Remote Sensing of Coastal Plumes and Ocean Fronts - BioOne

Journal of Coastal Research

28

1A

1–7

West Palm Beach, Florida

January 2012

Remote Sensing of Coastal Plumes and Ocean Fronts: Overview and Case Study Victor Klemas www.cerf-jcr.org

College of Earth, Ocean and Environment University of Delaware Newark, DE 19716, U.S.A.

ABSTRACT KLEMAS, V., 2012. Remote sensing of coastal plumes and ocean fronts: Overview and case study. Journal of Coastal Research, 28(1A), 1–7. West Palm Beach (Florida), ISSN 0749-0208.

www.JCRonline.org

Coastal plumes, which carry run-off from land, influence the circulation patterns and ecology of nearby coastal areas, causing eutrophication, turbidity, and spread of harmful pollutants. They can be observed along many coasts. Estuarine and ocean fronts result when denser water under-rides lighter water giving rise to an inclined interface and a strong convergence at the surface, which can concentrate phytoplankton and pollutants. To detect and map fronts and plumes, remote sensors exploit their differences in turbidity, color, temperature, or salinity from ambient background water. The most effective remote sensing techniques for observing coastal plumes and estuarine/ocean fronts are reviewed. Studies are presented, which use data from multispectral and hyperspectral imagers, thermal infrared (TIR) radiometers, microwave radiometers, and Synthetic Aperture Radar (SAR). Mounted on satellites and aircraft, these sensors provide the spatial/temporal resolution and coverage needed for tracking plumes and fronts, including their high temporal and spatial variability. This article reviews the most effective remote sensing techniques for observing coastal plumes and ocean fronts and illustrates the application of these techniques in a case study.

ADDITIONAL INDEX WORDS:

Remote sensing, coastal plumes, estuarine fronts, water pollution.

INTRODUCTION AND BACKGROUND Coastal plumes, produced by the continuous discharge of rivers and estuaries containing run-off from land, are common features of shelf areas. The characteristics of these plumes reflect river basin properties and processes and significantly impact continental shelf circulation and associated marine ecosystems such as coral reefs. Estuarine and coastal fronts are formed when higher density water under-rides lighter water, giving rise to an inclined interface, which at the surface may produce a strong convergence. The convergence zone can collect high concentrations of biological and chemical material, including pollutants. Because of their high temporal and spatial variability, coastal plumes and estuarine fronts are difficult to track with ship measurements alone. Therefore an integrated approach using ship, aircraft, and satellite sensors is more effective (Purkis and Klemas, 2011). Remote sensors are truly indispensable during studies of large plumes (e.g., the Amazon River plume), which reach hundreds of km into the Atlantic, or ocean fronts (e.g., the Iceland-Faroes front, which separates the Gulf Stream from the cold water coming down from the Arctic) (Jo et al., 2005; Purkis and Klemas, 2011). Remote sensors can distinguish most plumes from ambient seawater because they often differ in color, turbidity, salinity, DOI: 10.2112/JCOASTRES-D-11-00025.1 received 4 February 2011; accepted 1 March 2011. Published Pre-print online 17 June 2011. ’ Coastal Education & Research Foundation 2012

or temperature. The same applies to estuarine and coastal fronts, which may separate waters having different turbidity, temperature, or salinity (Bowers et al., 2004; Morel and Prieur, 1977; Schofield et al., 2003). The objectives of this article are to review the most effective remote sensing techniques for observing coastal plumes and fronts and to illustrate remote sensing advantages and disadvantages with a case study.

RIVER AND ESTUARINE PLUMES The discharge of rivers and estuaries containing run-off from coastal watersheds often forms plumes which can be observed in coastal and shelf waters. The plumes influence various aspects of the coastal environment from circulation patterns to biogeochemical processes (Mestres, SanchesArcilla, and Sierra, 2007; Riegl and Purkis, 2009). For instance, river-borne nutrients induce eutrophication; hamper primary production by increasing turbidity; and influence other processes related to coastal pollution, larval transport, and sediment transport (Muller-Karger, McClain, and Richardson, 1988; Warrick et al., 2007; Yankovski, 2000). As shown in Figure 1, the increased input of sediments and nutrients from the U.S. agricultural heartland within the Mississippi-Atchafalaya River Basin contributes heavily to the plume patterns along the Louisiana coast. Furthermore, man-made channelization of the Mississippi River flow causes much of the river sediment to be carried into the Gulf of Mexico, producing these large plumes, rather than the

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Figure 1. True-color image of the Mississippi and Atchafalaya River plumes acquired by MODIS aboard NASA’s Terra satellite on March 5, 2001, shows the murky brown water of the Mississippi mixing with the dark blue water of the Gulf two days after a rainstorm. Credits: NASA Earth Observatory.

Figure 2.

Cross section of an estuarine tidal front in Delaware Bay.

ESTUARINE AND COASTAL FRONTS sediment being deposited in the wetlands along the Louisiana coast. Thus, the wetlands get devastated by storms like Hurricane Katrina, without receiving sufficient sediment replacement to become stabilized (Klemas, 2009; Pinet, 2009). The complex behavior of coastal plumes is determined by various factors, including river discharge characteristics, topography/bathymetry, wind, and tidal effects (Blanton, Amit, and Tisue, 1997; Stumpf, Gelfenbaum, and Pennock, 1993; Wiseman and Garvine, 1995). Stratification with large density gradients and the interaction of buoyancy-induced momentum fluxes with the turbulent mechanisms of dilution and dissipation also play major roles (Fennel and Mutzke, 1997; Fong and Geyer, 2002; Garvine, 1987, 1991, 1999). Chang et al. (2002) studied the physical, biological, and optical properties of coastal waters of the New York Bight, including plumes and fronts, on scales of minutes to months and m to 50 km using an extensive data set collected during the Hyperspectral Coastal Ocean Dynamics Experiment. Towed shipboard profilers and high-frequency coastal ocean dynamics applications radar (CODAR) provided complementary data. The ship data showed that phytoplankton and dissolved matter each accounted for approximately 50% of total absorption at midshelf, yet particulate matter dominated at the near-shore locations, as compared to Gelbstoff and other light-absorbing dissolved organics. A relatively high-salinity, low-temperature, low-particulate coastal jet decreased turbidity near shore and advected lower salinity, higher chlorophyll waters to the midshelf region, resulting in increased biomass at midshelf. Small-scale convergence and divergence zones formed from the interaction of semidiurnal tides with mean currents and a water mass/turbidity front. The authors conclude that optical and biological variability and distributions at midshelf and near-shore locations were influenced mainly by semidiurnal tides and the coastal jet.

Estuarine and ocean fronts are similar to atmospheric fronts in that the denser fluid tends to under-ride the lighter fluid giving rise to an inclined interface. A common feature of both large- and small-scale fronts is the persistence of this large density difference across the front for long periods of time. Since fronts are formed by a combination of mechanisms, there are many different types of fronts, such as estuarine fronts, shelf fronts, shelf-break fronts, coastal upwelling fronts, etc. (Belkin, 2005; Belkin and Cornillon, 2003; Garvine, 1995). Estuarine fronts form as interfaces between the freshwater outflow (plume) and the ambient seawater. They are mainly salinity fronts but often separate waters of different turbidity and color. Estuarine fronts may result from tidal advection of freshwater plumes back into the estuary, the emergence of tributary river plumes into the estuary, bathymetric control of flooding denser water, and lateral bathymetric modulation of tidal currents (Huzzy, 1982; Huzzy and Brubaker, 1988; Sarabun, 1980, 1993; Simpson and Turrell, 1986). As shown in Figure 2, the surface flow in a typical estuarine tidal-moving front converges where the front intersects the sea surface, resulting in a strong convergence and downward velocities. Also, horizontal shears of the velocity field parallel to the front are significant for the large-scale features but minimal for the small-scale fronts (Garvine, 1974; Ingram, 1976). At the surface, the convergence velocity at an estuarine front line can reach tens of centimeters per second, producing high concentrations of biological and chemical substances such as phytoplankton and oil (Klemas, 1980; Sarabun, 1993). Sometimes the front is accompanied by foam lines which have been shown to contain concentrations of heavy metals as much as three orders of magnitude greater than surrounding waters (Sick, Johnson, and Engel, 1978; Szekielda et al., 1972). Because the fronts form a barrier to lateral mixing, the water masses on either side of a front may have radically different

Journal of Coastal Research, Vol. 28, No. 1A (Supplement), 2012

Remote Sensing of Coastal Plumes and Ocean Fronts

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chemical and biological characteristics, often resulting in a pronounced color and turbidity difference. Open-ocean and shelf fronts are often related to opposing currents having different temperatures. On the other hand, coastal upwelling fronts separate cold, phytoplankton-rich upwelling water from warmer, ambient background water and can be detected by their color or temperature gradients. For instance, upwelling fronts can frequently be seen in color and thermal infrared (TIR) satellite images of California’s coastal waters. It is these differences, both in salinity and turbidity across estuarine fronts and temperature and color across ocean fronts, which remote sensors exploit to detect and map the fronts (Belkin and Cornillon, 2007).

REMOTE SENSING OF PLUMES AND FRONTS Coastal plumes have been studied for decades by traditional methods, such as ship surveys with Conductivity, Temperature, and Depth (CTD) sensors, current meter moorings, Lagrangian drogues and drifters, etc. Recent studies of coastal plumes and fronts have shown that satellite and airborneremote sensors can provide better spatial and temporal coverage than is possible with traditional methods (Burrage et al., 2003; Dzwonkowski and Yan, 2005; Lihan et al., 2008; Walker, 1996). To use remote-sensing techniques in studies of large plumes such as the ones emanating from the Amazon River or Delaware Bay, images of medium resolution (250 m–1 km) and short revisit periods (2–4 hours) are required. Good candidates for such studies are the National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) sensors onboard NOAA satellites. The AVHRR sensors have 1 km resolution, and with several satellites operating at the same time, can provide four to six visits of the same area per day. Another class of sensors that can be helpful is the ocean color sensors, including the Seaviewing Wide Field-of-view Sensor (SeaWiFS) onboard SEASTAR (or OrbView2) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard TERRA and AQUA. The resolutions of these sensors are better than 1 km and can be as fine as 250 m depending on the bands, and with three operational satellites, a high frequency of revisits can be achieved (Nezlin and Digiacomo, 2005; Nezlin et al., 2005). To detect and map fronts and plumes, remote sensors exploit their differences in turbidity, color, temperature, or salinity from ambient background water. As shown in Figure 1, most estuarine fronts and coastal plumes, such as the Mississippi River plume, can be detected by satellite multispectral sensors because of their high turbidity and different color (Froidefond et al., 1998; Otero and Siegel, 2004; Thomas and Weatherbee, 2006). Walker (1996) used visual and near-infrared bands of the AVHRR to identify the Mississippi River sediment plume; Jo et al. (2005) performed a multisensor study of the Amazon River plume; and Dzwonkowski and Yan (2005) tracked a Chesapeake Bay outflow plume with ocean-color data from both SeaWiFS and MODIS, demonstrating the suitability of ocean-color satellite remote sensing for monitoring such events. Because of their lower salinity and temperature, some

Figure 3. Satellite thermal infrared image of Iceland-Faroes front and eddies. Iceland and the Faroes Islands are outlined by the white dots. North is up. Purple and blue indicate cold arctic water; red and yellow show warmer Gulf Stream water (Millar and Rossby, 2004).

plumes, such as the Mississippi and La Plata River plumes, have been mapped with airborne scanning microwave radiometers and satellite TIR sensors (Burrage et al., 2008). Openocean fronts, such as the Iceland-Faroes front in Figure 3, often have strong temperature gradients, while coastal upwelling fronts can be detected by their colder temperatures and colors attributable to high chlorophyll concentrations (Belkin and Cornillon, 2007; Johnson et al., 2001, Szekielda et al., 2003, 2010). Satellite-remote sensors using the visible part of the spectrum measure the spectral radiances at the top of the atmosphere from which, after atmospheric and other corrections, the spectral radiances emerging from the ocean surface are extracted (Morel and Prieur, 1977; Philpot, 2007). The surface radiances are converted to reflectances, providing the spectral signatures required for identifying chlorophyll and other water constituents. Instrumented ships, buoys, and ocean gliders are used to calibrate and validate chlorophyll-a, total suspended sediment, and other data obtained with ocean-color sensors. In coastal and estuarine waters this data must usually be collected close to the satellite overpass time and must be statistically representative of prevailing conditions. The water samples are usually taken from the upper-half meter of the water column. Sites for calibrating remotely-sensed data, such as chlorophyll concentrations in coastal waters, must be located at well-known points representing the entire range of variables to be measured (Schofield et al., 2003). Lihan et al. (2010) conducted an interesting study of the Pahang River plume using MODIS color imagery. The Pahang River flows into the South China Sea (SCS) and at 440 km in


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length, it is the longest river in Malaysia. The SCS circulation is strongly driven by monsoon winds, which influence the spatial and temporal distribution of the Pahang River plume. The river plume strongly affects surrounding coastal ecosystems because it brings contaminants from land and, due to its heavy turbidity, limits the photic depth and reduces productivity. A time series of level 3 MODIS data (normalized waterleaving radiance) from June 2004 to May 2009 was downloaded and used to classify optical-water types into four classes, which are based on the properties of their suspended particulate matter. A high correlation between the plume size detected by MODIS and precipitation in the river basin showed that the classification of plume and coastal water was successful in identifying the Pahang River plume and providing muchneeded information on spatial and temporal dynamics of that plume (Lihan et al., 2008). Thermal infrared sensors on satellites have been very effective for observing coastal plumes and fronts on the shelf and in the open ocean (see Case Study section). It would be very hard to study open ocean fronts such as the Iceland-Faroes frontal system or the strong thermal gradient across the warm Brazil and cold Falkland current interface without temperature maps obtained from satellite TIR sensors such as the AVHRR (Purkis and Klemas, 2011; Saraceno et al., 2004). Thermal infrared sensors have been deployed for over 40 years on operational meteorological satellites to provide images of cloud top temperatures, and when there are no clouds they observe sea surface temperature (SST) patterns. The TIR radiance measured by the TIR sensor is proportional to the sea surface temperature and emissivity. One reason for the early success of measuring SST is that over water the TIR emissivity is nearly constant (0.98), approaching a perfect blackbody radiator. Thus, the TIR radiance measured over the oceans varies primarily with the SST, allowing the SST to be determined accurately (60.5uC) with certain atmospheric corrections (Barton, 1995; Hickox et al., 2000; Martin, 2004; Ullman and Cornillon, 1999). Airborne scanning low-frequency microwave radiometers (SLFMR) have been used to map the salinities of various bays and estuaries, including their oceanic plumes (Perez, Wesson, and Burrage, 2006). The SLFMR operation is based on the effect of salinity on conductivity, and hence, microwave emissivity of seawater. The SLFMR measures the physical temperature and the microwave brightness of the sea surface from which emissivity is determined. Emissivity is a function of sea-water conductivity, which is related to surface temperature and salinity. The relationship between the ocean salinity, temperature, and remotely-sensed brightness temperature is then used by the data processing system to produce maps of sea-surface salinity (Miller, Goodberlet, and Zaitzeff, 1998; Miller and Goodberlet, 2004). Over the Great Barrier Reef Lagoon in Australia, aircraft overflights of the SLFMR were combined with in situ instruments to map surface and subsurface salinity distributions. The input of freshwater plumes from rivers is a critical consideration in the study and management of coral and sea grass ecosystems because low-salinity water can stress marine ecosystems that are adapted to higher salinity levels. Furthermore, most plumes transport natural and man-made contam-

inants, which induce additional stress in these ecosystems (Burrage et al., 2003; Wang, Heron, and Hacker, 2007). The SLFMR was found to have sufficient precision (1 psu) and accuracy (3 psu) to provide a useful description of plumes emanating from estuaries at moderate discharge levels with a salinity range of 16 to 32 psu in the open sea. The combined airborne and ship approach allowed scientists to determine the structure and zone of influence of the plume and demonstrate the utility of microwave radiometers for mapping surface salinity and studying shelf circulation, including coastal plumes (Burrage et al., 2003).

CASE STUDY Remote Sensing for the Identification of Plumes along the Delaware Coast Plumes along the U.S. East Coast contain run-off from land and impact the environment and ecology of nearby coastal areas. Their characteristics differ from the ambient seawater because typically their water has lower salinity, is nutrient rich, and quite turbid. Often the run-off has pollutants that are harmful to marine life (Long et al., 1995). Furthermore, their high concentrations of nutrients give rise to phytoplankton blooms, which use up the oxygen and can lead to massive fish kills. The Delaware River plume also impacts the transport trajectory of larvae spawned in coastal waters and forms fronts with seawater, which trap nutrients, phytoplankton, and oil slicks (Epifanio and Garvine, 2001; Klemas, 1980). Therefore, plumes and fronts along the Delaware and New Jersey coasts are being studied by scientists in order to better understand them and be able to better predict their behavior (Garvine, 1974). In this case study several Delaware coastal plume events were studied using various remote sensing systems, including satellite multispectral and hyperspectral imagers, TIR radiometer scanners, and Synthetic Aperture Radar (SAR) (Jiang, Yan, and Klemas, 2009). The study site on the shelf off the Delaware Coast ranges from 76u W to 74u W and 37u N to 40u N. The shelf in this area is about 100 km wide, gently sloping with depths from 20 m near the coast to 100 m near the slope. Delaware Bay, one of the major estuaries in that area, widens from the river down the estuary to 45 km before it narrows to 18 km at its mouth. The water depth of the estuary is mostly less than 15 m, except for the shipping channel of more than 30 m, which runs along the bay axis. Outside the mouth, the low-salinity outflow turns clockwise due to the Coriolis Effect and can form a south-flowing, buoyancy-driven coastal current. Inside the bay and on the shelf, the circulation pattern is strongly affected by tidal forcing, and the magnitude of tidal currents near the mouth is approximately 1 m/s, compared with 10 cm/s for subtidal currents. The buoyant circulation is also affected by the wind, which can accelerate, decelerate, or even reverse the coastal current (Houghton et al., 2004; Jiang, Yan, and Klemas, 2009; Munchow and Garvine, 1993; Wong, 1999). To study the coastal plume dynamics, NOAA/Polar Orbiting Environmental Satellites (POES) AVHRR SST data was primarily used because the satellite sensors have a 1 km



Figure 4. Schematic diagram of the plume fronts and tidal currents at the mouth of Delaware Bay during (a) ebb and (b) flood tides. Cape Henlopen, Delaware, is on the left side of the baymouth and Cape May, New Jersey, on the right side (Jiang, Yan, and Klemas, 2009).

resolution and, with several satellites in orbit, can provide up to 4–6 revisits of the same area per day, cloud cover permitting. During October 1999, the surface temperature of the river and its plume was lower than that on the shelf and could easily be tracked by the AVHRR TIR sensors. During ebb tide AVHRR images showed the plume advecting out of the estuary on the Delaware side and reaching some distance south of the bay’s mouth (Figure 4). Just before high tide, the coastal plume was being pushed back to the estuary’s mouth, and eventually an intrusion of warmer seawater could be seen moving into the bay on the New Jersey side, with a front forming on the Delaware side of the bay. A series of SST data was used to track plume variability attributable to tidal forcing, including the different appearance of the plume front between ebb and flood tides. The data also showed that an upwelling-favorable wind not only expanded the plume, but also drove it up to 50 km offshore, separating it from the coast. Upwelled cooler water appeared onshore of the plume water (Whitney and Garvine, 2005). The plume was also tracked using the 490-nm band on SeaWiFS, which is sensitive to the water turbidity and can provide data on the diffuse attenuation depth. The turbidity is directly related to the presence of scattering particles in the water column, including suspended sediment, chlorophyll, etc. The attenuation depth was found to be generally less than 1 m in the turbid estuary, about 5 m on the shelf, and greater than 10 m in the deeper ocean (Jiang, Yan, and Klemas, 2009). Relatively small values of approximately 2 m were found near the estuary mouth and south of it, indicating the direction of the plume’s advection. Synthetic Aperture Radar can provide high resolution images (8–100 m) from satellite altitudes and can detect the roughness of the sea surface. It has been used to detect a wide range of sea surface and coastal features such as internal waves, oil slicks, coastal upwelling, and bathymetry signatures. Because SAR is not affected by cloud cover, it is an all-weather instrument (Clemente-Colo’n and Yan, 1999; Donato et al., 2004; Yan, Clemente-Colo’n, and Pichel, 1997; Zheng et al., 2004). In the Delaware study, because of its fine resolution SAR was able to map the strong plume front between coastal buoyant water and denser seawater and identify a weaker nearshore front, confirming the twin-front structure

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observed by Sanders and Garvine (1996) through field measurements. The RADARSAT-1 SAR data showed that the twin-front structure persists throughout the tidal period, with a stronger gradient during flood tides and weaker gradient during ebb tides. The enhanced radar backscatter from brighter features in the images is caused by the increased surface roughness induced by the convergent surface currents and an increased amount of breaking waves at the plume front (Clemente-Colo’n and Yan, 1999). The SAR data was able to clearly define the impressive length and strength of the offshore front. The SAR images also showed the joining of the Hudson River front with the Delaware River plume front that can be observed only after a strong discharge event when this area is strongly affected by the buoyant water from the Hudson River (Jiang, Yan, and Klemas, 2009; Johnson, Miller, and Schofield, 2003). In this case study a series of images from various satellites enabled researchers to study coastal plume and front variability under a wide range of tidal and wind-forcing conditions. The different remote sensors provided complementary information, enabling researchers to obtain acceptable spatial and temporal resolution despite frequent cloud cover. The cost of the data, its availability, processing time, and complexity of data integration were reasonable considering the variety of remote sensing data used (Jiang, Yan, and Klemas, 2009).

SUMMARY AND CONCLUSIONS Coastal plumes produced by the continuous discharge of rivers and estuaries containing run-off from land are common features in shelf and coastal waters. They influence various aspects of the coastal environment from circulation patterns to biogeochemical processes. The complex behavior of coastal plumes is determined by various factors including river discharge characteristics, topography/bathymetry, and wind and tidal effects. Estuarine and ocean fronts develop when higher density water under-rides lighter water, producing a strong convergence that collects high concentrations of biological and chemical substances such as phytoplankton and oil. To detect and map fronts and plumes, remote sensors exploit their differences in turbidity, color, temperature, and salinity from ambient background water. Because of their high turbidity and different color, most estuarine fronts and coastal plumes can be detected by satellite multispectral/hyperspectral sensors such as SeaWiFS and MODIS. The lower salinity and temperature of some shelf features, such as the Mississippi and La Plata River plumes, have been mapped with airborne scanning microwave radiometers and satellite TIR scanners. Open ocean fronts (e.g., the Iceland-Faroes front) often have strong temperature gradients, while coastal upwelling fronts can be detected by their colder temperatures and colors attributable to high chlorophyll concentrations. In the case study presented, a series of images of the Delaware coast from various satellite sensors, such as SeaWiFS, MODIS, AVHRR, and RADARSAT SAR, enabled researchers to study coastal plume and front variability under a wide range of tidal and wind-forcing conditions. The consistency and complementarity found between the different sensors proved important for remote sensing studies in which a


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single sensor cannot meet all requirements for spatial and temporal resolution, especially in areas where cloud cover reduces the temporal resolution.

ACKNOWLEDGMENTS This research was supported in part by the NOAA Sea Grant and by the NASA EPSCoR Programs at the University of Delaware.

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