International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
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Figure 4. Four days' averaged chlorophyll and wind profile
generated from OCM and Quickscat data
Each point represents average of chlorophyll and wind speed
over four consecutive days in bloom waters in NAS (19.75" N
latitude, 66.25? E longitude) for the period January to March
2003. It can be seen that chlorophyll pattern responds to
increasing or decreasing wind speed with time lag of four days
in most cases. There is an exception when there is sudden
increase or decrease in wind speed by a large magnitude.
Response of chlorophyll in accordance with wind force is
observed without any time lag in this case. A sequence of
actions followed by wind force acting on a water mass include
cooling of water mass, increase in density leading to sinking of
surface waters, convection, transport of bottom nutrients to
euphotic zone which, in due course, causes active
photosynthesis. The observed delay in response of chlorophyll
to wind may be attributed to time taken for all these processes.
Scatter of ship measured chlorophyll; SST and wind speed has
been generated in three parts and is shown in Figure 5.
The purpose was to study inter relation between the three
parameters to understand if influence of wind was there on
productivity during the event of bloom. Scatter of wind versus
SST shows an inverse trend over all. This is expected because
as wind speed increases, evaporation of surface water increases
and hence, temperature decreases. However, wind is not the
only factor influencing surface temperature and hence, it is not
proper to attempt polynomial fit.
Scatter of SST versus chlorophyll also shows an inverse
relation illustrating biological-physical coupling. Low SST
results from convection triggered by some physical forcing,
wind in this case. Hence, enrichment of nutrients occurs and
productivity (chlorophyll) is expected to correspond to low
SST. Production and grazing of phytoplankton occurs
simultaneously in practice and the measured chlorophyll from
the ship is net effect of this. For this reason, scatters gives only
approximate idea of influence of physical parameter (SST) on
biology of the water mass.
Scatter of wind versus chlorophyll shows that the two
parameters co vary and nature of relation is direct. Figure 4
brought out time lag in response of chlorophyll to wind. Where
as, the scatter shown in Figure 5 is generated from simultaneous
ship measurements of the two parameters and therefore, scatters
is relatively wider. However, it does indicate that wind force
influences chlorophyll / productivity pattern in
vánd ( m/s]
HH
+
SST (deg. C)
Chioroph! (mgfm™3)
T
05 1 15 2 25 3
chiorophyt (mogim^3)
wind speed (mis)
M a e eo S
t 4—————— A - i
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Figure 5. Scatter of chlorophyll, wind speed and SST from the
ship data recorded during winter bloom in the Northern Arabian
Sea (Period : 21 February — 11 March, 2004, Locations :
different ship stations located in the off shore waters of NAS
under influence of bloom)
NAS during the bloom. One outlier point is showing low
chlorophyll in presence of high wind speed. This could happen
either due to heavy grazing of phytoplankton or rigorous
mixing of water column that might dilute chlorophyll
concentration.
4. CONCLUSION
Using chlorophyll, SST and wind derived from satellite data
and ship data, it has been shown that biological productivity of
NAS is coupled with physical forcing mediated through
nutrient availability during the period of bloom.
The observed time lag in productivity in response to wind force
was about four days in most cases. The delayed response of
phytoplankton against wind stress can be explained as time
taken in sinking of surface waters as a consequence of increase
in surface density and in transport of bottom nutrients in
euphotic zone. Occasionally, in case when wind speed
increased or decreased suddenly by a large magnitude
phytoplankton pattern responded without any time delay.
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