IoE 184 The Basics of Satellite Oceanography' 7' Ocean Color and Phytoplankton Growth

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Lecture 7 Ocean Color and Phytoplankton Growth
IoE 184 - The Basics of Satellite Oceanography.
7. Ocean Color and Phytoplankton Growth
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This lecture includes the following topics
1. Chlorophyll and photosynthesis
2. Vertical distribution of phytoplankton in the
ocean
3. Estimation of phytoplankton biomass from
satellite ocean color observations
4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations
5. Coccolithophores and harmful algal blooms
6. Seasonal cycles of phytoplankton biomass
7. Global phytoplankton biomass and primary
production
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Multi-discipline approach implies the
simultaneous measurements of distribution of
ocean color (i.e., phytoplankton, suspended
sediments and CDOM) and physical environment
enable the studies of physical factors, which
determine the distribution of phytoplankton.
SeaWiFS surface chlorophyll
AVHRR Sea Surface Temperature
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1. Chlorophyll and photosynthesis
Green color of plants, including phytoplankton,
depends on the concentration of plant pigments,
primarily chlorophyll a.
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1. Chlorophyll and photosynthesis
Chlorophyll absorbs light energy and stores it in
the form of chemical agent ATP. This energy is
used for synthesis of organic matter.
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1. Chlorophyll and photosynthesis
The synthesis of organic matter by plants
(primary production) is a basic source of food
for all living organisms.
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2. Vertical distribution of phytoplankton in the
ocean
Photosynthesis cannot proceed without light so,
in the deep layer phytoplankton growth is light
limited Another requirement for photosynthesis
is a sufficient concentration of nutrients
(nitrates, phosphates, iron, etc.). In
stratified water nutrients in the upper mixed
layer are consumed by phytoplankton so,
phytoplankton growth there is nutrient limited.
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2. Vertical distribution of phytoplankton in the
ocean
The growth of phytoplankton occurs in the layer
where both light and nutrient concentrations are
sufficient. With increase of the upwelling
nutrient flux the conditions of phytoplankton
growth become better and the maximum of its
vertical distribution moves to more shallow
layer.
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2. Vertical distribution of phytoplankton in the
ocean
The growth of phytoplankton occurs in the layer
where both light and nutrient concentration are
sufficient. With increase of the upwelling
nutrient flux the conditions of phytoplankton
growth become better and the maximum of its
vertical distribution moves to more shallow
layer.
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2. Vertical distribution of phytoplankton in the
ocean
The growth of phytoplankton occurs in the layer
where both light and nutrient concentration are
sufficient. With increase of the upwelling
nutrient flux the conditions of phytoplankton
growth become better and the maximum of its
vertical distribution moves to more shallow
layer.
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2. Vertical distribution of phytoplankton in the
ocean
When nutrient flux is very intensive and
phytoplankton biomass is high, the maximum of
vertical distribution of phytoplankton is located
at the surface. The result is a direct
correlation between total phytoplankton (or
chlorophyll) concentration in water column (or
within the euphotic layer) and in the thin
surface layer.
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2. Vertical distribution of phytoplankton in the
ocean
Hence, both the surface chlorophyll concentration
and the chlorophyll concentration above the
penetration depth can be used as a measure of
water productivity, i. e., phytoplankton biomass.

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2. Vertical distribution of phytoplankton in the
ocean
Vertical distribution of ecosystem
characteristics at a typical station in the
oligotrophic waters shows deep phytoplankton
maximum and nutricline.
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2. Vertical distribution of phytoplankton in the
ocean
Vertical distribution of ecosystem
characteristics at a typical station in the
eutrophic boreal waters shows shallow
phytoplankton maximum and nutricline.
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2. Vertical distribution of phytoplankton in the
ocean
What layer contributes to the color of ocean
surface?
0
Vertical attenuation of sun light (I) with depth
(Z) can be described by exponential equation Iz
I0exp(-kZ) Deeper from the surface - less
light is reflected or scattered by phytoplankton
cells and contributes to the color of ocean
surface.
L
i
g
h
t
10
)
20
m
(

h
t
p
e
D
30
40
50
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2. Vertical distribution of phytoplankton in the
ocean
What layer contributes to the color of ocean
surface?
Iz I0exp(-kZ) Coefficient K is called
attenuation coefficient it is measured in 1/m
(or m-1). The value 1/K is called attenuation
length, and the layer of this length is called
penetration depth (Zpd).
Another depth used in ocean optic is euphotic
depth (Ze) it is defined as the depth where the
downwelling PAR (Photosynthetically Active
Radiation) is reduced to 1 of its value at the
surface. These two values are related by
empirical equation Zpd ? Ze / 4.6
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2. Vertical distribution of phytoplankton in the
ocean
What layer contributes to the color of ocean
surface?
The Csat (averaged concentration "seen" by a
remote sensor) is computed as follows
Csat is correlated with phytoplankton biomass in
water column.
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3. Estimation of phytoplankton biomass from
satellite ocean color observations
Empirical models are based on direct correlations
between normalized water-leaving radiation (nLw)
and chlorophyll concentration. nLw is is defined
to be the upwelling radiance just above the sea
surface, in the absence of an atmosphere, and
with the sun directly overhead. Semi-analytical
models are based on the Inherent Optical
Properties (IOPs) of water column, i.e.,
absorption and backscattering of different water
constituents (phytoplankton, suspended sediments,
CDOM, etc.). It is assumed that chlorophyll
concentration in phytoplankton is a constant. In
practice, chlorophyll content varies within a
wide range.
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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.
Recent studies of the College of Oceanic and
Atmospheric Sciences at Oregon State University.
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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.
Light energy not used for photosynthesis is lost
as heat and fluorescence.
Fp Ff Fh 1
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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.
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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.
Regular method to calculate Chl fluorescence
uses Fluorescence Line Height
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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.

• Fluorescence can be used as another measure of
  chlorophyll, but only in chlorophyll-rich water,
  because the optical signal produced by
  chlorophyll absorption substantially exceeds the
  signal of fluorescence.
• ADVANTAGE Absorption-based algorithms fail in
  waters where there are other materials that
  absorb and scatter and are not correlated with
  chlorophyll
• Sediment
• Dissolved organic matter
• Chlorophyll fluorescence is specific to
  chlorophyll
• LIMITATION it also depends on physiology

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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.
MODIS successfully estimates FLH from space even
in low chlorophyll case 1 waters
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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.

• FP FF Fh 1
• P photosynthesis F fluorescence H heat.
• Fh (heat) is assumed a constant
• Estimation of chlorophyll concentration
• assumes FF ? constant
• Estimation of primary production
• assumes a predictable relationship
• between FF and FP

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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.
Physiological parameters (APR and CFE) vary
spatially.
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4. Estimation of chlorophyll fluorescence from
MODIS ocean color observations.
The patterns of variability of phytoplankton
physiology estimated from fluorescence can be
used for evaluation of photosynthesis and primary
production.
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5. Coccolithophores and harmful algal blooms.
Coccolithophores are small algae containing
coccoliths inorganic carbon structures. The
blooms of coccolithophores result in very
intensive water surface backscattering and hinder
remotely-sensed estimation of phytoplankton
biomass.
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5. Coccolithophores and harmful algal blooms.
From typical to coccolithophores backscattering
spectra we can estimate the biomass of these
algae.
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5. Coccolithophores and harmful algal blooms.
From typical to coccolithophores backscattering
spectra we can estimate the biomass of these
algae.
Coccolithophore bloom in the Barents Sea, August
21, 2002
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5. Coccolithophores and harmful algal blooms.
SeaWiFs Image of a bloom in the Bering Sea on
July 20, 1998
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5. Coccolithophores and harmful algal blooms.
Optical measurements of MODIS enable estimation
of not only chlorophyll a concentration, but also
concentrations of pheopigments, which are
produced by zooplankton during grazing.
Decreased concentration of pheopigments
indicates absence of grazing typical to harmful
algal bloom.
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5. Coccolithophores and harmful algal blooms.
This image shows the area of harmful algal bloom
near the Pacific coast of Central America.
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6. Seasonal cycles of phytoplankton biomass
One of the main goals of remote-sensing
observations is the study of seasonal cycles of
phytoplankton biomass in different regions of the
World Ocean. In many regions these cycles
repeat every year including minor details. This
pattern is a result of seasonal oscillations of
physical environment. In high latitudes these
oscillations are more pronounced, and the
response of phytoplankton is more evident.
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6. Seasonal cycles of phytoplankton biomass
Typical pattern of seasonal variations of
phytoplankton in temperate latitudes is known
since the beginning of 20th century.
The main feature is a short-period (1-2 weeks)
"vernal bloom" called in parallel with seasonal
cycle of terrestrial plants. The cycle contains
the period of exponential growth and then abrupt
decrease resulting from grazing of phytoplankton
by zooplankton.
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6. Seasonal cycles of phytoplankton biomass
The hydrological conditions of the start of
phytoplankton spring bloom were described and
explained by Harold Sverdrup in 1953. He
attributed the beginning of spring bloom to the
formation of seasonal thermocline, when the upper
mixed layer is separated from deeper water column
and phytoplankton Is retained in illuminated
(euphotic) layer.
The strengthening of seasonal thermocline in
summer results in nutrient limitation of
phytoplankton growth.
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6. Seasonal cycles of phytoplankton biomass
Stratification within the euphotic layer is a
primary factor controlling phytoplankton growth.
We consider two main factors limiting
phytoplankton growth illumination and nutrients.
Light limitation is crucial under low
stratification (e. g., winter convection),
because algae cells are dispersed by turbulent
mixing within deep dark layers. Nutrient
limitation is crucial under enhanced
stratification (e. g., seasonal thermocline in
summer), when the euphotic (i. e., well
illuminated) upper mixed layer is isolated from
the deep layer rich in nutrients. The
hydrometeorological factors (heat flux, wind,
freshwater load with precipitation and river
discharge) either increase or decrease the
stratification within the euphotic layer.
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6. Seasonal cycles of phytoplankton biomass
Typical seasonal cycles of phytoplankton result
from the combined effect of seasonal cycles of
hydrometeorological factors influencing water
stratification within the euphotic layer. The
most illustrative is the phytoplankton seasonal
cycle in mid-latitudes with two maxima in spring
and autumn
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6. Seasonal cycles of phytoplankton biomass
IoE 184 - The Basics of Satellite Oceanography.
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6. Seasonal cycles of phytoplankton biomass
In high latitudes (cold and windy) winter minimum
is more pronounced and summer minimum is less
pronounced. In low latitudes (warm and less
windy) winter minimum is less pronounced or
absent and summer minimum is more pronounced.
Deviations from typical seasonal pattern of
hydrometeorological factors result in local
peculiarities of phytoplankton cycle.
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6. Seasonal cycles of phytoplankton biomass
Typical seasonal cycles of phytoplankton
described by Alan Longharst are given below. He
distinguishes eight types of cycle. The figures
illustrate pigment concentration (Chl), primary
production (P), mixed layer depth (Zm), and the
period when the picnocline is illuminated ( ).
IoE 184 - The Basics of Satellite Oceanography.
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6. Seasonal cycles of phytoplankton biomass
Typical seasonal cycles of phytoplankton
described by Alan Longharst are given below. He
distinguishes eight types of cycle. The figures
illustrate pigment concentration (Chl), primary
production (P), mixed layer depth (Zm), and the
period when the picnocline is illuminated ( ).
IoE 184 - The Basics of Satellite Oceanography.
7. Ocean Color and Phytoplankton Growth
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6. Seasonal cycles of phytoplankton biomass
Typical seasonal cycles of phytoplankton
described by Alan Longharst are given below. He
distinguishes eight types of cycle. The figures
illustrate pigment concentration (Chl), primary
production (P), mixed layer depth (Zm), and the
period when the picnocline is illuminated ( ).
IoE 184 - The Basics of Satellite Oceanography.
7. Ocean Color and Phytoplankton Growth
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6. Seasonal cycles of phytoplankton biomass
Typical seasonal cycles of phytoplankton
described by Alan Longharst are given below. He
distinguishes eight types of cycle. The figures
illustrate pigment concentration (Chl), primary
production (P), mixed layer depth (Zm), and the
period when the picnocline is illuminated ( ).
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6. Seasonal cycles of phytoplankton biomass
Near Newfoundland two different water masses
(cold Labrador Current and warm Gulf Stream) are
separated by frontal zone.
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6. Seasonal cycles of phytoplankton biomass
Four small regions were selected in the zones of
influence of the Labrador Current, the Gulf
Stream, and over shallow and deep parts of the
Newfoundland Bank.
Seasonal patterns were typical to Arctic,
coastal, mid-latitude, and subtropical regions.

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6. Seasonal cycles of phytoplankton biomass
Seasonal patterns were typical to Arctic,
coastal, mid-latitude, and subtropical regions.

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6. Seasonal cycles of phytoplankton biomass
In April 1999 unusual wind pattern (weak wind in
northern part and strong wind in southern part)
resulted in stronger bloom of phytoplankton.
Weak wind in northern (light-limited) zone
enhanced stratification strong wind in southern
(nutrient-limited) zone eroded thermocline both
favored phytoplankton growth.
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6. Seasonal cycles of phytoplankton biomass
These images show seasonal variations of plant
pigment concentration in in the Ligurian Sea.
January 1998, March 1998, August 1998
  Subtropical seasonal cycle with summer
minimum and higher chlorophyll concentration
during winter-spring is evident.
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6. Seasonal cycles of phytoplankton biomass
These images show seasonal variations of plant
pigment concentration in in the Ligurian Sea.
March 1999, April 1999, and May 1999   In
1999 typical to mid-latitudes spring bloom was
observed.
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6. Seasonal cycles of phytoplankton biomass
Significant correlation was revealed between air
temperature contrast in autumn and the magnitude
of spring bloom next spring (CZCS and SeaWiFS
data).
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6. Seasonal cycles of phytoplankton biomass
Cold and windy autumn of 1998 preceded vigorous
spring bloom in spring 1999. Explanation   1.
Deeper winter convection and enrichment of the
upper layer with nutrients.   2. Cold winter and
warm spring favors formation of seasonal
thermocline.
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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Seasonal variations of remotely-sensed CHL in the
Persian Gulf averaged over September 1997 May
2006
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The variability of CHL, SST and PAR was analyzed
separately in six sub-regions
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Highest CHL was observed in the zone of river
plume (1) and the region where the river waters
are supposedly transported by dominating cyclonic
circulation (3). CHL minimum was observed in
spring CHL gradually increased by
September-October.
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To the east of Qatar CHL was significantly lower
with minimum in February and maximum in
August-October).
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The central and northern pars of the Gulf, both
to the west (2) and to the east (4) of Qatar were
characterized by constantly low CHL with maximum
in winter and minimum in spring - early summer.
This seasonal cycle is typical to tropical and
subtropical ocean, where phytoplankton growth is
limited by lack of nutrients, separated from the
euphotic zone by pycnocline.
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In the eastern part of the studied region, in the
Strait of Hormuz and Gulf of Oman (Region 6), CHL
shows a pronounced spring bloom, with maximum in
February-March and minimum in June.
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Wind stress seasonal cycle was characterized by
maximum in winter and minimum in autumn.
1
1
2
2
3
3
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In the shallow northern, southwestern and
southern regions CHL seasonal cycles were
anticorrelated with wind stress. Light
limitation? or bottom reflection?
3
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The optical signal in optical shallow waters is
contaminated by bottom reflection, resulting in
overestimation of remotely-sensed chlorophyll
concentration. Wind-driven mixing in shallow
waters resuspends bottom sediments, increases
turbidity and decreases the contribution of
bottom reflection.
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High CHL in 2000 followed high NAO index.
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High CHL in 2000 followed high NAO index. That
period was characterized by very low
precipitation.
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High CHL in 2000 coincided with precipitation
minimum in the area around the Gulf. In the
catchment area of Tigris and Euphrates low
precipitation was not only in 2000, but also in
1999, resulting in very high salinity in Kuwait
waters in 2000-2001.
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Sediment from the Tigris and Euphrates
Low precipitation results in low river discharge.
High CHL in the Gulf suggests that discharged
nutrients play little role in the phytoplankton
growth. Within the theory of light limitation,
we can suggest, that in 1999-2000 low discharge
resulted in less than normal turbidity. However,
this suggestion doesnt look reasonable, because
the turbid zone in the Gulf is not observed in
its open part.
Image Courtesy NASA Visible Earth
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Sand storm in the Arabian Gulf
Another hypothesis is aeolian transport of iron
fertilizing phytoplankton in the Gulf. Low
precipitation could result in more dust
transported from desert areas to the Gulf waters.
Image Courtesy NASA Earth Observatory
This hypothesis is supported by the maxima of the
Aerosol Optical Thickness (T865) and minimum of
the Angström exponent (A510) in the first half of
2000 (SeaWiFS data). T865 is proportional to
aerosol particle concentration in the atmosphere.
A510 is related to the aerosol particle size
distribution.
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Recent MODIS imagery of dust storms in northern
and southern parts of the Gulf (February 4,
2007).
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7. Global phytoplankton biomass and primary
production
MODIS OCEAN NET PRIMARY PRODUCTION
(ONPP) Authors Behrenfeld Falkowski Net
Primary Production NPP f (Chl a, PAR,
SST) Integrated over the Euphotic zone (i.e.,
the depth of 1 of incident Photosynthatically
Available Radiation - PAR)
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3. Estimation of phytoplankton biomass from
satellite ocean color observations
Input fields (measured by MODIS)
Chlorophyll a
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3. Estimation of phytoplankton biomass from
satellite ocean color observations
Input fields (measured by MODIS)
Photosynthetically Available Radiation
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3. Estimation of phytoplankton biomass from
satellite ocean color observations
Input fields (measured by MODIS)
Sea Surface Temperature
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3. Estimation of phytoplankton biomass from
satellite ocean color observations
Equation
H day length (hours) PAR - Photosynthetically
Available Radiation Chl Surface Chlorophyll a
concentration Zeu - Depth of euphotic zone
(power function of Chl) Pbopt - Optimal
Photosynthetic Yield (7-th order polynomial
function of Sea Surface Temperature).
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3. Estimation of phytoplankton biomass from
satellite ocean color observations
Resulting NPP are estimated for 8-day intervals
at global grid of 4.5-km resolution.
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IoE 184 - The Basics of Satellite Oceanography.
7. Ocean Color and Phytoplankton Growth