Changeset 188 for altifloat/doc

Timestamp:

10/26/15 09:26:36 (9 years ago)

Author:

leila_ocean

Message:

Intro Oct26

File:

• altifloat/doc/ocean_modelling/Draft1.tex (modified) (1 diff)

altifloat/doc/ocean_modelling/Draft1.tex

@@ -143 +143 @@
 where satellite information is degraded; this is due to various factors such as ``land contamination, inaccurate tidal and geophysical
 corrections and incorrect removal
-of high frequency atmospheric effects at the sea surface. " [Caballero]. 
-
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-To improve geostrophic velocities, especially near the coast, several types of data can be combined: specifically in situ observations, [Bouffard et al., 2010; Ruiz et al., 2009] provided by drifters, are useful. Drifters follow the currents and when numerous, they allow for an extensive spatial coverage of the region of interest. They are relatively not very expensive, easily deployable and provide accurate information on their position and other
+of high frequency atmospheric effects at the sea surface." [Caballero]. 
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+To improve geostrophic velocities, especially near the coast, several types of data can be combined. In situ observations [Bouffard et al., 2010; Ruiz et al., 2009] provided by drifters are particularly useful. Drifters follow the currents and when numerous, they allow for an extensive spatial coverage of the region of interest. They are relatively not very expensive, easily deployable and provide accurate information on their position and other
 environmental parameters [Lumpkin and Pazos, 2007]. 
-Figure~\ref{fig:cnrs} shows the real-time positions of three drifters launched south of Beirut on August 28 2013, in the context of the ALTIFLOAT* project. We observe that unlike the corresponding positions simulated by the geostrophic field (provided by AVISO), the drifters stay within 10-20 km from the coast. The background field shown in that figure is the geostrophic field, averaged over a period of 6 days. The drifters' data render a more precise image of the surface velocity than the altimetric one, because it includes geostrophic and non-geostrophic components; however, this only possible along the path following their trajectory. These types of data are therefore complementary. In this work, we propose a new algorithm that blends these types of data in an optimal way, in order to estimate the surface velocity field in the 
-Eastern Levantine basin, taking into account the wind effect. We hope to shed light on a region not so-well studied in the literature before, that is between Cyprus and the Syrio-Lebanese coast. 
+Figure~\ref{fig:cnrs} shows the real-time positions of three drifters launched south of Beirut on August 28 2013, in the context of the ALTIFLOAT* project. We observe that unlike the corresponding positions simulated by the geostrophic field (provided by AVISO), the drifters stay within 10-20 km from the coast. The background field shown in that figure is the geostrophic field, averaged over a period of 6 days. The drifters' data render a more precise image of the surface velocity than the altimetric one, because it includes geostrophic and non-geostrophic components; however, this is only possible along the path following their trajectory. These two forms of data are therefore complementary. In this work, we propose a new algorithm that blends geostrophic and drifters data in an optimal way, taking into account the wind effect. The algorithm is then used to estimate the surface velocity field in the 
+Eastern Levantine basin, in order to shed light on the region between Cyprus and the Syrio-Lebanese coast, which has not been so well studied in the literature before. 
 %" not completely reliable when they However, they can be sparse and heterogeneous in space and time, rendering time averages over a mesoscale global grid fraught with possible sampling bias."
 
 
 
-From the methodological point of view, combining altimetric and drifters data has been done using statistical approaches, in the presence of extensive data sets. A common approach is to use regression models to combine geostrophic, wind and drifters components, the drifters' velocity component being computed from drifters' positions using a pseudo-Lagrangian approach. With large data sets, this approach produces an unbiased refinement of the geostrophic circulation maps, with better spatial resolution. [Poulain et al. 2012, Mena et al. 2012, Niller 2003, Centurino 2008, Uchida and Imawaki, 2003 ].
+From the methodological point of view, combining altimetric and drifters data has been done using statistical approaches, with availability of extensive data sets. A common approach is to use regression models to combine geostrophic, wind and drifters components, with the drifters' velocity component being computed from drifters' positions using a pseudo-Lagrangian approach. When large data sets are available, this approach produces an unbiased refinement of the geostrophic circulation maps, with better spatial resolution. [Poulain et al. 2012, Mena et al. 2012, Niller 2003, Centurino 2008, Uchida and Imawaki, 2003 ].
 Another approach relies on variational assimilation, a method classically used in weather predictions [Courtier, Talagrand, etc...]. 
-In the context of bending altimetric and drifters' data, the method was used by [Taillander 2006] (should cite other people as well? look at Taillandier's intro) and it is based on a simple advection model for the drifters' positions, matched to observations via optimisation. The implementation of the method relies on the time-independent approximation of the velocity correction during a time interval shorter than the typical time scale of the mesoscale field. Improvement of the method consists of 
-considering  inertial oscillations superimposed on the mesoscale field. This work 
+In the context of blending altimetric and drifters' data, the method was used by [Taillander 2006] (should cite other people as well? look at Taillandier's intro) and it is based on a simple advection model for the drifters' positions, matched to observations via optimisation. The implementation of the method relies on the time-independent approximation of the velocity correction during a time interval shorter than the typical time scale of the mesoscale field. The method is then improved by considering  inertial oscillations superimposed on the mesoscale field. This work 
 led to the development of the LAVA algorithm [Refs],  initially tested and applied to correct model velocity fields using drifter trajectories [Taillandier et al., 2006b, 2008] and later 
  customised to several other applications such as model assimilation [Chang et al., 2011; Taillandier et al., 2010]. Recently,  [Berta
 et al.] applied it to estimate surface currents in the Gulf of Mexico, where they also added a measure of performance consisting of skill scores, that compare 
 the separation between observed and hindcast trajectories to the observed absolute dispersion.
-From the application point of view, blending drifters and altimetric data has been applied to several basins, including the gulf of Mexico [Berta et al.], the black sea [A. A. Kubryakov and S. V. Stanichny], the North Pacific [Uchida et al.], and the Mediterranean basin [Poulain et al.]  In [Menna et al.], there was a particular attention to the Eastern Mediterranean, but the region of interest to us, which lies between the coasts of Lebanon, Syria and Cyprus, is characterised by sparsity of data. (NEMED?).
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+From the application point of view, blending drifters and altimetric data has been successfully applied to several basins, including the gulf of Mexico [Berta et al.], the black sea [A. A. Kubryakov and S. V. Stanichny], the North Pacific [Uchida et al.], and the Mediterranean basin [Poulain et al.]. In [Menna et al.], there was a particular attention to the levantine sub-basin, where large historical data sets from 1992 to 2010 were used to characterise surface currents. 
+The specific region which lies between the coasts of Lebanon, Syria and Cyprus, is however characterised by sparsity of data. In the present work, we use in addition to NEMED, more recent data to study this particular region.  
 %"The second purpose of this paper is to improve the knowledge on the sub-basin circulation and eddy generation in the eastern LSB. The study is mainly focused on the currents trapped on the topographic slope and on the seasonal and interannual varia- bility of specific sub-basin and mesoscale eddies in the period 2009Ð2010."
 
 
 
-Our contribution focuses on the methodical aspect, and it can be considered as an "extension" of the variational approach used in [Taillander, 2006], where we 
-the velocity used in the advection of the drifters is made of a geostrophic component that is divergence-free, and a component due to the effect of the wind. We 
-also provide a time-continuous correction by: (i) assimilating a whole trajectory of drifters at once and (ii) using a moving time window where observations are correlated. We show that our method (i) improves the estimation of an eddy between the Lebanese coast and Cyprus, and (ii) predicts real drifters trajectories along the Lebanese coast. 
+Our contribution focuses on the methodical aspect, and it can be considered an "extension" of the variational approach used in [Taillander, 2006]. The first purpose is to add more physical considerations to the surface velocity estimation, without making the method too complex, as to remain faithful to the spirit of  Near Real Time applications. We constrain the geostrophic component of that velocity to be divergence-free, and we add a component due to the effect of the wind, in the fashion done in [Poulain et al.]. We 
+also provide a time-continuous correction by: (i) assimilating a whole trajectory of drifters at once and (ii) using a moving time window where observations are correlated. We show that with few drifters, our method (i) improves the estimation of an eddy between the Lebanese coast and Cyprus, and (ii) predicts real drifters trajectories along the Lebanese coast. 
 %This particular coastal region of the Eastern Levantine Mediterranean is of interest, not studied in the literature.