Draft1 Accept Change

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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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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).

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