Table of Contents
- 1. Research Setting
- 2. Primary Research Question
- 3. Investigation Plan
- 4. Data Access and Visualization Methods
- 5. Preliminary Analysis
- 6. Refinement of Analysis
- 7. Statement of Results
- 8. Discussion of Results
- 9. Statement of Conclusions
- 10. Questions for Further Investigation
1. Research Setting
The research setting for this tutorial is the Pacific Ocean adjacent to
the central coast of California and Monterey Bay.
The primary oceanographic feature in this area is the California
Current, a cold-water current that flows from north to south along the coast of
California. The current interacts extensively with the coast, causing the
occurrence of periodic upwelling events that are observed as "jets" that
originate near the shore and extend a large distance offshore in just a few
days. Because of the highly variable nature of the California Current, it has a
fairly complex structure in ocean color images.
This SeaWiFS chlorophyll concentration image, provided by the University
of California - Santa Cruz, shows a "jet" south of Monterey Bay, the
semi-circular bay just south of 37 degrees North. The southern end of San
Francisco Bay can be seen at the top of this image.
2. Primary Research Question
In this tutorial, we are examining an area that has moderate to heavy
cloud cover at times, especially in the winter, to determine what effects, (if
any) can be perceived in the monthly average SeaWiFS ocean color data that is
used in Giovanni. (Note: in the future, Giovanni may include data products with
higher temporal resolution; see the final section, "Questions for Further
Research", for more on this possibility.) This area also has a large amount of
variability in ocean color, as noted above. So the primary research question
can be phrased:
Does the persistent presence of cloud cover affect the
quality of ocean color data in an area which has a large amount of
3. Investigation Plan
For this investigation, we will utilize 9km monthly SeaWiFS chlorophyll
concentration data that are available in Giovanni. We will examine patterns
over several years, one year, and one month, to see how the variability of
ocean color data in this region appear in the chlorophyll concentration data.
We will also look at some of the daily images of the area from one month to get
an idea of how cloud cover may influence the data.
4. Data Access and Visualization Methods
The SeaWiFS 9 km chlorophyll data are processed into monthly files
containing the average chlorophyll concentration for each 9 x 9 km "square"
area over the world's oceans. Giovanni accesses these files and provides the
capability of selecting areas of interest for examination. Giovanni can be used
to create a map of the chlorophyll concentrations for the area averaged over
selected time intervals, concentration vs. time plots for chlorophyll
concentration (averaged over the entire selected area), month-by-month
animations of the data for the selected area, or Hovmoller plots for the
Hovmoller plots can be particularly useful data visualizations to detect
variations over time and space. Hovmoller plots display data in a time vs.
longitude or time vs. latitude format. Thus, for the same area, a comparison of
the spatial variability over time is easy to comprehend.
5. Preliminary Analysis
The first thing to do is to define the area and then see what the data
look like averaged over a single year. So we will define the area around
Monterey Bay using a box with a northern latitude boundary of 37.5 degrees
North, a southern latitude boundary of 36.0 degrees North, a western longitude
boundary of 124.0 degrees West, and an eastern longitude boundary of 121.0
degrees West. Then we request Giovanni to plot the chlorophyll concentrations
for the year 2003 for this region:
Monterey Bay is the semi-circular bay approximately in the center of the
image. This image is a good start, but looking at it, only the concentrations
close to the shore are higher than 2.5 milligrams per cubic meter. So now we
can customize the color palette to see what the same plot looks like with a
palette ranging from 0.1 to 2.5 milligrams per cubic meter:
This palette choice gives a good indication of the variability at a
distance offshore, but because the concentrations are higher near the shore,
they are all swallowed up in the magenta color that indicates concentrations
higher than 2.5 mg per cubic meter. So let's try an alternative palette that is
better suited for the higher concentrations nearer to the coast:
In this image, the variability of the lower concentrations offshore is
lost in the purple haze, but the variability nearer to the coast in the higher
concentrations is clearer. These images illustrate the importance of tuning the
color palette to see features and patterns of interest. We'll return to this
point a bit later.
Now that the area and the data have been visualized, let's look at the
patterns of productivity using Hovmoller plots. Since we've just looked at the
average concentrations over 2003 in an area plot, we'll use a Hovmoller
longitude vs. time plot for 2003 next:
Because the California coastline is aligned north to south, the
longitude vs. time plot is a little easier to interpret. The angle of the
coastline actually allows us to examine the temporal dynamics of two different
areas in the same plot! The area from 122.1 W to 121.8 W is primarily the
Monterey Bay area; the area from 122.4 to 122.7 W is further up the coast, just
south of the mouth of San Francisco Bay. Looking at the plot above, and the
previous area plot for 2003, it appears that there's more productivity near the
mouth of San Francisco Bay than around Monterey Bay.
Now let's look at the Hovmoller plot for several years, from January
1998 to December 2003:
This plot indicates that 2003 was a bit strange; there is actually a lot
more "action" in the Monterey Bay region than the region south of the San
Francisco Bay outlet. There appears to be a basic pattern of lower productivity
in the winter, and higher productivity in the spring, summer, and fall,
generally highest in the summer. This could be due to several factors, such as
warmer temperatures, more sunlight, less clouds, and possibly some strong
wind-mixing events similar to what occurs in the Gulf of Panama. Examining the
possible causes of this pattern would be interesting, but that is not the main
goal of this tutorial.
6. Refinement of Analysis
In this section, a closer examination of data from one month - December
2003 - will be performed, and this will also include a closer look at the type
of data Giovanni is using for analysis, a mapped monthly average data product
of SeaWiFS chlorophyll concentration data.
Below is an image of the data for December 2003, produced using the
palette that was employed above for the Hovmoller plots.
Not very interesting!! So now we'll try the default palette to
see if a better choice can be determined:
This plot is considerably better. And it shows that there are only some
small areas with concentrations above 2.5 mg per cubic meter, so now we can try
the first color palette that we used earlier:
It's hard to tell whether the default palette or the customized palette
provides more information in this case. In either case, it can be seen that
there is a pattern of higher concentrations near the coast, and lower
concentrations offshore, with some small patches of higher concentrations. And
this plot looks a bit scattered, doesn't it?
There is a very good reason for the scattered appearance of the December
2003 plots. And the reason is: CLOUDS. December is a particularly foggy and
cloudy month off the coast of California, so SeaWiFS does not observe the
surface of the ocean every day. Because of the clouds, SeaWiFS may not observe
any of the region on a given day, or it may only observe parts of the
The images below are called "browse" images: they allow researchers to
take a look at the data for a given day at low resolution, to determine if they
would like to get the data file for that day. This type of data file can be
processed into the highest possible spatial resolution available for SeaWiFS
data, which is 1 kilometer at the center of the instrument's scanning swath
(also called the nadir point of the swath). Although SeaWiFS observes a
region almost every day, on some days the region is near the center of the
scanning swath, and on other days the same region may be near the edge of the
scanning swath. All of these factors affect the quality of the data.
Not every browse image for December 2003 was chosen for this tutorial;
these images provide an overview of the types of cloud conditions that were
occurring during the month. The letters "MB" were placed on each image close to
the location of Monterey Bay. In some of these images Vancouver Island can be
seen at the top (north); in other images the Baja Peninsula can be seen at the
December 3, 6, 7, and 8 (left to right): Fairly clear views of
the region on the 7th and 8th, but on the 3rd only the area south of the bay
was visible, and on the 6th only a small area offshore.
December 12, 14, 15, and 17 (left to right): December 14 and 15
were pretty good days to see this region, while December 12 and 17 were rather
December 18, 25, 27, 29 (left to right): Only a small region was
observable south of Monterey Bay on the 18th. Broken clouds were present on the
25th, and clear observations were made on the 27th. Two days later on the 29th,
the region was entirely clouded over.
So what does this mean for the quality of the data? The SeaWiFS Project
produces monthly average data products used by Giovanni through a process
called "binning". A simple explanation for binning is that any observation for
a particular spot on the ocean surface will be placed in the bin for that spot:
the bins are 9 km by 9 km, but the observations are at a higher spatial
resolution. A daily "bin" will thus hold a few observations (note that SeaWiFS
observes some places more than once a day at high latitudes). An 8-day bin will
hold all of the observations acquired over a period of 8 days, and a monthly
bin will hold all of the observations acquired in a month. To produce the data
in the monthly products, all of the observations in the bin for a given month
are averaged together.
In an area with high variability in chlorophyll concentrations and a
considerable amount of cloud cover, this process means that a high
concentration "feature" could either dominate the average, or be nearly lost in
the average. If a high concentration feature was observed on one or two days,
and then clouds covered that area for the rest of the binning period, then the
high concentrations would dominate the average. Alternatively, the high
concentration feature might only be observed once, and then a lot of other days
in which the feature was absent could have provided data, which would
substantially "dilute" the contribution of the high concentration feature in
the monthly data. In most cases, the binning process will reduce the
contribution of a short-lived feature, thus reducing the apparent variability
in that region; in a few cases, the binning process could be dominated by
observations of a feature if very little data were acquired when the feature
For December 2003 in the Monterey Bay region, it appears that the data
acquired on December 7 and 8, December 14 and 15, and December 27 -- only five
days in the month -- provides most of the data that Giovanni analyzed for this
month. (There may be data from a few of the other days, of course.) But the
substantial gaps in the data caused by cloudiness mean that most of the
connectedness of features offshore of Monterey Bay will be lost, which probably
accounts for the scattered appearance of the area plots.
If it was possible to see the region clearly every day, we might see the
progression of a "jet" such as the one shown at the begining of the tutorial,
where a productive area develops near the coast and then moves offshore.
SeaWiFS may only observe such a jet on one or two days, so it won't capture the
movement of the jet, only where it was at a particular time.
7. Statement of Results
This tutorial has demonstrated that the monthly data products used by
Giovanni provide an averaged view of chlorophyll concentrations in a given
region. If the region has considerable variability in chlorophyll concentration
and is affected by cloud cover, the averaging (binning) process will tend to
reduce the spatial variability in the data. This means that features which only
last a few days to a week may be difficult to discern in the monthly data.
The monthly data are therefore more suitable for the examination of
patterns in chlorophyll concentration that occur over seasonal, annual, or
This study determined that the Monterey Bay region exhibits a fairly
regular pattern of variability, particularly showing reduced chlorophyll
concentrations during the winter months and elevated chlorophyll concentrations
in the summer months. The spring and fall months had intermediate chlorophyll
concentrations between the low concentrations of winter and the high
concentrations of most summers.
8. Discussion of Results
While this tutorial showed that cloud cover can substantially reduce the
number of observations of a given region in a month, it also shows that a
cloudy month still provides enough data to give a general characterization of
the chlorophyll concentrations in that region. Therefore, use of the data for
the observation of patterns over seasons and years is still quite possible,
even for regions with a lot of cloud cover.
This study also indicates that in order to see features and "events" in
chlorophyll concentration data that last for periods of time considerably
shorter than a month, data products with higher temporal resolution should be
used. Section 10 provides a few questions related to this topic.
9. Statement of Conclusions
- The Monterey Bay region shows a consistent seasonal pattern in
chlorophyll concentration, with higher concentrations in the spring,
summer, and fall (highest in the summer), and lower concentrations in the
- Cloud cover likely affects the resolution of short-lived features in
this region, but is does not appear substantial enough to invalidate the use of
this data for the examination of seasonal and multi-year patterns of
- Color palettes must be chosen with care to allow the best
visualization of chlorophyll concentration data.
10. Questions for Further Research
A few questions related to this tutorial:
- The Hovmoller plot for January 1998 to December 2003 shows that
the year 1998-1999 looks significantly different than the other years.
What event was occurring at this time that could have influenced this
- What is the primary cause of the increased chlorophyll
concentrations, i.e., higher phytoplankton productivity, in the Monterey Bay
region? What data indicate that this is the primary cause?
- Will higher resolution SeaWiFS averaged data products, such as the
8-day data products, show the occurrence of short-lived features in the
California Current system?
- Are jets in the California Current system caused by variability in
the flow of the current, strong winds coming off the coast, or both? What
data can be used to determine the relationship between winds and jets, if a