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The best view of the ocean, of course, is from space. So scientists have
long launched satellites hundreds of miles above the Earth’s surface hoping
to gain a better view of the ocean. A variety of sensors have been placed
on satellites to measure the land, ocean and atmosphere of the Earth,
but the most common oceanographic datasets available are:
- Sea surface temperature (SST),
- Ocean color, including chlorophyll concentration, turbidity (sediment
concentration), and so-called “true color” or “RGB” images that resemble
a photograph taken from space,
- Sea surface height (SSH) and height anomalies (SSA) which is the difference
from climate norms and is useful for determining “geostrophic” currents,
and
- Satellite-derived atmospheric winds.
Satellite data is primarily map-based in nature. Hence most visualization
interfaces focus on generating static maps over designated regions. Sometimes
maps are generated at irregular intervals corresponding to when the satellite
passes over a given area. For geo-synchronous satellites (like the GOES
weather satellites) maps are generated at more regular intervals. Additionally,
because clouds often block the ocean from the satellites’ view scientists
will construct daily or monthly “composites,” which is similar to averaging.
They my also do this to study long-term changes. A climatological average,
which is calculated from many years of data, often several decades, can
be used to generate “anomaly” plots, which show the difference between
a certain time and what one would expect based on its long-term average.
When viewed as an animation, composites, means or anomaly plots can help
show seasonal or multi-year trends.
- NOAA
Coast Watch
The national Coast Watch site features a simple interface for searching
their extensive satellite image library, which includes SST, Ocean Color
and Satellite Winds from a number of pre-defined regional areas, including
many US coastal zones.
- Near-Real-Time
Image Distribution Server
This well-designed site from NASA’s Jet Propulsion Laboratory provides
global and regional real-time images of SST, SSH, winds, and ice cover,
presented in an easy to use site.
- East
Coast SST & Ocean Color
Rutgers Coastal Ocean Observation Lab’s satellite page features quick
access to real-time and archived SST and Ocean Color maps for over 20
regional East Coast areas (of varying sizes). Archived data for some
areas date back to 1993 (i.e. New York Bight). Some areas also have
daily composites available that simplify the number of images available
and may be easier to interpret for younger audiences looking at long-term
trends. SST/Codar Overlay maps (see surface currents below) are also
available for the NJ coast and NY Harbor, and can be used to demonstrate
how oceanic “fronts” can show up in both SST and surface currents.
- California
SST & Ocean Color
This Scripps site features an easy interface to access recent real-time
SST and Chlorophyll maps for several regions in California.
- Florida/Caribbean
SST & MODIS
IMaRS at USF features several tools for viewing SST and Ocean Color
data, including the ability to import any of their maps into Google
Earth. When viewing an SST map, a user can click on a point to obtain
its temperature value. Users can also create their own customized monthly
SST animations. The MODIS data archive includes SST, Chlorophyll and
True Color maps for regions covering much of the east coast.
- NASA
Earth Observatory
This new site from NASA features global SST and Chlorophyll maps which
can quickly be browsed using their online map interface, or the maps
can be viewed using Google Earth. Monthly composites are available and
are recommended for educational purposes, as they are easier to interpret,
especially when studying global patterns.
- Earth
Observatory Global Animations
NASA’s premiere public data site includes several tools for browsing
datasets like SST, Chlorophyll, SSH and more. Much of the data is not
in real-time, but is generally available within a few months. Students
can use this site to easily generate custom animations to study global
patterns.
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