Potential impacts of nonalgal materials on water-leaving Sun induced chlorophyll fluorescence signals in coastal waters

Potential impacts of nonalgal materials on water-leavingSun induced chlorophyll fluorescence signals in coastal

waters

David McKee,* Alex Cunningham, David Wright, and Lorraine HayDepartment of Physics, Scottish Universities Physics Alliance, University of Strathclyde, 107 Rottenrow,

Glasgow G4 0NG, Scotland

*Corresponding author: [email protected]

Received 27 June 2007; revised 7 September 2007; accepted 10 September 2007;posted 13 September 2007 (Doc. ID 84548); published 25 October 2007

It has been suggested that Sun induced chlorophyll fluorescence (SICF) signals could be used to estimatephytoplankton chlorophyll concentration and to investigate algal physiology from space. However, water-leaving SICF is also a product of the ambient light field. In coastal waters both algal and nonalgal materialsaffect the underwater light field. In this study we examine the independent impacts of varying loads ofmineral suspended solids (MSS) and colored dissolved organic materials (CDOM) on water-leaving SICFsignals using Hydrolight radiative transfer simulations. We show that SICF signals in coastal waters arestrongly influenced by nonalgal materials. Increasing concentrations of CDOM and minerals can reducethe water-leaving SICF per unit chlorophyll by over 50% for the concentration ranges explored here(CDOM � 0 to 1 m�1 at 440 nm, MSS � 0 to 10 g m�3). The moderate-resolution imaging spectroradiom-eter (MODIS) fluorescence line height algorithm is shown to be relatively unaffected by increasing CDOM,but performance is significantly degraded by mineral concentrations greater than 5 g m�3 owing to in-creased background radiance levels. The combination of these two effects means that caution is required forthe interpretation of SICF signals from coastal waters. © 2007 Optical Society of America

OCIS codes: 280.0280, 010.4450, 260.2510.

1. Introduction

The optical properties of coastal and shelf seas aredetermined by the contributions from a variety ofconstituents, often categorized as phytoplankton,minerals, and colored dissolved organic materials(CDOM), each of whose concentrations varies inde-pendently over potentially broad ranges. The result-ing optical complexity is a major obstacle to thedevelopment of robust algorithms for interpretingdata from satellite ocean color sensors. For example,algorithms for estimating chlorophyll concentration(Chl) using simple blue-green reflectance ratios havebeen found to perform poorly in coastal waters, lead-ing to the development of regionally tuned [1] andwater-type specific variants [2] as well as other semi-analytic approaches [3]. Each optical constituent in-

fluences radiative transfer in the water columnthrough its inherent optical properties (IOPs), includ-ing absorption, scattering, and backscattering. In-elastic scattering processes such as fluorescence byChl and CDOM as well as Raman scattering by wateritself can also play an important role in determiningspectral reflectance signals. Of these, chlorophyll flu-orescence appears to offer the greatest potential forextracting additional useful information from satel-lite measurements.

Neville and Gower [4] demonstrated that a peakcentered on 685 nm observed in surface leaving re-flectance spectra could be attributed to Sun inducedchlorophyll fluorescence (SICF). Since then numer-ous studies have examined the relationship betweenSICF and chlorophyll concentration [5–9]. Other re-searchers have worked on determining physiologicalstate or primary production through relationships be-tween fluorescence signals and the quantum yield forfluorescence, �, and chlorophyll-specific absorption,

0003-6935/07/317720-10$15.00/0© 2007 Optical Society of America

7720 APPLIED OPTICS � Vol. 46, No. 31 � 1 November 2007

achl* [10–13]. Kattawar and Vastano [14] and Mari-

torena et al. [15] provided a theoretical frameworkthat describes the radiative transfer processes thatgenerate the water-leaving Chl fluorescence signal.

Most of the analysis of remote sensing Chl fluo-rescence signals has concentrated on open oceanCase 1 waters where phytoplankton are the domi-nant optical constituent along with water itself, forinstance [16]. More recently satellite sensors suchas the moderate-resolution imaging spectroradiom-eter (MODIS) and the medium resolution imagingspectrometer (MERIS) [17,18] have been launchedwith sensors specifically configured to measure chlo-rophyll fluorescence from space [19]. Regular globalcoverage is a key benefit of these measurements, butit is important that the user community understandsthe processes affecting generation of SICF from Case2 waters, where mineral particles and CDOM mayalso contribute significantly to the optical propertiesof the water column. Previous studies have notedsome impact of nonalgal materials on fluorescencesignals using bio-optical models [20,21] and other ra-diative transfer methods [22]. Despite this, it hasbeen suggested that Sun induced Chl fluorescencemight be used to determine Chl in Case 2 waterswhere the presence of CDOM and minerals may in-validate other methods [23]. Indeed field results havebeen presented suggesting that water-leaving Chlfluorescence may be well correlated with Chl over adiverse range of optical environments [24]. Hoge et al.[25] found that the MODIS fluorescence line height(FLH) product was not influenced by CDOM for arange of water types in the western North AtlanticOcean. Laney et al. [26], referring to work done incoastal waters off Oregon, suggested that SICF mightbe particularly useful in turbid Case 2 waters. How-ever, since the Sun induced Chl fluorescence signal isa product of the ambient light field as well as thealgal population, and the light field is affected bynonalgal materials, there is good reason to investi-gate the degree to which water-leaving SICF signalsare subject to nonalgal influence.

Given the potential benefits of being able to use Chlfluorescence as a diagnostic indicator for phytoplank-ton, its sensitivity to physiological state, and theavailability of global-scale data as a standard productfrom more than one satellite system, it is appropriateto re-examine the radiative transfer processes under-pinning this signal and to examine in detail howthese are affected by the presence of significant con-centrations of nonalgal materials. In doing so, we canbring to bear on the problem advanced radiativetransfer simulations (Hydrolight, Sequoia) and re-cent estimates of material-specific IOPs obtainedfrom coastal waters using state-of-the-art in situ in-strumentation [27]. This radiative transfer simula-tion technique enables us to systematically analyzethe influence of nonalgal materials on Sun inducedChl fluorescence signals, specifically identify absorp-tion and scattering artefacts, and assess the potential

performance of the MODIS FLH algorithm for coastalwaters.

2. Theory

In this paper we are concerned with radiative trans-fer processes influencing the generation and prop-agation to the sea surface of solar-stimulatedchlorophyll fluorescence photons and factors affectingour ability to interpret these signals from water-leaving radiometry. A theoretical framework outlin-ing the radiative transfer processes contributing tofluorescence stimulation and emission has been pub-lished [14,15] and is summarized here. Note that forthis analysis all materials are assumed to be uni-formly distributed vertically through the water col-umn.

Chlorophyll fluorescence is excited by absorption ofphotons by phytoplankton between �400 and 690 nm(denoted with subscript ex), and is emitted in a broad-band with a peak wavelength at 685 nm (denoted bysubscript em). The fluorescence quantum yield, �, isdefined here as the ratio of photons emitted by fluo-rescence in the 685 nm emission band, Ff, to photonsabsorbed by phytoplankton in the 400–690 nm exci-tation band, Aex:

� � Ff�Aex. (1)

We note that this is an effective yield rather than atrue physiological yield, and that since we ignore par-tial reabsorption of fluorescence within algal cells thetrue physiological yield would be greater than ourrealized value [7,28].

The number density of photons (�mol photonm�3 s�1) absorbed by phytoplankton at a given pointin the water column can be calculated from

Aex � Chl a�ex* Eo

ex, (2)

where Chl is the local chlorophyll concentration�mg m�3�, Eo

ex is the quantum scalar irradiance in-tegrated across the excitation wavelength range��mol photon m�2 s�1�, and a�ex

* is the spectrallyweighted chlorophyll-specific algal absorption coeffi-cient, given by

a�ex* � �

�ex

a*��Eoex��d��

�ex

Eoex��d�. (3)

It has been shown [14,15] that the total quantumfluorescence signal integrated across the emissionwaveband, Lfq ��mol photon m�2 s�1 sr�1�, receivedby a nadir-viewing sensor from the layers immedi-ately below it, is given by

Lfq�z� ��a�ex

* Chl Eoex�z�

4��aem � Koex�

. (4)

1 November 2007 � Vol. 46, No. 31 � APPLIED OPTICS 7721

Equation (4) shows that the fluorescence signal isdependent on the underwater light field through thediffuse attenuation of scalar irradiance averagedacross the excitation wavelengths �Ko

ex�, the absorp-tion of fluorescence emission �aem� at �685 nm�640–730 nm�, the scalar irradiance Eo

ex integratedacross the excitation wavelengths �400–690 nm�, andalso through the dependence of a�ex

* on Eoex given by Eq.

(3). Thus there are four light field parameters thatcan be influenced by the presence of nonalgal mate-rials and have an impact on fluorescence signal gen-eration. We shall examine the sensitivity of each tononalgal contributions.

In deriving Eq. (4) it was assumed that aem wouldbe dominated by water absorption and that scatter-ing would have a negligible effect on the propagationof fluorescence to the surface. It is also assumed thatsince aem is relatively large, the fluorescence signalwill be received from relatively shallow depths [7]and therefore � and Ko

ex can be assumed to be effec-tively constant with depth for real-world applica-tions.

3. Materials and Methods

Radiative transfer simulations were performed withHydrolight v4.2 (Sequoia) using a four componentCase 2 model consisting of water, phytoplankton,CDOM, and mineral suspended solids (MSS). All sim-ulations were performed with 2 nm wavelength res-olution between 400 and 760 nm, vertically uniformIOPs, surface wind speed of 5 m s�1, zero cloud cover,solar zenith angle of 45°, and above-surface irradi-ance calculated using the Gregg and Carder model[29]. Simulations were performed to a depth of 40 mand Ko

ex was evaluated to the first optical depth for theexcitation waveband. Absorption and scattering val-ues for pure water were taken from Pope and Fry [30]and Smith and Baker [31], respectively. Material-specific IOPs for each nonwater constituent wereselected on the basis of consistency with samplesobtained from previous fieldwork in the Irish Sea�Bristol Channel [27]. Material-specific absorptionspectra are shown in Fig. 1(a). The chlorophyll-specific absorption spectrum was derived from filterpad absorption data and was selected since it had avalue of achl

* �676� � 0.022 m2 mg�1, consistent with[27]. Mineral-specific absorption was modeled withan exponential function set to 0.05 m2 g�1 at 440 nmand an exponent of �0.010, also consistent with pre-viously published Irish Sea data. The CDOM absorp-tion was modeled on an exponential function with anexponent of �0.014 and using absorption by CDOMat 440 nm as the principal factor [32]. Chlorophyll-and mineral-specific scattering spectra [Fig. 1(b)]were taken from Table 2 in [27] with typical values of0.35 m2 mg�1 and 0.35 m2 g�1, respectively. As theHydrolight ABCASE2 model only permits a singlescattering phase function for each constituent thatcannot be varied with wavelength, wavelength-averaged backscattering ratios were taken for algal(0.013) and mineral (0.040) components based on

data in Table 1 of [27]. These backscattering ratioswere used to select appropriate Fournier–Forandscattering phase functions for each component [33–35]. A relatively high value of quantum yield for flu-orescence �2%� was set for all simulations as thisfacilitated observation of fluorescence signals in tur-bid waters (see Subsection 4.E) though it should benoted that this is a strongly variable parameter innature, e.g. [7].

Hydrolight provides the option of including threeinelastic scattering processes within a simulation: al-gal fluorescence, CDOM fluorescence, and Ramanscattering. Three sets of radiative transfer simula-tions were performed: (a) with all three inelasticscattering processes included, (b) with no inelasticscattering processes included, and (c) with CDOMfluorescence and Raman scattering, but no chloro-phyll fluorescence included. The first set of runs pro-vided the most realistic light fields we could achieve.The second set was used to calculate diffuse attenu-

Fig. 1. Material-specific absorption and scattering spectra usedfor Hydrolight radiative transfer simulations were selected as rep-resentative of constituent populations previously observed incoastal waters of the Irish Sea.


ation coefficients without interference from inelasticprocesses. The third set provided baselines requiredfor calculating true fluorescence line heights andwavelength-integrated quantum water-leaving fluo-rescence signals. Each set of runs encompassed twosubsets, the first of which saw minerals and chloro-phyll varied �CDOM � 0�, with CDOM and chloro-phyll varied in the second �MSS � 0�. The Chl valuesvaried through 0.1, 0.5, 1, 5, and 10 mg m�3, MSSvaried though 0, 0.5, 1, 5, and 10 g m�3, and CDOMabsorption at 440 nm varied through 0, 0.05, 0.1, 0.5,and 1 m�1. It is worth noting that both CDOM andMSS absorption increase exponentially into the blueand that absorption at 440 nm (a potential represen-tative for absorption in the broader fluorescence ex-citation band) is the same for both components whenCDOM � 0.5 m�1 and MSS � 10 g m�3. The CDOM(which only absorbs) and MSS (which absorbs andscatters) were varied separately to facilitate investi-gation into the impacts of absorption and scatteringon fluorescence generation and transmission. Theseconstituent ranges were selected to cover moderatelyturbid coastal water conditions such as those ob-served in the Irish Sea. It should be noted that theydo not represent extreme values, and much broaderranges of constituent concentrations can be found innature.

Hydrolight simulates chlorophyll fluorescence emis-sion using a Gaussian distribution centered on685 nm �25 nm FWHM�. In this paper we use Lf685(see Fig. 2) as our preferred measure of water-leavingfluorescence. This parameter was obtained by sub-

tracting baseline upward radiance spectra (immedi-ately beneath the sea surface) generated withoutchlorophyll fluorescence from full subsurface radi-ance spectra with all inelastic processes included.The water-leaving fluorescence radiance, Lf685�W m�2 nm�1 sr�1�, can also be expressed in quan-tum terms as Lfq685 ��mol photon m�2 s�1 sr�1� bydividing Lf685 by 10�6 � �NAhc��, where NA isAvogadro’s number, h is Planck’s constant, c is thespeed of light, � is the wavelength, and �� is thebandwidth. Note: Lfq has to be integrated acrossthe entire emission bandwidth for incorporation intoEq. (4), and Lf685 should not be confused with theFLH generated from satellite data with limited num-bers of discrete wavebands and based on approximatebaselines. For example, the MODIS FLH product iscalculated by interpolating a baseline to 676 nmbetween measurements at 667 and 748 nm, and sub-tracting this approximate baseline from the mea-sured total radiance at 676 nm (see Fig. 2). The

Fig. 2. True water-leaving fluorescence signal, Lf685, is obtainedby subtracting water-leaving radiances calculated from radiativetransfer simulations with and without chlorophyll fluorescence.The MODIS FLH algorithm estimates the fluorescence line heightat 676 nm by interpolating a linear baseline between neighboringwavebands at 667 and 748 nm. This is off-center from the peakfluorescence emission waveband at 685 nm, but can be comparedwith true fluorescence line heights at 676 nm derived from radia-tive transfer simulations.

Fig. 3. (a) In Case 1 waters the subsurface �0�� water-leavingfluorescence signal, Lf685, increases nonlinearly with Chl, whileLf685 per unit chlorophyll decreases. (b) Increasing Chl raises bothKo

ex and Eoex (and also aem—not shown), which results in the ob-

served decrease in Lf685�Chl.


wavelength discrepancy between FLH at 676 nm andLf685 is necessary for practical reasons (it avoids anatmospheric oxygen absorption band), and is well un-derstood to have both sensitivity and phytoplanktonreabsorption issues [6,7,19]. In practice a small offsetis added to FLH measurements to account for base-line artifacts [19]. In this paper we shall examine theperformance of the FLH baseline procedure over arange of constituent concentrations with realisticmaterial-specific IOPs, comparing FLH values withLf676, which is calculated in the manner of Lf685, i.e.,by subtracting a true baseline from the total radiancesignal.

4. Results

In this section, all fluorescence and scalar irradiancesignals are taken from immediately beneath the seasurface (0�), while Ko

ex values are evaluated over thefirst optical depth for the excitation waveband.

A. Water-Leaving Fluorescence—Case 1 Waters

It is instructive to start by examining the generationof Sun induced fluorescence in Case 1 waters wherenonalgal materials have zero impact. An initial set ofHydrolight simulations were carried out with chloro-phyll varied between 0.1 and 10 mg m�3, and with

zero CDOM and minerals. Figure 3(a) shows that therelationship between Lf685 and Chl is nonlinear,with Lf685�Chl decreasing as Chl increases, in agree-ment with previous studies, e.g., [8]. Over this rangeof Chl concentration, the surface-leaving fluorescenceemission per unit chlorophyll reduces by almost athird. It is important to note that although Eq. (4)shows an explicit dependence on Chl in the numera-tor, Chl also potentially influences the four light fieldparameters identified in Section 2, with the observednonlinear relationship a consequence. Figure 3(b)shows that both Ko

ex and Eoex increase as Chl increases,

and aem also increases significantly ��30%� over thisrange of Chl. The observed nonlinear reduction insubsurface �0�� Lf685�Chl as Chl increases [Fig.3(a)] can be attributed to the impact of absorption andscattering by phytoplankton on the underwater lightfield, as increases in Chl and Eo

ex are offset by in-creases in Ko

ex and aem.

B. Water-Leaving Fluorescence—Case 2 Waters

The impact of increasing concentrations of firstCDOM �0–1 m�1 at 440 nm� and then minerals�0–10 g m�3� on the relationship between Lf685 andChl can be seen in Fig. 4. Increasing concentrations of

Fig. 4. (a) and (c) Increasing concentrations of CDOM reduce subsurface �0�� water-leaving fluorescence signals by up to 65%, withLf685�Chl varying by a factor of �2 for this range of CDOM. (b) and (d) Small concentrations of MSS slightly increase Lf685�Chl but largerconcentrations have the opposite effect.


CDOM in the water column results in a reduction inLf685 per unit of Chl, with Lf685 being reduced by upto 57% relative to the Case 1 scenario [Fig. 4(a)];Lf685�Chl varies by a factor of �2 for this range ofCDOM [Fig. 4(c)]. Since CDOM is assumed to havezero scattering, this behavior must be solely attrib-utable to absorption effects. The addition of up to10 g m�3 of MSS has less impact on Lf685 per unit ofChl, though the trend is again generally downward,with Lf685 being reduced by up to 24% [Fig. 4(b)]. Infact, at low chlorophyll and low �1 g m�3� MSS con-centrations Lf685�Chl actually increases by up to 6%[Fig. 4(d)]. Given the similarities in the MSS andCDOM absorption spectra, and the fact that similarranges of absorption are covered (MSS � 10 g m�3 isbroadly similar to CDOM � 0.5 m�1 in absorptionterms), the different impact on fluorescence signals ofthese two materials is presumably due to scatteringeffects from the mineral particles. Differential effectsof CDOM and MSS on water-leaving Chl fluorescencesignals can be identified by examining their impacton the light field parameters in Eq. (4).

C. Impact of Nonalgal Materials on Light FieldParameters

We previously identified four parameters in Eq. (4)that depend on the local light field and could poten-tially be influenced by the presence of nonalgal ma-terials in the water column (a�ex

* , aem, Koex, and Eo

ex).Analysis of Hydrolight output for all of the simula-tions performed for this paper shows that a�ex

* �0.018 � 0.001 m�1 for the entire range of samplingconditions. We can therefore effectively remove thisparameter as a potential source of the variabilityobserved in Fig. 4, though it should be noted for otherapplications that this parameter will vary withchanges in phytoplankton community compositionand physiological state, and with solar angle. Theabsorption coefficient for the fluorescence emissionband, aem, varies between �0.49 and 0.70 m�1 forthese ranges of constituent concentrations, with thewater absorption being the greatest contributor, fol-lowed by phytoplankton; aem has very little depen-dence on either CDOM or MSS (�0.04 m�1 for the fullrange of either constituent), consistent with both ofthese materials having absorption spectra that decayexponentially towards longer wavelengths. The im-pact of both CDOM and MSS is, however, signifi-cantly greater on both Ko

ex and Eoex. Strong absorption

by CDOM in the fluorescence excitation wavebandsexplains the variability of Ko

ex with CDOM [Fig. 5(a)].However, absorption only partially explains the rela-tionship with MSS in Fig. 5(b) (noting that the MSSrange covers less absorption variability than theCDOM range) as backscattering by mineral particlesalso contributes to the diffuse attenuation coefficient.Mineral backscattering also affects the relationshipbetween subsurface Eo

ex and MSS. Whereas increas-ing CDOM (which absorbs but does not scatter) re-duces Eo

ex by up to 10% over the chosen range ofCDOM [Fig. 6(a)], increasing MSS has the effect of

increasing Eoex by up to 43% [Fig. 6(b)]. It is worth

noting that prolonged exposure of phytoplanktoncells to the high subsurface �0�� scalar irradiancevalues shown in Fig. 6 could induce significantnonphotochemical quenching. Under these circum-stances the quantum yield for fluorescence mightvary significantly with depth.

The overall effect of CDOM is to reduce the avail-ability of photons in the excitation waveband by ab-sorbing light traveling in any direction beneath thesea surface. The effect of mineral particles is morecomplicated. Since these particles are absorbing, theyreduce the overall availability in the water column ofphotons capable of exciting fluorescence. However,

Fig. 5. The average diffuse attenuation coefficient for scalar ir-radiance in the excitation waveband, Ko

ex, increases with both (a)CDOM and (b) MSS. However, it is more sensitive to MSS, whichscatters as well as absorbs (MSS � 10 g m�3 has a similar averageabsorption coefficient to CDOM � 0.5 m�1 in the excitation wave-band).


scattering by mineral particles changes photon tra-jectories through the water column in such a way thatthe subsurface scalar irradiance increases as mineralparticle concentration increases. This results in moreexcitation photons being available to stimulate fluo-rescence close to the sea surface, where there is agreater probability of fluorescence reaching the air–sea interface. In effect mineral scattering effects par-tially compensate for absorption effects, reducing thenegative impact on water-leaving Chl fluorescencesignals.

D. Effective Quantum Yield Retrieval in Case 2 Waters

Equation (4) provides a computationally efficient al-ternative to solving the full radiative transfer equa-tion that might be particularly useful for remotesensing. It can also be rearranged to provide an esti-

mate of the effective yield of fluorescence, �. We canassess the validity of Eq. (4) for a wide range of Case2 water conditions, and also its potential for deter-mining � by attempting to retrieve our input value of0.02 �2%� using light field data supplied from Hy-drolight outputs. Figure 7 shows retrieval of � for theranges of constituent concentrations covered in thispaper. In the absence of any nonalgal materials theretrieved value of � varies between �10% of the truevalue. Adding CDOM [Fig. 7(a)] tends to reduce thevalue of � obtained, with the maximum error being a12% underestimate ��est � 0.0176�. Increasing theMSS concentration [Fig. 7(b)] causes overestimates of�, with maximum errors of 26% ��est � 0.0253�. � isknown to vary by up to an order of magnitude in re-sponse to physiological changes [13,15,16], and so the

Fig. 6. (a) CDOM absorption reduces integrated subsurface sca-lar irradiance in the excitation waveband, Eo

ex, as CDOM increases.(b) MSS scattering raises Eo

ex, even though MSS also absorbs in thefluorescence excitation waveband.

Fig. 7. Values of the effective quantum yield for fluorescencecalculated using Eq. (4). (a) Increasing CDOM reduces estimates of�, while (b) increasing MSS leads to overestimates of �. The truevalue of � was 0.020 for these simulations.


maximum retrieval error using Eq. (4) is considerablyless than the natural variability of this parameter. Wecan conclude that Eq. (4) provides a reasonable repre-sentation of the processes contributing to the genera-tion of water-leaving fluorescence signals. The factthat it does not provide a perfect retrieval of �, evenunder these highly idealized circumstances, is a re-minder that it is an approximation to a full solution ofthe radiative transfer equation. It does not fully ac-count for alterations in the geometrical distribution ofphotons in the water column in response to changes inthe balance between absorption and scattering. Thelimit on its usefulness in practice is likely to be theaccuracy with which each of its parameters can beestimated from remote sensing data products.

E. Fluorescence Line Height Baseline Correction inTurbid Case 2 Waters

The differential impacts of the two nonalgal materi-als on red water-leaving radiance signals are demon-strated in Fig. 8, where it can be seen that for a given

chlorophyll concentration: (a) increasing the CDOMabsorption generally reduces the radiance signal in-cluding fluorescence, (b) increasing the MSS gener-ally raises radiance levels (note the extra factor of 10on the y axis), and the fluorescence peak becomes lessprominent against the raised background signal. Theperformance of the MODIS FLH calculation proce-dure can be assessed for turbid waters by comparingFLH values with equivalent values of Lf676 calcu-lated by subtracting true baselines (Hydrolight runswith no Chl fluorescence) from total radiance spectra(Hydrolight runs with Chl fluorescence). Figure 9(a)shows that MODIS FLH systematically underesti-mates the true Lf676 signal by 20%–30% for low Chlvalues, even in the absence of nonalgal materials,

Fig. 8. (a) Effect of increasing CDOM absorption is generally tolower water-leaving radiances in the fluorescence emission wave-band. (b) Increasing MSS to 10 g m�3 increases background water-leaving radiances by an order of magnitude, and causes the Chlfluorescence peak to become less prominent. Note the order ofmagnitude difference in y axis scales in panels (a) and (b).

Fig. 9. (a) MODIS FLH algorithm generally underestimates thetrue fluorescence signal at 676 nm �Lf676� with the effect becomingmore pronounced as both Chl and CDOM increase. (b) High con-centrations of MSS cause the MODIS FLH algorithm to overesti-mate Lf676 by up to an order of magnitude when Chl is low andunderestimate by as much as 70% when Chl is high.


with the FLH signal reaching only 55% of Lf676 whenChl � 10 mg m�3. Adding small concentrations ofCDOM has a very limited impact on FLH algorithmperformance (there is a slight improvement at lowChl concentrations), which is consistent with Hogeet al. [25]. The FLH algorithm is considerably moreaffected by the presence of mineral particles. Figure9(b) shows that FLH underestimates Lf676 when Chland MSS values are high, reaching only �30% of thetrue value when both Chl and MSS are at the highends of their chosen ranges. However, the most dra-matic effect is the overestimation of Lf676 when Chlis low and MSS increases, when FLH values canoverestimate Lf676 by an order of magnitude. Itshould be noted that although these are high percent-age errors, the Lf676 values are not high when Chl islow. The FLH algorithm appears to breakdown forMSS values of 5 g m�3 and above, due to an inabilityto resolve the fluorescence peak over raised back-ground radiance levels in turbid waters. As theseradiative transfer simulations were performed with afluorescence yield of 2%, which is toward the high endof the range found in nature, it is possible that inpractice the FLH algorithm performance may de-grade at even lower MSS concentrations than theseresults suggest.

5. Discussion

The ability to observe phytoplankton fluorescencefrom space has raised the intriguing possibility ofsurveying variations in phytoplankton concentra-tions and physiology on unprecedented geographicalscales, e.g., [8]. Naturally, most effort has gone intointerpreting fluorescence signals from Case 1 waterswhere the effects of nonalgal materials are negligible.However it is also important to assess the potential ofsuch techniques for more optically complex coastalwaters where a significant proportion of global ma-rine productivity occurs. It is well known that otheralgorithms, such as blue–green reflectance ratios forchlorophyll, often perform poorly in coastal waters. Inthis paper we have used radiative transfer simula-tions based on realistic material specific IOPs tomodel the impact of varying mineral and CDOM con-centrations on water-leaving Sun induced fluores-cence signals. This means that our findings are freefrom the measurement artifacts that inevitably affectthe interpretation of in situ data. Using this ap-proach, we have determined that nonalgal materialsprimarily affect the stimulation of fluorescence byaltering the scalar irradiance field, Eo

ex, and the dif-fuse attenuation of scalar irradiance, Ko

ex. Their im-pact on the transmission of fluorescence from depth tothe surface appears to be limited for the concentrationranges examined. The overall effect of nonalgal mate-rials is to reduce the water-leaving fluorescence signalper unit chlorophyll. This has an effect on the mini-mum detectable Chl, but it does not prohibit the useof Eq. (4) to interpret the signal. However, to use Eq.(4) with remote sensing data, it is necessary to pro-vide estimates of each of its parameters from the data

set available, or make reasonable estimates based ona priori knowledge.

For remote sensing applications, the greatest ob-stacles to using Eq. (4) in turbid waters appear to beour ability to estimate the fluorescence signal itselfwhen background radiance levels are raised by min-eral backscattering [Fig. 9(b)], or when the signal isinhibited due to the presence of high CDOM concen-trations [Fig. 4(a)]. Prospects appear to be good forderiving other required parameters, such as Eo

ex andKo

ex, from standard MODIS (or equivalent) products[8,36], while the absorption of emitted fluorescenceaem may be approximated by water absorption [15] orwater plus phytoplankton absorption [8]. Improvedmethods for retrieving Chl in turbid coastal waters[1,2] are being developed that could also facilitateusing Eq. (4) to estimate effective quantum yields ��from remote sensing measurements of FLH. Notethat for our simulated data set there is a strong linearrelationship between Lf676 and total quantum fluo-rescence [Lfq: �mol photons m�2 s�1 sr�1—requiredfor Eq. (4)] of the form Lfq � 223.4 � Lf676. However,our results suggest that FLH measurements maybe compromised by the presence of high mineralor CDOM concentrations, and under such circum-stances the applicability of Eq. (4) is very much indoubt. Higher concentrations of CDOM or MSS andlower effective fluorescence yields than those consid-ered in this study would all further limit our abilityto resolve the water-leaving chlorophyll fluorescencesignal.

6. Conclusion

Water-leaving Sun induced Chl fluorescence signalsare a product of the phytoplankton population andthe surrounding light field. If that light field is sub-ject to nonalgal influence then so is the chlorophyllfluorescence signal. Users of remote sensing productsbased on SICF should be aware of the potential in-fluence of nonalgal materials, and be particularlycareful in interpreting such products from turbidcoastal waters.

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