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Merged time
series of chlorophyll-a data from full-resolution Aqua-MODIS, SeaWiFS and
Terra-MODIS data are created for the
Wimsoft (http://wimsoft.com) is used in generating the merged and mapped data products. A tutorial explaining the procedures is available here.
The processed files are
available from
http://spg.ucsd.edu/Satellite_data/Scotia_Sea/.
Please note that the files are not available through FTP but through HTTP. For
downloading multiple files at once you can use the widely available utility
wget (e.g.
http://www.gnu.org/software/wget/).
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Two Mercator
projections generated with the Terascan (SeaSpace Corp) utility master were chosen as standard maps for
respectively, Regional and Local view of the area. The Regional view has the following
parameters: center_lat=59S, center_lon=55W,
num_lines=1100, num_samples=1280,
pixel_width=1.0, pixel_height=1.0. The Local
view has the following parameters: center_lat=61S, center_lon=57.5W, num_lines=704, num_samples=824, pixel_width=1.0,
pixel_height=1.0. The sample images below are in the larger, Regional view.
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Mapped composites
were generated for both sensors for each calendar day using all available
passes with a WAM utility wam_l2_map.
Level-2 flags ATMFAIL,
LAND, HIGLINT, HILT, HISATZEN, STRAYLIGHT, CLDICE,
HISOLZEN, HITAU, LOWLW, CHLFAIL, NAVWARN, CHLWARN, DARKPIXEL, SEAICE, NAVFAIL were used to eliminate low-quality pixels. Other
flags (BADANC, COASTZ, NEGLW, COCCOLITH, TURBIDW,
ABSAER, TRICHO, MAXAERITER, MODGLINT, ATMWARN, FILTER, SSTWARN, SSTFAIL) were ignored.
It was found that the pixels marked with the latter flags were statistically
not different from neighboring pixels while their elimination would have decreased
the amount of usable data. In addition to eliminating the flagged pixels, the
cloud image determined with the flag CLDICE was dilated (expanded) to eliminate contaminated
pixels near cloud edges. Cloud edges are often associated with erroneously high
chl-a values. The resulting mapped daily composite was
saved as HDF with the standard chlorophyll log-scaling. In addition, a 2-times reduced and annotated JPEG quick-look was saved as
well. The filename pattern (e.g. S2004001_chl_a_mapped.hdf and S2004001_chl_a_mapped.jpg
for SeaWiFS) shows the year, the Julian day of the year and the variable. For
Aqua the first letter of the filename is “A”. Additional information is stored
as HDF attributes.
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When applied to
MODIS-Aqua data the utility wam_l2_map
produces both chl and SST daily mapped composites using all available passes
during the calendar day (using UTC time). Whereas ocean color data is available
only during light period of the day, infrared SST data is also available during
night. It was found that SST data derived from processed MODIS-Aqua Level-2
datasets had considerable differences between different passes, due to natural
diurnal variability and/or unresolved observation effects (e.g. viewing angle).
As a result, composited daily SST images look patchy and unnatural. I will try
to refine the SST compositing process, e.g. by eliminating passes with large
viewing angles or imposing other restrictions.
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For the
2002-2004 time period both MODIS-Aqua and SeaWiFS were
available. Daily datasets from both sensors were composited into merged images
with a WAM utility wam_composite_2sensors.
The same naming convention was used, except the first letter of the filenames
was replaced with “C”. The following is a sample image from January 28, 2004. A
complicating issue is the different resolutions of SeaWiFS data. SeaWiFS MLAC
(1 km) data was not always available during the time of SeaWiFS regular
operations (1997-2005) and therefore GAC (4-km) data had to be used. Starting
from the end of Decmber, 2005 only GAC SeaWiFS data
is available (with a delay). When merging Aqua 1-km data with SeaWiFS 4-km
mapped data, Aqua data were given precedence.
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As daily images
are largely covered by clouds, multi-day composites have to be used. As the
first step, 5-day composites were created using either the single sensor daily
composites (SeaWiFS MLAC or GAC or Aqua-MODIS) or the SeaWiFS-Aqua combined
daily composites. The 5-day composites were created with the WAM utility wam_composite_5day. This created 2 types
of HDF files: composited average concentration images and count images (the
number of valid pixels used for averaging each pixel). The filename pattern
(e.g. C2004001_C2004005_chl_a_comp.hdf and 2004001_S2004005_chl_a_count.hdf)
shows the start year and day and the end year and day of compositing. For each
average image a 2-times reduced JPEG quick-look was created as well. The
following example shows a 5-day average for January 26-30, 2004. Note the
increased coverage compared to the previous daily image.
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As even the
5-day composites are partly blank due to clouds, 15-day, 30-day and 60-day compositings were performed with a WAM utility wam_composite_2x. This process averages adjacent
5-day composites, e.g. for days 1-5, 6-10 and 11-15. The filename pattern is
similar to the 5-day composites (e.g. C2004001_S2004015_chl_a_comp.hdf) and
shows the year, start and end days of compositing. The reduced JPEG image is
also saved. The following example shows a 15-day average corresponding to the
previous daily and 5-day examples.
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An interactive
web-based utility using ASP.NET can be used to show any of the two images
(5-day, 15-day, 30-day) simultaneously and can be
accessed at http://spg.ucsd.edu/Show2SetsOfImages/Show2SetsofImages.aspx. First you need to pick the category of image (“Pick 1st image of:”) and then
the individual image in that category. Then you can do the same for the 2nd
image. The images shown in the browser are compressed. You can download the
full-resolution JPEG images by right-clicking on the image and choosing “Save Picture As:”.
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The 1-km daily,
5-day and 15-day images are all available as HDF or JPEG. The HDF files have
the numerical values for each pixel and can be used to generate statistics for any
selected area. The HDF files can be read with any HDF-aware software (e.g.
Matlab, IDL, and WIM). When read with WIM the geo-location and scaling are
automatically retrieved. For geo-location with other software the latitude and
longitude arrays corresponding to each pixel must be created.