Along or across front survey strategy? An operational example at an unstable front

Abstract

[1] We present results of the optimization of near-real time on-board sampling strategy in the Iceland-Faroes oceanic frontal area, based on the outputs of a mesoscale 3D operational data assimilation forecasting experiment. By minimizing a root mean square error cost function, we show that in this example an along-front sampling strategy, i.e. with transects parallel to the front, produces smaller errors in temperature, salinity, nitrate, phytoplankton, and zooplankton fields, as a result of a combination of the direction of the sampling of the front and errors associated with the asynopticy of observations (Doppler effect). This is contrary to the classic across-front sampling strategies that are used in most field experiments reported in the literature, i.e. where transects are perpendicular to the front. A control model shows that at these spatio-temporal scales, the along front sampling strategy is optimal when the frontal instability has sufficiently developed.

Marine algae are ‘taught’ the basics of angular momentum

“…For the second leg of FISHES, RRS Discovery cruise 253, real-time forecast modelling (Popova et al 2002) provided both a means for rapid assimilation of the datasets and a medium in which to objectively determine optimum sampling strategies (Rixen et al 2003). This resulted in the three highresolution SeaSoar sampling surveys presented and discussed above; the near real-time fast model survey simulations drove a reversal in the overall survey direction in survey 2, from east to west rather than from west to east as in survey 1, and of particular note, they drove the orthogonality of the track legs in the third survey and the overall direction of this survey from north to south.…”

A Quasigeostrophic Analysis of a Meander in the Palamós Canyon: Vertical Velocity, Geopotential Tendency, and a Relocation Technique

“…The vertical velocity, for instance, cannot be measured directly, and usually has been computed through the quasigeostrophic (QG) omega equation (Tintoré et al 1991;Pollard and Regier 1992;Allen and Smeed 1996;Pinot et al 1996). For a correct estimate of the QG vertical velocity it is highly recommended to have a regular and dense spatial sampling (Allen et al 2001;Gomis et al 2001). However, this will always be achieved at the expense of a loss of synopticity, so that an optimal compromise between spatial resolution and synopticity must be determined (Allen et al 2001).…”

A pseudo-Lagrangian method for remapping ocean biogeochemical tracer data: Calculation of net Chl-a growth rates

“…Creating Lagrangian trajectories from Eulerian data is not a novel concept: similar approaches have been applied to create better estimates of atmospheric tracer fields and modeling of rates [Sutton et al, 1994;Nilsson and Leck, 2002;Dragani et al, 2002;Taylor, 1992;Bowman et al, 2013], and many ocean studies analyze Lagrangian trajectories derived from Eulerian output of satellite data or ocean models [Blanke and Raynaud, 1997;d'Ovidio et al, 2004;Doglioli et al, 2006;Lehahn et al 2007;Lett et al 2008;d'Ovidio et al, 2010]. Indeed, SeaSoar data similar to ours have been advected using a comparable methodology to this study, but with the objective of evaluating sampling biases of dynamical variables Rixen et al, 2001Rixen et al, , 2003]. However, limited physical data sets and the general difficulty of measuring biological tracers have precluded application of this technique to the evolution of actual in situ tracer data in the ocean (though for a satellite-derived estimation of phytoplankton net growth rate, see Abbott and Zion [1985]).…”

“…; d'Ovidio et al ., ]. Indeed, SeaSoar data similar to ours have been advected using a comparable methodology to this study, but with the objective of evaluating sampling biases of dynamical variables [ Allen et al ., ; Rixen et al ., , ]. However, limited physical data sets and the general difficulty of measuring biological tracers have precluded application of this technique to the evolution of actual in situ tracer data in the ocean (though for a satellite‐derived estimation of phytoplankton net growth rate, see Abbott and Zion []).…”