2

Sustaining and Advancing Ocean Color Research and Operations

Ocean color satellites provide a unique vantage point for observing the changing biology in the surface ocean. Space observations have transformed biological oceanography (Box 2.1) and are critical to advance our knowledge of how such changes affect important elemental cycles, such as the carbon and nitrogen cycles, and how the ocean’s biological processes influence the climate system. In addition, ocean color remote sensing allows scientists to assess changes in primary production, which forms the base of the marine food chain. Thus, continuous satellite observation of ocean color is essential to monitoring the health of the marine ecosystem and its ability to sustain important fisheries, especially in a time of global change. Any interruption in the ocean color record would severely hamper the work of climate scientists, fisheries and coastal resource managers, and an expanding array of other users, from the military to oil spill responders.

It is increasingly recognized that despite the ocean’s vastness, its resilience is finite. The new National Ocean Policy recognizes the many threats to pelagic and coastal marine environments from human activities. Most notably, coral reef environments are degrading because of rising water temperatures, ocean acidification, and other environmental stressors. Overfishing, coupled with environmental variability and habitat loss, threatens many fish stocks. Other human-caused disturbances include chronic beach contamination, hypoxia in estuaries and the coastal ocean, and water quality degradation due to industrial, agricultural, and residential pollution. The 2010 BP oil spill in the Gulf of Mexico is a prime example of a severe anthropogenic impact on the marine environment.

To support the goals and priorities outlined in the National Ocean Policy (CEQ, 2010) and Ocean Research Priorities Plan (JSOST, 2007), continued monitoring of the ocean’s ecosystems on a global scale is essential. The 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 and marine ecosystems. Most of the spatial features that are important for marine ecosystems, i.e., ocean fronts, eddies, convergence zones, river plumes, and coastal regions, cannot be brought into full view and studied without satellite observations. Similarly, ocean color products are crucial for making observations frequently enough to study the timing of processes that can have important effects on living marine resources, such as upwelling, harmful algal blooms1 (HAB), seasonal transition, El Niño events, and oil spills.

The use of remotely sensed ocean color products has become ubiquitous in oceanography and marine resource management. This chapter, while not comprehensive, provides examples of the growing array of research and societal applications and related product requirements. In other words, the chapter details the research and resource management questions that ocean color products can help answer. Applications such as coastal marine resource monitoring require near-real time products at fine spatial and temporal scales available from Geostationary Earth Orbit (GEO) satellites (discussed in Appendix D), while others require global, long-term observations provided by traditional sun-synchronous Low Earth Orbit (LEO) satellites. As detailed below, different types of ocean color sensors will be required to meet these diverse demands.

RESEARCH AND SOCIETAL APPLICATIONS OF OCEAN COLOR PRODUCTS

Many basic research and ecosystem management applications of ocean color have long time frames. Users may have to wait weeks or months for data to be processed, and studies can take years before long-term processes and changes can be detected. But ocean color is also critical to users who rely on it for solving societal challenges on a near-real time basis.

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1 An algal bloom is defined as a rapid accumulation of algal biomass.



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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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17 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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19 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.