---IN SITU OPTICAL METHODS FOR CHLOROPHYLL ESTIMATION IN THE SEA
A Thesis Presented to The Faculty of the Department of Biology San Jose State University
In Partial Fulfillment of the Requirements for the Degree Master of Arts
by Jeffrey W. Nolten December 1980 Acknowledgements
This research was supported by National Oceanographic and Atmospheric Administration Grant No. 04-m~Ol-129. I 1-.rould like to thank Dennis Clark of NOAA and Robert Wrigley of NASA for free access to their cruise data and for their time and advise. A thank you to Lynn Krasnow of MLML for the art work. I would like to thank the students and staff of Moss Landing Marine Laboratories for making my tenure there a period of personal growth and fulfillment. I thank my wife Donna for her patience and understanding. A special thanks goes to Dr. William Broenkow of MLML, for without his guidance this work would never have been possible.
ii CONTENTS
Figures and Tables •.....•.....•...•.••.....••.•.•.•...•••.•.•... iv
Introduction ...... •...•...... •...... ••..•.•...... •..•.•. 1
Data Sources and ~1ethods ...... •...•..•..•... 8 Results and Discussion ...... •••...... •...•...... •••...•.. 11
The Secchi Disk •...... •...... •...... 15
Munsell Color ...... •.....••....•.•...... •...•...•.•. 22
Conclusion •...... •....•.•...... •...... ••...... 38 References ...... •..•...... ••...... •... 41
iii Figures
Figure 1. Attenuation of filtered seawater and absorption of natural phytoplankton as a function of wavelength ...... 3 Figure 2. Inverse Secchi depth vs. chlorophyll concentration ...... 16 Figure 3. Diffuse attenuation coefficient vs. chlorophyll con~entrati on ...... 19 Figure 4. Inverse of Secchi depth vs. chlorophyll concentration ...... •...... 20 Figure 5. Inverse of Secchi depth vs. diffuse attenuation coefficient at 440nm ...... 23 Figure 6. Inverse of Secchi depth vs. diffuse attenuation coefficient at 520nm ...... 24 Figure 7. CIE color matching functions ...... 26 Figure 8. Chromaticity coordinates for ocean colors ...... 29 Figure 9. Chromaticity coordinates for ocean colors and Munsell hues...... 33 Figure 10. Comparison of chlorophyll predictions by several optical methods ...... 39
Tables
Table 1. Paired replicate chlorophyll samples determined photometrically and fluorometrically ...... 12 Table 2. Linear regressions for various optical parameters ...... 13 Table 3. Regressions of optical parameters vs. ocean color ...... 31 Table 4. Proposed selection of Munsell colors ...... 36
iv INTRODUCTION
The photosynthetic pigments, chlorophyll ~'~'£and associated accessory pigments, are the only significant means of absorbing the sun•s light energy to fuel life processes. It follows that all methods of chlorophyll determination are based on the modification of light ·passing through the medium containing these pigments. Measures of the chlorophyll content of marine waters have long been used as an indi cator of phytoplankton standing stock and more generally, of the productivity of marine food chains as a whole. Traditional methods for measurement have included using the absorbance or fluorescence of chlorophyll pigments extracted from discrete marine water samples (Richards with Thompson 1952, Yentsch and Menzel 1963). Lorenzen (1966) introduced an extension of the fluorometric method which per mitted continuous horizontal or vertical chlorophyll profiles. When a beam of light passes through a medium, its radiance is attenuated
where L0 is the inherent radiance and Lr is the apparent radiance after passing through path length, r (symbols follow Jerlov 1976); cis the beam attenuation coefficient which may be divided into attenuation due to absorption, a, and to scattering, b. These two components are additive, such that
c = a + b. [1]
Both absorption and, to a lesser extent, scattering are wavelength dependent. For water, the absorption coefficient is very strong for 2 all wavelengths except in the range of visible light from about 350 to 750 nm. This absorption minimum is so striking in the visible wave- lengths that while ultraviolet and infrared light cannot penetrate more than a meter or two in the clearest waters, blue light has been detected photometrically at depths of 600 m (Duntley 1963). Scattering -4 by water mol~cules is wavelength dependent on the order of A and com- pared with absorption, only significant in the visible wavelengths. Sixty percent of the total attenuation for blue light in pure sea water is due to scattering (Duntley 1963). It is precisely in this visible light window for water that chlorophyll absorbs most strongly (Figure 1). The absorption spectra for the pigments in various species of phytoplankton appear quite similar (Yentsch 1960) with a broad maximum at about 440 nm, a local minima between 550 nm and a smaller peak at about 675 nm. The peak in the 650 nm range is relatively sharp and varies slightly in location
for chlorophylls ~' ~and£· It is thus the basis for the spectro photometric method of chlorophyll determination (Richards with Thompson, 1952). In sea water, this smaller peak is in the range of increasing absorption by water molecules. While dissolved chlorophyll, as ex- tracted in acetone, does not significantly scatter, a component of scattering is associated with the phytoplankton cells containing chlorophyll in natural waters. Consider now the addition of suspended particles such as phyto plankton, zooplankton, organic detrital material or inorganic sedi- ments. The absorption and scattering components of these particles must be added to those for sea water. Additional1y, 11 yellow sub- 3
0.24 1.0 -- - filtered seawater phytoplankton 0.20 I I 0.8 ·.E- I -E 0.16 I ' 0.6 ' -z I -z 0 0 1-- 0.12 I i= <:( I a.. ~ 0:: z I 0.4 0 w (/) 1- 0.08 I m / Figure 1. Attenuation of filtered seawater and &bsorption of natural phytoplankton as a function of wavelength '(after Yentsch, 1960). 4 stance" (dissolved organic matter) (Jerlov 1976) adds its component of absorbance. Thus, equation [1] becomes where subscripts, w~ indicate a coefficient for water, p for particles andy for 11 yellow substance". Separating out the absorption due to ·chlorophyll 'from the total attenuation as measured by a beam trans- missometer could prove difficult if interference from other scattering particles or "yellow substance" is significant. Thus far, we have considered factors affecting the attenuation of a collimated beam. Sun light in the sea is diffuse and the assumption of collimation no longer holds. The irradiance due to scattered light reaching a point at .some depth can be the major contributor to the total irradiance at that point. An irradiance meter can be used to determine the diffuse attenuation of downwelled irradiance, KE. Smith and Baker (1977) have divided this into the components of atten uation due to water, chlorophyll and other factors: Ktotal -K+K+K- ·w c other· [2] However, as irradiance attenuation is an apparent rather than an inherent optical property of ocean water (Preisendorfer, 1961), this decomposition is not strictly permissible. H¢jerslev (1980) suggests that light attenuation in the upper few meters of the water column is due primarily to absorption and thus equation [2] is approximately at = a + a + a . w c 0 Absorption is an inherent property and therefore appropriate for s in this manner. 5 Yentsch (1960, 1971) has proposed a method for deriving informa tion related to the absorption by chlorophyll from radiance upwelled from the sea surface. Light returning to the surface is mostly scat tered sun light, emission from fluorescence or bioluminescence being relatively insignificant (Yentsch 1971; but see Gordon 1979). Further, . Yentsch suggests that, since scattering is rather wavelength indepen dent when compared to absorption, the ratios of upwelled nadir radiances or irradiances at different wavelengths will be primarily affected by absorption. Considering the relatively uniform low absorbance by water in the 440 to 550 nm range as compared with the change in chloro phyll absorption in the same range (Figure 1), the ratio of upwelled radiances L440;L550 will strongly reflect changes in the relative contribution of chlorophyll to the total absorbance of the water column. Absorbance at 440 nm by 11 yellow substance 11 will be an inter fering factor where present. This method offers the most promise for remote sensing, but Yentsch (1960) stresses the need for narrow band width for selecting the 440 and 550 nm wavelengths by radiometers. Recently, with the ability to mount precision radiometers aboard aircraft or satellite platforms, increasing attention has been paid to deriving chlorophyll content from upwelled optical information (visible radiance from the sea surface). While the accuracy of prediction obtained thus far has been limited to a quarter of a log of the chloro phyll content (Morel and Gordon 1979), the speed of measurement and the area of coverage possible with these sensors yield valuable information (Clarke, et ~-· 1970; Arvesen, et ~., 1973; Mueller, 1976). In a single two-minute pass, the Coastal Zone Color Scanner 6 (CZCS) on board the NIMBUS-? satellite can cover an area of 1000 x 2000 km, an area sufficient to include the entire Gulf of Mexico, with a resolution of 1 km2. The ratios of radiances measured in the blue (440 nm) to green (550 nm} with atmospheric effects determined in the red (670 nm) are used to estimate chlorophyll content. From initial · CZCS scans computer enhanced for chlorophyll, several zones of relative chlorophyll content and associated patterns of dispersal are easily distinguishable (R. Wrigley, NASA-AMES, pers. comm.}. At the other end of the technology spectrum, Carlson (1977) has suggested the use of the Secchi disk as a quick estimator of trophic state in lakes. Austin, et ~- (unpubl. ms) have suggested that visual comparison of ocean color with Munsell color chips* can be used to estimate chlorophyll content. While these techniques may provide ·only crude estimates, their simplicity is appealing. As Tyler (1977) has pointed out, the Secchi disk remains widely used and cited as an estimator of water clarity in spite of its inability to estimate single optical parameters or accurately characterize ocean water types. It may well be that upwelled radiance, sensed either by the human eye or by radiometers, will never provide precise chlorophyll information (Duntley, et ~., 1974). Yet, precision is often secon dary to expediency or broad area of coverage, and interest in these techniques remains high. In this study, we will use data obtained primarily as surface- truthing for the CZCS to compare a number of shipboard ---in situ chloro- Munsell Color Co., 2441 North Calvert Street, Baltimore, MD 21218. 7 phyl1 predicting techniques. Emphasis is placed on the use of the Secchi disk and Munsell color because, when more time or equipment is available, other well documented techniques would be preferable. In situ radiometric data are used here primarily as a reference. DATA SOURCES AND METHODS The data used in the comparisons to follow were obtained from investigations by the National Oceanographic and Atrnospheric Admini stration (NOAA) and from investigations by Moss Landing Marine Labora tories for the National Atmospheric and Space Administration (NASA) . . The four extensive NOAA cruises covered the waters off southern Cali fornia, off Baja California, the Gulf of California, the Gulf of Mexico and the waters off the Atlantic coast from north of Cape Cod to southern Florida, including the Gulf Stream and the Sargasso Sea. The NASA cruises were all located in Monterey Bay, central California. Each cruise was of one day duration and repeated approximately monthly over a two-year period. Monterey Bay is a dynamic system affected by newly upwelled, nutrient rich waters advected into the bay from the south, primarily during late winter and spring, but periodically throughout the year. Cold offshore California Current waters dominate the bay during the summer and fall, and relatively warmer California Countercurrent (Davidson Current) waters enter the bay when they surface in the winter (Broenkow and Smethie, 1978). Over the two year sampling period, the NASA data provide a good scatter of chloro phyll concentrations in the medium to high range, which complement the predominance of medium to low chlorophyll values provided by the NOAA data. For both the NASA and NOAA sampling stations, vertical chloro phyll profiles were taken using a submersible pump connected to a Turner Designs Model 10 flow-through fluorometer. Discrete samples were taken from the fluorometer•s effluent at every 5 m depth for 8 9 calibration. The NOAA calibration samples were measured fluorometrically on a G.K. Turner Associates Model 111 fluorometer using the method of Yentch and Menzel (1963). NASA calibration samples were measured spectrophotometrically on a Beckman D.U. Spectrophotometer using the method of Richards with Thompson (1952) and the SCOR/UNESCO trichro- . matic equations (Strickland and Parsons 1968). For use in the regressions to follow, a mean chlorophyll concentra- tion for each station was obtained by integrating and optically weighting the vertical chlorophyll profiles from the surface to a depth equal to the inverse of the mean diffuse attenuation coefficient for irradiance, K -1 1 2 mean Ch1 = K -1 JE Ch1z e- KZctz J E e -2KZdZ 0 Where Chlz is the chlorophyll (or total pigment) concentration at depth, Z. The integration depth, 1/KE, represents the depth where a beam of light would be about 86% attenuated if it traveled to that depth and back to the surface. Thus, the contribution of the chloro phyll concentration at each depth to the mean concentration for the water column is weighted according to the amount of light that can be reflected from that depth and reach the surface. For each NOAA and NASA station, a Secchi depth measurement was taken by lowering the disk until it was just no longer visible, then raising it until just visible. The mean of the two depths was used as the Secchi depth~ D. The observer's position aboard ship for Secchi 10 depth measurement was chosen to optimize visibility through the sea surface. By letting the ship block sun glint and wind-generated ripple~ sea surface interference was much reduced. After the Secchi depth measurement, the disk was raised to half its measured depth. The color of the surface of the disk was then compared to the Munsell . color chart by holding the chart visually adjacent to the disk's image. The color chip with the closest color match to the disk's image was then chosen. Often, several observers repeated the Secchi depth and Munsell color measurements, usually with identical results. For NASA stations, diffuse irradiance attenuation was measured by 1oweri ng an i rradi ance meter using an unfiltered Weston photoe 1ectri c cell as the detector and comparing its output with a similar deck cell in unobstructed sun light. At each of the NOAA stations~ two NOAA spectroradiometers (Gordon and Clark, 1980) were used to take vertical profiles of spectral downwelled irradiance and spectral upwelled radiance. From these profiles, spectral diffuse irradiance attenuation coefficients, KE(1), and spectral inherent surface radiance, Lw(A), were calculated (Austin, 1979). RESULTS AND DISCUSSION As has been stated, chlorophyll concentrations used as reference standards for comparison of the various determination methods investi- gated here were themselves determined by the spectrophotometric method for the NASA data and by the fluorometric method for the NOAA data. All of the NASA data used in the regressions to follow were determined spectrophotometrically; however, twenty chlorophyll a samples (1 to 9 3 3 mg!m , mean 3.5 mg/m ) were analyzed by both spectrophotometric and fluorometric techniques. The standard error of the differences between techniques was 1.0 mg/m3. The mean difference was not significantly different from zero and thus, we may assume that the standard error of these differences is the standard error of estimate for the two tech- niques (Table 1). Strickland and Parsons (1968) have suggested that the 95% confidence limits for the spectrophotometric method are ±0.26 3 3 mg!m , while those for the fluorometric method are ±0.40 mg!m at a chlorophyll~ concentration of 5 mg/m3. Yentsch and Menzel (1963) cite a fluorometric standard error of ±0.26 mg!m3 at the 5 mg/m3 concentration. Only two single-sample replicates for each method were performed on the NASA data, but these varied by less than 0.1 mg/m3 for each method. Hhile Strickland and Parsons feel the spectrophoto- metric method is the more accurate, doubt remains as to the source of the ±1 mg/m3 standard error between methods. Table 2 summarizes the results of regressions of various in situ optical measurements versus chlorophyll ~or total chlorophyll ~-like pigments (chlorophyll a+ phaeophytin ~). It should be noted that the 11 12 TABLE 1: Paired replicate chlorophyll samples determined photometrically and fluorometrically. Photometric F1uorometric 3 3 N Chl a mg!m Ch1 a mg/m 1 3.73 1.85 2 4.53 3.63 3 4.66 5.08 4 4.42 4.46 5 l. 35 3.49 6 6.51 4.79 7 5.67 2.97 8 2.96 2.84 9 1.30 2.05 10 3.56 3.30 11 3.28 2.66 12 3.24 2.69 13 0. 92 0.90 14 1.29 l. 29 15 7.09 6.94 16 9.04 7.87 l7 0.89 0.95 18 1. 59 1.33 19 0.86 0.95 20 0.91 1.07 Mean difference between pairs 0.336 mg/m3; standard error of difference between pairs 1.026 mg/m3. TABLE 2: Linear regressions for various optical parameters (see text). Sslope is the.standard error of the slope; Sy/regres is the standard error of estimate for the dependent variable from the 2 regression; r is the coefficient of determination. Dependent Independent Variable Variable InterceQt SloQe \loQe s~/regr r2 N 1 1og 1: pigments log Lw 440/550 -0. 102 -1.315 ±0.060 ±0.232 0.897 57 3 2 1og Ch 1 ~ mg/m log 1/secchi Z 2.350 2.090 ±0.081 ±0.234 0.882 93 3 1og 1: pigments log 1/secchi z 2.582 2.209 ±0 .114 ±0.268 0.861 63 4 log Chl ~ mgJm3 Munsell hue 2.862 -0.055 ±0.004 ±0.362 0.717 91 5 1og 1: pigments ~·1unse 11 hue 3.031 -0.058 ±0.005 ±0.381 0. 726 61 6 KE 440 nm 1/secchi Z -0.045 2.678 ±0 .182 ±0.178 0.819 50 7 KE 520 nm 1/secchi Z -0.003 1.477 ±0.091 ±0.089 0.846 50 3 8 log Chl ~ mgJm log KE 520 nm 1.079 0.826 ±0.071 ±0 .180 0.736 50 3 9 Ch 1 ~ mg/m 520 nm 0.834 5.054 ±0.585 ±6.690 0.599 52 ..... w 14 standard errors of estimation for the traditional 1aboratory tech- niques are relatively independent of chlorophyll concentration within their recommended range of use. The chlorophyll concentrations for in situ techniques are log, tNnsformed and therefore, error estimates - I 0 vary strongly with concentration. The most precise of the n situ techniques avaiiable thus fal~ uses the l~atios of upwelled radiances measured in this case at 440 and 550 nm. :ne regression of log (total pigments) versus 1og (Lw 440/Lw 550) (regression l in Table 2) yields a standard error of estimate of ±0.23 log (total pigments). Thus, at ..., an estimated total pigment concentration of 3.5 mg/m~, the standard error of estimate translates to +1.2 mg;m3, -0.89 mg/m3 unlogged chloro- ..., phy11 concentrations. This compares favorably with the ±1 mg/m~ errOl- of estimate yielded from the laboratory techniques. However, at an estimated total pigment concentration of 10 mg/m3, the standard error of estimate from the optical technique becomes +7, -4.2 mg/m3. Thus, while the radiometric estimate is fairly accurate at low chlorophyll concentrations~ it becomes much less so at high concentrations. The ±0.23 log (total pigments) standard error of estimate corresponds well with the 1/4 log accuracy of Morel and Gordon (1980). The regression explains 90% of the variation of log transformed pigment concentra ":< tions ranging from< 0.05 to> 20 mg/rn~. An advantage of this tech- nique is that it requires the measurement of upwelled surface radiances at only two wavelengths. rather than the entire visible spectrum. Another method for deriving chlorophyll content from the spectra of upwelled radiances involves estimation of the augmentation of radiance upwelled at 685 nm by chlorophyll fluorescence to a measured 15 radiance level above that expected by reflected sunlight alone (Gordon, 1979; Gordon and Broenkow, in prep.}. Preliminary results indicate its predictive ability is slightly less accurate than the use of radiance ratios. Its use is hampered near the surface because the large relative amount of solar irradiance available obscures the ·fluorescence·. Also, high levels of solar irradiance in near-surface waters cause inhibition of fluorescence (Kiefer, 1973} which may lead to under-estimation of chlorophyll content. However, vertical pro files of upwelled radiances can yield measures of inhibition, perhaps the real value of this technique. The Secchi Disk The Secchi disk is perhaps the oldest device used to quantify water clarity. It remains widely used today, although it is generally recognized as only a crude estimator of the diffuse attenuation coef ficient, K. A rough relationship between Secchi depth and chlorophyll content has also been recognized (Saijo and Ichimura, 1960; Carlson, 1977, 1980}. The combined NOAA and NASA data show a strong relation ship between log (1/Secchi depth} and log (chlorophyll ~) (Figure 2). This relationship is particularly striking when the regression (2 in Table 2) is compared with the regression using radiance ratios men tioned previously (1 in Table 2}. Secchi depth is only slightly poorer at predicting chlorophyll-like pigments than is upwelled radiance; the standard error of estimate is different by only 0.002 log.{pigment concentration}. When converted to real pigment values, the use of radiance ratios predicts total pigments only half a percent 16 .oo0 @@ ..,- 0 0 • E ~ @) 'en E ,.·~ 0 - 0 @ 0 oo @ .....J 1.0 @ .....J @ @ >-:r: • @ (L •••• @ 0 • • 0::: •• g 0.1 •• I • u . - ••• • 0.0 ------'-----i----L...... J....---L...... -...I....-..-1.-...I....-..-.....-J 0.0 0.1 1.0 INVERSE OF SECCHJ DEPTH ( /m) Figure 2. Inverse of Secchi depth vs. chlorophyll ~concentration. Closed circles are NOAA stations, open circles are NASA stations. Circled data points are influenced by terrestrial sediments (see text). 17 better than use of the Secchi disk predicts chlorophyll ~· Tyler {1968) suggests that the light reaching the observer's eye from the submerged Secchi disk is affected by the diffuse attenuation of light, KE, down to the disk and the collimated attenuation of light, c, from the disk•s surface back to the observer; specifically, = C -{K + c)Z [3] CZ 0 e where c0 is the inherent contrast of the disk against its background, and Cz is the apparent contrast at the surface when the disk is at depth, Z. Z will equal the Secchi depth, 0, when Cz is at the limit of visual detection, CD. If we assume c0 and CD to be relatively constant, then 1/D will covary with chlorophyll content to the extent that (K +c) covary with chlorophyll. Various authors have offered theoretical decompositions of K and c {Yentsch, 1971; Kiefer and Austin, 1974; Morel and Prieur, 1977; Smith and Baker, 1977; Wilson and Kiefer, 1979; H~jers lev, 1980). Briefly, the components are ab- sorption due to water, plant pigments and "yellow substance", and scattering due to water, organic particles (living and detrital plank ton organisms), and inorganic suspended sediments. Each component contributes to both attenuation coefficients, but where they are simply additive for the inherent beam attenuation, c, they are not strictly so for the apparent diffuse attenuation coefficient, K (Priesendorfer, 1961). However, in the open ocean away from terres trial run-off, the major absorbers are water and phytoplankton pig ments and the major scatterers are detrital, zooplankton and phyto plankton particles (Zeitzschel, 1970). Thus, all of the major com- 18 ponents of attenuation besides the constants attributable to water would be expected to covary strongly with chlorophyll a content. 2 Kiefer and Austin (1974) found a strong linear relationship (r = 0.90, non-log transformed) between beam attenuation and chlorophyll a concentration for open water stations in the ~ulf of California. Smith and Baker (1977) cite data which support a relation between the diffuse attenuation coefficientt K, and chlorophyll a. They propose that the attenuation due to chlorophyll be redefined as a proportionality coefficient times the chlorophyll concentration Kc = k[C]. The relation is not strictly linear; i.e., k is not constant, and two values of k must be used, one for high and one for low concentrations. The relation between irradiance attenuation and chlorophyll for the NOAA data also shows curvature (Figure 3), but no clear zones of linearity are visible. Log transformation did not completely linear ize the data. Regressions 8 and 9 in Table 2 are for log transformed and untransformed data; neither regression predicts chlorophyll as well as do the Secchi disk data. That the relation between inverse Secchi d~pth and chlorophyll is also non-linear (Figure 4, but see Megard, et ~., 1980) and its predictive ability is greater than that for diffuse attenuation alone, confirm that both diffuse attenuation and collimated attenuation contribute to the relation. In all the non-log transformed distributions (Figures 3 and 4; see also Figures 5 and 6), the data are heavily biased toward the lower end of the range and scatter increases toward the higher end of the range. The log 19 15 -j'C') E • '01 E - 10 • c _J • _J >- I a... 0 a:: • 0 5 _J •• I ., u • 0 0.0 0.5 1.0 1.5 IRRADIANCE DIFFUSE ATTENUATION, KE (520) Figure 3. Diffuse attenuation coefficient for irradiance meausred at 520 nm vs. chlorophyll .! concentration for· NOAA stations. 20 0 0 0 ·f\1')- E a- 10 0 'E - 0 0 _j _j > I a.. 0 a::0 5 9 I u @ @ 0 0.00 0.25 0.50 INVERSE OF SECCHI DEPTH ( /m) Figure 4. Inverse of Secchi depth vs. chlorophyll ~concentration. Closed circles are NOAA stations, open circles are NASA stations. Circled data points are influenced by terrestrial sediments (see text). 21 transformations in Figure 2 were used to more evenly distribute chloro phyll values over their four order-of-magnitude range and to linearize the data. No improvement in prediction is obtained with non-log transformed Secchi disk data. The relation between Secchi depth and chlorophyll ~does not hold in the presence of materials derived from terrestrial runoff or from resuspended bottom sediments. Circled data points in Figures 2 and 4 are from stations influenced by runoff (e.g., Mississippi Delta or stations in Monterey Bay near stream mouths). These stations were not included in regressions 2 and 3 in Table 2. The relation between beam attenuation and chlorophyll (Kiefer and Austin, 1974) also failed for terrestrially influenced stations. Edmonson (1980) feels that Secchi depth is more influenced by particle scattering than by absorption. The sensitivity of Secchi depth to the presence of inorganic suspended particles certainly supports this idea. The presence of inorganic suspended sediments severely limits the Secchi disk's predictive ability in waters subject to mixing with terrestrial runoff. However, for the open ocean (perhaps 95% or more of the world•s oceans), the speed and simplicity of this technique are attractive and the accuracy may be acceptable for rough or preliminary estimates, especially in clearer waters. The regression statistics (2 in Table 2) may be simplified, yielding 3 2 2 Chl ~ rng;m = (10/0) ± 0.5(10/0) [4] where Dis the Secchi depth, in meters. Sverdrup~ et ~· (1942) offered the following estimate of diffuse 22 attenuation, KE, from Secchi depth KE = 1.7/D. [5] Attenuation coefficients calculated from the NOAA data at discrete wavelengths are not directly comparable to the coefficient in equa tion [5], which is for the integrated visible wavelengths. However, the 440 nm and 520 nm wavelengths used in Figures 5 and 6 to some extent bracket the range of maximum transmission of light in water, and it is interesting to note that the slopes of these regressions bracket the 1.7 slope of Sverdrup, et ~· {regressions 6 and 7 in Table 2). Tyler {1968) warns that c is not necessarily a fixed multiple of K {see equation [3]); therefore, equation [5] can only be approxi mate. The concluding comment of Lorenzen {1970) is worth reiteration regarding both relations [4] and [5]: If accurate information is required, it is advisable to measure directly the quantity of interest. Munsell Color Austin, --et al. (unpubl. ms) have introduced a new technique for determining chlorophyll content in surface waters based on the strong ability of the human eye to detect small differences in the spectral compositinn of light, perceived as differences in color. Yentsch {1960) has described how the absorption properties of phytoplankton pigments and water combine to modify the spectral composition of light upwelled from its surface. As the concentration of phytoplankton increases, the wavelength of maximum transmission gradually shifts from the blue to the green portions of the visible spectrum (see Figure 1). The choice of the blue, 440 nm, and green, 550 nm, radiances 23 -0 ~ -~ Slope :: 2.68 Intercept =-0.05 r2 :: 0.82 • • Cl- w u z ·<:{- ~0 ~ 0.0 0.2 0.4 0.6 0.8 INVERSE OF SECCHI DEPTH ( /m) Figure 5. Inverse of Secchi depth vs. diffuse attenuation coefficient for irradiance measured at 440 nm for NOAA stations. 24 -0 N 1.() -w ~ .... Slope = I. 48 z 2 0 Intercept = 0.00 r2 ~ = 0.85 z::J w 1-- 1-- <{ w (f) :::::> Lt... • Lt... 0 w u z <{ 0- <{ 0 0:: 0.0 0.2 0.4 0.6 0.8 0::: INVERS OF SECCHI DEPTH (I m) Figure 6. Inverse of Secchi depth vs. diffuse attenuation coefficient for irradiance measured at 520 nm for NOAA stations. 25 used in the radiance ratio method described earlier is based on this shift. Austin, et ~· have proposed taking advantage of this shift by visually comparing the observed color of the ocean with a variety of color chips selected from the Munsell Book of Colors (ASTM 1968). The process is similar to matching paint color chips, except that the Munsell chi~s are quantified as to hue, value and chroma, and rela table to the spectral composition of the viewed color. Hue is the perceived color; i.e., blue, green, purple, etc. Value is the per ceived lightness, ranging from ideal black to ideal white. Chroma is the perceived saturation or departure from gray of the same value (Wyszecki and Stiles, 1967; ASTM 1968). Thus, ideally, a limited number of Munsell color chips are selected with appropriate hue, value and chroma to represent the range of colors from blue to green of ocean waters of various chlorophyll concentrations. The Munsell color system is useful for matching and quantifying colors. However, to graphically compare colors, another system needs to be introduced. Virtually all the colors perceived by the human eye can be formed from mixtures of three primary colors. A variety of primaries can be defined, provided no single primary can be formed from mixtures of the other two. In the 1931 CIE* colorimetric system (Wyszecki and Stiles, 1967), three primary colors have been related to wavelength by the color matching functions rA, gA and 5A (Figure 7a). Each function has a value, tristimulus value, at each wavelength in the visible spectrum. To eliminate the negative values for some of Commission Internationale de 1 •Eclairage. 26 0.3 A (/) w 3 ~ 0.2 (/) :::> _J i 0.1 j:: (/) 0::: 1- 0.0 - 0. l .__.~..--.~..--.~..-.~..-.L..-~::.__..J..-..J..-..J..-..J..-..J..-..i--..!--..l..--'--..J..---1 350 400 450 500 550 600 650 700 750 800 WAVELENGTH Cn m) ,,, : \ B CJ) I ·. w I :::> z~ j ·, _J ' \ ~ I ' ' I (/) I 3t : I ,..--· :::> ! \ ~ \ y~ \ 1- (/) \ I I \ 0::: \ 1- I \ \; \ /\ ··~ 0 " 700 750 800 350 400 450 500 550 600 650 WAVELENGTH (n m) Figure 7. rgo color matching function vs. wavelength (A), and x y z color matching functions vs. wavelength (B). 27 the tristimulus values, a linear transformation to a new set of functions xA, yA and zA was adopted (Figure 7b). Thus, while the r g 6 system is relatable to the response of the eye, termed the 11 standard observer 11 by the CIE, the x y z system is an imaginary but operationally simpler system. A spectrum of light intensities between 380 and 780 nm may be evaluated in terms of each of the three color matching functions in the following manner (using the x function as an example): 780 X = J EAxAdA 380 where is the radiant energy at wavelength 1- and x'- is the tristi- mulus value at wavelength A. If the spectrum is evaluated for all three functions, then its visible color is defined by the values ~, Y and ;, which may be thought of as coordinates in a three-dimensional color space. If the three coordinates are standardized to a unit space (standardizing the total spectrum to unit luminance), X = X + y + z the colors can be plotted in a two-dimensional space of x and y with no loss of color information, since x + y + z = 1. The x, y and z values are the chromaticity coordinates of the color the evaluated spectrum would yield visually. The choice of the r g b and X y z systems was not arbitrary, because when a spectrum of equal inten- sities at all visible wavelengths is evaluated, the chromaticity coordinates l/3, 1/3, 1/3 will result in either system. If the chroma- ticity coordinates are evaluated for each discrete wavelength; i.e., 28 for a spectrum containing only one wavelength, the resulting locus of points and a line connecting the points for the 380 and 780 nm wave lengths will be the boundary within which the coordinates for all visible colors must lie. The chromaticity coordinates for the ocean colors derived from . the inherent· surface radiances for all the NOAA stations are plotted in Figure 8. Also shown are the spectrum (single wavelength) locus and the coordinates for the equal energy spectrum, E, and the spectra of direct and overcast sunlight, B and C. The observed ocean colors lie in a smooth curve ranging from the bluest waters in the lower left to the greenest waters in the upper right. Chlorophyll content also shifts fairly smoothly over the curve from 0.04 mg/m3 in the lower left to 16 mg/m3 in the upper right. The shift in color is most rapid at the lower chlorophyll values, with 1 mg/m3 occurring approximately in the center. There is some overlap in chlorophyll concentrations, however, and Pacific Ocean stations appear to be shifted somewhat bluer on the curve for a given chlorophyll content than Atlantic or Gulf of Mexico stations. If, on a chromaticity diagram such as Figure 8, a line is drawn from the coordinates for the color of a source light; e.g., points B or C in Figure 8, through the coordinates of a color of interest to the spectrum locus, the wavelength whose spectrum locus coordinates have been intersected is the dominant wavelength for that color. Color purity is the ratio of the distance from the source to the color coordinates and the distance from the source to the spectrum locus. Austin, et ~· have chosen to express ocean color in terms of dominant 29 w ~ z 0.8 c- a::: 0 0 u 0.6 ~ u ~ 0.4 ••• ~ 0 ( cc!J 0:: I (.) I 0.2 • ~ I 0.0 11...... 1.-~:;._-I...... --L--1----I...-.....L.---&..-..1--....J 0.0 0.2 0.4 0.6 0.8 I. 0 x CHROMATICITY COORDINATE Figure 8. Chromaticity coordinates for radiometrically~derived ocean colors for NOAA stations {•). Also shown are spectrum locus and coordinates for sources B, C, and E. 30 wavelength and purity. While this descriptively relates the color to a familiar reference, information is lost if treated statistically in this manner. Multiple regression 1 in Table 3 regresses log (total pigments) versus the CIE x and y coordinates derived from the NOAA radiometric data. Comparing the coefficients of determination of this .regression with that of the regression of log (total pigments) versus log (radiance ratios) (regression 1 in Table 2), the chromaticity coordinates are as good a predictor of chlorophyll as the radiance ratios~ Lw 440/550. In fact~ the standard error of estimate is better for the chromaticity coordinates. It must be remembered, however, that the whole spectrum of radiances (taken here at 5 nm intervals) is required to derive color. If log (total pigments) is regressed against radiometrically derived dominant wavelength (regression 4 in Table 3), the coefficient of variation is 0.70, much less than that of the other regressions. Further, some curvature remains in the relation that log or power transformations cannot remove. If the residuals of regres sion 1 in Table 3 are plotted against CIE x or y radiometrically determined, only random scatter is visible, indicating a linear rela tion between the components of chlorophyll variation accounted for by the CIE x andy variables. It thus appears that all the information on chlorophyll content available to present radiometric instruments is also available to the CIE 11 standard observer" under ideal conditions. Austin, et ~· have estimated that, under field conditions, an observer can distinguish ten steps or color changes over the range of colors observed for ocean waters. They further calculated that a change in value and chroma at a given Munsell hue will result in a TABLE 3: Linear and multiple linear regressions of various optical parameters related to ocean color. Sslope is the standard error of the slope for each independent variable; Sy/regres is the standard error of estimate for the dependent variable from the regression; r2 is the coef- ficient of variation. Dependent Independent Variable Variable Interce~t Slo~e \1o~e s~/regr r2 N 1 log Chl ~mg/m 3 CIE x from !Lw 2.493 ±0.897 -2.229 ±0.232 CI E y from !Lw 4.714 ±0.699 0.875 54 2 log r pigments CIE x from !Lw 2.094 ±0.841 CI E y from !Lw -2.161 5.021 ±0.655 ±0.218 0.889 54 3 log Chl ~ Dominant A from !Lw -9.806 0.019 ±0.002 ±0.356 0.701 54 4 log r pigments Dominant A from !Lw -9.708 0.019 ±0.002 ±0.352 0.704 54 5 log Chl ~ Munsell hue NOAA 2.350 -0.049 ±0.004 ±0.330 0.760 52 6 log r pigments Munsell hue NOAA 2.392 -0.048 ±0.004 ±0.334 0.752 52 7 log Chl ~ CIE x from Munsell -3.417 2.167 ±1. 778 ±0.339 0.753 52 CIE y from Munsell 7.908 ±1.407 8 log r pigments CIE x from Munsell -3.323 2.196 ±1. 795 ±0.342 0.746 52 CIE y from Munsell 7.803 ±1. 421 9 CIE x from !Lw CIE x from Munsell -0.138 1.426 ±0.072 ±0.025 0.887 51 10 CIE y from !Lw CIE y from Munsell -0. 182 1.454 ±0.083 ±0.036 0.861 51 NOTE: Munsell hues were converted to CIE coordinates at 3/4 value/chroma. w change in dominant wavelength of < 2 nm. This follows, since hue and dominant wavelength are related. Therefore~ of the three variables defining each Munsell color, they felt hue was the most important for relating color to chlorophyll. They selected ten hues in even incre ments from 7.5 purple-blue to 5 green-yellow. Munsell color increments . have been designed to approximate even visual changes in color. The values and chromas were to be held constant except that a range of shades was necessary for each hue to offset surface reflection or whether the color match was made using a Secchi disk. The total selection thus contained forty colors. The selection of colors used for the NOAA and NASA studies was taken from Austin (pers. comm.) and expanded by two hues into ·the ye 11 ow. The regressions of Munse 11 hue versus log (chlorophyll ~) and versus log (total pigments) (regressions 4 and 5 in Table 2 for NOAA and NASA data and regressions 5 and 6 in Table 3 for NOAA data only) show that Munsell hue alone is a poorer predictor of chlorophyll than is the Secchi disk. CIE x and y chromaticity coordinates can be obtained for each Munse 11 col or (using hue, va 1ue and chroma) from tab 1es in Wyszecki and Stiles (1969, Table 6.9, p. 488). It can be seen in the expanded chromaticity plot in Figure 9 that the distribution of Munsell hues with 3/4 value/chroma lie much closer to the line of ocean colors determined radiometrically than do the hues at 7/6 value/chroma. Yet for the NOAA and NASA data, 84% of all matches were made using hues at 7/6 value/chroma. This is reasonable, since the use of the Secchi disk changes the apparent color of the ocean from the color measured radiometrically. The color with the Secchi disk is less pure; i.e., 33 0.5 ,.------...,.---;o::--T"'----,----___.., , I I •• I w I . ,.--·-·• ' ti I /. "-. z / ~ Q- / • Ji." a:: / ..'/ 0 0 . / lf,{ (.) /·~/ 1->- 0.3 / f' jo I • • u I • - / p. 7/6 ~ I \ ~ i I o ·~3/4 0 0::: ... :r: \ u ·- ~-o 2/6 >. I •• 0 0.1 ~------~------~----~~----~ 0.1 0.3 0.5 x CHROMATICITY COORDINATE Figure 9. Chromaticity coordinates for radiometrically-derived ocean colors for NOAA stations (e). Also shown are distributions of Munsell hues at constant 2/6, 3/4 and 7/6 value/chromas. Open circles are coordinates for proposed set of Munsell colors (see text). 34 closer to the color of the source light. The distribution of ocean colors viewed using a Secchi disk probably lies close along the line of Munsell hues with constant 7/6 value/chroma. However, the plots of constant value/chroma curve sharply away from the distribution of radiometrically observed colors at the blue and yellow distribution extremes. F.urther, at lower chlorophyll concentrations, color matches were often made using valaes or chromas other than 7/6, such as the bluest two hues of the 2/6 value/chroma locus visible in Figure 9. The value/chroma choices at the blue end of the distribution tended to follow the radiometrically determined distribution, rather than trun cating as a constant value/chroma would. This follows, since the Secchi depth is also increasing from the green to the blue end of the distri bution. Munsell hue and Secchi depth are closely correlated (see below). Therefore, the observed colors would be darker and purer with a deeper Secchi depth. It appears that the use of a constant value and chroma, and therefore the assumption of the independent importance of Munsell hue in chlorophyll determination breaks down at the ends of the range of observed colors. It is perhaps fortuitous that the 7/6 and 3/4 value/chroma lines follow the center of ocean color distribu tion as well as they do. The multiple regression of CIE x and y derived from Munsell. hue at constant 3/4 value/chroma versus log (chlorophyll ~) (regression 7 in Table 3) has essentially the same predictive ability as that for Munsell hue (regression 5). The same regression at constant 7/6 value/chroma is slightly poorer and the regression using observed value/chroma is much poorer still. It therefore appears that, while 35 the eye is a good selector of hue, it is a much poorer selector of value and chroma. If the appropriate hues, values and chromas are predetermined to follow the range of Secchi disk modified ocean colors, and only these colors are available for comparison, the predictive ability may be much improved over the use of Munsell hue alone. We propose the Austin-Munsell color selection for application to estimation of open-ocean chlorophyll be changed in the following manner. First, the value and chroma of colors at the blue end of the distribution should be chosen to follow more closely a line paral leling the observed radiometric distribution but lying along the 7/6 value/chroma line in the center and yellower ends of the distribution. At the yellow end of the distribution, the waters are fairly turbid, generally reducing the precision of color selection. Second, the choices of value and chroma should be reduced to only those values on the line above. Thus,·the observer would pick the best color from among only twelve choices. A proposed selection of Munsell colors is listed in Table 4 and shown in Figure 9. If observations are to be made without using a Secchi disk, a second, separate selection of colors lying along the observed radiometric distribution line could be available. Each color would represent a range of chlorophyll concen trations, probably overlapping considerably the range of the adjacent color. It is hoped to improve the predictive ability to something close to that of the Secchi disk, as this would provide a second estimate with little additional effort. Further, since no sediment contaminated stations were deleted from the relatively smooth curves TABLE 4: Modified selection of Munsell colors proposed for use in future validation studies. Color CIE Coordinates Designation X y_ 5Y 7/6 0.401 0.420 lOY 7/6 0.386 0. 431 5GY 7/6 0.358 0.429 lOGY 7/6 0.314 0.406 5G 7/6 0.280 0.372 lOG 7/6 0.266 0.353 5BG 7/6 0.254 0.330 lOBG 7/7 0.234 0.304 58 7/8 0.220 0.273 lOB 7/10 0.200 0.230 5BP 5/12 0.192 0.186 7.5BP 4/16 0.186 0.132 37 in Figures 8 and 9 or the regressions in Tab1e 3, an improved Munsell color procedure may be less sensitive to inorganic suspended sediments than is the Secchi disk. The original Austin-Munsell selection should be retained for general ocean color quantification. lt had originally been hoped to use a multipie regression of both inver:se Secchi depth and fllunse11 hue on log (ch1orophy11 ~) to improve on th£ predictive ability of either alone. However, IVIunsell hue and Secchi depth are not independent. When one is regressed against the other, a correlation as strong as that obtained from the regression of either against chlorophyll results. ~Jhen the residual deviations of Sec chi predicted ch l orophy11 and observed ch 1orophy11 are regressed agai~t Munsell hue, the regression is not significant, indicating there is no deviation left for which Munsell hue can account. CONCLUSION In this study, we have presented evidence relating chlorophyll content to both ocean color and ocean water transparency. The obvious inference is that phytoplankton. or factors strongly covariant with phytoplankton,. are the major optical modifiers in the open ocean . Thus, any optical parameter measured will be relatable to chlorophyll. With the possible exception of slight color shifts, this relation remains constant in the eastern North Pacific, the western North Atlantic and the Gulf of Mexico and probably much broader areas of the ocean as well. The Secchi disk provides the fastest and simplest measures because it is the simplest device. Yet, if its sensitivity to terrestrially derived suspended sediments can be accepted, it provides a first approximation of chlorophyll ~content with negli gible effort. We feel that the Austin-Munsell system of ocean color deter mination shows promise as a simple technique potentially competitive with, and possibly superior to, use of the Secchi disk alone. While use of Munsell hue alone does not provide sufficient accuracy, modifi cations suggested here, and certainly subsequent modifications as well, should improve this new technique. The use of spectral upwelled radiances has provided the information, suggesting the direction for modification of the Austin-Munsell system. Similar in situ radio metric color data can provide additional insights into biological oceanographic processes. In Figure 10, the present predictive abilities of the ratio of 38 39 ~10.0 •• (/)t() I-'zo • • wv ~v ••••·"' (!) :l Q.._J <1·~ 0.1 A 1-0ocr 1-l.J... 10.0 • • • •• • oi~ • • • o::U 1.0 £ • LJ...U : ~~- w •• ~Ill o(J) __J ...• I•• •• I' 0.1 : u- .. .• 8 0.0 1----+--+----+--+--+--+----1 • 10.0 • • • w ~::> : . • oi • ••• •··-· • E :3 l.o ••- 0~ ....JZ ... -.. -- 3 ~ o.1 ••• •• c 0.0 ..__ _ _,___,_ __~..-~....-_....~.-_,_ _ ___.~ 0.0 0.1 1.0 10.0 REFERENCE CHL.a OR TOTAL PIGMENTS Figure 10. Chlorophyll ~or total pigment concentration (mg/m3) derived fluorometrically vs. total pigments derived from ratio of upwelled radiances at 440 and 550 nm (A), vs. chlorophyll ~derived from Secchi depth measurements (B), and vs. chlorophyll ~derived from Munsell hue (C). 40 upwelled radiances, Lw 440/550, primarily for use in remote sensing (Figure lOa), of the Secchi disk (Figure lOb), and of Munsell hue (Figure lOc) are compared. While these techniques offer speed and area of coverage, the traditional spectrophotometric or fluorometric laboratory techniques will remain essential for precise chlorophyll or pigment studies. '+I REFERENCES American Society for Testing and Materials. 1968. Standard method of specifying color by the Munsell system. Pub. D 1535. Arvesen, J.C., J.P. Millard and E.C. Weaver. 1973. Remote sensing of chlorophyll and temperature in marine and fresh waters. Astron nautica Acta. 18:229-239. Austin, R.W.' 1979. Coastal zone color scanner radiometry. Proceed. Soc. 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