Using SeaWiFS and In Situ Data for HAB Prediction in the Northern Gulf of Mexico: Decision Tree Analysis

To date, 13 potential HAB species have been detected in coastal waters of Mississippi and Alabama, including representatives of the diatom genera Pseudo-nitzschia and Chaetoceros, and dinoflagellate genera Karenia, Gonyaulax, Akashiwo, Karlodinium, and Prorocentrum. This study investigates the potential of satellite remote sensing (SeaWiFS) to predict environmental conditions leading to the formation of HABs in these turbid coastal waters. Phytoplankton populations and water quality were monitored in situ at 3 to 6 week intervals and 17 locations in Mobile Bay and the Mississippi Sound from December, 2004, through June, 2006. SeaWiFS imagery corresponding with in situ collections was acquired. Non-parametric multivariate analyses determined relationships between phytoplankton cell counts and in situ or satellite-derived water properties, including surface temperature, salinity, concentrations of chlorophyll, total suspended solids, colored dissolved organic material, and nutrient levels. This paper will describe an expert system decision tree analysis approach to prediction of ecological conditions necessary for the formation of HABs. The model assumes unique ranges of remote sensing reflectance ratios, Chl a, and total suspended solids must exist within the environment are conducive for the formation of HABs. 
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Average seasonal changes in chlorophyll a in Icelandic waters

The standard algorithms used to derive sea surface chlorophyll a concentration from remotely sensed ocean colour data are based almost entirely on the measurements of surface water samples collected in open sea (case 1) waters which cover ~60% of the worlds oceans, where strong correlations between reflectance and chlorophyll concentration have been found. However, satellite chlorophyll data for waters outside the defined case 1 areas, but derived using standard calibrations, are frequently used without reference to local in situ measurements and despite well-known factors likely to lead to inaccuracy. In Icelandic waters, multiannual averages of 8-d composites of SeaWiFS chlorophyll concentration accounted for just 20% of the variance in a multiannual dataset of in situ chlorophyll a measurements. Nevertheless, applying penalized regression spline methodology to model the spatial and temporal patterns of in situ measurements, using satellite chlorophyll as one of the predictor variables, improved the correlation considerably. Day number, representing seasonal variation, accounted for substantial deviation between SeaWiFS and in situ estimates of surface chlorophyll. The final model, using bottom depth and bearing to the sampling location as well as the two variables mentioned above, explained 49% of the variance in the fitting dataset

The use of algorithms to predict surface seawater dimethyl sulphide concentrations in the SE Pacific, a region of steep gradients in primary productivity, biomass and mixed layer depth

Dimethyl sulphide (DMS) is an important precursor of cloud condensation nuclei (CCN), particularly in the remote marine atmosphere. The SE Pacific is consistently covered with a persistent stratocumulus layer that increases the albedo over this large area. It is not certain whether the source of CCN to these clouds is natural and oceanic or anthropogenic and terrestrial. This unknown currently limits our ability to reliably model either the cloud behaviour or the oceanic heat budget of the region. In order to better constrain the marine source of CCN, it is necessary to have an improved understanding of the sea-air flux of DMS. Of the factors that govern the magnitude of this flux, the greatest unknown is the surface seawater DMS concentration. In the study area, there is a paucity of such data, although previous measurements suggest that the concentration can be substantially variable. In order to overcome such data scarcity, a number of climatologies and algorithms have been devised in the last decade to predict seawater DMS. Here we test some of these in the SE Pacific by comparing predictions with measurements of surface seawater made during the Vamos Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) in October and November of 2008. We conclude that none of the existing algorithms reproduce local variability in seawater DMS in this region very well. From these findings, we recommend the best algorithm choice for the SE Pacific and suggest lines of investigation for future work

SeaWiFS technical report series. Volume 6: SeaWiFS technical report series cumulative index: Volumes 1-5

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is the follow-on ocean color instrument to the Coastal Zone Color Scanner (CZCS), which ceased operations in 1986, after an eight year mission. SeaWiFS is expected to be launched in August 1993, on the Sea Star satellite, being built by Orbital Sciences Corporation (OSC). The SeaWiFS Project at the NASA/Goddard Space Flight Center (GSFC) has undertaken the responsibility of documenting all aspects of this mission, which is critical to the ocean color and marine science communities. This documentation, entitled the SeaWiFS Technical Report Series, is in the form of NASA Technical Memoranda Number 104566. All reports published are volumes within the series. This volume serves as a reference, or guidebook, to the previous five volumes and consists of four main sections including an index to key words and phrases, a list of all references cited, and lists of acronyms and symbols used. It is our intention to publish a summary index of this type after every five volumes in the series. This will cover the topics published in all previous editions of the indices, that is, each new index will include all of the information contained in the preceding indices

SeaWiFS calibration and validation plan, volume 3

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) will be the first ocean-color satellite since the Nimbus-7 Coastal Zone Color Scanner (CZCS), which ceased operation in 1986. Unlike the CZCS, which was designed as a proof-of-concept experiment, SeaWiFS will provide routine global coverage every 2 days and is designed to provide estimates of photosynthetic concentrations of sufficient accuracy for use in quantitative studies of the ocean's primary productivity and biogeochemistry. A review of the CZCS mission is included that describes that data set's limitations and provides justification for a comprehensive SeaWiFS calibration and validation program. To accomplish the SeaWiFS scientific objectives, the sensor's calibration must be constantly monitored, and robust atmospheric corrections and bio-optical algorithms must be developed. The plan incorporates a multi-faceted approach to sensor calibration using a combination of vicarious (based on in situ observations) and onboard calibration techniques. Because of budget constraints and the limited availability of ship resources, the development of the operational algorithms (atmospheric and bio-optical) will rely heavily on collaborations with the Earth Observing System (EOS), the Moderate Resolution Imaging Spectrometer (MODIS) oceans team, and projects sponsored by other agencies, e.g., the U.S. Navy and the National Science Foundation (NSF). Other elements of the plan include the routine quality control of input ancillary data (e.g., surface wind, surface pressure, ozone concentration, etc.) used in the processing and verification of the level-0 (raw) data to level-1 (calibrated radiances), level-2 (derived products), and level-3 (gridded and averaged derived data) products

SeaWiFS technical report series. Volume 10: Modeling of the SeaWiFS solar and lunar observations

Post-launch stability monitoring of the Sea-viewing Wide Field-of-view Sensor (SeaWifs) will include periodic sweeps of both an onboard solar diffuser plate and the moon. The diffuser views will provide short-term checks and the lunar views will monitor long-term trends in the instrument's radiometric stability. Models of the expected sensor response to these observations were created on the SeaWiFS computer at the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) using the Interactive Data Language (IDL) utility with a graphical user interface (GUI). The solar model uses the area of intersecting circles to simulate the ramping of sensor response while viewing the diffuser. This model is compared with preflight laboratory scans of the solar diffuser. The lunar model reads a high-resolution lunar image as input. The observations of the moon are simulated with a bright target recovery algorithm that includes ramping and ringing functions. Tests using the lunar model indicate that the integrated radiance of the entire lunar surface provides a more stable quantity than the mean of radiances from centralized pixels. The lunar model is compared to ground-based scans by the SeaWiFS instrument of a full moon in December 1992. Quality assurance and trend analyses routines for calibration and for telemetry data are also discussed

Going for the Green

This lesson will help students understand how primary production varies at different times of the year in the ocean over the southeastern U.S. continental shelf. Students will use satellite imagery to obtain information on chlorophyll concentration at selected locations in the Earth's oceans, explain the relationship between chlorophyll concentration and primary production, and describe seasonal variations in primary production off the southeastern coast of the United States. Students will also be able to describe the potential significance of observed variations in primary production to biological communities. Educational levels: Intermediate elementary, Middle school