DOI: 10.5061/dryad.zcrjdfnbv
title: Data from: Cyclone-anticyclone asymmetry of eddy detection on gridded altimetry product in the Mediterranean Sea

description: We perform an Observing System Simulation Experiment that simulates the
 satellite sampling and the mapping procedure on the sea surface of the
 high-resolution model CROCO-MED60v40, to investigate the reliability and
 the accuracy of the eddy detection. The main result of this study is a
 strong cyclone-anticyclone asymmetry of the eddy detection on the
 altimetry products AVISO/CMEMS in the Mediterranean Sea. Large-scale
 cyclones having a characteristic radius larger than the local deformation
 radius are much less reliable than large-scale anticyclones. We estimate
 that less than 60% of these cyclones detected on gridded altimetry product
 are reliable, while more than 85% of mesoscale anticyclones are reliable.
 Besides, both the barycenter and the size of these mesoscale anticyclones
 are relatively accurate. This asymmetry comes from the difference of
 stability between cyclonic and anticyclonic eddies. Large mesoscale
 cyclones often split into smaller sub-mesoscale structures having a rapid
 dynamical evolution. The numerical model CROCO-MED60v40 shows that this
 complex dynamic is too fast and too small to be accurately captured by the
 gridded altimetry products. The spatio-temporal interpolation smoothes out
 this sub-mesoscale dynamics and tends to generate an excessive number of
 unrealistic mesoscale cyclones in comparison with the reference field. On
 the other hand, large mesoscale anticyclones, which are more robust and
 which evolve more slowly, can be accurately tracked by standard altimetry
 products. We also confirm that the AVISO/CMEMS products induce a bias on
 the eddy intensity. The azimuthal geostrophic velocities are always
 underestimated for large mesoscale anticyclones.
description: <strong>Sea Surface Height from igh-resolution model of the
 Mediteranean Sea</strong> We used the results of
 a realistic numerical simulation that was carried out for the
 Mediterranean Sea using the CROCO numerical model
 (http://www.croco-ocean.org). For more details on the numerical
 characteristics of the CROCO model we refer to Shchepetkin and McWilliams
 (2005), Debreu et al (2012), and Auclair et al (2018). The simulation
 under investigation, CROCO-MED60v40-15-16, was forced at the ocean surface
 with ARPEGE HR analysed meteorological fields (winds, pressure, air
 temperature, relative humidity) thanks to the classical bulk COARE formula
 (Fairall et al (2003). The standard primitive equations are solved with an
 horizontal resolution of 1/60° in both longitudinal and latitudinal
 directions. The vertical coordinate used is a generalised terrain
 following one. It is stretched to keep as flat as possible the levels near
 the surface whatever the bathymetry gradient is. Fourty unevenly
 distributed vertical levels discretized the water column. They are closer
 one from each other next to the surface and more spaced by the bottom
 where the vertical gradients of hydrology parameters (temperature or
 salinity) are weak. The initial and the boundary conditions were built
 from CMEMS global system analysis optimally interpolated on the
 computational grid. CROCO-MED60v40-15-16 is a result of a free run
 simulation (no nudging nor assimilation of any kind) that started on the
 1st of August 2012 when the water column stability is at its maximum to
 avoid static instability in the spinning up phase. It ran till the end of
 December 2016.<br>   <strong>Sea Surface
 Height from Observing System Simulation
 Experiment</strong> An Observing System
 Simulation Experiment (OSSE) is performed in a four-satellite
 configuration, composed of the reference mission Jason-3 and three other
 missions Sentinel3-A, Sentinel3-B, and Cryosat-2. As the
 CROCO-MED60v40-15-16 resolves the response of the ocean to atmospheric
 pressure disturbances, it contains large-scale high-frequency signals that
 cannot be handled by the mapping method based on Optimal Interpolation.
 The SWOT simulator software (Gaultier et al, 2016) is then used to
 generated along track with realistic measurement errors and noise. The
 resulting ground truth references are finally ingested in the AVISO/CMEMS
 mapping procedure (Taburet et al, 2019) to compute gridded fields. Two
 distinct OSSE were performed. For the OSSE-SSH-D, the optimal
 interpolation of individual altimetry tracks (LeTraon et al, 1998) is made
 on backward and forward tracks within a time window of +/- 5 days. On the
 other hand, the OSSE-SSH-NRT maps are built every day with the altimetry
 tracks of the past ten days.  
 <strong>Reference</strong>
 Auclair, F., Benshila, R., Debreu, L., Ducousso, N., Dumas, F.,
 Marchesiello, P., & Lemari ́e, F. (2018, February). Some Recent
 Developments around the CROCO Initiative for Complex Regional to Coastal
 Modeling. In COMOD 2018 - Workshop on Coastal Ocean Modelling(p. 1-47).
 Hambourg, Germany. Debreu, L., Marchesiello, P.,
 Penven, P., & Cambon, G.(2012). Two-way nesting in split-explicit
 ocean models: Algorithms, implementation and validation. Ocean Modelling,
 49-50, 1–21. Fairall, C. W., Bradley, E. F., Hare, J.
 E., Grachev, A. A., & Edson, J. B.(2003,02).Bulk Parameterization
 of Air–Sea Fluxes: Updates and Verification for the COARE
 Algorithm.Journal of Climate,16(4), 571-591. Gaultier,
 L., Ubelmann, C., & Fu, L.-L.(01 Jan. 2016). The challenge of
 using future swot data for oceanic field reconstruction. Journal of
 Atmospheric and Oceanic Technology,33(1), 119 - 126. Le
 Traon, P. Y., Nadal, F., & Ducet, N. (1998, 04). An Improved
 Mapping Method of Multisatellite Altimeter Data. Journal of Atmospheric
 and Oceanic Technology,15(2), 522-534. Shchepetkin, A.
 F., & McWilliams, J. C. (2005). The regional oceanic modeling
 system (roms): a split-explicit, free-surface,
 topography-followingcoordinate oceanic model. Ocean Modelling,9(4),
 347–404. Taburet, G., Sanchez-Roman, A., Ballarotta,
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description: SSH_CROCO-MED60v40-15-16.nc contains SSH from croco model
 outputs<br> with corresponding longitude, latitude and land_mask in
 lon_lat_CROCO.nc SSH_OSSE_DT_2015_2016.nc and
 SSH_OSSE_NRT_2015_2016.nc contains SSH from the Delayed (DT) and Near-Real
 Time (NRT) Observing System Simulation Experiment of the Delayed<br>
 with corresponding longitude, latitude and data_mask in
 lon_lat_OSSE.nc