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04.14.11: Summary of recent analysis

This summary concerns the analysis of the regional HYCOM simulation and its comparison to observations:

  • 10-km wide sea surface temperature (SST) filaments becomes unstable within the surface mixed layer (SML) resulting in a partial and transient restratification of the SML. The spatial and temporal characteristics of the instabilities are consistent with the surface mixed-layer instabilities (SMLIs) described by Boccaletti et al. (2007), Fox-Kemper et al. (2008), Mahadevan et al. (2010).
  • These instabilities occur mostly from December to March when the SML is the deepest and the large-scale SST gradient the largest.
  • These instabilities are associated with a large vertical component of velocity (in the order of 50 m/day) that reaches the depths of the nutricline and may be responsible for the triggering of the Spring bloom: see Vertical velocity field in HYCOM
  • One of the characteristics of the SMLI is a strong correlation between SST filaments and anomalous restratification (via the Brunt-Vaisala frequency or BVF) of the upper SML: see Correlation between stratification and SST gradient for an example of correlation for one specific day in January, Link between SST gradient and BVF and statistics of BVF for the time series of the correlation between SST gradient and near-surface BVF, and Vertical structure of BVF during SMLI for a comparison of vertical BVF profile within and outside SST filaments (especially Fig. 42).
  • Another characteristics is that near-surface BVF during that period has some large values embedded in a sea of near-zero values. One way to quantify the shape of that histogram is the skewness. Skewness is larger and positive during that period than during the rest of the year both in the model and in the ARGO data (see Link between SST gradient and BVF and statistics of BVF, especially Fig. 3).
  • Finite-size Lyapunov exponent (FSLE) is found to be relatively well correlated with SST filaments (although spatial smooting is needed as a significant portion of FSLE are next to and not superimposed on SST filaments), especially in January-March (see Relationship between FSLE and SST gradient). There are SST and FSLE filaments during that period. This simple fact alone could explain why there is a high probability for a point within a FSLE filament to be within or nearby a SST filament and inversely (and not necessarily because FSLE and SST filaments are correlated).
  • Animations of map of FSLE during WHOTS-1 and WHOTS-2 show that in some cases –but not systematically–, partial restratification can be due to the passage of a SST filament: see Animation of FSLE and stratification at WHOTS site, especially February 16, March 6-10 and April 19-May 7 in 2005 during WHOTS-1 and September 18 and November 5 2005 as well as March 3-31 and June 11 in 2006 during WHOTS-2. Because 1) the density of FSLE filaments in time is high and 2) there may incertitude (in time and space) on the exact location of the SST filament, it is not possible at present to quantitatively link FSLE and BVF in the observations, either WHOTS or ARGO.
  • A final and potentially important point is that, in the model, for some occasions, the sudden erosion of the seasonal thermocline is due to the passage of an unstable SST filament: see SMLI and the erosion of the seasonal thermocline. During WHOTS-1, we could also associate that erosion with the passage of several FSLE filament on Dec. 28, 2004, Jan. 17 and Jan. 28, 2005. It is less clear in WHOTS-2 as the seasonal thermocline has larger variability than during WHOTS-1.

Questions and work to do

  • Are density profiles near or within FSLE filaments more restratified than the background?
  • Can we compute a reasonable estimate of SST gradient from the MUR SST dataset? If yes, how do they compare to FSLE? (in other words, can FSLE be used to estimate SST filaments?) Can we explain the sudden erosion of the seasonal thermocline by the passage of a SST filament and SMLI?
  • Use these results to write a proposal to sample a SST filament during January-March

Feedback from Kelvin and Yanli

  • Look at GOES dataset for SST (Google Oceanwatch)
  • Can we discriminate between vertical BVF profiles within and outside a FSLE (or SST if SST is available) filament using ARGO and/or WHOTS data?
  • Look at BVF map at the depth of the seasonal thermocline in January through March and see if the loss of the thermocline is due to the presence of SST filaments or due to the change between water masses of different thermocline?
  • Have a look at the KPP HYCOM simulation
  • Animation of vertically-averaged BVF to discriminate between local BVF formation and stirring by mesoscale eddies of water that has a shallower stratification (in which case no actual upwelling –at least at the sub/mesoscale scale– occur).