Changeset 199 for altifloat/doc

Timestamp:

11/25/15 12:48:32 (9 years ago)

Author:

leila_ocean

Message:

Nov 25

Location:

altifloat/doc/ocean_modelling

Files:

• Draft1.tex (modified) (3 diffs)
• mybib.bib (modified) (3 diffs)

altifloat/doc/ocean_modelling/Draft1.tex

@@ -121 +121 @@
 
 \begin{abstract}
-We present a new and fast method for blending surface drifters data and altimetry in the Eastern Levantine Mediterranean. The method is based on a variational assimilation approach where drifters data are matched  to a simple advection model for drifters' positions. This model takes into account the effect of the wind. The assimilation is continuous in time. This is done by assimilating a whole trajectory of drifters at once and by using a moving time window where observations are correlated. 
-We show that with few drifters, our method improves the estimation of an eddy between the Lebanese coast and Cyprus, and predicts real drifters trajectories along the Lebanese coast. 
+We present a new and fast method for blending surface drifters data and altimetry in the Eastern Levantine Mediterranean. The method is based on a variational assimilation approach where the velocity is corrected after drifters data are matched to a simple advection model for their positions, taking into account the effect of the wind. The velocity correction is done in a time-continuous fashion by assimilating at once a whole trajectory of drifters in a time window, and by moving that window to exploit correlations between observations. We show that with few drifters, our method improves the estimation of an eddy between the Lebanese coast and Cyprus, and predicts real drifters trajectories along the Lebanese coast. 
 
 \end{abstract}
@@ -154 +153 @@
 environmental parameters \citep{lumpkin2007measuring}.
 
-To illustrate the information provided by drifters data, we show in Figure~\ref{fig:cnrs} the real-time positions of three drifters launched south of Beirut on August 28 2013. These positions can be compared to the positions that would have been obtained if the drifters were advected by the altimetric velocity field. We observe that unlike the corresponding positions simulated by the altimetric field provided by \textit{Aviso} (see section~\ref{sec:aviso}), the drifters stay within 10-20 km from the coast. The background velocity field shown in that figure is the geostrophic field, averaged over a period of 6 days. The drifters' in situ data render a more precise image of the local surface velocity than the altimetric one; 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 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 
+To illustrate the information provided by drifters data, we show in Figure~\ref{fig:cnrs} the real-time positions of three drifters launched south of Beirut on August 28 2013. These positions can be compared to the positions that would have been obtained if the drifters were advected by the altimetric velocity field. We observe that unlike the corresponding positions simulated by the altimetric field provided by \textit{Aviso} (see section~\ref{sec:aviso}), the drifters stay within 10-20 km from the coast. The background velocity field shown in that figure is the geostrophic field, averaged over a period of 6 days. The drifters' in situ data render a more precise image of the local surface velocity than the altimetric one; however, this only possible along the path following their trajectory. These types of data are therefore complementary. 
+
+
+Numerous studies aim at exploiting the information provided by drifters (Lagrangian data) to assess the Eulerian surface velocity. A large number of these rely on modifying a dynamical model of this velocity by minimising the distance between observed and model simulated drifters trajectories. This variational assimilation approach, which was classically used in weather predictions \citep{courtier1994strategy,dimet1986variational}, was tested successfully in this context, by using several types of models for the velocity, such as idealised point vortex models \citep{kuznetsov2003method}, General Circulation Models with simplified stratification (e.g. \cite{kamachi1995continuous};  \cite{molcard2005lagrangian}; \cite{ozgokmen2003assimilation}, \cite{nodet2006variational}). However, in a lot of applications involving pollutant spreading such as the ones we are interested in, a fast diagnosis of the velocity field is needed in areas which are not a priori known in details. This prompts the need for a simple model that is fast and easy to implement, but that keeps the essential physical features of the velocity. In this work, we propose a new algorithm that blends geostrophic and drifters data in an optimal way. The method is based on a simple advection model for the drifters, that takes into account the wind effect and that imposes a divergence free constraint on the geostrophic component. 
+The algorithm is used to estimate the surface velocity field in the 
 Eastern Levantine basin, in particular in the region between Cyprus and the Syrio-Lebanese coast, a part of the Mediterranean basin that has not been so well studied in the literature before. 
-
-
-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. (e.g. \citet{poulain2012surface,menna2012surface,uchida2003eulerian,maximenko2009mean,niiler2003near}).
-Another approach relies on variational assimilation, a method classically used in weather predictions \citep{courtier1994strategy,dimet1986variational}.
-In the context of bending altimetric and drifters' data, the method was used by \citet{taillandier2006variational} and it is based on a simple advection model for the drifters' positions, matched to observations via optimisation. In the work of \citet{taillandier2006variational}, the implementation of the method first assumes the time-independent approximation of the velocity correction, then superimposes inertial oscillations on the mesoscale field. 
+ 
+
+%In the present work, we are interested in Near- Real time applications, simple model for combining drifters with altimetry. challenge remains to keep it physical  
+
+
+%Realistic models involving highly complex physics are of course desirable but 
+
+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. (e.g. \citet{poulain2012surface,menna2012surface,uchida2003eulerian,maximenko2009mean,niiler2003near,stanichny2015parameterization}). Another approach relies on variational assimilation: the work of  \citet{taillandier2006variational} is based on a simple advection model for the drifters' positions that is matched to observations via optimisation. The implementation of this method first assumes the time-independent approximation of the velocity correction, then superimposes inertial oscillations on the mesoscale field. 
 These variational techniques had
-led to the development of the so called ``LAgrangian Variational Analysis" (LAVA),  initially tested and applied to correct model velocity fields using drifter trajectories \citep{taillandier2006assimilation,taillandier2008variational} and later 
+led to the development of the so called ``LAgrangian Variational Analysis" (LAVA) algorithm,  initially tested and applied to correct model velocity fields using drifter trajectories \citep{taillandier2006assimilation,taillandier2008variational} and later 
  customised to several other applications such as model assimilation \citep{chang2011enhanced,taillandier2010integration} and more recently blending drifters and altimetry to estimate surface currents in the Gulf of Mexico \citet{berta2015improved}. 
  %applied it 
@@ -169 +175 @@
 
 
-From the application point of view, blending drifters and altimetric data has been successfully applied to several basins, for example in: the Gulf of Mexico \citep{berta2015improved}, the Black Sea \citep{kubryakov2011mean}, the North Pacific \citep{uchida2003eulerian}, and the Mediterranean Sea \citep{taillandier2006assimilation,poulain2012surface,menna2012surface}. In \citet{menna2012surface}, 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. 
+From the application point of view, blending drifters and altimetric data has been successfully applied to several basins, for example in: the Gulf of Mexico \citep{berta2015improved}, the Black Sea \citep{kubryakov2011mean,stanichny2015parameterization} the North Pacific \citep{uchida2003eulerian}, and the Mediterranean Sea \citep{taillandier2006assimilation,poulain2012surface,menna2012surface}. In \citet{menna2012surface}, 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 a scarcity of data. In the present work, we use in addition to the data sets used in \citet{menna2012surface}, more recent data from 2013 (in the context of Altifloat project) to study this particular region.  
 
 
-Our contribution focuses on the methodological aspect, and it can be considered an extension of the variational approach used in \citet{taillandier2006variational}. The purpose is to add more physical considerations to the surface velocity estimation, without making the method too complex, in order to still allow for Near Real Time applications. We do that by constraining the geostrophic component of that velocity to be divergence-free, and by adding a component due to the effect of the wind, in the fashion done in \citet{poulain2009}. 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. 
+Our contribution focuses on the methodological aspect, and it can be considered an extension of the variational approach used in \citet{taillandier2006variational}. The purpose is to add physical considerations to the surface velocity estimation, without making the method too complex, in order to still allow for Near Real Time applications. We do that by constraining the geostrophic component of that velocity to be divergence-free, and by adding a component due to the effect of the wind, in the fashion done in \citet{poulain2009}. 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 improves the estimation of an eddy between the Lebanese coast and Cyprus, and predicts real drifters trajectories along the Lebanese coast. 

altifloat/doc/ocean_modelling/mybib.bib

@@ -3 +3 @@
 
 
-%% Created for Leila Issa at 2015-10-30 11:43:18 +0200 
+%% Created for Leila Issa at 2015-11-25 11:56:13 +0200 
 
 
@@ -9 +9 @@
 
 
+
+@article{stanichny2015parameterization,
+        Author = {Stanichny, Sergey Vladimirovich and Kubryakov, Arseny Alexandrovich and Soloviev, Dmitry Markovich},
+        Date-Added = {2015-11-25 09:56:10 +0000},
+        Date-Modified = {2015-11-25 09:56:10 +0000},
+        Journal = {Ocean Dynamics},
+        Pages = {1--10},
+        Publisher = {Springer},
+        Title = {Parameterization of surface wind-driven currents in the Black Sea using drifters, wind, and altimetry data},
+        Year = {2015}}
+
+@article{nodet2006variational,
+        Author = {Nodet, Ma{\"e}lle},
+        Date-Added = {2015-11-25 09:51:56 +0000},
+        Date-Modified = {2015-11-25 09:51:56 +0000},
+        Journal = {Inverse problems},
+        Number = {1},
+        Pages = {245},
+        Publisher = {IOP Publishing},
+        Title = {Variational assimilation of Lagrangian data in oceanography},
+        Volume = {22},
+        Year = {2006}}
+
+@article{ozgokmen2003assimilation,
+        Author = {{\"O}zg{\"o}kmen, Tamay M and Molcard, Anne and Chin, Toshio M and Piterbarg, Leonid I and Griffa, Annalisa},
+        Date-Added = {2015-11-25 09:29:58 +0000},
+        Date-Modified = {2015-11-25 09:29:58 +0000},
+        Journal = {Journal of Geophysical Research: Oceans (1978--2012)},
+        Number = {C7},
+        Publisher = {Wiley Online Library},
+        Title = {Assimilation of drifter observations in primitive equation models of midlatitude ocean circulation},
+        Volume = {108},
+        Year = {2003}}
+
+@article{molcard2005lagrangian,
+        Author = {Molcard, Anne and Griffa, Annalisa and {\"O}zg{\"o}kmen, Tamay M},
+        Date-Added = {2015-11-25 09:28:44 +0000},
+        Date-Modified = {2015-11-25 09:28:44 +0000},
+        Journal = {Journal of Atmospheric and Oceanic Technology},
+        Number = {1},
+        Pages = {70--83},
+        Title = {Lagrangian data assimilation in multilayer primitive equation ocean models},
+        Volume = {22},
+        Year = {2005}}
+
+@article{kamachi1995continuous,
+        Author = {Kamachi, M and O'Brien, JJ},
+        Date-Added = {2015-11-25 09:26:52 +0000},
+        Date-Modified = {2015-11-25 09:26:52 +0000},
+        Journal = {Journal of Marine Systems},
+        Number = {1},
+        Pages = {159--178},
+        Publisher = {Elsevier},
+        Title = {Continuous data assimilation of drifting buoy trajectory into an equatorial Pacific Ocean model},
+        Volume = {6},
+        Year = {1995}}
+
+@article{kuznetsov2003method,
+        Author = {Kuznetsov, L and Ide, Kayo and Jones, CKRT},
+        Date-Added = {2015-11-25 09:17:14 +0000},
+        Date-Modified = {2015-11-25 09:17:14 +0000},
+        Journal = {Monthly Weather Review},
+        Number = {10},
+        Pages = {2247--2260},
+        Title = {A method for assimilation of Lagrangian data},
+        Volume = {131},
+        Year = {2003}}
 
 @article{weaver2001correlation,
@@ -276 +343 @@
 
 @article{badran2008,
-  title={Inversion of satellite ocean colour imagery and geoacoustic characterization of seabed properties: Variational data inversion using a semi-automatic adjoint approach},
-  author={Badran, Fouad and Berrada, Mohamed and Brajard, Julien and Cr{\'e}pon, Michel and Sorror, Charles and Thiria, Sylvie and Hermand, J-P and Meyer, Matthias and Perichon, Laura and Asch, Mark},
-  journal={Journal of marine systems},
-  volume={69},
-  number={1},
-  pages={126--136},
-  year={2008},
-  publisher={Elsevier}
-}
+        Author = {Badran, Fouad and Berrada, Mohamed and Brajard, Julien and Cr{\'e}pon, Michel and Sorror, Charles and Thiria, Sylvie and Hermand, J-P and Meyer, Matthias and Perichon, Laura and Asch, Mark},
+        Journal = {Journal of marine systems},
+        Number = {1},
+        Pages = {126--136},
+        Publisher = {Elsevier},
+        Title = {Inversion of satellite ocean colour imagery and geoacoustic characterization of seabed properties: Variational data inversion using a semi-automatic adjoint approach},
+        Volume = {69},
+        Year = {2008}}