\documentclass[11pt]{article}
\usepackage{epsf}
\usepackage{multicol} 

\topmargin -0.5in
\oddsidemargin -0.125in
\textwidth 6.5in
\textheight 9in

\def\A{${A}$}
\def\AV{${A_v}$}
\def\AH{${A_h}$}
\def\B{${B}$}
\def\BV{${B_v}$}
\def\BH{${B_h}$}
\def\sigmao{$\sigma^o$\ }
\def\sig{$\sigma^o$~}
\def\signo{$\sigma^o$}
\def\sigo {$\sigma^o$}
\def\sigest {$\widehat{\sigma}^o$}
\def\sigstd {$\kappa$}
\def\polrat {$\gamma$}
\def\deg{^\circ}

\def\doublesp{\large \renewcommand{\baselinestretch}{1.5} \normalsize}
\def\singlesp{\large \renewcommand{\baselinestretch}{1.0} \normalsize}

\begin{document}
\title{Standard BYU QuikScat/Seawinds Land/Ice Image Products}
\author{David G. Long \\
	Microwave Earth Remote Sensing Laboratory\\
	BYU Center for Remote Sensing\\
        Brigham Young University \\
        459 Clyde Building,
        Provo, UT  84602\\
        long@ee.byu.edu \ \ \ (801) 378-4383\\  
	}

\date{Revision 2.0 \\ \today}

\maketitle

\begin{abstract}

Following up on the successful NSCAT mission, the QuikScat/Seawinds scatterometer
(Qscat) provides normalized radar cross section ($\sigma^o$) measurements of the 
Earth's surface at unprecedented coverage and resolution.  While originally
designed for wind observation, scatterometers have proven useful in a variety of 
land and ice studies. To further improve the utility of the data, resolution 
enhancement algorithms have been developed and applied to the data.  These 
algorithms produce images of the surface \sigmao at enhanced resolution (to better 
than 10 km).  This report briefly describes a standard product suite of Qscat 
enhanced resolution image products developed and produced at the 
Brigham Young University (BYU) Microwave Earth Remote Sensing (MERS) Laboratory.

\end{abstract}

\section{Introduction}

Though the mission was cut short by the loss of the host spacecraft, 
the NASA Scatterometer (NSCAT) was an unqualified success.  In addition to 
its primary wind observation mission, NSCAT has also had an impact on a 
variety of polar ice \cite{cryo} and tropical vegetation \cite{long:views} studies.
In particular, NSCAT data is very effective in mapping the extent of
sea ice \cite{quinn}.  It is clear that scatterometers will continue to play
an increasingly important role in monitoring tropical vegetation and polar ice
in the future. 

As a follow-up/replacement for the NSCAT mission, the QuikScat/Seawinds
scatterometer (Qscat) provides measurements of the near-surface ocean wind field with
unprecedented coverage and resolution.  Qscat makes dual polarization measurements of
the normalized radar cross section ($\sigma^o$) at both vertical and horizontal
polarization using a conically scanning pencil-beam antenna (see Fig. 1). 
The \sigmao measurements have demonstrated application in land and 
ice studies (e.g., \cite{ashcraft,longaz,longqscat,stephenh,quinn2}).
The Brigham Young University (BYU) Microwave Earth Remote Sensing (MERS)
Laboratory has developed a standard set of Qscat land/ice image products for
distribution.  This report describes these products.  Both conventional and
enhanced resolution products are included in the product suite.  The enhanced
resolution products are produced with the aid of the Scatterometer Image
Reconstruction (SIR) algorithm described below.

\section{The Scatterometer Image Reconstruction Algorithm}

NSCAT, launched in August of 1996 is a real aperture dual polarization Ku-band 
radar scatterometer designed to measure the \sigmao of the Earth's surface.  NSCAT
made dual-polarization \sigmao measurements over an incidence angle range of
$17^\circ-55^\circ$.  Over the limited incidence angle range of
$\theta\in$[20$\deg$, 55$\deg$], \sig (in dB) is approximately a 
linear function of $\theta$, 
\begin{equation}
\label{eq:siglinear}
\sigma^o(\theta)={A}+{B}(\theta-40^\circ)
\end{equation}
where {\A} and {\B} are functions of surface characteristics, azimuth
angle, and polarization.   {\A} is the incidence-angle normalized \sig value at
40$\deg$ incidence while {\B} describes the dependence of \sigmao on $\theta$. 

NSCAT produces nominally 25 km resolution \sigmao measurements on a 25 km sampling 
grid.  Not originally designed as an imaging sensor, the measurements
are disjoint in the along-track dimension and vary somewhat in shape over the
swath.  Combining multiple passes and using the Scatterometer Image Reconstruction
(SIR) with Filtering (SIRF) algorithm enhanced resolution images of the surface
backscatter can be produced \cite{dyalj}.  The SIR algorithm was originally
developed to enhance
Seasat scatterometer data\cite{long:sirf}. The SIR algorithm has also been used 
with SSM/I radiometer \cite{tgarsdaum} and ERS scatterometer data 
\cite{long:igarss94}.  A number of improvements to the original SIR algorithm
have been developed to optimize its performance for NSCAT \cite{quinn_sirf}.  
The SIRF algorithm applied to
NSCAT data produces both {\A} and {\B} images from the NSCAT \sig measurements. 
The NSCAT SIRF image pixel resolution is nominally 4.45 km with an effective
resolution of 8-10 km \cite{dyalj,cryo,long:views}.

The SIR algorithm is based on a multivariate form of block multiplicative
algebraic reconstruction.  Combining multiple overlapping passes and robust
performance in the presence of noise, it provides enhanced resolution
measurements of the surface characteristics \cite{earlyd:theory}.  To provide a
simple intuitive explanation of the idea behind SIR, consider the following. 
(The incidence angle dependence of \sigmao is ignored in the following
discussion.)  More detailed discussions are contained in \cite{long:sirf} and
\cite{earlyd:theory}.

Let $f(x,y)$ be a function that gives the surface \sigmao at a point
$(x,y)$. The scatterometer measurement system can be modeled by 
\begin{eqnarray}
z= H f + \mbox{noise}
\label{forward}
\end{eqnarray}
where $H$ is an operator that models the measurement system (sample spacing 
and aperture filtering) and $z$ represents the measurements of \sig made by
the instrument sensor. The set of measurements $z$ are a discrete
sampling of the function $f$ convolved with the aperture function (which may
be different for each measurement).   A particular measurement $z_i$ can be
written as
\begin{equation}
z_i=\int\int h_i(x,y) dx dy + noise
\end{equation}
where $h_i(x,y)$ is the measurement response (due, for example, to the antenna
pattern and the Doppler filter response) of the $i$th measurement.  

For resolution enhancement, we are interested in the inverse problem:
\begin{eqnarray}
\hat{f}=\hat{H}^{-1}z
\label{backward}
\end{eqnarray}
where $\hat{f}$ is an estimate of $f$ from the measurements $z$. The inverse of
the operator $H$, $\hat{H}^{-1}$, is exact only if $H$ is invertible and the
measurements are noise free, in which case $\hat{f} = f$.  This represents a
form of resolution enhancement since information in the sidelobes of the
measurement response or aperture function is recovered in the inversion.  In
effect, this is what the iterative SIR algorithm does, producing images at a finer
resolution than the original measurements \footnote{Note that the image products
are produced at a particular {\em pixel} resolution; however, the {\em effective}
resolution of the images is typically coarser by a factor of 2 or depending
on the number of available measurements, the spatial location distribution of the
measurements, temporal variations in the surface, the size of the grid, etc.}.  It
should be noted that SIR is a true resolution enhancement algorithm which extracts
information from the sidelobes of the measurement response function to generate the
final image product \cite{earlyd:theory}; in effect, it is an inverse
reconstruction filter optimized to minimize noise in the reconstructed image.  

While the enhanced resolution {\A} and {\B} images are normally of the most
interest, BYU also produces a number of ancillary image products along with the
enhanced resolution images.  These include non-enhanced images (i.e., {\A} and {\B}
images produced at the intrinsic resolution of the sensor), low resolution browse
images, and quality assurance image products.



\section{Qscat}

Unlike NSCAT which made \sigmao measurements over a broad range of incidence
angles, Qscat makes \sigmao measurements at only two nominal incidence
angles, $46^\circ$ and $54.1^\circ$, corresponding to the inner and outer beams. 
The inner beam measurement is horizontal-polarization while the outer beam is
vertical-polarization. Since it is undesirable to combine measurements from different
polarizations, it is not possible to infer {\B} from the Qscat \sigmao
measurements.  Instead, a single-variate form of SIR similar to the type
developed for radiometer applications \cite{tgarsdaum} is used to generate
enhanced resolution images of \sigmao (which will be termed {\AV} and {\AH}) at
each of the two polarizations and nominal incidence angles of the antenna beams. 

Qscat \sigmao measurements are reported in two forms: termed `eggs' and
`slices' \cite{Qscatusersguide}.  These differ in their spatial sizes and shapes. 
The nominal instantaneous Qscat antenna footprint is an ellipse. However, the
on-board range-doppler processing incorporated within the instrument improves the 
resolution.  Using the on-board processor, twelve individual \sigmao measurements
are obtained for each footprint, though only 8 are reported in the L1B data product.  
These individual measurements are termed `slices'.  The slices are
typically 4-6 km long (depending on the instrument mode and antenna beam) by 20 km
wide.  The summed measurements of the 8 center slices are known as `egg'
measurements and are reported as a standard product.  The effective resolution and
shape of the egg measurement nearly matches the elliptical 3 dB antenna footprint
(approximately 15 km by 25 km depending on the antenna beam and instrument mode). 
Although lower resolution, the egg measurements have less noise are less
sensitive to calibration errors.  Figure 1 illustrates the spatial response functions
of eggs and slices while Fig. 2 illustrate the spatial overlap in the slices.

\section{Standard Qscat Image Products}

As implemented by BYU, a number of standard Qscat image products are produced. 
A description of these follow.   The standard Qscat image set consists of both
SIR enhanced resolution images, as well as non-enhanced images and a number of 
auxiliary data images.  All image products are generated and stored in the
BYU MERS {\bf SIR} file format. 
Viewer and reader programs for the BYU MERS {\bf SIR} file format are available
on line from the BYU MERS web and anonymous ftp sites at URLs 
{\tt http://www.mers.byu.edu/} and
{\tt ftp://ftp.cers.byu.edu/}, respectively.  A standard file naming
convention (described below) is used.

Two main divisions of Qscat data products are produced from the two types of
\sigmao measurements reported by Qscat: 1) slices and 2) eggs.  
Separate SIR resolution enhanced and non-enhanced images are produced from each type
of \sigmao measurement.  The nominal pixel resolution
of the slice-based SIR images is 2.225 km with an estimated effective resolution
of $\sim4$ km.  Egg-based SIR images have a nominal pixel resolution of 4.45 km
with an estimated effective resolution of $\sim8-10$ km.  Slice-based SIR images
have  a nominal pixel resolution of 2.225 km with an estimated effective resolution
of $\sim5$ km. A set of low-resolution  (5 pixels/deg) global browse products are
also produced.

Gridded image products are not resolution enhanced and are produced at
pixel resolution of 5 times the nominal SIR resolution (11.125 km and 22.25 km
for slices and eggs, respectively).  Gridded images are created by accumulating
all of the measurements whose center falls with a given grid element (pixel),
i.e., by the ``binning'' or ``drop in the bucket'' method: for a given grid
element {\A} is generated by averaging all the measurements whose centers
fall within the grid element.  The resulting {\A} values are temporal averages
over the imaging time interval. Since part of the spatial response of the
measurements fall outside of the grid elements (or, bins) the {\em effective}
resolution of the gridded products is somewhat less than the grid sizes.  

To aid in comparison of enhanced resolution and non-enhanced resolution products,
selected gridded products are pixel replicated to produce images with the same
number of pixels as the enhanced resolution products. These images are referred
to as `non' images.  Figure 3 illustrates simulation results for non and SIR
egg and slice images.

Standard products images are made over several standard regions identified by number,
name, and a rectangular box in lat/long (see Table \ref{tab:standardregions} and
Figs. 4 and 5).  Land
images are typically produced in Lambert projection while polar images are
produced in polar stereographic projection.  A list of the standard image regions
is given in Table \ref{tab:standardregions}.  Polar images are based on one day's
worth of data and are produced every day (see Fig. 4).  
Non-polar image products generally use four days of data.
Non-polar images (other than the Bering Sea region) are land
masked and have ocean pixels set to the no-data value (see Fig. 5).  
Figures 6 and 7 compare the resolution of the various products.  Figure 8 shows a sample
of the ancillary image products.

A standardized {\tt SIR} naming scheme (described below) is used which has
key information about the contents of the image file in the file name.


\begin{table}
\centering
\begin{tabular}{l|l|r|r|r|r|c}
Region & Region &\multicolumn{2}{|c|}{Lower-Left Corner} &
\multicolumn{2}{|c|}{Upper-Right Corner} & Region Code \\
Name & Abreviation &Latitude & Longitude & Latitude & Longitude & Number \\ \hline
Antarctic  & Ant  &  -90.0   &     -180.0  &    -52.0   &    180.0 &   100 \\
Arctic     & Arc  &   60.0   &     -180.0  &     90.0   &    180.0 &   110 \\
Greenland  & Grn  &   59.0   &      -74.0  &     84.5   &    -11.0 &   202 \\
Alaska     & Ala  &   50.0   &     -180.0  &     73.0   &   -130.0 &   203 \\
Cntrl-Amer & CAm  &    5.0   &     -115.0  &     30.0   &    -57.0 &   204 \\
North-Amer & NAm  &   25.0   &     -135.0  &     65.0   &    -50.0 &   205 \\
South-Amer & SAm  &  -58.0   &      -83.0  &     15.0   &   -32.0  &   206 \\
North-Afri & NAf  &    2.0   &      -20.0  &     40.0   &     65.0 &   207 \\
South-Afri & SAf  &  -38.0   &        5.0  &     10.0   &     53.0 &   208 \\
Siberia    & Sib  &   50.0   &       60.0  &     75.0   &    180.0 &   209 \\
Europe     & Eur  &   35.0   &      -12.0  &     72.0   &     65.0 &   210 \\
South-Asia & SAs  &    5.0   &       60.0  &     30.0   &    130.0 &   211 \\
Chin-Japan & ChJ  &   25.0   &       60.0  &     55.0   &    150.0 &   212 \\
Indonesia  & Ind  &  -15.0   &       93.0  &     10.0   &    165.0 &   213 \\
Australia  & Aus  &  -48.0   &      110.0  &    -10.0   &    180.0 &   214 \\
Bering Sea & Ber  &   50.0   &      135.0  &     75.0   &   -135.0 &   256 \\
% 311  &    0.0  &      -180.0 &      90.0  &     180.0 &   EASE-north \\
% 312  &  -90.0  &      -180.0 &       0.0  &     180.0 &   EASE-south \\
% 313  &  -85.0  &      -180.0 &      85.0  &     180.0 &   EASE-globe \\
% & 500 & -90.0 & -180.0 & 90.0 & 180.0 & Globe \\
\end{tabular}
\caption{Standard product regions.  The products are produced in a
local radius Lambert projection except for the Antarctic and Arctic regions (region 
numbers 100 and 110) which are produced in polar stereographic form.
\label{tab:standardregions} }
\end{table}

For a given region, the following list of SIR product files are produced for each
beam. Similar products are also produced using the gridding algorithm.  In
addition to SIR enhanced resolution products, an `{em A}' product is also produced
using the SIR-related AVE algorithm (see \cite{long:sirf}) which has 
intermediate resolution.   Each product can be produced
for both slices and eggs unless otherwise indicated. The SIR algorithm is used
for egg processing while the SIR algorithm with filtering (SIRF) is used for
slice processing. The product type is denoted by a one character type designator
in the file name.
\begin{enumerate}
\item[{\bf a:}] {\A} value.  \sigmao value in dB.  For QuikScat/Seawinds slices, the 
nominal reference incidence angles are H-pol (inner beam) $46^\circ$ and V-pol 
(outer beam) $54.1^\circ$.
\item[{\bf C:}] counts. The number of \sigmao measurements which hit the pixel
during the imaging interval. (produced for only slices)
\item[{\bf E:}] mean reconstruction error in dB.  The mean difference between each
measurement which hits the pixel and its forward projection based on the final
image estimate.
\item[{\bf I:}] incidence angle standard deviation in deg.  The standard deviation
is over all the \sigmao measurements which hit the pixel during the imaging
interval.
\item[{\bf J:}] mean incidence angle in deg.  The mean is
over all the \sigmao measurements which hit the pixel during the imaging interval.
\item[{\bf p:}] time image (in minutes from the start of the imaging interval). 
The time value reports the effective time center of the measurements used to
compute the image \cite{gardner}.
\item[{\bf V:}] reconstruction std image (in dB).   The standard deviation of the
difference between each measurement which hits the pixel and its forward
projection based on the final image estimate.  Useful for evaluating temporal
variation in the surface, azimuth modulation, etc.
\end{enumerate}

A sample product listing of the standard products is contained in the Appendix. Table
\ref{tab:sizes} gives the approximate file sizes for the egg-derived product files
for each region.  Slice-derived products are approximately 4 times larger.

\begin{table}
\centering
\begin{tabular}{c|r|c|c|l}
Region & Region Code & SIR/SIRF & Gridded & Region  \\
Abreviation & Number & Image size (MB) & Image size (MB) & Name \\ \hline
Ant & 100  &  7.5 &  3.0 &   Antarctic  \\
Arc & 110  &  4.7 &  1.9 &   Arctic     \\
Grn & 202  &  1.1 &  0.5 &   Greenland  \\
Ala & 203  &  1.0 &  0.4 &   Alaska     \\
CAm & 204  &  2.0 &  0.8 &   Cntrl-Amer \\
NAm & 205  &  4.3 &  1.8 &   North-Amer \\
SAm & 206  &  4.8 &  2.0 &   South-Amer \\
NAf & 207  &  4.8 &  2.0 &   North-Afri \\
SAf & 208  &  3.1 &  1.2 &   South-Afri \\
Sib & 209  &  2.8 &  1.1 &   Siberia    \\
Eur & 210  &  3.2 &  1.3 &   Europe     \\
SAs & 211  &  2.5 &  1.0 &   South-Asia \\
ChJ & 212  &  3.8 &  1.5 &   Chin-Japan \\
Ind & 213  &  2.4 &  1.0 &   Indonesia  \\
Aus & 214  &  3.8 &  1.5 &   Australia  \\
Ber &  256  &  0.1 &  0.1 &   Bering Sea \\
%Glb & 500  &  3.2 &  0.3 &   Globe \\
\end{tabular}
\caption{Approximate Qscat standard product file sizes for egg-derived products in
MB for each region.  Slice-derived products are approximately 4 times larger due
to the higher resolution of the products.
\label{tab:sizes} }
\end{table}

\newpage
\section{User Notes}

This section provides additional specific details regarding the generation and
application of the standard Qscat products.  SIR images are generated from Qscat
L1B files.

In generating enhanced resolution images, the SIR algorithm combines \sigmao
measurements (only measurements from a single beam are combined) from multiple
azimuth angles and (possibly) multiple orbit passes collected over the imaging
period. The resulting images represent a non-linear weighted average of the
measurements.  There is an implicit assumption that the surface characteristics
remain constant over the imaging period.  The effective resolution depends on the
number of measurements and the precise details of their overlap, orientation,
spatial locations.  

\subsection{Quality flags and \sigmao measurements used}

Only \sigmao measurements flagged as `usable' in the Qscat L1B files are included in the
processing. Note that the SIR algorithm forms images in dB space and thus excludes use
of negative \sigmao measurements.  Since most land/ice areas have fairly large
$\sigma^o$, relatively few measurements are excluded.

While 8 slice measurements per pulse are reported in the L1B file, 
the outer slices tend to more noisy than the inner
slices and are more sensitive to calibration/balance problems.  For this reason only the
center 4 slices are currently used in slice image products.
%As a result of the
%higher noise levels (compared to the egg measurements) in the slice measurements,
%slice images are typically made with at least two days of data rather than the one
%used for egg measurements.

\subsection{Ascending/Descending}

Ordinarily, both ascending and descending data passes are combined in creating the
images.  This, in effect, assumes that the surface is essentially the same for both
ascending and descending passes, equivalent to assuming that the diurnal variation
is small since ascending and descending passes are approximately 12 hours apart.  
However, some diurnal variations have been observed, particularly in the polar
regions during peak melting periods.  While the assumption of limited diurnal
variation appears appropriate for most land surface, additional
products will be produced for selected regions and time periods which use
only ascending and descending data.  The naming scheme reflects this.

\subsection{Antenna azimuth angles}

Note that due to the rotation of the antenna, the cross-track density of
\sigmao measurements varies with more measurements at the outer edges of the swath
than at the swath center.  As a result, swath edges are clearly visible in the count
images. 

Note that in producing the images the forward-looking and aft-looking 
measurements are combined  and the resulting average is
over the various azimuth angles of the measurements.  The azimuth angles of the
measurements hitting a given location vary with the pixel location and with time
and may be further affected by missing or low-quality data. 
While most land and sea-ice regions exhibit little variation in \sigmao with
azimuth angle, \sigmao in some regions (notably, parts of East Antarctica) is
dependent on the azimuth angle of the observations.  Since \sigmao measurements from
multiple azimuth angles may be combined, the resulting image value is sensitive to
the azimuth angle distribution of the measurements.  This effect can result in
artifacts near the edge of the swath.  In this area the \sigmao measurements
span a large range of azimuth angles.  Thus, to improve the image quality, 
\sigmao measurements in
the outer edges of each beam's swath are not used to generate the SIR image products.
\sigmao measurements with antenna azimuth angles within $\pm15^\circ$ of orthogoal
to the flight path are discarded prior to applying SIR.  The 
$\pm15^\circ$ threshold was subjectively
chosen based on a tradeoff of computation and image artifact reduction.  While
eliminating far swath \sigmao measurements reduces the swath width somewhat, the
swath width reduction is small and results in a substantial reduction in 
computational time required to generate the enhanced resolution images.

\subsection{Coverage}

QuikScat is in a near-four day repeat orbit.  While 95\% of the Earth's oceans
are covered in one day, the frequency of swath coverage is highly latitude dependent
with most frequent passes near the poles.  (Note that while the V pol beam covers
the exact poles, the H pol beam does not.)  It takes a minimum of two days to
provide complete coverage of the Earth's surface.  For this reason, several
days of data (typically 4, to obtain the maximum diversity) are used for
non-polar regions.  Some special products may use more or less than this.

\subsection{Slice balancing and topographic effects}

Currently, no special calibration correction is applied to the QuikScat L1B \sigmao
measurements.  However, initial studies suggest that improved calibration can be
obtained by so-called egg and slice balancing techniques.  This may be applied
later.

The X factor used in computing the \sigmao measurement from the raw power
measurements is somewhat dependent on the height of the surface. JPL's processing
includes a correction factor to account for this.  The correction is estimated
to be accurate to within 0.15 dB.  A correction is also applied for the measurement
location.  While the spatial response function is somewhat dependent on the surface
height, this dependence is ignored in image formation.

\subsection{Incidence angle correction}

The observed variation in incidence angle of the \sigmao measurements over a given
region is very small, typically less than $0.1^\circ$. For comparison, over
vegetated regions typically \B [the variation in \sigmao with incidence
angle, see Eq. (1)] is $\sim -0.13$ dB/deg.  For ice this may be as large as $0.25$
dB/deg. (Over the ocean ${\cal B}\sim 1$ dB/deg.)  Since only \sigmao measurements from
a given beam are combined and the egg incidence angle variation is small,
incidence angle normalization is felt to be unnecessary
at this time for egg images
and no \sigmao incidence angle correction is made; thus, the image \A~values
correspond to the \sigmao value at the beam incidence angle.  For slice images,
individual slice \sigmao measurements are incidence angle corrected to the
nominal reference angle using a \B value of $\sim -0.13$ dB/deg.
The mean incidence angle ({\bf I}) and the standard deviation ({\bf J}) of incidence
angles of the measurements for each pixel are reported.

%\clearpage 

\section{BYU {\tt SIR} File Format}

The BYU-MERS {\tt SIR} image format was developed by the Brigham Young
University (BYU) Microwave Earth Remote Sensing (MERS) laboratory
to store a variety of types and projections of EArth images along with the
information required to earth-locate the image pixels.

A {\tt SIR} format file consists of one or more 512 byte headers followed by the
image data and additional zero padding to insure the file is a multiple of
512 bytes long\footnote{This ensures that images can be transferred to and from
all platforms without loss using binary ftp.}.  The file header record contains
all of the information required to read the remainder of the file and the map
projection information required to map pixels to lat/long coordinates
on the Earth surface.
The image pixel values generally represent floating point values and may be stored 
in one of three ways.  The primary method
is as 2 byte integers (with the high order byte first), though the pixels may be
stored as single bytes or IEEE floating point values.   Scale factors are
stored in the header to convert the integer or byte pixel values to native
floating point units.  The image is stored in row-scanned (left to right) order
from the lower left corner (which is the origin of the image) up 
through the upper right corner.  
By default, the location of a pixel is identified with its lower-left
corner.  The origin of pixel (1,1) is the lower left corner of the image.  The array
index $n$ of the $(i,j)^{th}$ pixel where $i$ is horizontal and $j$ is vertical is
given by $n=(j-1)*N_x+i$ where $N_x$ is the horizontal dimension of the image.
The last pixel stored in the file is at ($N_x,N_y$).

The {\tt SIR} file header contains various numerical values and strings which
describe the image contents. For example, a no-data flag value is set within the header
as well as the nominal display range and the minimum and maximum representable values. 
Optional secondary header records (512 bytes) can be used to
store additional, non-standard information.

The standard {\tt SIR} file format supports a variety of image projections
including:
\begin{enumerate}
  \item Rectangular array (no projection)
  \item A rectangular lat/lon array
  \item Two different types of Lambert equal-area projections which can be 
     used in either non-polar or polar projections
  \item Polar stereographic projections
  \item EASE grid polar projection with various resolutions
  \item EASE global projection with various resolutions
\end{enumerate}
For the Qscat products described here, only the Lambert and polar
stereographic projections are used.

Readers for the {\tt SIR} file format are available in C, FORTRAN, Matlab, and
IDL/PVWAVE.  Viewer and reader programs are available on line 
from the BYU MERS web and anonymous ftp sites at URLs {\tt http://www.mers.byu.edu/}
and {\tt ftp://ftp.cers.byu.edu/pub/sir}, respectively\footnote{The reader code may be 
copied and modified and freely distributed so long as (1) original or modified code is 
not redistributed for profit and (2) acknowledgment is made that the original code was 
obtained from the  Microwave Earth Remote Sensing Laboratory at Brigham 
Young University,  Provo, UT.}.  Documentation for these readers are located there.
Sample files and various utility and display routines are also available.
(Be sure to use binary ftp to transfer {\tt .sir} files!) 

A customized version of {\bf xv} which reads {\tt .sir} files and can convert images
to other forms is also available on this site.  Routines for display in Matlab and
IDL/PV-Wave are available at the site.  Adobe Photoshop can display the
image data {\tt .sir} file stored as two-byte integers.  Read the file as `raw',
specify a 512 header and 16 bit data, and enter the image dimensions in pixels.


\subsection{{\tt SIR} Standard file name format}

Where possible, a standardized file naming scheme for {\tt SIR} format files,
suitable for unix, vms, and windows 9X and above.  The general naming scheme is:
$$
SENS-T-{\bf REG}YR-DY1-DY2.RCN
$$
where $SENS$ is the four character sensor name in Table \ref{tab:sensor},
$T$ is the one character image type code given in Table \ref{tab:type}, ${\bf
REG}$ is a region identifier string, $YR$ is a two digit year code, $DY1$ and
$DY2$ are the three digit Julian day-of-the-year of the data used to make the image, and
$RCN$ is the reconstruction type file extension given in Table \ref{tab:rcn}. 
A number of three character region identification strings are listed in Table
\ref{tab:region}.  Special product files may use other longer strings for the
region name.  Optionally, additional file extensions may be appended to the
standard name to denote a post-processed image (see Table \ref{tab:extension}).

\begin{table}
\centering
\begin{tabular}{c|l}
$SENS$ & Sensor \\ \hline
	ers1 & ERS1 AMI scatterometer mode\\
	ers2 & ERS2 AMI scatterometer mode \\
	F$XXY$ & SSM/I F$XX$ channel index $Y$ \\
	nsDP & NSCAT\\
        q$DEP$ & QuikScat/Seawinds\\ 
	sasP & SASS \\
	trmm & TRMM PR surface \sigmao \\
\end{tabular}
\caption{Standard sensor strings for {\tt SIR} file names.
Special symbols $XX$, $Y$, $D$, $E$, $G$, and $P$ are defined in Tab. \ref{tab:sens2}.
\label{tab:sensor} }
\end{table}


\begin{table}[b]
\centering
\begin{tabular}{c|c|l}
$T$ (type) & Code Number & Description \\ \hline
 	a & 1 & {\A} image (\sigmao in dB at reference incidence angle) \\
% 	b & 2 & reserved \\ % {\B} image (slope of sigma-0 in dB/deg) \\
% 	c & 4 & reserved \\ % \C image (2nd order curvature of sigma-0 in dB/deg**2)
	 C & 8 & counts or hits (measurements) per pixel \\
% 	d & 5 & reserved \\ % \D image (3rd order curvature of sigma-0 in dB/deg**3)
	E &21 & average reconstruction error image (dB) \\
%	h &19 & height (in m) \\
 	I & 7 & incidence angle standard deviation (in deg)  \\
 	J & 9 & average incidence angle (in deg) \\
 	m & 0 & mask image \\
% 	N & 6 & counts of negative \sigmao values \\
	p &11 & pixel time estimate (min from start of image interval)\\
%	q &32 & magnitude of 1st harmonic of azimuth modulation (dB) \\
%	r &33 & phase angle of 1st harmonic of azimuth modulation (deg) \\
%	s &34 & magnitude of 2nd harmonic of azimuth modulation (dB) \\
%	S &12 & counts of small \sigmao values \\
%	t &35 & phase angle of 2nd harmonic of azimuth modulation (deg)\\
%	T &3  & $T_b$ brightness temperature (in K) \\
%	u &36 & standard deviation image w/Az mod removed (dB) \\
%	v &10 & vegetation index \\
	V &22 & reconstruction error standard deviation image (dB) \\
%	W &16 & mean wind speed image (m/s) \\
	x & 3 & longitude image (deg) \\
	y &31 & latitude image (deg) \\
%	Y &17 & wind speed standard deviation image (m/s) \\
\end{tabular}
\caption{Selected standard type codes for {\tt SIR} file names \label{tab:type} }
\end{table}

\begin{table}
\centering
\begin{tabular}{c|l|l}
Symbol & Valid Values & Definition  \\ \hline
 $XX$ & 10-14 & DMSP platform identifier \\
 $Y$  & 1-7   & SSM/I channel number (19H, 19V, 22, 37H, 37V, 85H, 85V)\\
 $D$  & c,u,a,d & Ascending/descending indicator \\
      &  & c: Both ascending and descending data used \\
      &  & u: Both ascending and descending data used \\
      &  & a:\ \ \ Ascending data only used \\
      &  & d:\ \ \ Descending data only used \\
 $E$  & e,s & Ascending/descending indicator \\
      &  & e: QuikScat egg \sigmao measurements \\
      &  & s: QuikScat slice \sigmao measurements \\
 $P$  & h,v & Polarization 
\end{tabular}
\caption{Standard sensor string characters used in standard file naming scheme in
Tab. \ref{tab:sensor}. \label{tab:sens2} }
\end{table}

\begin{table}
\centering
\begin{tabular}{c|l}
$RCN$ & Standard reconstruction technique  \\ \hline
	.sir & SIR or SIRF algorithm \\
	.ave & AVE image algorithm \\
	.non & non-enhanced \\
	.grd & gridded \\
	.brw & low resolution gridded browse image\\
%	.lis & ascii information file \\
\end{tabular}
\caption{Standard reconstruction algorithm extensions for {\tt SIR} file names
\label{tab:rcn} }
\end{table}



\begin{table}
\centering
\begin{tabular}{l|l}
Extension & Description \\ \hline
.lmsk  & land masked data image \\
.imsk  & Ice masked image \\
.omsk  & Ocean masked image \\
.dif   & Difference image \\
.sr    & Subregion extracted image \\
.ed    & Manually edited image \\
.lmask & binary land mask image \\
\end{tabular}
\caption{Standardized extra file extensions for {\tt SIR} file names.  These are
optional.
\label{tab:extension} }
\end{table}


\begin{table}
\centering
\begin{tabular}{c|c|l}
${\bf REG}$ & Code Number & Description \\\hline
%	Ama &  1 &Amazon\\
	Ant &100 &Antarctica\\
	Arc &110 &Artic\\
	Grn &202 &Greenland\\
	Ala &203 &Alaska\\
	CAm &204 &Central America \\
	NAm &205 &North America \\
	SAm &206 &South America \\
	NAf &207 &North Africa\\
	SAf &208 &South Africa\\
	Sib &209 &Siberia\\
	Eur &210 &Europe\\
	SAs &211 &South Asia\\
	ChJ &212 &China-Japan\\
	Ind &213 &Indonesia\\
	Aus &214 &Australia\\
	Ber &256 &Bering Sea\\
%        Glb &500 &Globe\\
\end{tabular}
\caption{Standard three character region abbreviation strings for {\tt SIR} file names
\label{tab:region}} 
\end{table}
 



\newpage


\begin{thebibliography}{1}

\bibitem{ashcraft}
I.S.~Ashcraft and D.G.~Long, ``SeaWinds Views Greenland,'' {\em  Proc. Int.
Geosci. Rem. Sens. Sym.}, Honolulu, Hawaii, 6-10 July, 200.

\bibitem{earlyd:theory}
D.S.~Early and D.G.~Long,``{Enhanced Resolution Imaging From Irregular
Samples},'' to appear, {\em IEEE Trans. Geosci. Remote Sens.}, 2000.

\bibitem{dyalj}
J.~Dyal and D.G.~Long, ``NSCAT Views the Earth,'' MERS Technical Report, \# MERS
97-004, Brigham Young University, 21 Oct. 1997.  Available on the
web at {\tt http://www.mers.byu.edu/Papers/mers\_reports.html}

\bibitem{longaz}
D.G.~Long and M.R.~Drinkwater, ``Azimuth Variation in Microwave Scatterometer 
and Radiometer Data Over Antarctica,'' {\em  IEEE Trans. Geosci. Remote Sens.}, 
Vol. 38, No. 4, pp. 1857-1870, 2000. 

\bibitem{longqscat}
D.G.~Long, ``Land and Ice Applications of SeaWinds Data,'' {\em  Proc. Int.
Geosci. Rem. Sens. Sym.}, Honolulu, Hawaii, 6-10 July, 200.

\bibitem{long:sirf}
D.G.~Long, P.~Hardin, and P.~Whiting, ``{Resolution Enhancement of Spaceborne
Scatterometer Data},'' {\em IEEE Trans. Geosci. Remote Sens.}, vol. 31,
pp. 700--715, 1993.

\bibitem{long:igarss94}
D.G.~Long, D.~Early, and M.R.~Drinkwater, ``Enhanced Resolution ERS-1
Scatterometer Imaging of Southern Hemisphere Polar Ice,'' {\em  Proc. Int.
Geosci. Rem. Sens. Sym.}, Pasadena, California, 8-12 August, pp. 156--158, 1994.

\bibitem{tgarsdaum}
D.G.~Long and D.~Daum,``{Spatial Resolution Enhancement of SSM/I Data},''
{\em IEEE Trans. Geosci. Rem. Sens.}, vol. 36, pp. 407--417, 1997.

\bibitem{cryo}
D.G.~Long and M.R.~Drinkwater, ``Cryosphere Applications of NSCAT Data,'' 
{\em IEEE Trans. Geosci. Remote Sens.}, Vol. 37, No. 3, pp. 1671-1684, 1999.

\bibitem{long:views}
D.G.~Long, ``NSCAT Views Land and Ice,'' {\em  Proc. Int.
Geosci. Rem. Sens. Sym.}, pp. 1973-1975, Seattle, Washington, 6-10 July, 1998.

\bibitem{quinn_sirf}
Q.P.~Remund and D.G.~Long, ``Optimization of SIRF for NSCAT,'' MERS Technical
Report \# MERS 97-003, Brigham Young University, 3 July 1997.  Available on the
web at {\tt http://www.mers.byu.edu/Papers/mers\_reports.html}

\bibitem{quinn}
Q.P.~Remund and D.G.~Long, ``Polar Sea Ice Extent Mapping Using Ku-Band
Scatterometer Data,'' {\em J. Geophys. Res.}, Vol. 104, No. C5, pp. 11515-11527,
1999.

\bibitem{quinn_qscat}
Q.P.~Remund and D.G.~Long, ``Sea Ice Mapping Algorithm for QuikSCAT and
Seawinds,'' {\em  Proc. Int. Geosci. Rem. Sens. Sym.}, pp. 1686-1688, Seattle,
Washington, 6-10 July, 1998.

\bibitem{quinn2}
Q.P.~Remund and D.G.~Long, ``Iterative Estimation of Antarctic Sea Ice Extent
Using SeaWinds Data,'' {\em  Proc. Int.
Geosci. Rem. Sens. Sym.}, Honolulu, Hawaii, 6-10 July, 200.

\bibitem{stephenh}
H.~Stephen and D.G.~Long, ``Study of Iceberg B10A Using Scatterometer Data,'' {\em  Proc. Int.
Geosci. Rem. Sens. Sym.}, Honolulu, Hawaii, 6-10 July, 200.

\bibitem{gardner}
G.~Watt and D.G.~Long, ``Temporal Average Estimate Algorithm for ERS-1/2,'' MERS
Technical Report, \# MERS 97-07, Brigham Young University, 5 Aug. 1997. 
Available on the web at {\tt http://www.mers.byu.edu/Papers/mers\_reports.html}

\bibitem{Qscatusersguide}
`SeaWinds/QuikScat Users Guide'', SeaWinds Project Office, 
Jet Propulsion Laboratory, Padadena, CA, 1999.

\end{thebibliography}

\clearpage
\newpage

\appendix
\section{Sample Qscat Product Listing}

The following is a sample listing of the egg product files for the h pol
beam.  Similar products are produced for the v pol beam.  Note that files with a
{\tt .non} extension contain the same data as the corresponding {\tt .grd} file
but the gridded data pixels have been replicated to produce images the same size
as the {\tt .sir} images. Browse (low resolution grided data) products 
have a {\tt .brw} extension and are not land or ice masked.  Selected products are
also produced from slices, in which case the sensor prefix is `qus' rather than
`que'.

\begin{multicols}{2}
\noindent
\subsubsection*{Browse Products}
{\tt 
queh-a-Glb99-001-001.brw     \\
queh-V-Glb99-001-001.brw     \\
queh-C-Glb99-001-001.brw     \\
quev-a-Glb99-001-001.brw     \\
quev-V-Glb99-001-001.brw     \\
quev-C-Glb99-001-001.brw     \\
}
\subsubsection*{Enhanced resolution and Grid Products}
{\tt
queh-C-Ala99-001-001.grd.lmsk     \\
queh-C-Ant99-001-001.grd     \\
queh-C-Arc99-001-001.grd     \\
queh-C-Aus99-001-001.grd.lmsk     \\
queh-C-Ber99-001-001.grd     \\
queh-C-CAm99-001-001.grd.lmsk     \\
queh-C-ChJ99-001-001.grd.lmsk     \\
queh-C-Eur99-001-001.grd.lmsk     \\
queh-C-Grn99-001-001.grd.lmsk     \\
queh-C-Ind99-001-001.grd.lmsk     \\
queh-C-NAf99-001-001.grd.lmsk     \\
queh-C-NAm99-001-001.grd.lmsk     \\
queh-C-SAf99-001-001.grd.lmsk     \\
queh-C-SAm99-001-001.grd.lmsk     \\
queh-C-SAs99-001-001.grd.lmsk     \\
queh-C-Sib99-001-001.grd.lmsk     \\
queh-E-Ala99-001-001.sir.lmsk     \\
queh-E-Ant99-001-001.sir     \\
queh-E-Arc99-001-001.sir     \\
queh-E-Aus99-001-001.sir.lmsk     \\
queh-E-Ber99-001-001.sir     \\
queh-E-CAm99-001-001.sir.lmsk     \\
queh-E-ChJ99-001-001.sir.lmsk     \\
queh-E-Eur99-001-001.sir     \\
queh-E-Eur99-001-001.sir.lmsk     \\
queh-E-Grn99-001-001.sir.lmsk     \\
queh-E-Ind99-001-001.sir.lmsk     \\
queh-E-NAf99-001-001.sir.lmsk     \\
queh-E-NAm99-001-001.sir.lmsk     \\
queh-E-SAf99-001-001.sir.lmsk     \\
queh-E-SAm99-001-001.sir.lmsk     \\
queh-E-SAs99-001-001.sir.lmsk     \\
queh-E-Sib99-001-001.sir.lmsk     \\
queh-I-Ala99-001-001.grd.lmsk     \\
queh-I-Ala99-001-001.sir.lmsk     \\
queh-I-Ant99-001-001.grd     \\
queh-I-Ant99-001-001.sir     \\
queh-I-Arc99-001-001.grd     \\
queh-I-Arc99-001-001.sir     \\
queh-I-Aus99-001-001.grd.lmsk     \\
queh-I-Aus99-001-001.sir.lmsk     \\
queh-I-Ber99-001-001.grd     \\
queh-I-Ber99-001-001.sir     \\
queh-I-CAm99-001-001.grd.lmsk     \\
queh-I-CAm99-001-001.sir.lmsk     \\
queh-I-ChJ99-001-001.grd.lmsk     \\
queh-I-ChJ99-001-001.sir.lmsk     \\
queh-I-Eur99-001-001.grd.lmsk     \\
queh-I-Eur99-001-001.sir.lmsk     \\
queh-I-Grn99-001-001.grd.lmsk     \\
queh-I-Grn99-001-001.sir.lmsk     \\
queh-I-Ind99-001-001.grd.lmsk     \\
queh-I-Ind99-001-001.sir.lmsk     \\
queh-I-NAf99-001-001.grd.lmsk     \\
queh-I-NAf99-001-001.sir.lmsk     \\
queh-I-NAm99-001-001.grd.lmsk     \\
queh-I-NAm99-001-001.sir.lmsk     \\
queh-I-SAf99-001-001.grd.lmsk     \\
queh-I-SAf99-001-001.sir.lmsk     \\
queh-I-SAm99-001-001.grd.lmsk     \\
queh-I-SAm99-001-001.sir.lmsk     \\
queh-I-SAs99-001-001.grd.lmsk     \\
queh-I-SAs99-001-001.sir.lmsk     \\
queh-I-Sib99-001-001.grd.lmsk     \\
queh-I-Sib99-001-001.sir.lmsk     \\
queh-J-Ala99-001-001.grd.lmsk     \\
queh-J-Ala99-001-001.sir.lmsk     \\
queh-J-Ant99-001-001.grd     \\
queh-J-Ant99-001-001.sir     \\
queh-J-Arc99-001-001.grd     \\
queh-J-Arc99-001-001.sir     \\
queh-J-Aus99-001-001.grd.lmsk     \\
queh-J-Aus99-001-001.sir.lmsk     \\
queh-J-Ber99-001-001.grd     \\
queh-J-Ber99-001-001.sir     \\
queh-J-CAm99-001-001.grd.lmsk     \\
queh-J-CAm99-001-001.sir.lmsk     \\
queh-J-ChJ99-001-001.grd.lmsk     \\
queh-J-ChJ99-001-001.sir.lmsk     \\
queh-J-Eur99-001-001.grd.lmsk     \\
queh-J-Eur99-001-001.sir.lmsk     \\
queh-J-Grn99-001-001.grd.lmsk     \\
queh-J-Grn99-001-001.sir.lmsk     \\
queh-J-Ind99-001-001.grd.lmsk     \\
queh-J-Ind99-001-001.sir.lmsk     \\
queh-J-NAf99-001-001.grd.lmsk     \\
queh-J-NAf99-001-001.sir.lmsk     \\
queh-J-NAm99-001-001.grd.lmsk     \\
queh-J-NAm99-001-001.sir.lmsk     \\
queh-J-SAf99-001-001.grd.lmsk     \\
queh-J-SAf99-001-001.sir.lmsk     \\
queh-J-SAm99-001-001.grd.lmsk     \\
queh-J-SAm99-001-001.sir.lmsk     \\
queh-J-SAs99-001-001.grd.lmsk     \\
queh-J-SAs99-001-001.sir.lmsk     \\
queh-J-Sib99-001-001.grd.lmsk     \\
queh-J-Sib99-001-001.sir.lmsk     \\
queh-V-Ala99-001-001.grd.lmsk     \\
queh-V-Ala99-001-001.non.lmsk     \\
queh-V-Ala99-001-001.sir.lmsk     \\
queh-V-Ant99-001-001.grd     \\
queh-V-Ant99-001-001.non     \\
queh-V-Ant99-001-001.sir     \\
queh-V-Arc99-001-001.grd     \\
queh-V-Arc99-001-001.non     \\
queh-V-Arc99-001-001.sir     \\
queh-V-Aus99-001-001.grd.lmsk     \\
queh-V-Aus99-001-001.non.lmsk     \\
queh-V-Aus99-001-001.sir.lmsk     \\
queh-V-Ber99-001-001.grd     \\
queh-V-Ber99-001-001.non     \\
queh-V-Ber99-001-001.sir     \\
queh-V-CAm99-001-001.grd.lmsk     \\
queh-V-CAm99-001-001.non.lmsk     \\
queh-V-CAm99-001-001.sir.lmsk     \\
queh-V-ChJ99-001-001.grd.lmsk     \\
queh-V-ChJ99-001-001.non.lmsk     \\
queh-V-ChJ99-001-001.sir.lmsk     \\
queh-V-Eur99-001-001.grd.lmsk     \\
queh-V-Eur99-001-001.non.lmsk     \\
queh-V-Eur99-001-001.sir.lmsk     \\
queh-V-Grn99-001-001.grd.lmsk     \\
queh-V-Grn99-001-001.non.lmsk     \\
queh-V-Grn99-001-001.sir.lmsk     \\
queh-V-Ind99-001-001.grd.lmsk     \\
queh-V-Ind99-001-001.non.lmsk     \\
queh-V-Ind99-001-001.sir.lmsk     \\
queh-V-NAf99-001-001.grd.lmsk     \\
queh-V-NAf99-001-001.non.lmsk     \\
queh-V-NAf99-001-001.sir.lmsk     \\
queh-V-NAm99-001-001.grd.lmsk     \\
queh-V-NAm99-001-001.non.lmsk     \\
queh-V-NAm99-001-001.sir.lmsk     \\
queh-V-SAf99-001-001.grd.lmsk     \\
queh-V-SAf99-001-001.non.lmsk     \\
queh-V-SAf99-001-001.sir.lmsk     \\
queh-V-SAm99-001-001.grd.lmsk     \\
queh-V-SAm99-001-001.non.lmsk     \\
queh-V-SAm99-001-001.sir.lmsk     \\
queh-V-SAs99-001-001.grd.lmsk     \\
queh-V-SAs99-001-001.non.lmsk     \\
queh-V-SAs99-001-001.sir.lmsk     \\
queh-V-Sib99-001-001.grd.lmsk     \\
queh-V-Sib99-001-001.non.lmsk     \\
queh-V-Sib99-001-001.sir.lmsk     \\
queh-a-Ala99-001-001.ave.lmsk     \\
queh-a-Ala99-001-001.grd.lmsk     \\
queh-a-Ala99-001-001.non.lmsk     \\
queh-a-Ala99-001-001.sir.lmsk     \\
queh-a-Ant99-001-001.ave     \\
queh-a-Ant99-001-001.grd     \\
queh-a-Ant99-001-001.non     \\
queh-a-Ant99-001-001.sir     \\
queh-a-Arc99-001-001.ave     \\
queh-a-Arc99-001-001.grd     \\
queh-a-Arc99-001-001.non     \\
queh-a-Arc99-001-001.sir     \\
queh-a-Aus99-001-001.ave.lmsk     \\
queh-a-Aus99-001-001.grd.lmsk     \\
queh-a-Aus99-001-001.non.lmsk     \\
queh-a-Aus99-001-001.sir.lmsk     \\
queh-a-Ber99-001-001.ave     \\
queh-a-Ber99-001-001.grd     \\
queh-a-Ber99-001-001.non     \\
queh-a-Ber99-001-001.sir     \\
queh-a-CAm99-001-001.ave.lmsk     \\
queh-a-CAm99-001-001.grd.lmsk     \\
queh-a-CAm99-001-001.non.lmsk     \\
queh-a-CAm99-001-001.sir.lmsk     \\
queh-a-ChJ99-001-001.ave.lmsk     \\
queh-a-ChJ99-001-001.grd.lmsk     \\
queh-a-ChJ99-001-001.non.lmsk     \\
queh-a-ChJ99-001-001.sir.lmsk     \\
queh-a-Eur99-001-001.ave.lmsk     \\
queh-a-Eur99-001-001.grd.lmsk     \\
queh-a-Eur99-001-001.non.lmsk     \\
queh-a-Eur99-001-001.sir.lmsk     \\
queh-a-Grn99-001-001.ave.lmsk     \\
queh-a-Grn99-001-001.grd.lmsk     \\
queh-a-Grn99-001-001.non.lmsk     \\
queh-a-Grn99-001-001.sir.lmsk     \\
queh-a-Ind99-001-001.ave.lmsk     \\
queh-a-Ind99-001-001.grd.lmsk     \\
queh-a-Ind99-001-001.non.lmsk     \\
queh-a-Ind99-001-001.sir.lmsk     \\
queh-a-NAf99-001-001.ave.lmsk     \\
queh-a-NAf99-001-001.grd.lmsk     \\
queh-a-NAf99-001-001.non.lmsk     \\
queh-a-NAf99-001-001.sir.lmsk     \\
queh-a-NAm99-001-001.ave.lmsk     \\
queh-a-NAm99-001-001.grd.lmsk     \\
queh-a-NAm99-001-001.non.lmsk     \\
queh-a-NAm99-001-001.sir.lmsk     \\
queh-a-SAf99-001-001.ave.lmsk     \\
queh-a-SAf99-001-001.grd.lmsk     \\
queh-a-SAf99-001-001.non.lmsk     \\
queh-a-SAf99-001-001.sir.lmsk     \\
queh-a-SAm99-001-001.ave.lmsk     \\
queh-a-SAm99-001-001.grd.lmsk     \\
queh-a-SAm99-001-001.non.lmsk     \\
queh-a-SAm99-001-001.sir.lmsk     \\
queh-a-SAs99-001-001.ave.lmsk     \\
queh-a-SAs99-001-001.grd.lmsk     \\
queh-a-SAs99-001-001.non.lmsk     \\
queh-a-SAs99-001-001.sir.lmsk     \\
queh-a-Sib99-001-001.ave.lmsk     \\
queh-a-Sib99-001-001.grd.lmsk     \\
queh-a-Sib99-001-001.non.lmsk     \\
queh-a-Sib99-001-001.sir.lmsk     \\
queh-p-Ala99-001-001.grd.lmsk     \\
queh-p-Ala99-001-001.sir.lmsk     \\
queh-p-Ant99-001-001.grd     \\
queh-p-Ant99-001-001.sir     \\
queh-p-Arc99-001-001.grd     \\
queh-p-Arc99-001-001.sir     \\
queh-p-Aus99-001-001.grd.lmsk     \\
queh-p-Aus99-001-001.sir.lmsk     \\
queh-p-Ber99-001-001.grd     \\
queh-p-Ber99-001-001.sir     \\
queh-p-CAm99-001-001.grd.lmsk     \\
queh-p-CAm99-001-001.sir.lmsk     \\
queh-p-ChJ99-001-001.grd.lmsk     \\
queh-p-ChJ99-001-001.sir.lmsk     \\
queh-p-Eur99-001-001.grd.lmsk     \\
queh-p-Eur99-001-001.sir.lmsk     \\
queh-p-Grn99-001-001.grd.lmsk     \\
queh-p-Grn99-001-001.sir.lmsk     \\
queh-p-Ind99-001-001.grd.lmsk     \\
queh-p-Ind99-001-001.sir.lmsk     \\
queh-p-NAf99-001-001.grd.lmsk     \\
queh-p-NAf99-001-001.sir.lmsk     \\
queh-p-NAm99-001-001.grd.lmsk     \\
queh-p-NAm99-001-001.sir.lmsk     \\
queh-p-SAf99-001-001.grd.lmsk     \\
queh-p-SAf99-001-001.sir.lmsk     \\
queh-p-SAm99-001-001.grd.lmsk     \\
queh-p-SAm99-001-001.sir.lmsk     \\
queh-p-SAs99-001-001.grd.lmsk     \\
queh-p-SAs99-001-001.sir.lmsk     \\
queh-p-Sib99-001-001.grd.lmsk     \\
queh-p-Sib99-001-001.sir.lmsk     \\
}
\end{multicols}

\end{document}\end