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GELBSTOFF IN THE NORTHEASTERN GULF OF MEXICO: SPATIAL AND
TEMPORAL VARIABILITY AND ITS RELATIONSHIP WITH SALINITY
Bisman Nababan1, Chuanmin Hu
1, Frank E. Muller-Karger
1, Douglas C. Biggs
2, and
Ou Wang
2
1College of Marine Science, University of South Florida, St. Petersburg, Florida
2Department of Oceanography, Texas A&M University, College Station, Texas
Abstract
Fluorescence and absorption coefficient of colored dissolved organic matter (CDOM,
also called Gelbstoff) were measured seasonally in the surface waters of [you sure both
data were collected 10-1000m?] the Northeastern Gulf of Mexico (NEGOM) in 1998-
2000. Strong correlations between CDOM absorption coefficient (ag443) and fluorescence
were consistently observed during each of 7 cruises. Relatively high a g443 (>0.1 m-1) was
observed generally inshore (inner shelf) near the major river mouths, except for the
summer cruises when riverine CDOM from the Mississippi River reached the outer shelf.
In general, in all near-shore regions ag443 co-varied linearly and inversely with salinity
during spring and winter cruises, indicating conservative mixing.. In contrast, the
offshore region (outer shelf) showed similar correlation only during summer cruises.
There was no significant indication that the increase of chlorophyll concentration would
lead to the increase of CDOM [Bisman: this is a significant statement, please confirm].
Except in Tampa Bay region during summer cruises, the increase of chlorophyll
concentration also indicated the increase of CDOM pool [This is in contradiction with
what you just said]. We did not observe any significant correlation between total fresh
water discharge and ag443 for the Mississippi, Escambia, and Choctawhatchee regions, but
positive correlations were found in Apalachicola (r=0.54, n=?), Alabama (r=0.82, n=?)
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and Suwannee (r=0.97, n=?) river regions. The high correlation between ag443 and surface
salinity in spring and winter near-shore regions shows that it might be possible to derive
salinity from satellite ocean color sensors, provided that ag443 is estimated consistently
from ocean color and a seasonal and regional relationship be ag443 and salinity is obtained
empirically from field measurements.
1. Introduction
Colored dissolved organic matter (CDOM), also called gelbstoff, originates from
the degradation of plant material of both terrestrial and aquatic origins (Kirk, 1994). In
coastal waters, most of CDOM typically derives from land drainage and river runoff.
Away from continental margins, the effect of rivers declines and CDOM is presumably
related to primary productivity as a by-product of algal cell degradation (Fogg and
Boalch, 1958; Yentsch and Reichert, 1962; Carder et al., 1989; Siegel and Michaels,
1996) and zooplankton grazing (Momzikoff et al., 1994). For some upwelling areas,
however, for chlorophyll concentration changes of two orders of magnitude, there may be
little change in CDOM concentration (Bricaud et al., 1981). Del Castillo et al. (2000)
also reported that the increase in primary productivity did not result in the production of
significant amounts of CDOM in the West Florida Shelf.
CDOM strongly absorbs light in the biologically damaging ultraviolet (UV) region,
thus protecting phytoplankton and other biota (Blough and Green, 1995; Arrigo and
Brown, 1996). CDOM also plays an important role in light absorption in the blue region
of the spectrum, reducing the light available for phytoplankton photosynthesis. CDOM
absorption can also degrade the accuracy of satellite-derived chlorophyll concentrations
(Carder et al., 1989, Vodaceket al., 1994, Hochman et al., 1994; 1995). Photolysis of
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CDOM provides another pathway to understand carbon cycling in the ocean (Moran and
Zepp, 1997). Knowledge of the spatial distributions and the temporal changes of CDOM
on the continental shelf is thus important to help understand biogeochemical processes in
the region.
In estuaries and coastal areas surface salinity is a relatively conservative property
(assuming balanced precipitation/evaporation) and therefore can be used to trace the
transport and mixing process. The buoyancy factor, based on salinity distribution, is an
important component in physical models dealing with coastal dynamics. Salinity
distributions can also be used to monitor and predict the health, hydrography, and habitat
potential (e.g., Montague and Ley, 1993). It is thus greatly desirable to estimate salinity
distributions in a synoptic way, for example from space. Unfortunately, the current
microwave sensors provide only coarse (~50km) salinity estimates, making them little
useful in coastal areas.
Since CDOM and pollutants transported in river plumes are often diluted in a manner
consistent with that of salinity, CDOM has been proposed as a proxy to estimate surface
salinity from high-resolution (~
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linear relationship is often found because of conservative mixing (Carder et al., 1993;
Ferrari and Dowell, 1998; Hu et al., 2003), non-conservative relationship has also been
reported (Benner and Opsahl, 2001; Akl et al., submitted).
The Northeastern Gulf of Mexico (NEGOM, Figure 1) receives significant amount of
fresh water input from rivers like the Mississippi, Alabama, Escambia, Choctawhatchee,
Apalachicola, and the Suwannee. The river discharge varied seasonally with maximum
during spring and minimum during summer (Gilbes et al., 1996). The discharge leads to
strong seasonal buoyancy variation on the shelf, and to high nutrient, chlorophyll, and
dissolved organic carbon concentrations (Turner and Rabalis, 1999; Pennock et al., 1999;
Guo et al., 1999; Del Castillo et al., 2000; Gilbes et al., 1996). The NEGOM region is
activive inmixing, advection, and upwelling processes (Muller-Karger, 2000; Muller-
Karger et al., 1991; Gilbes et al., 1996), and is also sometimes affected by the Loop
Current or by cold and warm rings shed by the large Western Boundary Current
(Vukovich and Hamilton, 1989) [are you sure of this shedding? Where is this WBC?].
Several studies on CDOM characteristics on the NEGOM region have been
conducted (Carder et al., 1989; Del Castillo et al., 2000; Del Castillo et al., 2001),yet the
present understanding of its spatial and temporal distribution and factors controlling these
distributions is very limited. Moreover, little information is currently available in the
literature regarding the relationship of CDOM and salinity and factors affecting the
relationship in this region.
In this study, using field observations of seven cruises for the period of 19982000
in the NEGOM, we examined the spatial and temporal variability of CDOM and the
relationship between surface salinity and CDOM. The objectives of this study were to
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determine 1) spatial and temporal distributions of CDOM in the NEGOM and factors
controlling the distributions, 2) how CDOM correlates with salinity for each major river
outflow region in the NEGOM, and 3) how the relationship changes with space and time.
The ultimate goal is to determine if surface salinity in the NEGOM can be predicted from
CDOM and further from satellite ocean color sensors.
2. Methods
2.1. Study Area
The NEGOM (Fig. 1) extends from the Mississippi River Delta to the West Florida
Shelf off Tampa Bay. It is bounded by the 10-m to 1000-m isobaths. Six major river-
impacted regions, namely the Mississippi (R1), Alabama (R2), Escambia (R3),
Choctawhatchee (R4), Apalachicola (R5), Suwannee (R6), and Tampa Bay (R7), plus
one offshore region (central of the NEGOM, R8) were chosen as the focus of this study.
2.2. Data Collection, Processing and Analysis [you don't have satellite, so no need to
mention in situ]
Data were collected onboard the TAMU Research Vessel Gyre. Detailed description
of data collection and analysis methods can be found in Hu et al. (2003), yet a brief
summary is given below.
The seven two-week cruises during 1998-2000 were conducted in three different seasons:
spring (April or May), summer (July/August), and winter (November) (Table 1). Each of
the seven cruises surveyed eleven cross-margin transects from the 10-m to the 1000-m
isobath (Figure 1).
Continuous near-surface flow-through data for salinity, chlorophyll, and CDOM
fluorescence were recorded every 2 minutes along the cruise transects with Sea-BirdTM
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and Turner DesignsTM
sensors. Near-surface water (3-m hull depth) was pumped at a rate
of 10 liters/minute through a debubbler and mixing chamber of 10-liter volume with 1-
minute residence time. CDOM fluorescence was measured with 330 nm excitation and
450 nm emission.
At selected stations, water samples from the flow-through outflow were filtered using
0.2 m Millipore. The filtrate was drained into the sample bottles (amber-colored glass,
precombusted at 500C for 24 h) and stored in a freezer for later analysis of CDOM
(gelbstoff) absorption coefficient (ag). The ag spectra were analyzed using a Hitachi U-
3000 Double Beam Spectrophotometer (10-cm pathlength), and smoothed to eliminate
instrument noise and corrected for residual scattering.
Similar to the method used by Hu et al., (2003), the flow-through CDOM
fluorescence data were calibrated into ag443 with > 30 discrete samples collected from
various water types (to ensure good dynamic range) for each cruise.
Continuous sub-surface (10-14 m deep) current along the cruise tracks were also
measured using a shipboard 150 kHz Acoustic Doppler Current Profiler (ADCP).
Supplemental current profiling with a 38-kHz ADCP occurred on some cruises. To
produce sub-surface current map, raw ADCP data were gridded using the Generic
Mapping Tools (GMT) software package employing 40 km as the smoothing radius in
Barnes algorithm. Using 40 km as the smoothing radius means that features with scales
less than 40 km are likely smoothed out. However, the 40 km scale seemed to be the best
compromise between filtering out noise features and keeping the basic patterns. Details
of these measurements and data processing can be found in Jochens et al. (2002) and
Wang et al. (2003, submitted).
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Daily river discharge rates for the Mississippi, Alabama, Escambia, Choctawhatchee,
Apalachicola and Suwannee Rivers were obtained from the U.S. Geological Survey and
the U.S. Army Corps of Engineers.
Sea surface height (SSH) anomaly fields were obtained from Dr. Robert Leben,
University of Colorado as a blended product of TOPEX/POSEIDEN and ERS-2 satellite
altimeter. The SSH anomaly fields were produced by temporal and spatial smoothing
using decorrelation scales of 12 days and 100 km. Therefore, features may appear
weaker than they actually were, and smaller scale features may not be represented. To
estimate the total dynamic topography, the residual mean in the SSH anomaly was
removed before adding a model mean to produce the synthetic height estimate. The
resulting time series of SSH fields were interpolated to obtain one SSH field per day.
More details in data processing and analysis can be found in Leben et al. (2002). To map
SSH field for each cruise, we used daily SSH field of each mid-cruise time.
3. Result and Discussion
3.1. Spatial and Temporal Distribution of CDOM and Salinity
The spatial and temporal near-surface distributions of CDOM absorption coefficient
at 443-nm (ag443) are shown in Figure 2. Relatively high ag443 (>0.1 m-1
) was generally
found only inshore near the major river mouths. For the summer cruises (N3, N6 and
N9), relatively high ag443 (>0.1 m-1) was was also found offshore, following the
Mississippi River advection (Figure 2) [Bisman: except for the summer or for the
summer?]. The spatial and temporal near-surface distribution of salinity was also
coherent with that of ag443 (Figure 3). Low salinity (
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N9). The results indicated that riverine CDOM from most of the rivers was limited to
coastal (inshore) region, while riverine CDOM from the Mississippi can be a major
source of terrigenous CDOM in the outer shelf of the NEGOM.
High CDOM and low salinity observed in eastward or southeastward of the
Mississippi River Delta and extended to the West Florida Shelf during each summer of
1998-2000 appeared to be facilitated largely by a warm slope eddy located southeast of
the Mississippi River Delta. To locate eddies and to see the sub-surface water (10-14 m
deep) circulation in the NEGOM, we overlaid sub-surface current map produced from
continuous Acoustic Doppler Current Profiler (ADCP) over sea surface height anomaly
produced from blended product of TOPEX/POSEIDEN and ERS-2 satellite altimeter.
Our result (Figure 4 [color legend should be "SSH anomaly" instead of "SSH"]) indicated
that a warm slope eddy as high as 30 cm was always observed southeast of the
Mississippi River Delta each summer of the year of 1998-2000. Sub-surface current in
this region also showed northeastward and then southeastward flows with speed of up to
0.7 m s-1, indicating anticyclonic circulation. The warm slope eddy with anticyclonic
circulation located southeast of the Mississippi River Delta are thought to be responsible
for the low salinity, high CDOM, nutrients, and sediment in the offshore NEGOM waters
during the summer [Doug should have reference on the forcing mechanism. Put the
reference here]. Eastward dispersal of the Mississippi plume was also observed during
summer of 1993 (Walker et al., 1994).
[I like Fig. 5, but it needs redraw. Ag and chl should be drawn on log scale, and salinity
should be drawn in the range of 25-40 for the y-axis to zoom in the difference]
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Mean chlorophyll concentration ranged from 0.09+0.01 (mg/m3) in central of the
NEGOM (R8) during spring 2000 (N8) to 3.41+2.96(mg/m3) in the Mississippi region
(R1) during spring 1999 (N5) (Figure 5, lower panel). Variability patterns are found
similar to those of ag443 and salinity
3.2. CDOM and Salinity Relationship
Figure 6 shows salinity-ag443 relationship at each selected region for all seasons,
where the statistics are listed in Table 2. Figure 7 presents the same data, but rather
focuses on each season (cruises). In general, ag443 covaries linearly and inversely with
salinity. For near-shore regions, mostly in spring and winter seasons (cruises), high
negative correlation coefficients (r~-0.8 to r~-0.99) were found, indicating conservative
mixing behavior. Some low (r~-0.7) to non-significant (r~0.0) correlation coefficients
were also found mostly in summers, for example in the Mississippi river region (R1)
during summer 1999 (N6)
The non-conservative mixing found during most of the summertime cruises in the
near-shore regions suggests that photodegradation and/or local generation may play a
role. Strong thermal stratification during summertime observed in this region may also
enhance rates of CDOM photolytic decay in near-surface waters (Vodaceket al., 1997).
A non-conservative behavior with net removal of dissolved organic carbon in the
Mississippi River plume was also observed during summer by Benner et al. (1992).
The central NEGOM region showed low to non- significant correlation between
salinity and ag443 during winter and spring seasons (except winter 1999 for N7) and high
negative correlation during summer seasons (Table 2, Figure 6). The former resulted
from the negligible influence of the Mississippi River, as indicated by the narrow range
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and high level of salinity. For the same reason, the latter result was due to the eastward
intrusion of the Mississippi River plume. Such intrusion occurred every summer in 1998-
2000, facilitated by a warm slope eddy located southeast of the Mississippi Delta region
that entrained turbid, low salinity water with high CDOM and nutrient concentrations
from the Mississippi River, and spread it over the West Florida Shelf (Del Castillo et al.,
2001; Nowlin et al., 2000; Muller-Karger, 2000, Hu et al., 2003).
3.3. CDOM and Fresh Water Discharge Relationship
The Mississippi River is the largest river in North America and ranked as the 7
th
largest in the world in term of annual discharge (Milliman and Meade, 1983). This river
contributes over 70% of the freshwater input to the Gulf of Mexico (Deegan et al., 1986),
therefore significantly affects the biogeochemical processes in the region.
The mean daily discharge of the local rivers displays significant seasonality (Fig. 8B),
with typical maximum discharge during winter-spring and minimum discharge during
summer.
Using a linear ag443-salinity regression relationship (ag443=a + b*salinity) from all
surface data (Figs. 6 and 7), but excluding those with non-significant correlation (r
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CDOM composition in these regions may be dominated by reverine CDOM and may
mostly have a soil-derived source (Meybeck, 1981).
3.4. CDOM and Chlorophyll Relationship
River plumes and upwelling processes are significant sources of nutrients. Yet the
relationship between CDOM and chlorophyll for these two scenarios is often different.
The upwelling-induced enhance in chlorophyll and CDOM often covaries [this is in
contradiction with what you said about Bricaud 1981, so I add] or chlorophyll is the
dominant species, indicating a classical Case I water type (Prieur and Morel, 1977). In
contrast, in river plumes (Case II water) CDOM is either unrelated to chlorophyll or the
dominating water constituent due to significant terrestrial influence (Hu et al., submitted).
Figure 9 shows the relationship between CDOM and chlorophyll concentration.
Both high and low correlations were observed, while all high positive correlations
(r>0.80) were found associated with conservative mixing curves of salinity versus ag443.
Based on these conservative mixing behavior, therefore, the significant high positive
relationships between chlorophyll and ag443 did not indicate a significant increase
(addition) of ag443 into the CDOM pool [why?]. Del Castillo et al. (2000) also reported
similar result in the West Florida Shelf that there was no significant increase in CDOM
due to the increase in chlorophyll concentration [did you observe this? I didn't see that].
However, exception was observed in Tampa Bay region where salinity was relatively
high and no significant correlation between salinity and ag443 was observed (Table2,
Figure 5, 8). In this region we found significant positive correlations between
chlorophyll concentration and ag443 (r>0.8) during summer seasons, an indication of
strong biological activities (upwelling and phytoplankton degradation/grazing). Within
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these cruise [what cruises?] in different studies [which studies?], upwelling event was
also observed in this region during summer cruises (e.g., Weisberg et al., 2000).
3.5. Predicting Salinity from CDOM
Can surface salinity be derived from CDOM? To answer this question we performed
error analysis for salinities predicted from ag443 data within 95% confidence level.
Results are listed in Table 2, where sample graphical results are shown in Figure 10.
Within 95% confidence level, we calculated mean percentage error (MPE), i.e., the mean
value of 95% predicted interval line data divided by the mean value of regression line
data and multiplied by 100% (Figure 11). Our result indicated that mean percentage error
(MPE) of ag443-derived salinity varied regionally and seasonally (Figure 11), varying
between 0.09% (R7, N8) and 8.12% (R1, N6) (Table 2). [Figure 10 should present these
two cases instead]. These results indicated that using CDOM data to predict salinity
resulted MEP less than 10% (statistically acceptable) if the correct relationship (derived
empirically on a seasonal and regional basis) is used. Regionally, lower MEP variability
was found in Suwannee river region (0.51-0.83) while higher MEP variability was
observed in the Mississippi river region (1.22-8.12) (Figure 11, upper panel). The high
MEP found in the Mississippi River region may result from non-point sources where
little correlation is found between fresh water discharge volume and ag443 (see above)
[Bisman: have you carefully read your own paper? If you copy some text from your
thesis you should revise the text!]. Seasonally, lower MEP variability was found during
winter (N7, 0.33-1.89) while higher MEP variability was found during summer (N6,
0.53-8.12) (Figure 11, lower panel) [using one example in each season can't get this
generalized conclusion! To be able to say this you should have at least for spring cruises
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behave like this, all summer cruise behave like that]. Strong thermal stratification
occurred during summer may enhance rates of photobleaching process in near surface
waters leading to the decomposition of CDOM.
CDOM has been proposed as a proxy to estimate surface salinity from satellite ocean
color sensor for terrestrial runoff dominated regions (Hu et al., 2003; D'Sa et al., 2002)
provided 1) CDOM can be estimated accurately from satellite (e.g., Carder et al., 1999;
Hu et al., 2003) and 2) there exists a predictable relationship between CDOM and
salinity. Relatively low MEP (0.1 m-1
) generally was observed only
inshore (inner shelf) near the major rivers outflow. Except during summer cruises,
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relatively high ag443 (>0.1 m-1
) was not only found inshore near the major rivers outflow
but also was found offshore (outer shelf) eastward and southeastward of the Mississippi
River Delta. These results indicated that riverine CDOM from all rivers draining into the
NEGOM shelf was limited to coastal (inshore) region except riverine CDOM from the
Mississippi River which play role as main source of terrigenous CDOM in outer shelf of
the NEGOM.
In general, ag443 covaried linearly and inversely with salinity. Therefore, salinity-
CDOM relationships are sufficiently robust for water mass identification. For all near-
shore regions, high negative correlation coefficients (r~-0.8 to r~-0.99) between salinity
and ag443 were observed during spring and winter seasons, indicating conservative mixing
behavior. In contrast, mostly during summer seasons, low (r~-0.7) to non-significant
(r~0.0) correlations between salinity and ag443 were also found, indicating non-
conservative mixing behavior. Contrast to near-shore regions, offshore (outer shelf)
region showed low to non-significant correlation between ag443 and salinity mostly during
spring and winter seasons while high negative correlations were found during summer
season. However, the relationships between ag443 and salinity varied both seasonally and
regionally, illustrating the complexity of the salinity-CDOM relationship in the NEGOM
region. Therefore, prediction of salinity based on CDOM fluorescence or absorption
values would be highly dependent upon regional and seasonal relationships.
There was no significant indication that the increase of chlorophyll concentration
would lead to the increase of CDOM pool. Except in Tampa Bay region during summer
cruises, the increase of chlorophyll concentration also indicated the increase of CDOM
pool. We also found that there was no direct correlation between total fresh water
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discharge and ag443 for the Mississippi, Escambia, and Choctawhatchee regions, while
significant positive correlations were found in Apalachicola (r=0.54), Alabama (r=0.82)
and Suwannee (r=0.97) river regions.
Relatively low MEP (
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References
Benner, R., C. Chin_leo, W. Gardner, B. Eadie, and J. Cotner. 1992. The fates and
effects of riverine and shelf-derived DOM on Mississippi River plume/Gulf shelf
processes, p. 84-94. In: Nutrient Enhanced Coastal Ocean Productivity, NCOPWorkshop Proceeding, October 1991, NOAA Coastal Ocean Program, TAMU-SG-
92-109.
Arrigo, K.R., and C.W. Brown. 1996. Impact of chromorphoric dissolved organic matter
on UV inhibition of primary productivity in the sea. Mar. Ecol. Prog. Ser. 140:207-216.
Benner, R., and S. Opsahl. 2001. Molecular indicators of the sources and
transformations of dissolved organic matter in the Mississippi river plume. OrganicGeochemistry 32:597-611.
Blough, N.V., and S.A. Green. 1995. Spectroscopic characterization and remote sensing
of non-living organic matter, p. 23-45.In: R.G. Zepp and C. Sonntag (eds), The roleof non-living organic matter in the earths carbon cycle. John Wiley & Sons.
Blough, N.V., and O.C. Zafiriou, and J. Bonilla. 1993. Optical absorption spectra of
waters from the Orinoco river outflow: Terrestrial input of colored organic matter to
the Caribbean. J. Geophys. Res. 98:2271-2278.Bricaud, A., A. Morel, and L. Prieur. 1981. Absorption by dissolved organic matter in
the sea (yellow substance) in the UV and visible domains. Limnol. Oceanogr.
26:43-53.Carder, K.L., R.G. Steward, G.R. Harvey, and P.B. Ortner. 1989. Marine humic and
fulvic acids: Their effects on remote sensing of ocean chlorophyll. Limnol.
Oceanogr. 34:68-81.
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Carder, K.L., F.R. Chen, C.P. Lee, S.K. Hawes, and D. Kamykowski. 1999.
Semianalytic moderate-resolution imaging spectrometer algorithms for chlorophylla and absorption with bio-optical domains based on nitrate depletion temperatures.
J. Geophys. Res. 104:5403-5421.
Deegan, L.A., J.W. Day, Jr., J.G. Gosselink, A. Yanez-Arancibia, G. Soberon-Chavez,
and P. Snachez-Gil. 1986. Relationships among physical characteristics, vegetationdistribution and fisheries yield in Gulf of Mexico Estuaries, p.83-100. In: D.A.
Wolfe (ed.), Estuarine variability. Academic Press.
Del Castillo, C.E., P.G. Coble, R.N. Conmy, F.E. Muller-Karger, L. Vanderbloemen, andG.A. Vargo. 2001. Multispectral in situ measurements of organic matter and
chlorophyll fluorescence in seawater: Documenting the intrusion of the Mississippi
River plume in the West Florida Shelf. Limnology and Oceanography, 46(7):1836-1843.
Del Castillo, C.E., F. Gilbes, P.G. Coble, and F.E. Muller-Karger. 2000. On the
dispersal of riverine colored dissolved organic matter over the West Florida Shelf.
Limnol. Oceanogr. 45(6):1425-1432
DSa, E.J., C. Hu, F.E. Muller-Karger, and K.L. Carder. 2002. Estimation of coloreddissolved organic matter and salinity fields in case 2 waters using SeaWiFS:
Examples from Florida Bay and Florida Shelf. Proc. Indian Acad. Sci. (EarthPlanet Sci.), 111(3), September 2002, pp. 197-207.
Ferrari, G.M., and M.D. Dowell. 1998. CDOM absorption characteristics with relation
to fluorescence and salinity in coastal areas of the Southern Baltic Sea. Estuarine,Coastal and Shelf Science 47:91-105.
Fogg, F.E., and G.T. Boalch. 1958. Extracellular products in pure cultures of brown
alga. Nature, 181:789-790.
Hochman, H.T., F.E. Muller-Karger and J.J. Walsh. 1994. Interpretation of the CoastalZone Color Scanner signature of the Orinoco River plume. J. Geophys. Res.,
99(C4):7443-7455.
Hochman, H., J.J. Walsh, K.L. Carder, A. Sournia, and F.E. Muller-Karger. 1995.
Analysis of ocean color components within stratified and well-mixed waters of thewestern English channel. J. Geophys. Res. 100:10,777-10787.
Hu, C., (2003).
Hu, C., F.E. Muller-Karger, D.C. Biggs, K.L. Carder, B. Nababan, D. Nadeau, and J.
Vanderbloemen. (in press). Comparison of ship and satellite bio-optical
measurements o the continental margin of the NE Gulf of Mexico. Int. J. Rem.Sensing.
Jochens, A. E., S. F. DiMarco, W. D. Nowlin, Jr., R. O. Reid, and M. C. Kennicutt II.
2002. Northeastern Gulf of Mexico Chemical Oceanography and Hydrography
Study: Synthesis Report. U. S. Department of the Interior, Minerals ManagementService, Gulf of Mexico OCS Region, New Orleans, LA. OCS Study MMS 2002-
055. 586 pp.
Leben, R.O., G.H. Born, and B.R. Engebreth. 2002. Operational altimeter data processingfor mesoscale monitoring. Marine Geodesy 25:3-18.
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Malcolm, R.L., and W.H. Durum. 1976. Organic carbon and nitrogen concentration and
annual carbon load of six selected rivers in the United States. U.S. Geol. Surv.Water-Supply Pap. 1817 p.
Meybeck, M. 1981. River transport of organic carbon to the ocean, p.216-267. In: Flux
of carbon by rivers to the oceans. Conf. 8009140, UC-11. U.S. Office of Energy
Research.Milliman, J.D., and R.H. Meade. 1983. Worl-wide delivery of river sediment to the
ocean. J. Geol. 91:1-21.
Momzikoff, A., S. Dallot, and G. Gondry. 1994. Distribution of seawater fluorescenceand dissolved flavins in the Almeria-Orant front (alboran Sea, Western
Mediterranean Sea). J. Mar. Sys. 5:361-376.
Montague, C.L., and J.A. Ley. 1993. A possible effects of salinity fluctuation onabundance of benthic vegetation and associated fauna in northeastern Florida Bay.
Estuaries 16:703-717.
Muller-Karger, F.E. 2000. The spring 1998 Northeastern Gulf of Mexico (NEGOM)
cold water event: Remote sensing evidence for upwelling and for eastward
advection of Mississippi water (or: How an errant Loop Current Anticyclone tookthe NEGOM for a spin). Gulf of Mexico Science 18(1):55-67.
Nowlin, W.D., A.E. Jochens, M.K. Howard, S.F. DiMarco, and W.W. Schroeder. 2000.Hydrographic properties and inferred circulation over the Northeastern Shelves of
the Gulf of Mexico during spring to midsummer of 1998. Gulf of Mexico Science
18(1):40-54.Siegel, D.A., and A.F. Michaels. 1996. Quantification of non-algal attenuation in the
Sargasso Sea: Implication for biogeochemistry and remote sensing. Deep-Sea Res.
II 43:321-345.
Turner, R.E., and N.N. Rabalais. 1991. Changes in Mississippi River quality thiscentury. Bioscience 3:140-147.
Vodacek, A., N.V. Blough, M.D. DeGrandpre, E.T. Peltzer, and R.K. Nelson. 1997.
Seasonal variation of CDOM and DOC in the Middle Atlantic Bight: Terrestrial
inputs and photooxidation. Limnol. Oceanogr. 42(4):674-686.Walker, N.D., G.S. Fargion, L.J. Rouse, and D.C. Biggs. 1994. The great flood of
summer 1993: Mississippi River discharge studies. EOS Trans. Am. Geephys.
Union 75:409-411.Weisberg, R.H., B.D. Black, and Z. Li. 2000. An upwelling case study o Florida's west
coast. J. Geophys. Res. 105(C5):11,459-11,469.
Yentsch, C.S., and C.A. Reichert. 1962. The interrelationship between water-solubleyellow substances and chloroplastic pigments in marine algae. Bot. Mar. 3:65-74.
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List of Tables and Figures
Table 1. Cruise identifiers and dates.
Table 2. Regression coefficient (intercept and slope) with respective standard deviation,
correlation (r) between salinity and ag443 (sal=a + b*ag443) and mean error percentage(MEP) for salinity prediction based on ag443 data within 95% prediction interval of each
region in different cruises (seasons).
Figure 1. Study area of the NEGOM region, encompassing the area between 27.3 - 30.7
N and 82.6 - 89.6W. The map shows the bathymetry of 10, 20, 100, 200, 500, and 1000
m, a cruise transect lines in which flow-through system of CDOM fluorescence andsalinity were collected, and numbered open squares from which salinity, CDOM
absorption, chlorophyll concentration and sea surface temperature were extracted.
Rectangle area in the Gulf of Mexico inset is the area of the study.
Figure 2. Near-surface ag443 (m-1) distribution map of the NEGOM cruises. Thin white
line indicates the cruise transect in which continuous flow-through system of CDOM
fluorescence were collected.
Figure 3. Near-surface salinity distribution map of the NEGOM cruises. Thin white line
indicates the cruise transect in which continuous flow-through system of salinity werecollected.
Figure 4. Sea surface height (SSH) anomaly and sub-surface current (10-14 m deep) map
of the NEGOM cruises. Note: no sub-surface current data on N4 due to the problem of
ADCP equipment.
Figure 5. Near-surface ag443 (m-1
) (top panel), salinity (middle panel) and chlorophyllconcentration (bottom panel) mean values with respect to standard deviation of each
region in different cruise seasons.
Figure 6. Scatter plots of salinity vs ag443 for each region in different seasons (cruises).
Figure 7. Scatter plots of salinity vs ag443 for each season (cruise) in different regions.
Figure 8. Scatter plot of ag443 at zero salinity (A) and river discharge average of six
major rivers for each cruise period (B). Note the difference of axis scale for theMississippi River discharge in Figure A and B is m3/day x 10
9.
Figure 9. Scatter plots of ag443 vs chlorophyll for each region in different seasons (cruises)
and registered with level of salinity range.
Figure 10. Some examples of error analysis for salinity prediction based on ag443 data
within 95% prediction interval.
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Figure 11. Mean error percentage (%) of predicted salinity based on ag443 data for each
region in different seasons (top panel) and for each season in different regions (lowerpanel).
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Table 1. Cruise identifiers and dates
Cruise no. Start date End date Cruise ID Cruise season
1 25 July 1998 6 August 1998 N3 summer
2 13 November 1998 24 November 1998 N4 winter
3 15 May 1999 28 May 1999 N5 spring4 15 August 1999 28 August 1999 N6 summer
5 13 November 1999 23 November 1999 N7 winter
6 15 April 2000 26 April 2000 N8 spring
7 28 July 2000 8 August 2000 N9 summer
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Table 2. Regression coefficient (intercept and slope) with respective standard deviation,
correlation (r) between salinity and ag443 (sal=a + b*ag443) and mean error percentage(MEP) for salinity prediction based on ag443 data within 95% prediction interval of each
region in different cruises (seasons).
Note: P is level of probability for non-linear or linear relationship testFor P
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Table 3. Summary of analysis of variance for comparison of salinity-ag443 regression
slopes both among seasons within each region and among regions within each season________________________________________________________________________
F DF P F DF P
Among seasons within each region Among regions within each season
R1 186.40 6, 3341 0.0000 N3 223.48 7, 1865 0.0000R2 111.23 6, 1094 0.0012 N4 670.61 7, 1940 0.0000R3 53.16 6, 2165 0.0006 N5 60.49 7, 2025 0.0000
R4 345.96 6, 1248 0.0000 N6 105.47 7, 1660 0.0019
R5 58.50 6, 1188 0.0000 N7 120.54 7, 2088 0.0000R6 327.40 6, 1330 0.0000 N8 327.24 7, 1887 0.0000
R7 125.05 6, 1173 0.0000 N9 139.66 7, 2260 0.0026
R8 364.51 6, 2186 0.0000
Note: DF is degree of freedom, P is the probability of significant level
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Figure 1. Study area of the NEGOM region, encompassing the area between 27.3 - 30.7N and 82.6 - 89.6W. The map shows the bathymetry of 10, 20, 100, 200, 500, and 1000m, a cruise transect lines in which flow-through system of CDOM fluorescence and
salinity were collected, and numbered open squares from which salinity, CDOM
absorption, chlorophyll concentration and sea surface temperature were extracted.
Rectangle area in the Gulf of Mexico inset is the area of the study.
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Figure 2. Near-surface ag443 (m-1
) distribution map of the NEGOM cruises. Thin whiteline indicates the cruise transect in which continuous flow-through CDOM fluorescence
were collected.
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Figure 3. Near-surface salinity distribution map of the NEGOM cruises. Thin white line
indicates the cruise transect in which continuous flow-through system of salinity werecollected.
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Figure 5. Mean and standard deviation of the near-surface ag443 (m-1
) (top panel), salinity
(middle panel) and chlorophyll concentration (bottom panel) for each selected region(R1 to R8 in Fig. 1) and for each season (cruise).
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
R1 R2 R3 R4 R5 R6 R7 R8
ag443(1/m)
Region
N3
N4
N5
N6
N7
N8
N9
0
5
10
15
20
25
30
35
40
R1 R2 R3 R4 R5 R6 R7 R8
Salinity
Region
N3 N4 N5 N6 N7 N8 N9
0.0
1.0
2.0
3.0
4.0
5.0
6.0
R1 R2 R3 R4 R5 R6 R7 R8
ChlorophyllConc.
(mg/m^3)
Region
N3
N4
N5
N6
N7
N8
N9
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Figure 6. Scatter plots of salinity vs ag443 for each region in different seasons (cruises).
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Figure 7. Scatter plots of salinity vs ag443 for each season (cruise) in different regions.
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Figure 8. Scatter plot of ag443 at zero salinity (A) and river discharge average of six
major rivers for each cruise period (B). Note the difference of axis scale for the
Mississippi River discharge in Figure A and B is m3/day x 109.
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Figure 9. Scatter plots of ag443 vs chlorophyll for each region in different seasons
(cruises) and registered with level of salinity range.
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Figure 10. Some examples of error analysis for salinity prediction based on ag443 data
within 95% prediction interval.
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Figure 11. Mean error percentage (%) of predicted salinity based on ag443 data for each
region in different seasons (top panel) and for each season in different regions (lowerpanel).