OS13A-1170
Interaction of Hurricane Katrina with Optically Complex Water in the Gulf of Mexico: Interpretation Using Satellite-Derived Inherent Optical Properties and Chlorophyll Concentration
When Hurricane Katrina passed over southern Florida, Florida Bay and the West Florida Shelf, and into the Gulf of Mexico, empirically derived chl a increases were observed in the Tortugas Gyre circulation feature, and in adjacent waters. Analysis of the empirically derived chl a increase within the gyre has been primarily attributed to initiation of a phytoplankton bloom promoted by nutrients upwelled by Katrina's winds. Detailed analysis of inherent optical properties (IOPs) derived from remotely-sensed radiances, however, indicated the interaction of Katrina with shallow coastal and shelf waters likely entrained waters with higher concentrations of chromophoric dissolved organic matter (CDOM) into the gyre circulation, augmenting the chl a signal. Storm-induced upwelling would also transport optically active CDOM to the surface. Increases in empirically derived chl a in the Florida coastal waters influenced by Katrina's winds were therefore partly due to increased absorption by CDOM. This analysis indicates that elevated empirically derived chl a in hurricane-influenced waters should not be unambiguously attributed to increased phytoplankton productivity, particularly in an optically complex coastal environment.
OS13A-1171
Comparison of Techniques for Satellite Detection of Red Tides in the Gulf of Mexico
Toxic dinoflagellate Karenia brevis (K. brevis) blooms have regularly been reported in the Gulf of Mexico, particularly in the West Florida Shelf (WSF), and increasing efforts have gone into their detection, which, from space, still remains a challenge in the coastal waters due to the interferences from land and bottom reflectance. Detection algorithms that use blue-green reflectance ratios often have more uncertainties than the red or red-NIR algorithms, due to spectral interferences from colored dissolved organic matters (CDOM), which furthermore, does not correlate with chlorophyll in the coastal waters. Recently we proposed a bloom detection algorithm which uses the difference between two selected bands in the red (identified by us as the Red Band Difference (RBD)) technique, and a K. brevis classification technique, which uses the normalized difference of the two selected red bands (and identified by us as the K. brevis bloom index (KBBI)). In this study, we apply both of these approaches to satellite measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Medium Resolution Imaging Spectrometer (MERIS) ocean color sensors, which have a couple of bands in the red and NIR regions. We also make a comparison between our approaches and Fluorescence Line Height (FLH) approaches applied to bloom detection. Our analysis shows that although FLH can sometimes be used to detect blooms, it breaks down in highly scattering waters, often erroneously identifying other bloom like features, such as sediment plumes, as algal blooms, while our approaches generally correctly distinguish bloomed areas (give positive values) from non-bloom areas (give negative values) even in the highly scattering waters. Further analysis of the impact of CDOM on RBD and KBBI also shows that these techniques are less sensitive to CDOM. Thus, while there is a small reduction in the chlorophyll fluorescence signal due to the absorption of CDOM in the excitation wavebands, which slightly reduces the RBD and KBBI values, they still remain high enough to be detected and classified as blooms. Applications of the proposed approaches to satellite measurements are considered successful, since we were generally able to detect, trace and classify different K. brevis blooms documented in the literature with only minor ambiguities. The classification technique applied to MERIS data seems to give more false bloom alarms. The reason for this is not known at this point. However, this can probably be overcome by making agreement between both the detection and classification techniques a criterion for positive bloom detection.
OS13A-1172
Evaluating a Gulf of Maine Bio-Optics Dataset Using Hydrolight and Simplified Bio-optical Models
One of the central goals of the ocean color community is to estimate global primary productivity. This task is currently attempted using satellite measurements of the reflected light from the upper ocean. The light measurements are processed in ocean color algorithms to produce indicators of change in the biomass, which convey the dynamics of primary productivity. This work involves an evaluation of an in situ bio-optics dataset used to develop and improve ocean color algorithms. The dataset was collected from the western Gulf of Maine by the Coastal Ocean Observing and Analysis Center at the University of New Hampshire. The evaluation entails a comparison of in situ and modeled remote-sensing reflectance (Rrs), an apparent optical property. The modeled Rrs is produced from Hydrolight, a radiative transfer numerical code that uses fundamental physics to calculate Rrs from in situ absorption and scattering measurements (which are inherent optical properties, i.e, IOPs). The IOPs are dependent on ocean constituents including phytoplankton, colored dissolved organic matter (CDOM), and non-algal particles. Because Hydrolight is based on fundamental principles of radiative transfer, its products are not subject to the many sources of uncertainty associated with the in situ measurements. Differences between in situ and modeled Rrs are evaluated systematically through sensitivity testing of various parameters in Hydrolight. The Rrs and IOP data are also examined using simplified bio-optical models that express Rrs as a function of IOPs (Gordon, et al., 1988; Sydor, 2007). These models are currently used as the basis for semi-analytical ocean color algorithms.
OS13A-1173
ON DEQUE: Optical and Nutrient-DEpendence of QUantum Efficiency. Preliminary Results from the Western North Atlantic Ocean.
We present preliminary results from the ON DEQUE field studies in the western North Atlantic Ocean. The study was designed to ascertain the dependence of phytoplankton maximum photosynthetic quantum yield (phi-max) on water optics and nutrient chemistry in thermally-stratified ocean environments. We tested the hypothesis that in the near-surface waters where light intensity is high enough to saturate photosynthesis, phi-max is controlled by light intensity through the synthesis of photoprotective pigments, but deeper in the euphotic zone where photosynthetic rate is proportional to light intensity, phi-max is controlled by the vertical flux of nutrients through the nutricline. We measured photosynthesis – irradiance parameters using C14- labeled bicarbonate as tracer, seawater chemistry, and phytoplankton absorption coefficients at high vertical resolution in thermally-stratified environments at and around the BATS site near Bermuda. Preliminary data indicate a strong dependence of phi-max to the vertical nitrate gradient, suggesting a dependence of phi-max on the vertical flux of nitrate into the euphotic zone. Our research provides a mechanism to relate nutrient supply and irradiance, together, to natural populations of phytoplankton, a long-standing problem in biological oceanography.
OS13A-1174
Mesoscale and Submesoscale Influence on Variability and Anisotropy Observed in Ocean Color Data Near Bermuda
Submesoscale and mesoscale physical variability strongly modulate the structure, biomass, and rates of marine ecosystems. Characteristic time and space scales of key ocean physical-biological phenomena range from the submesoscale (0.3-10 km in space; day-week in time) to mesoscale (10-300 km; week-few months). We present results characterizing the joint distribution of mesoscale and submesoscale ocean color variability using structure function techniques applied to high spatial resolution (1 km), regional satellite data near Bermuda. Our results of progressively low-pass filtered data indicate that submesoscale contributes a substantial portion of total variability. No distinct scale separation exists between mesoscale and submesoscale variability, but rather there is a smooth transition following a power law with a negative slope. Local anisotropy is detected by applying ANOVA tests to decorrelation scale lengths evaluated in multiple directions for sub-regions of each image. Quantification of submesoscale variability is an essential first step in deriving physical-biological models with parameterizations that may deviate significantly from purely physical, conservative tracers.
OS13A-1175
Role of Ocean Biology-Induced Climate Feedback in Modulation of El Niño-Southern Oscillation (ENSO)
ENSO properties can be modulated by many factors; most previous studies have focused on physical aspects of the climate system in the tropical Pacific. Ocean biology-induced feedback (OBF) onto physics and bio-climate coupling have been a subject of much recent interests, but with strikingly model dependent and even conflicting results. Current satellite data are able to resolve the space-time structure of oceanic signals both in biology and physics and thus can be used to quantify their relationship. Here we use the biological signature from satellite ocean color data to estimate interannual variability of the attenuation depth of solar radiation (Hp), a field linking ocean biology and physics. Then we apply a Singular Value Decomposition (SVD) analysis to the Hp and sea surface temperature (SST) data to derive an empirical model for Hp, which is then used to represent OBF in a hybrid coupled ocean-atmosphere model. It is shown that the OBF has significant effects on ENSO amplitude and oscillation periods, which can be explained in terms of a negative feedback.
OS13A-1176
Assessing the Application of SeaWiFS Ocean Color Algorithms to Lake Erie
The feasibility of monitoring phytoplankton chlorophyll a concentrations in Lake Erie is assessed by applying globally calibrated ocean color algorithms to spatially and temporally collocated measurements of SeaWiFS remote sensing reflectance. Satellite-based chlorophyll a retrievals were compared with fluorescence-based measurements of chlorophyll a from 68 field samples collected across the lake between 1998 and 2002. Twelve ocean color algorithms, one regional algorithm derived for the Baltic Sea's Case 2 inland waters, and a set of regional algorithms developed for the western, central and eastern basins of Lake Erie were considered. While none of the ocean-color algorithms performed adequately, the outlook for the use of regionally calibrated and validated algorithms, with forms similar to the oceanic algorithms, is promising over the central and eastern basins of the lake. The application of several procedures for screening clouds and other atmospheric effects was found to significantly reduce a component of misfit due to unresolved atmospheric contamination in most regions of the lake. Statistical measures of performance for the regional algorithms were particularly good in the eastern basin, while additional improvements might be realized from a better understanding of other color-producing agents (CPAs) in the central basin. In the western basin, other CPAs confound the signal so significantly that different approaches to algorithm development will be needed. In the western basin of the lake, remaining errors due to unresolved atmospheric effects are expected to be small compared with errors remaining due to inadequate separation of chlorophyll a from other CPAs.