SIBER SPIS sept 2011.pdf - IMBER

SIBER
Science Plan and Implementation Strategy
a more concerted effort to specifically apply the insight these products can provide to the
IO must be targeted. Basic characterization of the typical seasonal cycles of ecological and
biogeochemical processes in equatorial waters is critical, particularly as a comparative baseline
for determining how the annual variability is altered on intra- and interannual timescales (i.e.
by MJO and IOD). These analyses can potentially be augmented by India’s OCM (Ocean
Color Monitor) sensors on Oceansat-1 and 2 and by ESA’s MERIS sensor.
Ocean color measurements have also been used in studies of regional and basinwide biological
response to climate change (Goes et al., 2005; Gregg et al., 2005). Additional studies along
these lines should be motivated. Presumably, climate change is differentially impacting the
sub-basins of the IO; e.g. what regions of the IO are warming fastest, and how are chlorophyll
concentrations and productivity responding to these changes At some level, retrospective
remote sensing studies can also be focused on anthropogenic impacts in coastal waters,
e.g. true color imagery can be used to characterize long-term trends in terrigenous inputs to
coastal zones around the IO rim (e.g. Fig. 4, r i g h t p a n e l). In addition to chlorophyll, standard
ocean color products provided by the NASA-Goddard DAAC such as diffuse attenuation,
CDOM, POC and FLH (fluorescence line height) can be employed to investigate interannual
to interdecadal variation in these properties that can be of particular relevance for coastal
regions impacted by riverine influence.
Satellite ocean color data (SeaWiFS, MODIS-Aqua and OCM) have already revealed striking
contrasts in the chlorophyll distributions and seasonal cycles between the AS and the BoB
(Lévy et al., 2007; Wiggert et al., 2006). However, specific comparative remote sensing
studies that focus on the differences in the ocean color variability between the AS and the
BoB have not been undertaken. Satellite SST, SSH and SSS measurements can/should be
similarly analyzed focusing on differences in the physical variability (upwelling, filaments,
eddy structures, etc.) between the two regions. Combining ocean color, SST and SSH
remote sensing measurements provides potential means to study, for example, differences
in upwelling signatures between the AS and the BoB, e.g. it may be possible to “see” and
characterize cryptic upwelling variability in the BoB because upwelling and eddies that do not
outcrop at the surface should have a strong signature in SSH but a weak signal in SST and
ocean color. Remote SSS measurements can also be combined with ocean color, SST and
SSH to study differences in the freshwater inputs and sea surface density variability between
the AS and the BoB and how this impacts biological response. Satellite remote sensing can
also be gainfully applied to study atmospheric transport, i.e. transport of dust during the SWM
and anthropogenic pollutants particularly during the NEM.
Atmospheric correction problems are still a significant issue for ocean color measurements,
especially in the northern AS where SWM-period aeolian dust loadings are a particular concern
(Banzon et al., 2004). Efforts need to be made to develop better atmospheric correction
algorithms that are specific to the IO.
Although it is not possible to directly detect and survey protozoan, metazoan and higher trophic
level species using satellites, remote sensing can provide useful data. Satellite-derived SST
data can be used to define thermal regimes for micro- and mesozooplankton species. Ocean
color data are particularly useful because they provide the means to map phytoplankton
distributions, i.e. the food source of zooplankton. In general, zooplankton biomass increases in
proportion to phytoplankton biomass, and zooplankton composition may, with study, be found
to vary with chlorophyll concentration in predictable ways. This linkage between phytoplankton
and zooplankton (and often also larval fish) is particularly well defined in strongly advective
regimes, e.g. in filaments where coastal water with high chlorophyll concentration is rapidly
advected offshore and in eddies (e.g. Logerwell and Smith, 2001). Satellites should, in particular,
be employed in combination with in situ process studies that seek to define relationships
between food web parameters and large-scale physical and biological (chlorophyll) patterns.
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