Description: Marine scientists investigate the movement of oceanic water particles with floating measurement devices released in the real ocean, as well as with virtual particles released in numerical model simulations. The detection, visualization, and evolution of clustered particles is key for gaining a comprehensive understanding of the underlying processes in the oceans. Thereby, vast amounts of mobility data (3D coordinates of these particles over time) need to be analyzed using mobility data science methods. In this paper, we describe the application of data science techniques to detect particle clusters and, more importantly, to track the evolution of these clusters over time in order to support the analysis of oceanic flows. In particular, we apply a well-known concept for tracking the cluster evolution from the data mining community that relies on pair-counting and, thus, is rather inefficient. In order to be applicable to large amounts of particles, we further elaborate two heuristic solutions to compute the cluster transitions based on spatial approximations. Experiments on real world data show a considerable speed-up while sacrificing marginal accuracy drops. Our prototype is used by domain experts for the analysis of the large-scale ocean by virtual particle release experiments in ocean simulations.

Description: North Atlantic Deep Water (NADW) is a crucial component of the Atlantic Meridional Overturning Circulation and, therefore, is an important factor of the climate system. In order to estimate the mean relative contributions, sources and pathways of the three different deep water mass components (namely Labrador Sea Water, Northeast Atlantic Deep Water and Denmark Strait Overflow Water) at the southern exit of the Labrador Sea, Lagrangian particle experiments were performed. The particles were seeded according to the strength of the velocity field along the 53° N section and computed 40 years backward in time in the three-dimensional velocity and hydrography field. Water masses were defined within the model output in the central Labrador Sea and the subpolar North Atlantic. The resulting transport pathways, their sources and corresponding transit time scales were inferred. Our experiments show that the majority of NADW passing 53° N is associated with diapycnal mass flux, accounting for 14.3 Sv (48 %), where 6.2 Sv originate from the Labrador Sea, compared to 4.7 Sv from the Irminger Sea. The second largest contribution originates from the mixed layer with 7.2 Sv (24 %), where the Labrador Sea contribution (5.9 Sv) dominates over the Irminger Sea contribution (1.0 Sv). Another 5.7 Sv (19 %) of NADW cross the Greenland–Scotland Ridge within the NADW density class, where about 2/3 pass Denmark Strait, while 1/3 cross the Iceland Scotland Ridge. The NADW exported at 53° N is hence dominated by entrainment through diapycnal mass flux and the mixed layer origin in the Labrador Sea.

Description: Western Boundary Currents, such as the Gulf Stream, are regions of vivid air-sea interaction. Mesoscale features of these currents play a fundamental role in global ocean heat transport and exchange with the atmosphere. Related processes and their interactions across scales have gained increasing attention in the last years, since high-resolution, mesoscale-resolving modeling became computationally feasible on climate time scales. Here, we show the impact of explicitly resolving the oceanic mesoscale in the coupled global climate model FOCI on North Atlantic and European climate. For this purpose, we use the ocean nesting capability in FOCI, which facilitates regional ocean grid refinement. We explore and compare pre-industrial simulations each extending over at least 150 years: a reference run without any grid refinement and an experiment with a nest in the North Atlantic. Technically, the regional ocean nest maintains frequent two-way exchange with the global host grid, which in turn is fully coupled to the atmosphere model. The ocean model NEMO has a global resolution of 1/2˚ model with 46 vertical levels and 1/10˚ refinement in the nest region, while the atmosphere model ECHAM6 has a 1.8˚ horizontal resolution (T63) and 95 vertical levels, including the strato- and mesosphere. Within the nest region, the increased resolution leads to a more eddy-rich simulation and an improved mean state. The North Atlantic Current is considerably better represented, which reduces the typical North Atlantic cold bias from -8˚C in the reference run without nest to -2˚C. Beyond local bias correction of the mean state, we will also discuss the impact of explicitly modeling ocean mesoscale dynamics on atmospheric variability on different time scales, such as the North Atlantic Oscillation or the Atlantic Multidecadal Variability.