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2
Sustaining and Advancing Ocean Color
Research and Operations
O
cean color satellites provide a unique vantage point and marine ecosystems. Most of the spatial features that are
for observing the changing biology in the surface important for marine ecosystems, i.e., ocean fronts, eddies,
ocean. Space observations have transformed biologi- convergence zones, river plumes, and coastal regions, can-
cal oceanography (Box 2.1) and are critical to advance our not be brought into full view and studied without satellite
knowledge of how such changes affect important elemental observations. Similarly, ocean color products are crucial for
cycles, such as the carbon and nitrogen cycles, and how the making observations frequently enough to study the timing
ocean’s biological processes influence the climate system. of processes that can have important effects on living marine
resources, such as upwelling, harmful algal blooms1 (HAB),
In addition, ocean color remote sensing allows scientists to
assess changes in primary production, which forms the base seasonal transition, El Niño events, and oil spills.
of the marine food chain. Thus, continuous satellite observa- The use of remotely sensed ocean color products has
tion of ocean color is essential to monitoring the health of the become ubiquitous in oceanography and marine resource
marine ecosystem and its ability to sustain important fisher- management. This chapter, while not comprehensive, pro-
ies, especially in a time of global change. Any interruption vides examples of the growing array of research and soci-
in the ocean color record would severely hamper the work of etal applications and related product requirements. In other
climate scientists, fisheries and coastal resource managers, words, the chapter details the research and resource manage-
and an expanding array of other users, from the military to ment questions that ocean color products can help answer.
oil spill responders. Applications such as coastal marine resource monitoring
It is increasingly recognized that despite the ocean’s require near-real time products at fine spatial and temporal
vastness, its resilience is finite. The new National Ocean scales available from Geostationary Earth Orbit (GEO)
Policy recognizes the many threats to pelagic and coastal satellites (discussed in Appendix D), while others require
marine environments from human activities. Most notably, global, long-term observations provided by traditional sun-
coral reef environments are degrading because of rising synchronous Low Earth Orbit (LEO) satellites. As detailed
water temperatures, ocean acidification, and other environ- below, different types of ocean color sensors will be required
mental stressors. Overfishing, coupled with environmental to meet these diverse demands.
variability and habitat loss, threatens many fish stocks.
Other human-caused disturbances include chronic beach
RESEARCH AND SOCIETAL APPLICATIONS OF
contamination, hypoxia in estuaries and the coastal ocean,
OCEAN COLOR PRODUCTS
and water quality degradation due to industrial, agricultural,
and residential pollution. The 2010 BP oil spill in the Gulf of Many basic research and ecosystem management
Mexico is a prime example of a severe anthropogenic impact applications of ocean color have long time frames. Users
on the marine environment. may have to wait weeks or months for data to be processed,
To support the goals and priorities outlined in the and studies can take years before long-term processes and
National Ocean Policy (CEQ, 2010) and Ocean Research changes can be detected. But ocean color is also critical to
Priorities Plan (JSOST, 2007), continued monitoring of users who rely on it for solving societal challenges on a
the ocean’s ecosystems on a global scale is essential. The near-real time basis.
continuity, global coverage, and high temporal and spatial
resolution of ocean color products make remote sensing a
critical tool for monitoring and characterizing ocean biology 1 An algal bloom is defined as a rapid accumulation of algal biomass.
14
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15
SUSTAINING AND ADVANCING RESEARCH AND OPERATIONS
Box 2.1
The Unique Vantage Point from Space
“The ability to derive global maps of chlorophyll-a concentration (milligrams per cubic meter) in the upper ocean from
ocean color sensors was a groundbreaking achievement for the oceanographic community” (see figure below; NRC, 2008a).
The unique vantage point from space has revolutionized Earth sciences in general. For the first time, scientists have
been able to obtain a global synoptic view of the biomass of phytoplankton in the ocean. This unique observing platform
has also allowed scientists for the first time to visualize and study dynamic features, such as mesoscale eddies and ocean
fronts, and their impact on ocean biology.
Map of chlorophyll concentration (milligrams per cubic meter) in the upper Atlantic Ocean derived from data obtained by the Sea-viewing
Box 2.1.eps
Wide Field-of-view Sensor.
bitmap
SOURCE: SeaWiFS Project, NASA Goddard Space Flight Center, and GeoEye.
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16 SUSTAINED OCEAN COLOR RESEARCH AND OPERATIONS
Research Applications for Ocean Color Products lennia. It is critical that we continue to improve our under-
standing of these processes in the ocean, as they are key to
Tracking changes in global marine plant biomass is
the global carbon cycle and other biogeochemical cycles that
fundamental to ocean biology. Satellite data provide an
are essential to life on Earth.
incredibly powerful tool for observing and quantifying
Ocean color observations are important for verifica-
changes in ocean plant biomass over various spatial and
tion of numerous models that show that the response of
temporal scales and for monitoring climate variations and
ocean biology to changes in ocean circulation may signifi-
trends. Most of the plant biomass in the ocean comprises
cantly impact the air-sea balance of CO2 in the future (e.g.,
microscopic photosynthetic organisms (phytoplankton) that
Sarmiento and Le Quéré, 1996; Sarmiento et al., 1998; Joos
are moved around, mixed, and dispersed by ocean currents
et al., 1999; Matear and Hirst, 1999; Plattner et al., 2001;
and other physical processes. Phytoplankton are different
Friedlingstein et al., 2006) and for determining if changes
from land plants, which have a large standing biomass that
are actually occurring. In addition, ocean color data pro-
includes large amounts of carbon tied up in structures such
vide various methods to identify areas of nitrogen fixation
as roots and trunks. Phytoplankton standing biomass is com-
(Subramanium et al., 2002; Westberry et al., 2005), which
paratively low (about 0.1 percent of land plant biomass) but
have the potential to alter global biogeochemical cycles.
they grow quickly—in some cases doubling in a single day.
Ship-based observations provide insufficient spatial cov-
Grazing rates on phytoplankton can also be very high. Thus,
erage to quantify these biogeochemical processes. Because
compared with land plants, phytoplankton biomass is highly
phytoplankton blooms and their associated areas of high
variable in space and time and can change much more rapidly
productivity are such large-scale yet short-lived phenomena,
in response to changing environmental conditions (Chavez et
it is impossible to survey large enough areas of the ocean
al., 2011). The dynamic nature of the system, coupled with
with ships in order to map phytoplankton productivity and
the difficulty of routinely sampling the global ocean from
changes in the carbon cycle. Only since the availability of
ships or moorings, demonstrates the incomparable value of
ocean color satellites have scientists been able to routinely
remotely sensed ocean color data for tracking phytoplankton
estimate global net primary production on weekly to inter-
biomass variability in different ocean regions over time. Sus-
annual time scales and thus to detect global trends (NRC,
taining this record is essential to test many hypotheses about
2008a).
long-term changes in biogeochemical cycles. One example
Biological uptake of nutrients and carbon at the surface
is the current hypothesis that future sea surface warming
of the ocean plays a crucial role in linking the carbon-rich
associated with long-term climate change will result in a
reservoir of the deep ocean with the atmosphere. Indeed,
decrease in algal biomass, which could affect the ocean’s
there are indications that changes in Southern Ocean cir-
ability to take up atmospheric CO2 and support marine life
culation, together with the response of biology to these
that includes valuable fish stocks.
changes, may already be affecting the oceanic uptake of CO2
from the atmosphere (Le Quéré et al., 2007; Lovenduski et
Climate and Biogeochemical Research Applications al., 2007, 2008). The Southern Ocean is estimated to have
weakened as a CO2 sink between 1984 and 2004, relative
How does the ocean’s biology affect the carbon cycle to the trend expected from the corresponding large increase
and other biogeochemical cycles? in atmospheric CO2 (Le Quéré et al., 2007). The increase
in dissolved CO2 in the surface ocean is also making the
Carbon is continuously exchanged between the ocean,
ocean more acidic, which has important implications for
atmosphere, and land (Figure 2.1). Carbon enters the sur-
many marine organisms and ecosystems (Doney et al., 2009;
face ocean and is dissolved in the water. Compared to the
NRC, 2010). Ocean acidification has the potential to reduce
intermediate or deep ocean, the carbon residence time in the
rates of calcification, which could lower the efficiency of the
surface ocean is relatively short. The biggest reservoir of
biological pump, because de-calcified organisms sink less
carbon is in the intermediate and deep ocean. The solubility
rapidly and therefore transport organic carbon to the deep sea
and biological pumps combined represent the net uptake of
at a slower rate. These possible effects of ocean acidification
carbon by the ocean. When cold, dense water is formed in
are only now beginning to be investigated (Hofmann and
high latitude, the water containing the dissolved carbon sinks
Schellnhuber, 2009).
to the deep ocean (solubility pump). Phytoplankton take up
While almost all marine primary production occurs in
some of the carbon in the sun-lit surface layers of the ocean
the sun-lit surface layer of the ocean, large pools of macro-
during photosynthesis to produce particulate and dissolved
nutrients are found in the deep ocean. In nutrient-limited
organic carbon. A fraction of this particulate organic carbon
regions of the surface ocean, vertical upwelling brings
can sink (biological pump) to the abyssal plains; an even
nutrients to the surface and drives primary production (Lewis
smaller fraction is buried in the sediments. In these ways,
et al., 1986). With some exceptions, nitrate is the nutrient
CO2 is removed from surface waters and moved to deep
that limits phytoplankton growth in the surface ocean on
waters and sediments, where it remains for centuries to mil-
short time scales (Lewis et al., 1986). Some organisms
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SUSTAINING AND ADVANCING RESEARCH AND OPERATIONS
FIGURE 2.1 “The global carbon cycle for the 1990s, showing the main annual fluxes in Gigatons of Carbon (GtC) yr –1: pre-industrial
2.1.eps
‘natural’ fluxes in black and ‘anthropogenic’ fluxes in red (modified from Sarmiento and Gruber, 2006, with changes in pool sizes from
Sabine et al., 2004). The net terrestrial loss of –39 GtC is inferred from cumulative fossil fuel emissions minus atmospheric increase minus
bitmap
ocean storage. The loss of –140 GtC from the ‘vegetation, soil, and detritus’ compartment represents the cumulative emissions from land
use change (Houghton, 2003), and requires a terrestrial biosphere sink of 101 GtC (in Sabine et al., given only as ranges of –140 to –80 GtC
and 61 to 141 GtC, respectively; other uncertainties given in their Table 1). Net exchanges of anthropogenic carbon with the atmosphere
are based on IPCC WGI Chapter 7. Gross fluxes generally have uncertainties of more than ±20 percent but fractional amounts have been
retained to achieve overall balance when including estimates in fractions of GtC yr –1 for riverine transport, weathering, deep ocean burial, etc.
‘GPP’ is annual gross (terrestrial) primary production. Atmospheric carbon content and all cumulative fluxes since 1750 are as of end 1994.”
SOURCE: IPCC, 2007; used with permission from Intergovernmental Panel on Climate Change.
migrating diatom mats (Wilson et al., 2008). The nitrogen
(e.g., Trichodesmium) can thrive in nitrate-depleted waters
provided by nitrogen fixation could contribute substantially
by fixing dissolved nitrogen. The fixed nitrogen becomes
to the total available nitrogen for oceanic new production
subsequently available to other photosynthetic organisms
(Capone et al., 1997; Gruber and Sarmiento, 1997; Karl et
and might shift the ecosystem toward phosphorus limitation
al., 1997). While total nitrogen fixation is estimated at 110
(Karl et al., 1997; Cullen, 1999; Tyrrell, 1999).
Tg y–1 (Gruber and Sarmiento, 1997), nitrogen fixation from
Different methods exist to identify nitrogen fixation
Trichodesmium species is estimated at 80 Tg y–1 (Capone
from satellite ocean color remote sensing (Subramanium et
and Carpenter, 1999). Improving our understanding of the
al., 2002; Westberry et al., 2005). For example, large blooms
spatial and temporal patterns and production of these blooms
of chlorophyll-containing phytoplankton in the southwest
is essential because of their size, duration and potential to
Pacific, observed by both Coastal Zone Color Scanner
alter global climate through changes in the biological pump
(CZCS) and the Sea-viewing Wide Field-of-view Sensor
(Michaels et al., 2001; Sañudo-Wilhelmy et al., 2001).
(SeaWiFS), have been identified as Trichodesmium blooms
Ocean color data have also revealed extensive open-
(Dupouy et al., 1988, 2000; Westberry and Siegel, 2006).
ocean blooms in the northeast Pacific Ocean (Wilson, 2003;
Satellite images also revealed large blooms in late summer in
Wilson et al., 2008) and southeast of Madagascar (Longhurst,
the oligotrophic Pacific northeast of Hawaii (Wilson and Qiu,
2001; Srokosz et al., 2004; Uz, 2007). These blooms are
2008). Based on biological observations made in situ, those
unusual in that they occur in nutrient-depleted regions of the
blooms have been attributed to nitrogen fixers or vertically
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18 SUSTAINED OCEAN COLOR RESEARCH AND OPERATIONS
ocean, and the physical mechanisms that deliver nutrients to strongly biased by the ENSO effects. Analyses of SeaWiFS
support them remain unknown. The discovery highlights how data with CZCS observations from 1979 to 1983, and SST
little we know about the open ocean and how our understand- observations from both periods, suggest that the basin-scale
ing of the complexity of marine ecosystems evolves. Ocean phytoplankton responses were related to the Pacific Decadal
color data have played and will play a crucial role in the Oscillation and the Atlantic Multidecadal Oscillation with
discovery process. little evidence to suggest long-term trends (Martinez et al.,
2009). Comparing satellite records with the results of climate
models incorporating ocean ecosystems and biogeochemical
How is the global marine phytoplankton biomass
cycles indicate that the magnitude of the chlorophyll changes
changing in response to short-term climate variability
observed during the SeaWiFS era were not unusual. Compar-
and long-term climate trends?
able changes have occurred during multiple-year intervals in
SeaWiFS was launched in August 1997 and contributed the past and can be accounted for by interannual variability
to the understanding of the subsequent 1997-1998 El Niño (Henson et al., 2010; Yoder et al., 2010).
(IOCCG, 2008). The satellite data combined with in situ data Because the time-series of remotely sensed phytoplank-
from the equatorial Pacific helped scientists understanding ton chlorophyll is not long enough to detect long-term trends
El-Niño Southern Oscillation (ENSO) dynamics and their in response to climate change (see Box 2.2), Secchi disk
impacts on ecosystems. For example, the deepening of the
thermocline and associated weakening of upwelling along
the equator and in the coastal ecosystems lowers ocean
Box 2.2
productivity and causes substantial decreases in the anchovy
How Long Before a Time-Series Can
fisheries of Peru and Chile (Alamo and Bouchon, 1987;
Reveal Long-Term Climate Trends?
Escribano et al., 2004).
Moreover, satellite ocean color products have demon-
Using the methodologies of trend detection,
strated that El Niño effects are not restricted to the equatorial
Henson et al. (2010) concluded that 40 years of ob-
and coastal upwelling regions (IOCCG, 2008). For example,
servations will be required to sort out the effects of
during the 1997-1998 ENSO event, the Transitional Zone
natural modes of climate variability, such as ENSO,
Chlorophyll Front, an important region of the North Pacific from trends related to a changing climate and chang-
ecosystem, was shifted about 5°S of its regular position ing ocean. Climate data often contain autocorrelation
(Bograd et al., 2004). Also, decreased chlorophyll concentra- and large interannual and decadal natural variability
tions were observed across most of the subtropical Pacific that tend to increase the number of years necessary
(Wilson and Adamec, 2001). This basin-scale response, for trend detection (Tiao et al., 1990; Weatherhead et
al., 1998). Other factors that make trend detection in
detected with satellite observations, had not been previously
climate data challenging include a change in the mea-
detected with in situ observations.
surement procedures (e.g., instrument replacement) or
One of the most important challenges for marine sci-
a data gap. Changes in measurement procedures can
ence is to distinguish ocean changes caused by interannual
affect data by introducing artificial shifts and/or gradual
variability (e.g., ENSO variability) from trends caused by
bias and thus affect the ability to detect trends (Peterson
long-term climate changes or other human effects (Chavez
et al., 1998). Such biases can be confused with the
et al., 2011). Recent satellite studies show a general decrease magnitude of a real trend and must be corrected for
in chlorophyll either in the mid-ocean gyres with some or otherwise taken into account while estimating the
regional variability (Vantrepotte and Melin, 2009) or in the trend. Weatherhead et al. (1998) take gaps in the data
“stratified parts of the low-latitude ocean” (Behrenfeld et al., into account and show that in the worst scenario, the
2006). The same studies show chlorophyll increases in other years required to detect a trend can increase by 50
percent.
parts of the world’s ocean, based on SeaWiFS observations
To arrive at the 40-year time frame, Henson et al.
(Antoine et al., 2005; Gregg et al., 2005; Behrenfeld et al.,
(2010) assume that there will be no interruption in sat-
2006; Polovina et al., 2008; Vantrepotte and Melin, 2009).
ellite data. This number varies according to the satellite
Sea surface temperature (SST)-based indexes of stratification
data characteristics and the expected trend magnitude
show a relation between decreasing chlorophyll and NPP
( estimated by using three ocean biogeochemical
and increasing stratification, which suggests a link between
models) in 14 different regions. If the continuity of
reduced phytoplankton abundance and a gradual warming measurements is broken over this period, as many as
of ocean surface waters (Behrenfeld at al., 2006). Devred et 20 additional years of observations will be necessary.
al. (2009) showed that in the Northwest Atlantic, the trends Distinguishing the effects of ocean cycles from long-
differed among ecological provinces studied. term trends, and identifying the implications for marine
SeaWiFS was launched during the ENSO event that ecosystems, is a major challenge that ocean satellites
can help to resolve.
began in 1997—one of the strongest events of the twen-
tieth century—and thus the initial years of the record are
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SUSTAINING AND ADVANCING RESEARCH AND OPERATIONS
records that date to 1899 have been used as a proxy for phy-
Box 2.3
toplankton chlorophyll (Falkowski and Wilson, 1992; Hou et
How Might Climate Change Affect the
al., 2007; Boyce et al., 2010). These records have been inter-
Ocean’s Biology in the Future?
preted as showing an annual decline of about 1 percent in
global median chlorophyll (Boyce et al., 2010), which would
Bopp et al. (2001) carried out the first modeling
have major ramifications for the global marine ecosystem.
study to demonstrate how increased stratification and
Although the conclusions of Boyce et al. (2010) are chal-
associated processes tend to reduce nutrient supply,
lenged by some (Mackas, 2011; McQuatters-Gollop et al.,
and thus biological productivity, in low latitudes. At
2011; Rykaczewski and Dunne, 2011), they are consistent
the same time, these climate-related changes increase
with the hypothesis (see also Box 2.3) that increasing ocean
the length of the growing season and thus biological
warming contributes to changes in the marine ecosystems, productivity in high latitudes, where nutrients are
which has implications for biogeochemical cycling, fishery more abundant and less affected by the increased
yields, and ocean circulation. However, longer records stratification (Bopp et al., 2001). Sarmiento et al. (2004)
of remotely sensed chlorophyll will be required to detect compared a suite of coupled climate models and il-
associated trends in phytoplankton biomass and to improve lustrated how changes in ocean properties shift the
the estimates of regional rates of change. Assembling those boundaries of biomes in the ocean. More recent studies
(e.g., Schneider et al., 2008; Steinacher et al., 2010)
records will be possible only with continuous satellite obser-
compared model simulations that have been used to
vations of ocean color. Future research to detect trends in
predict ocean ecosystems. The differences between the
phytoplankton chlorophyll will also have to consider changes
models are large; subtle interactions between different
in the phytoplankton assemblages and in the relative contri-
drivers of biology and the response of these drivers to
bution to the Lw signal from chlorophyll and color dissolved
climate change yield results that may seem counterin-
organic matter (CDOM) (Dierssen, 2010). The color of the tuitive (e.g., Rykaczewski and Dunne, 2010).
ocean is driven by the optical properties of the dissolved and Testing of the models with chlorophyll and pri-
particulate materials (including living phytoplankton) in sea- mary production estimated on the basis of satellite
water, modulated by the optical properties of pure seawater ocean color observations is crucial for developing the
itself. Thus, the ocean color signals will reflect the combined models and increasing our confidence in them (Doney
influences of these materials, all of which vary in abundance, et al., 2009), particularly with regard to changes in the
seasonal cycle. However, because the chlorophyll:
in time, and in spectral characteristics. Detecting these trends
carbon ratio can change substantially in response to
and the changes in the relative contribution from CDOM will
changing light levels, it is possible that chlorophyll-
only be possible with advanced sensor capabilities such as
based algorithms will not capture relatively small
additional spectral bands.
changes in net seasonal productivity. Validation of new
products—such as carbon biomass from particulate
backscatter (Behrenfeld et al., 2005) or from chloro-
How does ocean color affect radiative heat transfer in
phyll (Sathyendranath et al., 2009), particle size struc-
the climate system?
ture from the backscatter spectrum (Kostadinov et al.,
To predict the climate accurately, SST has to be simu- 2009), and production associated with individual func-
lated correctly. Because older models had such coarse tional groups (Alvain et al., 2008; Uitz et al., 2010)—is
vertical resolution in the upper ocean, variability in the likely to be critical in mechanistically improving the
models and in distinguishing changes associated with
absorption by chlorophyll and CDOM did not make much
anthropogenic climate change from those associated
of a difference in computing depth-dependent heating rates.
with natural variability (Henson et al., 2010).
Recent research has shown that the absorption of light by
chlorophyll and CDOM can have a major effect on SST and
resulting climate predictions (Marzeion et al., 2005). This
discovery demonstrates that the current distribution of ocean
color is key to determining the pattern of tropical SSTs. mining large-scale climate changes through altering the
Moreover, as much of the absorbing material is CDOM rather absorption profile of solar radiation have yielded somewhat
than chlorophyll (Siegel et al., 2005a), these results highlight inconsistent results. Some model studies resulted in cooling
the importance of understanding CDOM dynamics and how of the equatorial waters (Nakamoto et al., 2001; Sweeney
they may change under different climates. There is a rapidly et al., 2005) while others yielded increased surface heating
growing recognition of the importance of including these (Marzeion et al., 2005; Lengaigne et al., 2007) when a real-
processes in climate models, using primarily satellite-based istic distribution of chlorophyll-dependent absorption was
observations of ocean color for re-interpreting observations, included in their models.
for reanalysis simulations and ecosystem models, and for Recent work suggests that the ambiguity may arise
simulating future conditions. from the fact that different regions respond differently to
Studies that examine the role of ocean color in deter- perturbations in shortwave absorption. In the relatively
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20 SUSTAINED OCEAN COLOR RESEARCH AND OPERATIONS
stagnant eastern oceanic margins, associated with the oxy- important because of their different effects on ecosystem
gen minimum zones, trapping solar radiation closer to the processes, such as their different capabilities for exporting
surface cools deeper waters. Because the colder water is organic matter, including carbon, to depth. Therefore, it is
essentially trapped in place, it results in cooling the mar- important to understand where the functional groups are
ginal zone (Gnanadesikan and Anderson, 2009). That also found, how they vary interannually, and how they might
results in stabilizing the Walker2 circulation and dampening respond to climate change.
El Niño (Anderson et al., 2009). In contrast, trapping solar Because different phytoplankton species have differ-
radiation closer to the surface in the gyres results in surface ent optical properties, they can sometimes be identified
heating, as the deeper, cooler waters tend to be carried away with careful analyses of the different wavebands of ocean
and brought up along the equator. That in turn tends to spin color. For example, coccolithophores are highly reflective.
down the Hadley cells, allowing convection to move more Under bloom conditions they turn the water a turquoise
freely in the tropics and increasing the amplitude of ENSO. color that appears as a milky colored patch in satellite
At high latitudes a different scenario is observed, where images that can be easily discerned by remote sensing.
phytoplankton blooms result in increased cloud cover and Coccolithophores were the first type of phytoplankton to
cloud albedo, which decreases the local precipitation and be specifically isolated by using satellite data (Holligan et
incoming solar radiation (Krüger and Graßl, 2011). Ocean al., 1983a; Ackleson et al., 1994; Brown and Yoder, 1994;
color remote sensing will be an important tool to understand- Brown and Podesta, 1997; Tyrrell, 1999; Gordon et al.,
ing these ocean-climate feedbacks. 2001; Smyth et al., 2002). There also has been some suc-
cess in identifying Trichodesmium by using satellite ocean
color data (Subramaniam et al., 2001; Westberry et al., 2005;
How variable in space and time are plant physiology
Westberry and Siegel, 2006). Ocean color data also have
and functional groups?
been used to identify functional groups of phytoplankton,
Some ocean color satellites can measure fluorescence such as haptophytes, Prochlorococcus, cyanobacteria, and
emitted by phytoplankton (Moderate Resolution Imaging diatoms (Sathyendranath et al., 2004; Alvain et al., 2005,
Spectroradiometer [MODIS] and Medium-Resolution Imag- Aiken et al., 2007) and to infer the distribution of different
ing Spectrometer [MERIS]) (Gower et al., 2004; Gower size classes of phytoplankton (Ciotti and Bricaud, 2006;
and King, 2007; Behrenfeld et al., 2009). This fluorescence Devred et al., 2006; Loisel et al., 2006; Uitz et al., 2006;
measurement can be used to assess phytoplankton physiol- Hirata et al., 2008; Kostadinov et al., 2010). Increasing the
ogy, especially as it relates to nutrient availability and irra- spectral resolution of satellite sensors will improve methods
diance (Kromkamp and Peene, 1995). A global analysis of for detecting functional groups from space.
chlorophyll fluorescence using MODIS data found generally
high values associated with waters depleted in iron, and
Fisheries and Ecosystem-Based Management
low fluorescence where other environmental factors con-
trol growth (Behrenfeld et al., 2009; Sathyendranath et al., Sustaining the health and resilience of our marine eco-
2009). An important component of phytoplankton physiol- systems is a high national priority. With the creation of the
ogy is the cellular ratio of chlorophyll to carbon (Chl:C). first National Policy for the Stewardship of the Oceans, Our
Because changes in light and temperature conditions can Coasts, and the Great Lakes (CEQ, 2010) it is now the policy
impact the Chl:C ratio, observed changes in chlorophyll are of the nation to “protect, maintain, and restore the health
not always an accurate proxy for changes in phytoplankton and biological diversity of ocean, coastal, and Great Lakes
biomass. Satellite ocean color data can be used to derive ecosystems and resources” (CEQ, 2010).
global fields of the Chl:C ratio, which have strong seasonal- The National Oceanic and Atmospheric Administra-
ity and variability driven by light, nutrients, and temperature tion’s (NOAA) National Marine Fisheries Service (NMFS)
(Behrenfeld et al., 2005). is responsible for conserving, protecting, and managing
Among the big challenges in ocean color research is to living marine resources in order to maintain a healthy, func-
move beyond chlorophyll and to identify specific types and tional marine ecosystem and the economic opportunities it
functional groups of phytoplankton on the basis of Lw data provides. In this context, NOAA’s fisheries service encom-
(e.g., Brewin et al., 2011). Identifying functional groups is passes commercial fish stocks and all living marine resources
(LMR), including threatened and endangered species of fish,
marine mammals and invertebrates, and the harvesting and
2 Walker circulation refers to a conceptual model of the air circulation
management of commercial fish species. Whereas satellite
in the tropics. It was first described by Gilbert Walker. According to this
ocean color products have been used to help harvest fish more
model, the air moves along the surface of the Pacific Ocean from east to
efficiently in India and Japan (Wilson et al., 2008; Saitoh et
west, caused by a pressure gradient force that results from a high pressure
al., 2009), the following section focuses on how ocean color
system over the Eastern Pacific and a low pressure system over Indonesia.
The air circulates back at high altitude towards the East, closing the loop products are used in the United States to assess and manage
of the Walker circulation.
fisheries and ecosystem health.
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21
SUSTAINING AND ADVANCING RESEARCH AND OPERATIONS
How does environmental variability affect fish stocks are a key indicator used in the California Current Integrated
and ecosystem health? Ecosystem Assessments (NOAA, 2011).
Fish stock assessments provide the technical basis
for setting annual fish quotas and other management mea- How to assess the impact of climate change on fisheries?
sures to achieve optimum yield while avoiding overfishing
There is considerable long-term temporal variability
and ecosystem harm. At a minimum, a quantitative stock
in fish stocks. It is a challenge to differentiate the effects
assessment requires monitoring of catch, abundance, and
of interannual variability and overfishing from long-term
biological characteristics of the stock. Achieving a balance
changes such as regime shifts (IOCCG, 2008). These regime
between exploitation and conservation requires substantial
shifts are characterized by relatively rapid changes in base-
information about the stock, its fishery, the ecosystem, and
line abundances of both exploited and unexploited species
the habitat. However, the environmental factors influenc-
(Kendall and Duker, 1998). In addition to SST, changes in
ing fish populations are complex, and many remain poorly
chlorophyll can be an index to detect these climate regime
understood.
shifts early on because these measurements are available
Ocean color products are helping to answer a funda-
from satellites with little time lag and provide basin-scale
mental research question in fisheries oceanography: How
and global views. To sustain fisheries, management practices
does environmental variability affect annual recruitment?3
need to be flexible enough to recognize and accommodate
Because most fish have a planktonic larval stage, success-
ecosystem-wide regime shifts (Polovina, 2005).
ful recruitment depends on the availability of a suitable
Long-term changes in ecosystems can be linked to ocean
food source such as phytoplankton. Thus, fish reproduction
and atmosphere parameters (Mantua et al., 1997; Hare and
tends to coincide with the seasonal peak in phytoplankton
Mantua, 2000; Peterson and Schwing, 2003). For example,
abundance (IOCCG, 2008). The Cushing-Hjort or match-
a regional change from a cool to warm climate in the North
mismatch hypothesis suggests that recruitment success is
Pacific in the 1970s coincided with a shift from a shrimp-
related to the match in timing between spawning and the
dominated ecosystem to one dominated by several species
seasonal phytoplankton bloom (Cushing, 1990). Because
of groundfish (Botsford et al., 1997; Anderson and Piatt,
of the limited spatial and temporal resolution of traditional
1999). Similar shifts have been observed for many different
ship-based measurements, testing that hypothesis requires
species and in all ocean basins. Yet the mechanisms that link
satellite-based observations. On the Nova Scotia Shelf, for
changes in population abundance to large-scale ocean and
example, highly successful year classes of haddock were
atmosphere dynamics are not always clear (Botsford et al.,
associated with exceptionally early spring blooms of phy-
1997; Baumann, 1998), and the relationships are not always
toplankton, which supports the match-mismatch hypothesis
constant (Solow, 2002).
(Platt et al., 2003). Similarly, the timing of the spring bloom
In most cases the relationship between chlorophyll and
and the growth rate of shrimp are correlated (Fuentes-Yaco
a specific fish stock is indirect. However, for herbivorous
et al., 2007).
species such as anchovies and sardines, the link can be direct
Further, resource managers and scientists recognize the
(Ware and Thomson, 2005). Satellite-derived measurements
need to move toward ecosystem-based management of fish-
of chlorophyll data provide a fundamental measurement of
eries (Browman and Stergiou, 2005; Rosenberg and McLeod,
the base of the oceanic food web that is key to measuring
2005; Sherman et al., 2005; Frid et al., 2006). This provides
ecosystem changes on a global scale. For example, by extrap-
new impetus to improve our understanding of environmen-
olating satellite-derived values of net primary productivity
tal factors that influence fish stock dynamics and to make
up several trophic levels, Wilson et al. (2009) calculated that
environmental variability an integral part of the assessment
the biomass of fish in the ocean are a major but previously
process. Therefore, routine monitoring of ecosystem param-
unrecognized source of oceanic carbonate that can contribute
eters such as chlorophyll and marine primary productivity
significantly to the marine inorganic carbon cycle. Satellite
will be increasingly important.
measurements of primary productivity also are important for
Many spatial features that characterize ecosystems and
assessing the distribution and diversity of marine organisms
ecosystem variability—such as ocean fronts, eddies, conver-
(Rosa et al., 2008). In addition, ocean color remote sensing
gence zones, and river plumes—can be resolved only with
can be used to indirectly extrapolate to benthic habitat or to
satellite data (Holligan et al., 1983b; NRC, 2008a). More-
export production from the base of the euphotic zone (Laws
over, remote sensing of primary productivity and chlorophyll
et al., 2000).
facilitates monitoring the base of the oceanic food chain,
Understanding the mechanisms that link changes in fish
which is part of the assessment strategy for large marine eco-
population to the climate system will require long-term time-
systems (Sherman and Hempel, 2008; Chassot et al., 2011;
series of key ecosystem parameters. Such understanding will
Sherman et al., 2011). For example, satellite chlorophyll data
be central to developing new management strategies, given
the projected long-term climate trends. Modeling studies
3 Annual recruitment definition: the number of new individuals of a stock
suggest that climate change will result in a large-scale redis -
that enter the fishery in a given year.
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22 SUSTAINED OCEAN COLOR RESEARCH AND OPERATIONS
tribution of fisheries’ catch potential (Cheung et al., 2008b). the entire west Florida shelf. Such turbidity events can affect
The high-latitude regions are projected to experience a 30 seagrasses or corals in two ways: these events can be associ-
to 70 percent increase in catch potential, while a decline of ated with potential eutrophication, which can lead to hypoxic
up to 40 percent is projected for low-latitude regions. These conditions that increase benthic mortality, and increases
major changes will be accompanied by changes in biodiver- in water column turbidity that reduces available light for
sity (Cheung et al., 2008a). photosynthesis (Adjeroud et al., 2002; Zimmerman, 2006).
Global primary production measurements from satel-
lites, together with fish catch statistics and food web models,
How to manage protected species?
can be used to estimate the carrying capacity of the world’s
fisheries (IOCCG, 2008; Chassot et al., 2010). Much of the NOAA’s Office of Protected Resources manages
world’s fish catch comes from coastal areas, which are near approximately 300 species, including those listed under the
or beyond their carrying capacity based on recent estimates Endangered Species Act and the Marine Mammal Protec-
(Pauly and Christensen, 1995). Ocean color data, therefore, tion Act. The Endangered Species Act requires NOAA to
is paramount for managing fisheries over the long term. designate “critical habitat” and to develop and implement
recovery plans for threatened and endangered species. As the
only satellite measurement of the marine ecosystem, ocean
How to characterize ocean habitats remotely?
color data are a crucial tool for characterizing the habitat and
Reflectance of the seafloor holds great promise for behavior of protected species. The Transition Zone Chlo-
characterizing and monitoring shallow benthic habitat from rophyll Front (TZCF), which migrates seasonally between
space. In “optically shallow waters,” where the reflectance 30°N and 40°N in the North Pacific, is an important forag-
of the seafloor influences the ocean color observed at the sea ing and migration corridor for a number of marine species
surface, ocean color is used to characterize bottom types. (Polovina et al., 2001, 2004), including the endangered monk
Ocean color remote sensing offers a cost-effective and seal. The interannual variability of the TZCF also affects the
repeatable approach for mapping and potentially quantifying ecosystem as far south as the northern atolls of the Hawaiian
benthic substrate. In addition, ocean color can help detect Archipelago—the Kure, Midway, and Laysan Atolls. In some
large-scale changes in the health of coastal pelagic and ben- years, the TZCF remains north of those atolls all year. In
thic ecosystems, particularly in large homogenous regions other years, the TZCF shifts far enough south during winter
(Dekker et al., 2006). Current and planned U.S. research to infuse the atolls with higher-chlorophyll water, making
satellites, however, do not provide the required high spatial the region more biologically productive. This variability has
and spectral resolution for all applications in this class. Many been observed to affect the population of the monk seal. After
resource managers and other users will likely need a better a winter during which the TZCF shifted south, monk seal pup
mix of satellites with superior resolution. survival increased (Baker et al., 2007).
Airborne ocean color sensors have been used to docu- Ocean color data also have been used to help with the
ment resilience of benthic features to hurricanes and other management of the North Atlantic Right Whale, one of the
large-scale disturbances. Seagrass distributions observed most endangered whale populations with fewer than 400
in the eastern portion of the Bahamas Banks near Lee individuals left (International Whaling Commission, 1998;
Stocking Island using high-resolution imagery from the Kraus et al., 2005). High mortality, especially as a result
Portable Hyperspectral Imager for Low Light Spectroscopy of ship strikes and whales becoming entangled in fishing
(PHYLLS) were analyzed. Meadows varied from sparse to gear, limits the recovery of this population. Because whale
dense over meter scales (Dierssen et al., 2003). Although habitat overlaps with lucrative fishing grounds and shipping
Hurricane Floyd inflicted significant damage to structures lanes of major U.S. ports, reducing mortality is politically
on the adjacent island, ocean color data revealed that turtle- and economically challenging (International Whaling Com-
grass distributions in the region were virtually undisturbed. mission, 1998; Kraus et al., 2005). The current management
Satellite observations from Landsat and other multispectral strategy limits adverse impacts by requiring modifications
imagers have been used to determine the space-time distri- of fishing gear or vessel speeds in regions where and during
bution of Giant Kelp biomass in California and its relation- times when whales are likely to be present. Satellite ocean
ship to nutrient availability and surface wave disturbance color data have been used to identify whale feeding grounds.
(Cavanaugh et al., 2011). For example, an effort to provide managers with a forecast
In addition, ocean color imagery can easily identify of right whale distributions has the goal of avoiding whale
turbidity or sediment re-suspension events, often caused by strikes by merchant ships (Pershing et al., 2009a,b).
storms or high winds, because of the high backscattering Lastly, satellite ocean color data are crucial in biolog-
signals of the suspended sediments (Acker et al., 2004; Chen ging studies, in which animals are tagged to obtain measure-
et al., 2007; Hu and Müller-Karger, 2007; Dierssen et al., ments as they move undisturbed through their environments.
2009). For example, after the passage of Hurricane Dennis in Recent advances in biologging technology have advanced
July 2005, substantial sediment re-suspension covered nearly our understanding of the ecology of top predators and have
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23
SUSTAINING AND ADVANCING RESEARCH AND OPERATIONS
permitted observations previously unavailable from standard tion, and backscatter that affect visibility and mixed-layer
measurement techniques (Bograd et al., 2010). Satellite data thermodynamics.
make it possible to place the tagging data in an environmental
context so that we can understand the foraging and migra-
Monitoring of Oil Spills
tion patterns. This approach has been used to characterize
the behavior and habitat of a wide variety of tagged species, The Oil Spill Response Research Program in the U.S.
including turtles, penguins, seals, salmon, whales, and sea Department of the Interior pursues techniques for early
birds (Hinke et al., 2005; Ream et al., 2005; Polovina et al., detection, containment, and clean up of oil spills. Remote
2006; Weng et al., 2007; Block et al., 2011). sensing can be used to detect spills because the oil changes
surface reflectance properties and the color of the ocean.
Application of MODIS 250-m imagery can help locate
Near-Real Time Applications for Ocean Color
natural oil seeps and improve estimates of natural oil seep
Products
rates in the ocean because of the near-daily revisit and wide
Applications for ocean color products that require near- sun-glint coverage (sensors are usually designed to avoid sun
real time (NRT) turnaround, from image acquisition until glint, which interferes with obtaining good chlorophyll data,
final products reach users, present significant challenges. The but sun glint is particularly effective at capturing the presence
best possible analysis must be done with whatever imagery of oil at the surface; Hu et al., 2009). In addition, data from
is available at a given moment, which often is not the best both the MODIS and MERIS sensors were used to track the
imagery for the task. GEO satellites are ideal for collecting massive Deep Water Horizon oil spill in the Gulf of Mexico
NRT data, but the only ocean color geostationary satellite in spring and summer 2010. Surface manifestation of oiled
is the Korean Communications Oceanography and Meteo- water within the region of sun glint in the full resolution “true
rology Satellite (COMS) that currently provides data over color” images was readily apparent. Scientists mapped the
the Korean Pacific Ocean. Other approaches are possible; extent of the spill and the location of areas of convergence
Appendix D describes one cost-effective option to obtain in order to direct ship activities focused on rescuing oiled
GEO ocean color data. turtles (Dave Foley, personal communication).
A irborne Visible InfraRed Imaging Spectrometer
(AVIRIS) provides full solar spectral reflectance observa-
Military Applications
tions that were used during the Deepwater Horizon event
Much U.S. Navy-sponsored research in the past 10 to to determine the spatial distribution of oil layer thickness.
15 years has been directed at coastal and optically shallow These observations are useful in routine oil spill monitoring
waters. The main goal is to characterize the optical proper- and response efforts to differentiate recoverable oil films
ties of the environment for operation of ships, submarines, (> 0.1 mm) from thinner films. The use of multispectral
and divers in the water. A major thrust of the research has UV-visible detectors, coupled to thermal infrared detectors,
been to develop and test airborne hyperspectral sensors and allows detection and discrimination of oil films. During spill
algorithms for mapping bathymetry and bottom type at meter events, decision makers need access to imagery within two
spatial scales in optically shallow waters.4 Recent projects hours of data collection.
funded by the Office of Naval Research that investigate these However, current satellites are limited in their capacity
and related topics include Coastal Benthic Optical Properties to assist in oil spill detection. Coarse spatial and temporal
(1997 to 2002) and Hyperspectral Coastal Ocean Dynam- resolution, limited spectral bands, cloud-cover issues and the
ics Experiment (1999 to 2004). Other countries, especially need to operate in conditions of high sunlight have generally
Australia and the People’s Republic of China, have invested restricted the usefulness of ocean color data from low Earth
heavily in the development of airborne hyperspectral imag- orbit satellites for oil-spill detection (Fingas and Brown,
ery capabilities for their coastal waters. 1997, 2000; Hu et al., 2003). Moreover, current processing
The Navy also uses ocean color to determine water methods may not allow for data availability within two hours
clarity, in order to decide whether particular sensors (such of data capture. The AVIRIS sampling covered only a small
as mine-finding or bathymetric LIght Detection and Ranging part of the Gulf of Mexico region.
sensors [LIDAR]) can be deployed or visibility is adequate The spatial, temporal, and spectral resolution needed for
for diver operations. The military uses surface measurements oil spill recovery planning requires high resolution, hyper-
of ocean color products to initialize or validate physical- spectral ocean color radiometers deployed in geostationary
biological ecosystem models, which permit the extrapolation orbit. Geostationary sensors can scan large regions of the
to greater depth of properties such as chlorophyll, absorp- ocean over long periods—a clear advantage over airborne
sensors. This reduces problems with cloud cover, and the
4
wide coverage can help optimize the deployment of airborne
Shallow waters are defined as waters where bottom reflectance
significantly affects the water-leaving radiance. Depending on inherent and marine assets. Plans for the proposed hyperspectral
optical properties of the water, this depth ranges from less than one to tens
ocean color sensor on Geostationary Coastal and Air Pollu-
of meters.
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24 SUSTAINED OCEAN COLOR RESEARCH AND OPERATIONS
tion Events mission (GEOCAPE; a decadal survey mission; use satellite ocean color and regional ocean circulation model
[NRC, 2007]) call for a spatial resolution of about 300 m and data products (Anderson et al., 2011). As with monitoring for
the operational flexibility to observe special events, such as oil spills, geostationary ocean color satellites (Appendix D)
oil spills. In addition, Appendix D describes a cost-effective would be invaluable assets for monitoring HABs because
means to provide ocean color data from commercial GEO they provide the required frequency and spatial resolution
satellites, to be demonstrated in fall 2011 by the Commer- to be effective.
cially Hosted Infrared Payload (CHIRP) program.
Locating Productive Fishing Areas
Detection and Early Warning of Harmful Algal
As fish stocks dwindle, the fishing industry increasingly
Blooms
relies on technology to locate and catch fish quickly and at
Ocean color products are an important component in less cost. Satellite maps of sea surface temperature and ocean
forecasting HABs, which requires frequent observations color can help increase efficiency by identifying sites of fish
over a large area to assess bloom location and movements aggregation and migration, such as temperature fronts, mean-
(IOCCG, 2008). HABs can sicken or kill animals and ders, eddies, rings, and upwelling areas (Laurs et al., 1984;
humans by degrading the water quality or by producing algal Fiedler and Bernard, 1987; Chen et al., 2005). In addition,
toxins, which harm by direct exposure or through consump- ocean color or temperature gradients can be used to indicate
tion of contaminated food. biologically productive regions. Fishermen with knowledge
For example, some HAB species cause areas of of particular fish species’ temperature ranges and preferences
extremely low-oxygen water, which can kill a large portion have been using SST from the NOAA polar orbiting satellite
of the sessile fauna (Rabalais et al., 2001). Other HAB spe- for the past 20 years.
cies have caused large kills of birds and marine mammals However, for ocean color to be of practical use to the
along the U.S. West Coast (Trainer et al., 2000). To avoid fishing industry on a large scale, remotely sensed chlorophyll
human deaths, such as in eastern Canada in 1987 (Subba Rao maps must be made available in near-real time. In Japan
et al., 1988; Bates et al., 1989; Wright et al., 1989), fisheries and India the national fisheries agencies use ocean color to
are closed in affected areas, and their closure is associated increase the efficiency of their fishing fleets. For example,
with a loss in revenue. Toxins released to the atmosphere data from the Indian Ocean color satellite is used to provide
maps of potential fishing zones in NRT (Nayak et al., 2010).
by Karenia brevis blooms have been linked to respiratory
illnesses along the Gulf of Mexico coast (Hoagland et al., In contrast, NMFS does not distribute “fish-finding maps” or
2009). provide other services that would compete with commercial
HAB events adversely affect commercial and recre- interests. Chlorophyll data from the privately owned Sea-
ational fishing, tourism, and valued habitats. Advanced warn- WiFS satellite were only available on a real-time basis to
ings of HABs and estimations of their spatial distributions commercial subscribers. Only clients of the service company
increase the options for managing these events, avoiding can receive custom-tailored maps of ocean color and other
exposure of humans to the toxins, and minimizing the nega- satellite-derived data directly onboard their fishing vessels.
tive effects on local economies and the livelihood of coastal
residents.
Identifying Areas with Potential for Marine Debris
Various methods are being developed to improve the
Convergence
detection of HABs with ocean color sensors (Stumpf et al.,
2003; Hu et al., 2005; Tomlinson et al., 2009; Zhao et al., Marine debris and abandoned fishing nets, also called
2010). However, many challenges remain. In particular, the “ghost nets,” pose a serious hazard to many marine mam-
spatial and spectral resolution of current ocean color sen- mals and sea birds (Jacobsen et al., 2010). Endangered sea
sors can be too coarse to detect features in many coastal turtles, seals, and whales are among the species that become
regions. In the case of some harmful algal blooms, there entangled in the nets and die. The nets become ensnared on
may not be any feature among their optical properties that coral reefs and damage the reef structure, destroy flora and
can be used to distinguish them from non-toxic blooms fauna that depend on a healthy reef ecosystem (Donohue et
(Sathyendranath et al., 1997). Despite the limitations, sat - al., 2001), and can harm commercial fisheries (Kaiser et al.,
ellite ocean color can be an effective tool for monitoring 1996; Gilardi et al., 2010).
HABs, which NOAA has done in the United States since Satellite ocean color data are part of the methods being
2006, producing HAB bulletins twice a week for the Gulf developed to identify and prioritize the likely locations of
of Mexico (Stumpf et al., 2009). Efforts also are under way marine debris in order to remove it from the ocean. In one
to develop ocean color-based operational HAB forecasts in instance, satellite ocean color data were used in the sub-
Europe (Johannessen et al., 2006) and Australia (Roelfsema tropical North Pacific to detect probable locations of debris
et al., 2006). Recently methods have been developed for pre- convergence. A field program validated the detection method
dicting domoic acid-producing Pseudonitschia blooms that (Pichel et al., 2007). Satellite measurements of chlorophyll
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25
SUSTAINING AND ADVANCING RESEARCH AND OPERATIONS
TABLE 2.1 Four Types of Satellite Sensors Required to
and the chlorophyll gradient were analyzed in conjunction
with observer sightings to generate a map of the likelihood Meet the Observational Needs
and density of debris. Ocean color data were vital to this Type Description Examples
identification method; initial efforts using only satellite 1 Polar orbiting sensors with SeaWiFS, MODIS,
temperature data were much less effective. relatively low spatial resolution VIIRS, PACE/ACE
(1 km) with 8 (or many more)
wave bands.
Cruise Support 2 Polar orbiting sensors with MERIS, OCM-1, OCM-2
medium spatial resolution
Near-real time satellite data are invaluable for guid- (250-300 m) and more bands to
ing oceanographic research and operational fishery survey provide a global synoptic view
cruises and are used in this manner by NOAA, the Coast at the same time as allowing
for better performance in
Guard, and the research community. The Warm Core Rings
coastal waters (but with
experiment in the early 1980s, using the Coastal Zone Scan-
longer repeat times for global
ner (Brown et al., 1985), demonstrated the utility of NRT coverage).
ocean color data for guiding oceanographic expeditions. 3 Hyper-spectral sensors with HyspIRI
NRT data are important for locating blooms, fronts, eddies, high spatial resolution (~30-
100 m) in polar orbit and even
and other relevant features for sampling or process studies.
longer repeat times.
The spatial coverage provided by satellite data is crucial
4 Hyper- or multi-spectral GOCI, GOCI-II,
for placing ship-based observations in a larger geographic sensors with high spatial GEOCAPE
context. resolution in geostationary
orbit.
Future Applications
Chapter 5 describes how future enhancements could less than 1×1 m to more than 1×1 km. Wavelength resolu-
increase the value of ocean color products. Advances in tion refers to the number of wavelengths measured and their
satellite sensor technology, increased spectral and spatial bandwidths. It can vary from monochromatic (a gray scale
resolution, and the addition of sensors in geostationary orbits with perhaps all visible wavelengths sensed) to multispec-
that would allow frequent sampling and even greater spatial tral (typically 5-15 wavelengths with each band 10-20 nm
resolution would expand the value of ocean color products wide), to hyperspectral (~30 to a few hundred wavelengths
to climate scientists, the ocean research community and the with bandwidths of 10 nm or better). Repeat time refers to
military, among others (NASA, 2006). Such advances would the time between successive images of a given location on
allow better characterization of coastal environments from Earth. It varies from multiple images per day, available only
space, including the benthic and estuarine environments. from GEO satellites, to several days for satellites in polar
LIDAR sensors would expand ocean color observations orbit, or on a monthly or less frequent basis (especially in
to greater depths, dramatically enhancing the accuracy of areas with frequent clouds).
global plant biomass and carbon estimates. Lastly, the Navy While a polar orbiting satellite sensor like SeaWiFS
is eager to obtain higher spatial and temporal resolution in can deliver a global image about every three days, it can-
shallow coastal waters, available from GEO (Appendix D), not increase its spatial or temporal resolution to respond
and would benefit from the vertical resolution provided by to requirements for higher resolution during an event such
LIDAR sensors. as an oil spill. In such a case, a geostationary satellite
(Appendix D) that could increase its sampling frequency
for a given location would be ideal. The committee identi-
OCEAN COLOR DATA SPECIFICATIONS IN
fied four general types of sensors to cover the spectrum of
SUPPORT OF OCEAN COLOR APPLICATIONS
observational needs (Table 2.1).
As the user community broadens, ocean color product The required data specifications were determined for
requirements grow increasingly diverse. For example, global each application of ocean color data described in this chapter
biogeochemical modeling studies require global images (Table 2.2).
of relatively coarse spatial resolution, whereas HAB work As Table 2.1 illustrates, the needs of the research and
requires frequent, high-resolution observations only avail- operational community are too diverse to be met by a single
able from GEO (Appendix D). satellite. For example, a sensor in polar orbit designed to
There are three primary product characteristics for appli- provide global synoptic coverage will not be able to provide
cations of ocean color data: spatial resolution, wavelength the high spatial and temporal resolution required to meet the
resolution, and repeat time. Spatial resolution refers to the operational needs of the military or to be of use during an
area of the ocean surface that corresponds to a single image oil spill response.
pixel (i.e., ground sample distance). This can range from
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26 SUSTAINED OCEAN COLOR RESEARCH AND OPERATIONS
TABLE 2.2 Current Applications of Ocean Color Data and Required Data Specifications
Spatial Wavelength Repeat Sensor
Resolutiona Timeb
Application Resolution Coverage Type References
Research and Societal Applications:
Chlorophyll variability and trends at 1 km Multispectral 2-3 days Global 1 Many
regional to global scales
Trends and variability in carbon 1 km Multispectral 2-3 days Global 1 or 2 Many
fixation at regional to global scales
Measure inherent optical properties 1 km Multispectral 2-3 days Global 1 IOCCG, 2006
Phytoplankton physiology; C:chl 1 km Multispectral 2-3 days Global 1 Behrenfeld et al.,
ratios; physiological states and including 2005, 2009
growth rates fluorescence wave Sathyendranath et
band al., 2009
Phytoplankton phenology; Time- 4-10 km for open Week- Global 1 Platt and
series of chlorophyll, primary ocean; better for monthly Sathyendranath,
production, phytoplankton functional coastal waters 2008
types Siegel et al., 2002
Carbon inventory of the ocean 4-10 km for open Often derived from Week- Global 1, 2 or 4 Balch et al., 2005
(colored dissolved organic matter, ocean; better for chlorophyll and monthly depending on Behrenfeld et al.,
particulate carbon, particulate coastal waters IOPs application 2005
inorganic carbon, phytoplankton Gordon et al., 2001
carbon) Siegel et al., 2002
Climate change impacts on ocean 1 km Multispectral 2-3 days Global 1 Henson et al., 2010
ecosystem
Detection of phytoplankton functional 1 km Multispectral, Weekly Global 1 and 2 Bracher et al., 2009
groups selected narrow Sathyendranath et
bands; sometimes al., 2004
derived from IOPs Alvain et al., 2005
or chlorophyll Nair et al., 2008
Heat budget and upper ocean 1 km or better Multispectral 1 day Global 1 Many papers; e.g.,
dynamics; air-sea interactions Gnanadesikan et al.,
(Diffuse attenuation coefficient for 2010
visible solar energy) Murtugudde et al.,
2002
Ohlmann et al., 1996
Sathyendranath et
al., 1991
Fisheries and Ecosystem Based Management:
Ecosystem Based Management 1 km Multispectral 2-3 days Global 1
(Fisheries)
Mapping the boundaries of ecological 4-10 km for open Derived from Various time Global 1 IOCCG Report No.
provinces in the ocean and their ocean; better for chlorophyll, scales of 8, 2009
movement coastal SST and other interest, from
applications satellite-derived 1 week to 1
products year
Coastal dynamics (suspended 100 m to 1 km Multispectral Hourly Coastal and 1, 2, 3, or 4 Many papers (e.g.,
sediment load, sediment transport, to 3 days estuarine waters Warrick et al., 2004)
river plumes, etc.) depending on
region and
need;
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27
SUSTAINING AND ADVANCING RESEARCH AND OPERATIONS
TABLE 2.2 Continued
Spatial Wavelength Repeat Sensor
Resolutiona Timeb
Application Resolution Coverage Type References
Monitor coral reefs 10 m best, 50 m Multispectral Annual Coastal, 3 Hochberg, 2011
OK for mapping 30 N to 30 S, so Lubin et al., 2001
entire reef systems Geostationary
OK
Monitor sea grass beds and kelp 3-30 m for Multispectral Twice a year Coastal and 3 Cavanaugh et al.,
forests and biomass biomass (100 m for estuarine, 2011
mapping) 60 N to 60 S Hill and Zimmerman,
2010
Near-Real Time Applications:
Naval application for shallow water 1-10 m Hyperspectral On Coastal waters, 1-4 Dekker et al., in
bathymetry and bottom classification best, multispectral demand as needed press
is still useful Mobley et al., 2005
Monitoring oil spills 100 m Multispectral Hourly Episodic 4 Hu et al., 2009
regional events
Detection of HABs 100 m to 1 km Multi, but 1 day to Coastal and 1 and 2 Ruddick et al., 2008
hyper better monitor estuarine waters
blooms
a Minimum to sustain current capabilities, not necessarily optimal.
b Equatorial revisit.
CONCLUSION research and resource management demands a range of spa-
tial and temporal product specifications that are beyond the
The extensive list of research and societal applications
ability of a single satellite mission to deliver (see Chapters
presented in this chapter demonstrates that ocean color is
4 and 5 for details). Wavelength resolution requirements
fundamental to and irreplaceable for a wide array of appli-
range from only a few bands (to determine chlorophyll) to
cations at local to global spatial scales and near-real time to
hyperspectral data (for coastal and naval applications as well
decadal time scales.
as for advanced algorithms for atmospheric correction and
Exploring the full potential of ocean color research will
the separation of phytoplankton absorption from CDOM;
require more than sustaining current efforts including major
see Chapter 3). A polar orbiting satellite can provide a
advances in sensor capabilities, atmospheric corrections, and
global image about every three days at relative coarse spatial
algorithm and product development as further described in
resolution and meet requirements for applications that need
Chapter 5. Ocean color has been recognized as an essential
a global synoptic view, such as climate research. The same
climate variable5 by Global Climate Observing System6
satellite, however, cannot deliver multiple images per day
(GCOS). To detect long-term climate trends in marine phy-
at the high spatial resolution required by the Navy or by an
toplankton abundance, long time-series of sufficient quality
oil spill response. Those scenarios require a GEO satellite
are required, making it imperative that we maintain and
(Appendix D).
advance satellite capabilities. With the anticipated impacts
of climate change on the marine ecosystem, monitoring
Conclusion: A mix of orbits and sensors are required to
the changes will be essential to managing the diminishing
meet the indisputable demand for a continuous ocean
resources in the ocean.
color record that will help us to understand changes in
Further, the expanding use of ocean color products in
the global climate system, assess the health of the marine
ecosystem, and sustain important fisheries, among other
crucial societal tasks.
5 See http://www.wmo.int/pages/prog/gcos/index.php?name=Essential
ClimateVariables; accessed June 10, 2010.
6 See http://www.wmo.int/pages/prog/gcos/Publications/gcos-138.pdf.
