[cig-commits] r11986 - in seismo/3D/automeasure/latex: . figures/050295B.050-150 figures/060994A.050-150 figures/101895B.050-150 figures/fig

Tue May 20 05:37:40 PDT 2008

Author: alessia
Date: 2008-05-20 05:37:39 -0700 (Tue, 20 May 2008)
New Revision: 11986

Modified:
   seismo/3D/automeasure/latex/abstract.tex
   seismo/3D/automeasure/latex/discussion.tex
   seismo/3D/automeasure/latex/figures/050295B.050-150/ABKT.II.LHZ.seis_nowin.pdf
   seismo/3D/automeasure/latex/figures/060994A.050-150/event_recordsection.eps
   seismo/3D/automeasure/latex/figures/060994A.050-150/event_winstats.eps
   seismo/3D/automeasure/latex/figures/101895B.050-150/event_recordsection.eps
   seismo/3D/automeasure/latex/figures/101895B.050-150/event_winstats.eps
   seismo/3D/automeasure/latex/figures/fig/composites_global.pdf
   seismo/3D/automeasure/latex/figures_paper.tex
   seismo/3D/automeasure/latex/flexwin_paper.pdf
   seismo/3D/automeasure/latex/introduction.tex
   seismo/3D/automeasure/latex/method.tex
Log:
Made modifications suggested by Carl

Modified: seismo/3D/automeasure/latex/abstract.tex
===================================================================

--- seismo/3D/automeasure/latex/abstract.tex	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/abstract.tex	2008-05-20 12:37:39 UTC (rev 11986)
@@ -1,4 +1,3 @@
 \begin{abstract}
-%We present an algorithm for the automated selection of time-windows on pairs of observed and synthetic seismograms.  The algorithm was designed specifically to automate window selection and measurement for adjoint tomography studies, but is sufficiently flexible to be adapted to most tomographic applications and seismological scenarios.  Adjoint tomography requires a data selection method that maximizes the number of measurements made on each seismic record while avoiding seismic noise.  Such a method must  adapt to the features that exist in the seismograms themselves, because 3D wavefield simulations are able to synthesize phases that do not exist in 1D simulations or traditional travel-time curves.  It must also be automated in order to adapt to changes in the synthetic seismograms after each iteration of the tomographic inversion.  These considerations led us to favor a signal processing approach to the time-window selection problem, and to the development of the FLEXWIN algorithm we present here. 
 We present an algorithm for the automated selection of time windows on pairs of observed and synthetic seismograms.  The algorithm was designed specifically to automate window selection and measurement for adjoint tomography studies, but is sufficiently flexible to be adapted to most tomographic applications and seismological scenarios.  Adjoint tomography utilizes 3D wavefield simulations that capture complex phases that do not exist in 1D simulations or traditional travel-time curves. It therefore needs a data selection method that maximizes the number of measurements made on each seismic record while avoiding seismic noise. It must also be automated in order to adapt to changes in the synthetic seismograms after each iteration of the tomographic inversion.  These considerations led us to favor a signal processing approach to the time-window selection problem, and to the development of the FLEXWIN algorithm we present here. We illustrate the algorithm using datasets from three distinct regions: the full Earth, the Japan subduction zone, and the southern California crust.
 \end{abstract}

Modified: seismo/3D/automeasure/latex/discussion.tex
===================================================================
--- seismo/3D/automeasure/latex/discussion.tex	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/discussion.tex	2008-05-20 12:37:39 UTC (rev 11986)
@@ -7,14 +7,14 @@
 
 It is becoming clear, as more finite-frequency tomography models are published, that better kernels on their own are not the answer to the problem of improving the resolution of tomographic studies.  \cite{TrampertSpetzler2006} and \cite{BoschiEtal2007} investigate the factors limiting the quality of finite-frequency tomography images, and conclude that incomplete and inhomogeneous data coverage limit in practice the improvement in resolution that accurate finite-frequency kernels can provide.  The current frustration with the data-induced limitations to the improvements in wave-propagation theory is well summarized by \cite{Romanowicz2008}.  The ability of adjoint methods to deal with all parts of the seismogram indifferently means we can incorporate more information from each seismogram into a tomographic problem, thereby improving data coverage.
 
-The computational cost of constructing an adjoint kernel is independent of the number of time-windows on each seismogram we choose to measure, and also of the number of records of a given event we choose to work with.  It is therefore to our advantage to make measurements on as many records as possible, while covering as much as possible of each record.  There are, however, certain limits we must be aware of.  As mentioned in the introduction, there is nothing in the adjoint method itself that prevents us from constructing a kernel from noise-dominated portions of the data.  As the purpose of 3D-3D tomography is to improve the fine details of Earth models, it would be counterproductive to pollute the inversion process with such kernels.  
+The computational cost of constructing an adjoint kernel is independent of the number of time windows on each seismogram we choose to measure, and also of the number of records of a given event we choose to work with.  It is therefore to our advantage to make measurements on as many records as possible, while covering as much as possible of each record.  There are, however, certain limits we must be aware of.  As mentioned in the introduction, there is nothing in the adjoint method itself that prevents us from constructing a kernel from noise-dominated portions of the data.  As the purpose of 3D-3D tomography is to improve the fine details of Earth models, it would be counterproductive to pollute the inversion process with such kernels.  
 
 The use of adjoint methods for tomography requires a method of selecting and windowing seismograms that avoids seismic noise while at the same time extracting as much information as possible from the signals.  The method must be automated in order to adapt to the changing synthetic seismograms at each iteration of the tomographic inversion.  The method must also be adaptable to the features that exist in the seismograms themselves, because 3D wavefield simulations are able to synthesize phases that do not exist in 1D simulations or traditional travel-time curves.  These considerations led us to favor a signal processing approach to the problem of data selection, approach which in turn led to the development of the FLEXWIN algorithm we have presented here.  
 
 Finally, we note that the design of this algorithm is predicated on the desire {\em not} to use the entire time series of each event when making a measurement between data and synthetics. If one were to simply take the waveform difference between two time series, then there would be no need for selecting time windows of interest. However, this ideal approach \citep[e.g.,][]{GauthierEtal1986} may only work in real applications if the
 statistical properties of the noise is well known, which is rare.
 %noise in the observed seismograms is described well, which is rare.
-Without an adequate description of the noise, it is prudent to resort to the selection of time-windows even for waveform difference measurements. 
+Without an adequate description of the noise, it is prudent to resort to the selection of time windows even for waveform difference measurements. 
 
 %------------------------------
 
@@ -23,5 +23,5 @@
 
 The FLEXWIN algorithm is independent of input model, geographic scale and frequency range. Its use need not be limited to tomography studies, nor to studies using 3D synthetics. It is a configurable process that can be applied to different seismic scenarios by changing the parameters in Table~\ref{tb:params}.  We have configured the algorithm separately for each of the tomographic scenarios presented in Section~\ref{sec:results}.  The configuration process is data-driven: starting from the description of how each parameter influences the window selection (Section~\ref{sec:algorithm}), the user tunes the parameters using a representative subset of the full dataset until the algorithm produces an adequate set of windows, then applies the tuned algorithm to the full dataset. The choice of what makes an adequate set of windows remains subjective, as it depends strongly on the quality of the input model, the quality of the data, and the region of the Earth the tomographic inversion aims to constrain.  We consider the algorithm to be correctly tuned when false positives (windows around undesirable features of the seismogram) are minimized, and true positives (window around desirable features) are maximized.  For a given dataset, the set of tuned parameters (Table~\ref{tb:params}) and their user-defined time dependencies completely determine the window selection results. Finally, we envision that successive iterations of a particular tomographic model may require minor adjustments to the tuning parameters, as the fits improve between the synthetic and observed seismograms, permitting higher frequency information to be used.
 
-The desire to study regions of detailed structure and to examine the effects of finite source processes requires seismologists to deal with increasingly complex seismic records.  Furthermore, with increasing coverage and sampling rate, the available data becomes voluminous and challenging to manage. In using the FLEXWIN package, the onus would still be on the seismologist to tune the algorithm parameters so as to pick time-windows appropriate for each specific study target. For a given data-set and a given set of tuning parameters, the time-window picking is entirely reproducible.  The automated and signal processing nature of the procedure should eliminate some of the human bias involved in picking measurement windows, while expediting the process of analyzing tens to hundreds of thousands of records.
+The desire to study regions of detailed structure and to examine the effects of finite source processes requires seismologists to deal with increasingly complex seismic records.  Furthermore, with increasing coverage and sampling rate, the available data becomes voluminous and challenging to manage. In using the FLEXWIN package, the onus would still be on the seismologist to tune the algorithm parameters so as to pick time windows appropriate for each specific study target. For a given data-set and a given set of tuning parameters, the time-window picking is entirely reproducible.  The automated and signal processing nature of the procedure should eliminate some of the human bias involved in picking measurement windows, while expediting the process of analyzing tens to hundreds of thousands of records.
 

Modified: seismo/3D/automeasure/latex/figures/050295B.050-150/ABKT.II.LHZ.seis_nowin.pdf
===================================================================
--- seismo/3D/automeasure/latex/figures/050295B.050-150/ABKT.II.LHZ.seis_nowin.pdf	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/figures/050295B.050-150/ABKT.II.LHZ.seis_nowin.pdf	2008-05-20 12:37:39 UTC (rev 11986)
@@ -3,169 +3,205 @@
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Modified: seismo/3D/automeasure/latex/figures/060994A.050-150/event_winstats.eps
===================================================================
--- seismo/3D/automeasure/latex/figures/060994A.050-150/event_winstats.eps	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/figures/060994A.050-150/event_winstats.eps	2008-05-20 12:37:39 UTC (rev 11986)
@@ -4,7 +4,7 @@
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Modified: seismo/3D/automeasure/latex/figures/101895B.050-150/event_recordsection.eps
===================================================================
--- seismo/3D/automeasure/latex/figures/101895B.050-150/event_recordsection.eps	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/figures/101895B.050-150/event_recordsection.eps	2008-05-20 12:37:39 UTC (rev 11986)
@@ -4,7 +4,7 @@
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Modified: seismo/3D/automeasure/latex/figures/101895B.050-150/event_winstats.eps
===================================================================
--- seismo/3D/automeasure/latex/figures/101895B.050-150/event_winstats.eps	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/figures/101895B.050-150/event_winstats.eps	2008-05-20 12:37:39 UTC (rev 11986)
@@ -4,7 +4,7 @@
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Modified: seismo/3D/automeasure/latex/figures/fig/composites_global.pdf
===================================================================
(Binary files differ)

Modified: seismo/3D/automeasure/latex/figures_paper.tex
===================================================================
--- seismo/3D/automeasure/latex/figures_paper.tex	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/figures_paper.tex	2008-05-20 12:37:39 UTC (rev 11986)
@@ -107,13 +107,13 @@
 \begin{figure}
 \center \includegraphics[width=6in]{figures/050295B.050-150/ABKT_II_LHZ_seis_nowin.pdf}
 \caption{\label{fg:stalta}
-Synthetic seismogram and its corresponding STA:LTA timeseries.
+Synthetic seismogram and its corresponding envelope and STA:LTA timeseries.
 The seismogram was calculated using SPECFEM3D and the
 Earth model S20RTS \citep{RitsemaEtal2004} for the CMT catalog event
 050295B, whose details can be found in Table~\ref{tb:events}.  The
 station, ABKT, is at an epicentral distance of 14100~km and at an azimuth of 44
 degrees from the event.  The top panel shows the vertical component synthetic
-seismogram, filtered between periods of 50 and 150 seconds.  The bottom panel
+seismogram, filtered between periods of 50 and 150 seconds. The center panel shows its envelope, and the bottom panel
 shows the corresponding STA:LTA waveform.  The dashed line overlaid on
 the STA:LTA waveform is the water level $w_E(t)$.
 } 

Modified: seismo/3D/automeasure/latex/flexwin_paper.pdf
===================================================================
(Binary files differ)

Modified: seismo/3D/automeasure/latex/introduction.tex
===================================================================
--- seismo/3D/automeasure/latex/introduction.tex	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/introduction.tex	2008-05-20 12:37:39 UTC (rev 11986)
@@ -1,22 +1,8 @@
-\pagebreak
-\subsection*{Notes for Alessia and Min (things we need to figure out)}
-
-\begin{enumerate}
-\item For the record section figures, what label do we use for the y-axis?  I do not like the $/$ used in the \verb+Distance / deg+ notation. I went with ``Distance to receiver, units'' on mine and Min's.
-\item I use ``time window'' as a noun and ``time-window'' as an adjective.
-\item We need at least one envelope function in the paper, preferably in Figure~1.
-\item Min, I deleted your shallow-event figure and associated text, as we had discussed.  If either of you think it is essential, then add it back in.
-\item Min, you need to state which period range the coverage is for in the captions for Figures \ref{fg:KIS_BO_091502B}a and \ref{fg:SHR_BO_200511211536A}a.
-\end{enumerate}
-
-\pagebreak
-
 \section{Introduction}
 
 Seismic tomography - the process of imaging the 3D structure of the Earth using
 seismic recordings - has been transformed by recent advances in methodology.
-%Ray-based approaches are being superseded by finite-frequency kernel-based approaches, and 1D reference models by 3D reference models.
-Finite-frequency approaches have been used in place of ray-based approaches, and 3D reference models in place of 1D reference models.
+Finite-frequency approaches are been used instead of ray-based approaches, and 3D reference models instead of 1D reference models.
 These transitions are motivated by a greater understanding of the volumetric sensitivity of
 seismic measurements \citep{MarqueringEtal1999,ZhaoEtal2000,DahlenEtal2000} and by computational advances in the forward
 modelling of seismic wave propagation in fully 3D media \citep{KomatitschVilotte1998,KomatitschEtal2002,CapdevilleEtal2003}.  
@@ -40,16 +26,17 @@
 relation between the measured misfit and the model parameters
 (in terms of partial derivatives or a sensitivity kernel). 
 
-%In order to remain within a domain in which these assumptions are still valid,
 It is common practice in tomography to work only with certain subsets of the
-available seismic data. The choices made in selecting these subsets are inextricably linked to the choice of tomographic method.  For example, ray-based travel-time tomography deals
+available seismic data. The choices made in selecting these subsets are
+inextricably linked to the choice of tomographic method, and are often dictated
+by the assumptions made within the method itself.  For example, ray-based
+travel-time tomography deals
 only with high frequency body wave arrivals, while great-circle
 surface wave tomography must satisfy the path-integral approximation,
 and only considers surface waves that present no evidence of multipathing.
 The emerging 3D-3D tomographic methods seem to be the best candidates for studying
 regions with complex 3D structure. These methods take advantage of
 full wavefield simulations and numeric finite-frequency kernels,
-%the accuracy of which releases tomographers from many of
 thereby reducing
 the data restrictions required when using approximate forward modelling and simplified descriptions
 of sensitivity.  3D-3D tomographic methods require their own specific data selection strategies.
@@ -66,13 +53,11 @@
 the waveform that are dominated by noise.  We define noise as any signal that
 cannot be modeled using physically reasonable values of the simulation
 parameters.
-%It is important to note that by this definition
 Thus,
 what we consider
-to be noise varies with our simulation abilities.  For example:
-%body waves are noise for surface wave simulations;
+to be noise varies with our simulation abilities.  For example,
 short period signals are noise for long
-period simulations; multiple scattering and coda signals are noise for most
+period simulations, while multiple scattering and coda signals are noise for most
 waveform simulation methods, including the spectral element method \citep{KomatitschEtal2002} we use for adjoint tomography.
 
 The adjoint kernel calculation procedure allows us to measure and use for

Modified: seismo/3D/automeasure/latex/method.tex
===================================================================
--- seismo/3D/automeasure/latex/method.tex	2008-05-20 04:29:01 UTC (rev 11985)
+++ seismo/3D/automeasure/latex/method.tex	2008-05-20 12:37:39 UTC (rev 11986)
@@ -97,7 +97,7 @@
 where the use of $T_0$, the low-pass corner period of our band-pass filter,
 substitutes that of the dominant period.  
 
-An example of a synthetic seismogram and its corresponding STA:LTA timeseries $E(t)$ is
+An example of a synthetic seismogram and its corresponding envelope and STA:LTA timeseries $E(t)$ is
 shown in Figure~\ref{fg:stalta}.  Before the first arrivals on the synthetic
 seismogram, the $E(t)$ timeseries warms up and rises to a plateau.  At each
 successive seismic arrival on the synthetic, $E(t)$ rises to a

