Benchmarking the mesoscale variability in global ocean eddy-permitting numerical systems

Abstract

The role of data assimilation procedures on representing ocean mesoscale variability is assessed by applying eddy statistics to a state-of-the-art global ocean reanalysis (C-GLORS), a free global ocean simulation (performed with the NEMO system) and an observation-based dataset (ARMOR3D) used as an independent benchmark. Numerical results are computed on a 1/4 • horizontal grid (ORCA025) and share the same resolution with ARMOR3D dataset. This "eddy-permitting" resolution is sufficient to allow ocean eddies to form. Further to assessing the eddy statistics from three different datasets, a global threedimensional eddy detection system is implemented in order to bypass the need of regional-dependent definition of thresholds, typical of commonly adopted eddy detection algorithms. It thus provides full three-dimensional eddy Istituto Nazionale di Geofisica e Vulcanologia (INGV), Bologna, Italy statistics segmenting vertical profiles from local rotational velocities. This criterion is crucial for discerning real eddies from transient surface noise that inevitably affects any twodimensional algorithm. Data assimilation enhances and corrects mesoscale variability on a wide range of features that cannot be well reproduced otherwise. The free simulation fairly reproduces eddies emerging from western boundary currents and deep baroclinic instabilities, while underestimates shallower vortexes that populate the full basin. The ocean reanalysis recovers most of the missing turbulence, shown by satellite products , that is not generated by the model itself and consistently projects surface variability deep into the water column. The comparison with the statistically reconstructed vertical profiles from ARMOR3D show that ocean data assimilation is able to embed variability into the model dynamics, constraining eddies with in situ and altimetry observation and generating them consistently with local environment.

A Surface “Superconvergence” Pathway Connecting the South Indian Ocean to the Subtropical South Pacific Gyre

“…The present reanalysis shows some improvements as compared to predecessors as discussed and validated in Storto and Masina (2016). Recently, Cipollone et al (2017) show that data assimilation enhances and corrects mesoscale variability on a wide range of features that cannot be well simulated by the free simulation. Comparisons with observations show that the "eddy-permitting" resolution is sufficient to allow ocean eddies to form and the assimilation recovers most of the missing turbulence as observed by satellite products.…”

“…The reanalysis spans 1979-2013, but we focused on the 1985-2013 period when the assimilation uses the daily satellite sea-surface temperature supplied by National Oceanic and Atmospheric Administration (Reynolds et al, 2007) and along-track altimetric observations provided by AVISO. Recently, Cipollone et al (2017) show that data assimilation enhances and corrects mesoscale variability on a wide range of features that cannot be well simulated by the free simulation. The present reanalysis shows some improvements as compared to predecessors as discussed and validated in Storto and Masina (2016).…”

Up to What Extent Can We Characterize Ocean Eddies Using Present‐Day Gridded Altimetric Products?

“…Others have compared those properties with other ocean variables (e.g., ocean color; Gaube et al, ; Kobayashi et al, ; Zhang et al, ) to relate spatial and temporal patterns. And others use the altimetry estimates of the eddy field to validate or constrain ocean models (Cipollone et al, ; Nagai et al, ). In all those cases the results should be analyzed with caution as they are based on a biased characterization of the eddy field: Most of the actual eddy field is missed and the part that could be correctly captured suffer from aliasing and noise.…”

Editorial—the 8th International Workshop on Modeling the Ocean (IWMO 2016) in Bologna, Italy, June 7–10, 2016

“…The results show that during strong northerly storms, the bottom currents are dominated by wave-induced velocities while direct wind-induced currents are smaller. Cipollone et al (2017) compared three global ocean products: global reanalysis (C-GLORES), observed global data set (ARMOR3D), and a free running Beddy-permitting^global ocean model (NEMO). The goal was to evaluate data assimilation schemes and see how well these systems can represent mesoscale variability in the ocean.…”

“…The papers can be generally divided into four categories: (1.) Model development, analysis, and data assimilation (Byun and Hart 2017;Cipollone et al 2017, Jordi et al 2017Liu et al 2017;Wei et al 2017); (2.) Coastal modeling and process studies (Bie et al 2017;Ezer 2017;Ezer and Atkinson 2017;Liao et al 2017;Lu et al 2017, Trotta et al 2017; (3.)…”