly realistic. At the same time, these models generate increasingly large volumes of model output data. These trends make analysis of the model data harder for two reasons. First, researchers must use high-performance data-analysis clusters to access these large data sets. Second, they must post-process the data to extract oceanographically-useful information. Moreover, the increasing model realism encourages researchers to compare simulations to observations of the natural ocean. To achieve this task model data must be analyzed in the way observational oceanographers analyze field measurements; and, ideally, by the observational oceanographers themselves. The OceanSpy package addresses these needs.
Computational Oceanography is the study of ocean phenomena by numerical simulation, especially dynamical and physical phenomena. Progress in information technology has driven exponential growth in the number of global ocean observations and the fidelity of numerical simulations of the ocean in the past few decades. The growth has been exponentially faster for ocean simulations, however. We argue that this faster growth is shifting the importance of field measurements and numerical simulations for oceanographic research. It is leading to the maturation of Computational Oceanography as a branch of marine science on par with observational oceanography. One implication is that ultra-resolved ocean simulations are only loosely constrained by observations. Another implication is that barriers to analyzing the output of such simulations should be removed. Although some specific limits and challenges exist, many opportunities are identified for the future of Computational Oceanography. Most important is the prospect of hybrid computational and observational approaches to advance understanding of the ocean.
Computational Oceanography is the study of ocean phenomena by numerical simulation, especially dynamical and physical phenomena. Progress in information technology has driven exponential growth in the number of global ocean observations and the fidelity of numerical simulations of the ocean in the past few decades. The growth has been exponentially faster for ocean simulations, however. We argue that this faster growth is shifting the importance of field measurements and numerical simulations for oceanographic research. It is leading to the maturation of Computational Oceanography as a branch of marine science on par with observational oceanography. One implication is that ultra-resolved ocean simulations are only loosely constrained by observations. Another implication is that barriers to analyzing the output of such simulations should be removed.Although some specific limits and challenges exist, many opportunities are identified for the future of Computational Oceanography. Most important is the prospect of hybrid computational and observational approaches to advance understanding of the ocean.2
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