Spatial and temporal variability of phytoplankton pigment distributions in the central equatorial...

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 92, NO. C2, PAGES 1745-1755, FEBRUARY 15, 1987

Spatial and Temporal Variability of Phytoplankton Pigment Off Northern California During Coastal Ocean Dynamics Experiment 1

MARK R. ABBOTT

Scripps Institution of Oceanography, University of California, San Diego, La dolla det Propulsion Laboratory, Cali[brnia Institute qf Technology, Pasadena

PHILIP M. ZION

Jet Propulsion Laboratory, Cali[brnia Institute qf Technology, Pasadena

The distribution of phytoplankton pigment during the 1981 Coastal Ocean Dynamics Experiment ICODE) was examined using coastal zone color scanner (CZCS) imagery. Twenty-five CZCS images were of sufficient quality to be used for further analysis. The distribution of the data was dependent on the patterns of wind forcing, with the data set biased toward regions and periods of strong equatorward winds. The weighted mean pigment image and the coefficient of variation image showed three clearly defined regions: a coastal region approximately 100 km wide, an offshore region of low pigment and low variability, and two filaments that extended several hundred kilometers offshore. Coastline topography and longshore variations in wind forcing are important in the coastal region. The offshore filaments appear to be related to the patterns of wind stress curl and perhaps explain the large-scale patterns of zooplankton biomass in the California Current. Analysis of the temporal variability delineated three nearshore areas: a northern region off Cape Mendocino. a central region near the CODE Central line, and a southern area off San Francisco. The width of the coastal zone seemed to vary with a 5- to 6-day cycle. During two equatorward wind events, the patterns of temporal variability were consistent with the patterns of wind forcing revealed by empirical orthogonal function decomposition.

1. INTRODUCTION

The spatial and temporal distribution of phytoplankton biomass is determined primarily by physical processes in a variety of marine environments. In the California Current system, surveys by the California Cooperative Oceanic Fish- eries Investigations ICalCOF1) have focused on large temporal and spatial scale patterns of physical processes coupled with studies o[ the chemical and biological patterns. At smaller scales, individual cruises have focused on specific processes and regions, such as upwelling dynamics and fronts. The link between these two scales is difficult to achieve using only ship measurements. Satellite data have the potential to connect the event-scale phenomena observed by a single ship cruise and the large-scale patterns observed over many years by pro- grams such as CalCOFl.

It has been hypothesized that large-scale variability in biological patterns in the California Current system is driven by changes in southward advection and wind stress curl and is largely uncoupled from nearshore effects such as coastal upwelling [Chelton et al., 1982; Chelton, 1982]. This concept runs counter to many of the prevailing theories concerning the importance of coastal upwelling in oceanic primary pro- duction [Boje and Tomczak, 1978; Richards, 1981]. Although the CalCOF! data are not well suited to study such mesoscale phenomena because of inadequate sampling [Chelton, 1982], the accumulated evidence is compelling for the relative unim- portance of coastal upwelling in large-scale variability of biological patterns.

The Coastal Ocean Dynalnics Experiment (CODE) took place on the northern California shelf in the spring and

Copyright 1987 by the American Geophysical Union.

Paper number 6C0427. 0148-0227/87/006C-0427$05.00

summer of 1981 and 1982 and was designed to study the relationship of shelf waters and time-varying winds in an area of high lnean wind stress and relatively simple bottom topography [CODE Group, 1983]. Measurements included a full suite of lnoored oceanographic and meteorological instru- ments as well as ship, drifter, and aircraft surveys. Data from two satellite sensors were also collected: advanced very high resolution radiometer (AVHRR) data from the NOAA series of satellites and coastal zone color scanner (CZCS) data from the Nimbus 7 satellite. Although no specific biological measurements were made during CODE ship surveys, the CZCS data set can be used to study the biological response to physical forcing, at least in the surface waters.

We present results from a study of CZCS imagery covering a 4-month period (March-July 1981) during the primary upwelling season in the CODE area [Huyer, 1983]. In section 2 we discuss the methods and the sampling problems associated with CZCS data. We describe the spatial patterns of phytoplankton biomass in section 3 and compare them with Cal- COFI maps of zooplankton biomass and with CODE-derived wind statistics [Kelly, 1985]. In section 4, we compare the temporal variation of biomass with patterns in the wind field. Section 5 contains a summary and discussion of these results.

2. DESCRIPTION OF THE CODE 1 CZCS DATA SET

Figure 1 shows the northern California coast containing the region covered by the CZCS imagery and studies during CODE. The CODE moorings were placed on the shelf between Point Arena and Point Reyes. (See Winant et al. [this issue] for a discussion of the data sets from the moorings.) Fifty-five CZCS images of varying quality were collected at the Scripps Satellite Oceanography Facility and by the NOAA National Environmental Satellite Data and Information Ser-

vice between March 1 and July 31, 1981. Of these, 30 scenes

1745

1746 ABBOTT AND ZION: VARIABILITY OF PHYTOPLANKTON PIGMENT

Fig. 1.

40'

Map of northern California coast showing location of CODE Central line and the meteorological buoy at NDBO 13.

either were too cloudy or were too close to the edge of the satellite swath so that atmospheric correction could not be done accurately. The other 25 scenes were judged to be useful for further analysis. Photos of most of the available CZCS imagery are in the work of Abbott and Zion [1984]. Figure 2 shows the temporal distribution of usable CZCS imagery during CODE 1.

The CZCS data were processed with software developed by O. Brown and R. Evans (University of Miami). Corrections for atmospheric effects were made based on the results of Gordon et al. [1983a, hi. A 1024 by 1024 pixel area was selected out of each satellite pass, with a center at 39:•N, 125øW. These sub- samples were remapped to an equirectangular grid of 512 by 512 points where each element was approximately 1 km on each side. The images were then passed through a 3 by 3 median filter to reduce small-scale variability.

We compared the satellite estimates of near-surface phytoplankton pigment concentration with the results from the Cal- COFI survey made during May-June 1981 [Scripps Institu- tion of Oceanography (SIO), 1985]. The satellite data were compared with the value of chlorophyll a measured at 10 m during the ship survey, since not every station had a surface chlorophyll measurement. At all stations where surface data were available, the value at 10 m was nearly equal to the surface value. There were only 11 stations within the CODE area, but in situ chlorophyll varied from 0.10 mg m -3 to

greater than 11.0 mg m -3. The regression of the log- tra_nsforn_•_ed satellite-derived chlorophyll on ship-measured chlorophyll gave an r 2 of 0.8 and a slope of 1.0. This is an acceptable result, given that the satellite measures a depth- weighted chlorophyll concentration [Smith, 1981] and that the satellite images were occasionally separated by as much as 24 hours from the in situ measurements.

Of more concern to this study is the sampling pattern of the CZCS data. AVHRR and CZCS data are limited to periods and areas that are cloud-free. In general, the amount of cloudiness was inversely related to the strength of the equatorward winds in the CODE area. This led to a series that was

strongly biased toward this type of wind forcing; we rarely obtained useful CZCS data during calm conditions. Examina- tion of the longshore winds from NOAA Data Buoy Office (NDBO) buoy 46013 (see Figure 1) as shown in Figure 3 of Kosro [this issue] revealed that all of the usable CZCS images were from days where the longshore winds were in excess of 9 m s-1 from the north. This bias was somewhat less serious

with the AVHRR data set as a result of its more frequent coverage [Kelly, 1985].

The significant temporal bias was further confounded with a spatial bias. Plate 1 shows the spatial distribution of usable data from the 25 image time series from CODE 1. To first order, the amount of cloudiness in a particular area is inversely proportional to the wind speed (C. E. Dorman, personal

,WAY / •u/•œ / •u/ Y /

I I •9o .... - ,%, ,%7

128 1õ3 188

AUGUST I

205 I

Fig. 2. Temporal distribution of usable CZCS imagery during the period March 30, 1981, to July 31, 1981.

ABBOTT AND ZION: VARIABILITY OF PHYTOPLANKTON PIGMENT 1747

Plate 1. Spatial distribution of usable CZCS data during the period March 30, 1981, to July 24, 1981. The number of times a particular pixel was clear is color coded according to the scale at the bottom.


communication, 1986). On large spatial scales the large clear area that began at Cape Mendocino and extended westward to about 126øW was coincident with the area of maximum

spring-summer wind stress computed from long-term measurements [Nelson, 1977; Huyer, 1983]. It also was coincident with the area of positive wind stress curl [Nelson, 1977; Chelton, 1980]. The sharp discontinuity at 126øW appeared to be located where the sign of the wind stress curl changes from positive to negative during this time of year. The northern boundary (just north of Cape Mendocino) also seemed to be located at this sign change in wind stress curl [Chelton, 1980] during the spring-summer season. Also, this large-scale pattern of increasing cloudiness toward the west is associated with the deepening of the marine layer [Beardsley et al., this issue].

The wind data described by Nelson [1977] and Chelton [1980] are available only on coarse scales. We note in Plate 1 that there was considerable variation in the amount of cloudi-

ness even on small scales. There are three salient points in the data distribution image. First, the areas adjacent to Point Arena and Cape Mendocino tended to be clear more fre- quently than other areas. According to C. E. Dorman (personal communication, 1986), this results in part from the geostrophic adjustment of the equatorward wind when it attempts to follow the bend in the coastline at these two headlands.

This adjustment causes a shallowing of the marine layer and hence fewer stratus clouds. Second, there was a relatively sharp increase in the amount of cloudiness to the east of a line that began at about the CODE Central line (approximately 123.5øW), particularly south of Point Reyes. In several of the images, an extensive layer of low-lying stratus covered this area. This stratus was caused by a temporary deepening of the marine layer. Dorman [1985, this issue] discusses two possible mechanisms responsible for this deepening. The first mechanism he proposed was a Kelvin wave propagating north from the southern California area, temporarily deepening the marine layer [Dorman, 1985]. For unknown reasons, this wave does not usually propagate past Cape Mendocino. The second mechanism Dorman [this issue] discusses is the rapid lifting of the marine layer along the entire central California coast in response to atmospheric disturbances off southern California which result in a gravity current. This deepening is apparently stopped at Point Arena by the formation of a blocking wave. The deepening of the marine layer by either process results in an increase in low-lying stratus and is often associated with calm or northward winds. Note that mean winds south of the

CODE area were usually weaker than those in the CODE area itself [see Ha!!iwell and Allen, this issue; Kelly, 1985]. The third region of note is the nearshore region between Cape Mendocino and Point Arena that tended to be cloudier than

the adjacent offshore regions. Winds were slightly less than they were in the CODE area to the south (although there was only one measuring site in this area during CODE).

The patterns of cloudiness run counter to the traditional view of upwelling zones as being areas of persistent clouds [e.g., Tont, 1981]. To the contrary, in Plate 1 areas associated with strong, upwelling-favorable winds tended to be cloud- free. The areas of lowest sea surface temperature (SST), Cape Mendocino and Point Arena [Kelly [1985]), were the clearest as well. These patterns varied on small scales (tens of kilometers) as well as on large scales (hundred of kilometers). Periods of cloudiness were episodic and often resulted from changes in the atmosphere several hundred kilometers to the south of the

CODE area [Dorman, 1985; Beardsley et al., this issue]. These observed patterns of cloudiness result from the superposition of coastally trapped processes that temporarily deepen the marine layer and the large-scale deepening of the marine layer as one moves away from the coast toward the central North Pacific [Simon, 1977; Beardsley et al., this issue].

3. SPATIAL PATTERNS OF PHYTOPLANKTON PIGMENT

To counter the inherent bias in the CZCS time series, we

calculated a weighted average of phytoplankton pigment from the available imagery. We assumed that the decorrelation time for the phytoplankton biomass patterns was 5 days, the same as that derived for SST from the AVHRR imagery [Kelly, 1985]. That is, we assumed that the processes responsible for temporal changes in phytoplankton pigment concentrations had temporal scales similar to those of the processes responsible for temporal changes in SST. We also assumed that these scales were constant over the study area. While these assump- tions may not be strictly valid (as is discussed in detail in the next section), the frequency spectrum of the alongshore wind stress did show a pronounced peak corresponding to fluctuations with a period of 4 days [Winant et al., this issue; Beards- ley et al., this issue]. Over the l 1 S-day study period, we derived 14 CZCS samples that were relatively independent. There were several periods when no usable CZCS data were available. These 14 pigment maps were then averaged (Plate 2a). We then calculated the variance using this weighted mean and normalized it by the mean to produce an image of the coefficient of variation in Plate 2b (ratio of standard deviation to the mean).

There are several features of note in the weighted mean. First, the areas of apparently high pigment far offshore (west of 126•W) were artifacts of the CZCS that were the result of

sensor saturation caused by bright clouds (J. L. Mueller, personal communication, 1986). Second, there was a broad band (30-80 kin) of high pigment (>2.0 mg m -3) near the coast that roughly followed the coastline topography. Third, there was a narrow nearshore band of very high pigment (> 10 mg m -•) between Cape Mendocino and Point Arena. Fourth, there was a 60-km broad band of very high pigment (> 10 mg m -3} south of the CODE Central line and north of Half

Moon Bay (Figure 1). Fifth, there was evidence of high pigment concentration filaments that extended 200-300 km off-

shore at Cape Mendocino and Point Arena. The broad band of high pigment nearshore is similar to the

band of cold water shown in the mean SST image by Kelly [1985]. We defined the band of high-pigment water nearshore as that water which had pigment concentrations higher than 2.0 mg m-3. Neglecting the filaments off Cape Mendocino and Point Arena, we estimated the width of this coastal band.

North of Cape Mendocino, the band was approximately 30 km wide. Between Cape Mendocino and Point Arena, the band was approximately 50 km wide. OFF San Francisco, the band was approximately 70 km wide. The width of this band is greater than one would expect from linear theories of coastal upwelling [Yoshida and Mao, 1957]. The fact that this band mirrors the shape of the coastline indicates that topo- graphic effects (either through their direct influence on water motions or through their indirect influence on coastal winds) play an important role in the dynamics of this area. The reasons for the broadening of this coastal area are not clear. That is, one expects the effects of coastal upwelling to be restricted to an area within one Rossby radius, which is approximately

ABBOFT AND ZION' VARIABILITY OF PHYTOPLANKTON PIGMENT 1749

4•

Plate 2a. Weighted-mean CZCS image of phytoplankton pigment from the same period as Plate 1.

,.,

Plate 2b. Coefficient of variation of weighted pigment for the same period as Plate 1


20 km in this area [Kelly, 1985]. Such predictions are based on linear Ekman theory. However, this broadening of the upwelling zone, coupled with other observations such as local- ized areas of offshore flow [Dat, is, 1985a, b; Kosro, this issue] suggests that simple linear theory may not be adequate.

Although Kelly [1985] noted some longshore variations in the nearshore band of cold water (upwelling centers at Cape Mendocino and Point Arena), they seemed to be less intense than the variations in pigment apparent in Plate 2a. Upwell- ing centers (which may be characterized by low pigment concentrations common in deep water} were not obvious in the mean image, although low-pigment water did appear several days after an upwelling event began [Abbott and Zion, 1985]. Presumably, the pigment "signal" (the switching between low pigment values and high pigment values as the intensity of upwelling waxes and wanes) of such upwelling centers was averaged out by using a 5-day decorrelation time to calculate the weighted average. This suggests that the decorrelation time may not be constant over the entire study area. This result is discussed in the following section.

The two areas of very high pigment (between Cape Men- docino and Point Arena and south of Point Reyes) had only a weak analog in the mean SST field. The area off San Fran- cisco tended to be slightly warmer, perhaps as a result of weaker winds. This area was also noted by Huyer [1984] and Oli•era [1982] as having high salinity, characteristic of the freshly upwelled water nearshore in the CODE area. Huyer and Olivera suggested that the waters were indeed upwelled but had been subjected to local solar heating, leading to warm, salty water. This water has been observed to propagate northward during wind relaxations and reversals [Davis, 1985a: Send el al., this issue], although much of the nearshore increase in SST north of Point Reyes resulted from local heating during these wind relaxations [Send et al., this issue] rather than simple northward advection. These relaxation events result from coastally trapped disturbances in the depth of the marine layer and are discussed by Beardsley et ai. [this issue]. This region between Point Reyes and the CODE Cen- tral line was also the site of convergence zones during the relaxation events [Dat, is, 1985a]. An empirical orthogonal function decomposition of the wind field by Kelly [1985] showed that the second mode changed sign at the CODE Central line. She interpreted this mode as separating upwelling-favorable winds from downwelling-favorable winds. It is interesting to note that this corresponds with the line dividing the relatively clear area near Point Arena and the cloudier area near Point Reyes. Low-level aircraft flights doc- umented a recurrent region of high wind speed between Point Arena and the Central line and an area of lower wind speed between the Central line and Point Reyes [Beardsley et al., this issue]. This change in the wind field may be associated with atmospheric Kelvin waves (which result in increased stratus and northward or weak winds) or other small-scale changes in the depth of the marine layer [Dorman, this issue; Beardsley et al. this issue]. Finally, note that the area of high pigment and high SST coincided with an area of high cloudiness (Plate 1). This seems somewhat contradictory to the local solar heating proposed by Huyer and by Olivera earlier. How- ever, the increased clouds would result in less radiative loss at

night, and the decreased water transparency caused by the high phytoplankton biomass would cause most of the in- coming solar radiation to be absorbed near the surface. These

processes, coupled with the reduced wind mixing, could result in the shallow, warm mixed layer seen by Olivera [1982] and Huver [ 1984].

The high-pigment area off San Francisco (Plate 2a) has been observed in other surveys, including CalCOFI cruises [e.g., Simpson, 1985; SIO, 1985]. The northern boundary of this area was at the CODE Central line, similar to some of the wind and cloud field boundaries described earlier. Advection

of this high-pigment water northward around Point Reyes has been observed at the end of at least one upwelling event [Abbott and Zion, 1985], and nearshore currents in the CODE area occasionally reverse during these relaxation events [Davis, 1985a; Kelly, 1985; Send et al., this issue; Winant et al., this issue; Kosro, this issue]. However, in situ growth anal- ogous to the in situ heating described by Send et al. [this issue] for SST cannot be ruled out. The western extent of this high-pigment water seemed to match the boundary in the amount of cloudiness described earlier. The southern bound-

ary near Monterey did not seem to have an analog in either cloudiness or winds. In summary, this regime seemed to be maintained by the particular combination of upwelled nutrients and reduced wind mixing. This warm, salty, high-pigment "pool" of water occasionally moved northward during wind relaxations.

The high-pigment area between Cape Mendocino and Point Arena was less dramatic than the one off San Francisco. Al-

though it did not show up in the mean SST image presented by Kelly, a narrow strip of warm water was occasionally present in this nearshore area [Abbott and Zion, 1985]. Although there were no direct wind measurements to confirm this, this

area probably had weaker winds than the CODE area, a view supported by the increased cloudiness. During wind relaxations, this water seemed to move north towards Cape Men- docino [Abbott and Zion, 1985]. North of Cape Mendocino, cloudiness increased and winds decreased. As in the area off

San Francisco and in the nearshore region between Cape Mendocino and Point Arena, this pattern apparently fostered the accumulation of high near-surface pigment concentrations near the coast.

Large filaments extended a few hundred kilometers off Cape Mendocino and Point Arena. These filaments in Plate 2a were

nearly identical to the filaments in the mean SST image of Kelly [1985]. The filament off Point Arena was about 100 km longer than the Cape Mendocino filament. Considering that this is a 4-month average, the filaments were surprisingly persistent in terms of location. There is no evidence that they propagated longshore. Rather, they seemed to vary only in length and orientation. The frontal region separating the filament water from the open ocean was relatively sharp; the SST change was about 3øC over 100 km, and the pigment change was about a factor of 10 over 100 km. (The relative change in SST compared with the change in pigment was similar to the SST-pigment relationship shown by Abbott and Zion [1985], which used only a small subset of the data in this study.)

The offshore limit of the filaments coincided with the line

where the sign of the wind stress curl changes at 126øW. It has been shown by Chelton [1982] that wind stress curl plays an important role in the dynamics of the California Current sytem. It is possible that positive curl plays a key role in the dynamics of these offshore filaments, perhaps by governing their offshore extent. We might expect that there are synoptic- scale variations in the strength of the wind stress curl which


would result in fluctuations in the length of the filaments. However, the wind sampling grid is not fine enough in time or space to test this idea.

These filaments may also explain the offshore zooplankton biomass maximum described by Chelton [1982]. Chelton noted that the maximum was located 200 km offshore and did

not respond to changes in coastal upwelling. He hypothesized that anomalous southward transport (and hence increased southward nutrient transport) was driven by changes in the strength of the wind stress curl. Although the CODE images presented here are from only 1 year, the observed filaments have been seen in other years and in generally the same location [e.g., Breaker and Gilliland, 1981]. Chelton proposed a second hypothesis which stated that high phytoplankton biomass, formed nearshore in the rich, coastal waters, was trans-

ported offshore. As a result of the longer generation time for zooplankton, their biomass maximum would occur offshore as the high phytoplankton biomass water was advected by Ekman transport. However, Chelton stated that the CalCOFI data did not have a fine enough sampling grid to test this hypothesis. In these data we can see clearly that the physical mechanism for advection (the filaments) is present. It is also worth noting that the three CalCOFI sampling lines off central and northern California are off Point Reyes, Point Sur, and Point Conception, which are usually associated with such offshore filaments. This sampling pattern increases the likeli- hood that an offshore biomass maximum created by this mechanism would be observed in the CalCOFI data. We suggest that Chelton's second hypothesis may be correct. How- ever, as the length, and presumably the intensity, of the filaments is perhaps affected by the strength of the wind stress curl, one might see variations in zooplankton biomass coupled with variations in curl as described by Chelton.

The coefficient of variation in Plate 2b shows much less

structure than the mean image. Note the areas of high variability offshore. These resulted from the sensor artifacts described earlier. Neglecting this effect, the open ocean area west of 126•W was relatively uniform, with a coefficient of variation (CV) less than 1. Inshore of this, CV was greater than or equal to 1 nearly everywhere. Again, we see a distinction between the coastal waters, where the wind stress curl was positive, and the open ocean waters, where the wind stress curl was negative. Within the coastal waters, there were some areas of low

CV. The waters adjacent to Cape Mendocino and Point Arena had a surprisingly low CV. One would expect that these upwelling centers would vary considerably as upwelling epi- sodes strengthened and weakened. We see some indication in the mean image of lower pigment values in this area. How- ever, as was discussed earlier, the decorrelation time of 5 days used in computing the mean and CV effectively averaged away this variability, so the result was a low CV. A narrow filament of low CV extended westward from Cape Mendocino in the middle of the high-pigment filament. This filament was relatively constant over time; compare this with the Point Arena filament. The final region of low CV was a narrow nearshore area between Point Reyes and the entrance to San Francisco Bay. This also happened to be an area of lower pigment than the warm, high-pigment water mass farther offshore. This seemed to be the outflow from San Francisco Bay that should be freshet than the surrounding water. Simple geostrophic models suggest that this lighter, fresher water should have flowed to the north.

Fig. 3.

.6

/• .5• /3' .6

• 6 .'7 ß

5 /"• ß I-I .•

.7

,•0

:.

Location of 21 subareas. Each box is 16 km by 16 km. Solid lines indicate significant correlation (r).

4. TEMPORAL PATTERNS OF PHYTOPLANKTON PIGMENT

We examined 21 subareas of each of the 25 CZCS scenes.

These areas were 16 km by 16 km and were chosen to repre- sent the various regimes described in the mean and CV images. First, we chose five lines of subareas i-oughly oriented perpendicular to the coastline. Each line had one nearshore subarea, one subarea near the edge of the coastal band of high pigment, and one subarea in oceanic waters. The lines were chosen such that there was a transect through the filaments at Cape Mendocino and Point Arena and there were transects adjacent to these filaments. Additional stations were selected beyond these initial 15 to ensure that we had adequate coverage. We also constrained the subarea selection to those areas where there was adequate sampling in the time domain. Figure 3 shows the subareas. Note that we do not have any subareas far offshore because of the relatively persistent cloudiness. For each of the 21 subareas, we examined each CZCS image and judged whether the subarea was sufficiently clear to be used in later analysis. We then calculated the average pigment concentration in each subarea. Table 1 is a listing of the mean and coefficient of variation for each subarea.

This method of examining subareas was used to reduce the volume of data and the gappiness of the data set. Empirical orthogonal function (EOF) analysis is naturally the preferred method for analyzing time series of spatial maps [e.g., Kelly, 1985]. However, this particular time series is relatively short, as well as having a significant temporal and spatial bias as a result of recurrent cloud (and hence wind) patterns. The re- suiting modes derived from an EOF analysis of such a series would be difficult to interpret because of this irregular sampling pattern. Even with the more complete AVHRR data set from CODE 1, it was difficult to examine the temporal patterns of the EOF modes because of the shortness of the series.

Instead, we decided to look at temporal and spatial patterns using simple regression analysis between various subareas. We used all of the available CZCS data for these time series, rather than only the weighted samples described earlier. This

1752 ABBOTT AND ZION' VARIABILITY OF PHYTOPLANKTON PIGMENT

TABLE 1. Mean and Coefficient of Variation of Phytoplankton Pigment for 21 Subareas Shown in Plate 1

Mean,

Subarea mg m-

Coefficient

of

Variation, mg m -3

1 4.40 0.96

2 4.80 0.71

3 4.59 1.15

4 3.75 0.65

5 4.35 O.76

6 6.62 1.10

7 6.41 0.92

8 12.49 0.95

9 3.70 0.96

10 1.15 0.82

11 1.24 0.80

12 1.72 0.66

13 0.73 0.89

14 2.32 1.30

15 1.89 0.58 16 0.94 1.16

17 0.34 0.50

18 0.74 0.84

19 0.32 0.47

20 0.52 0.69

21 0.48 0.83

allowed us to examine small time scale changes in the pigment patterns. However, one must use care in the interpretation of these correlations derived from gappy time series. That is, the actual series of sample dates used in the correlation calcula- tion for each pair of stations will differ between pairs. This can easily result in a correlation matrix that is not positive definite. Although one can consider interpolation of such series [e.g., Chelton et al. 1982], the short length of these time series makes such an interpolation suspect. Although these limi- tations must be borne in mind, we feel that such a correlation

analysis may reveal useful results. Figure 3 shows the correlation coefficients between the

various subareas. The solid lines are significant at the 95% level. There appeared to be three regimes where there was a high degree of connectivity. The first was a northern regime consisting of boxes 1, 2, 10, and 17 off Cape Mendocino. The central area near Point Arena (consisting of boxes 3, 4, 5, and 15) formed a second regime. Even though boxes 2 and 3 were close together, the correlation was only -0.06. It is interesting that the northern regime showed clustering perpendicular to the coast while the central regime showed a more oblique clustering offshore. This might be related to the increased wind stress in the central area [Kelly, 1985; Winant et al., this issue]. The third regime consisted of boxes 6, 7, 8, and 9 off San Francisco. It is not surprising that this area behaved co- herently. That is, this region was coincident with the area of warm, saline water described by Huyer [1983] that was apparently freshly upwelled water that had been exposed to local solar heating. The correlation between box 5 and box 6 was only 0.22, suggesting that there was only a weak relationship between the central area off Point Arena and the southern

area off San Francisco.

In addition to these three regions, there are some other relationships of note. Box 18 and box 20 were highly correlated with each other. Note that box 18 was at the end of the

Cape Mendocino filament and that box 20 was at the end of the Point Arena filament (Plate 2a). This suggests that similar

processes were affecting the temporal patterns at the offshore end of each filament. Also note that boxes 13 and 16 were also

correlated and that these two areas were located in the con-

cave areas between the filaments. Their correlation was likely the result of coherent changes in the width of the band of the high pigment coastal water observed in Plate 2a. The correlation between these two boxes in between the filaments and

the two boxes at the ends of the filaments (18 and 20) was not significantly different than zero, indicating that the processes affecting the length of the filaments were perhaps different than processes affecting the width of the coastal band.

The correlation between boxes 15 and 20 indicates that

there was some coherence between patterns within the Point Arena filament and those close to shore. However, as a coun- terexample, note that box 14, which was in the middle of the Point Arena filament, had no significant correlation with any of the surrounding boxes. The area just south of the Point Arena filament (boxes 16 and 21) also were highly correlated. Finally, there was some correlation between box 16 and box 5 near Point Arena.

We may speculate on some of the processes that may be responsible for these groupings of the various subareas. The northern region near Cape Mendocino was in an area of less wind stress than the region off Point Arena [see Halliwell and Allen, this issue]. The amount of cross-shore coherence is surprising, given that there were no obvious cross-shore flow patterns in any of the satellite imagery. It is also worth noting that the pigment levels ranged from nearly 5.0 mg m-3 near the coast to 0.50 mg m -3 offshore (Table 1). The simplest explanation of these patterns would involve Ekman transport' as equatorward wind stress increases, nutrient-rich water brought up near the surface results in increased phytoplankton growth near the coast. These waters are transported offshore and are gradually depleted of nutrients. Thus fluctuations in equatorward wind stress would affect pigment concentrations offshore as well as nearshore. Note that in this

area, the band of high-pigment, coastal water was only 30 km wide, which is consistent with two-dimensional, Ekman-type upwelling [Huyer, 1983].

The central region near Point Arena was in a different physical regime. Wind stress was much higher in this region, and it also appeared to be an area of eddy formation [Davis, 1985b' Huyer and Kosro, this issue]. Huyer and Kosro [this issue] show that isotherms and isohalines diverged from the coast at this point. That is, they continued in a near-southerly direction, while the coastline bears more southeasterly. The waters off Point Arena were warmer and fresher than those off'

the Central line (Figure 1). The equatorward surface current was shallower and weaker off Point Arena as well. Huyer and Kosro suggest that the area off' Point Arena is favorable for the generation of eddies or meanders whenever the upwelling- favorable wind relaxes, based on arguments concerning con- servation of potential vorticity and the interaction of the equatorward surface current and the northwestward inshore cur-

rent that is present during wind relaxations. The patterns of pigment variability were consistent with these patterns in the velocity field. Note that box 5 at the southern end of the central area was correlated not with box 6 in the southern

area but rather with box 15 that is offshore. Similar processes may be occurring south of Cape Mendocino, but there were no current measurements made in that area during CODE 1. As was described earlier, there was a narrow band of high- pigment, high-temperature water nearshore between Cape


Mendocino and Point Arena that did appear to move northward towards the end of an upwelling event as the wind re- laxed. This appears to be similar to the processes occuring in the Point Arena-Point Reyes area described by Huyer and Kosro, although they were much less intense in the Cape Mendocino-Point Arena area.

Individual surveys of surface velocity showed considerable mesoscale variability [Davis, 1985a; Kosro, this issue; Huyer and Kosro, this issue]. However, average velocity fields [Davis, 1985b; Winant et ai., this issue; Huyer and Kosro, this issue] showed a much simpler structure which was more reminiscent of classic two-dimensional upwelling [Huyer, 1983]. The average velocity maps (calculated from current meter moorings, hydrographic surveys, and Doppler acoustic log surveys) showed some evidence of a recurrent meander or eddy west of Point Reyes, near the site of box 15. The interaction of this eddy and the recurrent filament at Point Arena with the coastal region may have been responsible for the broadening (from 50 km north of Point Arena to 70 km south of Point Arena) of the band of high-pigment coastal water.

The southern region off Point Reyes (boxes 6, 7, 8, and 9) was located in the area of high-temperature, high-salinity described by Hto, er [1984] and O/irera [1982]. This area appears to be a partial source of the warm water that moves northward during wind relaxations [Send et al., this issue; Winant et al., this issue: Kosro, this issue]. Given the differ- ences in the physical processes occuring in this part of the CODE region compared with the area off Point Arena, it is not surprising that there was no correlation between these two areas. Also note that box 9 was also part of this group, even though its pigment concentration was much less.

The correlation between boxes 15 and 20 is not surprising, given the presence of the recurrent filament off Point Arena. Note also the correlation between boxes 16 and 21, which is

just south of this filament. The associated length scales (approximately 150 kin) were long, when one considers that these were in the cross-shore direction. What is more interesting however, was the lack of correlation between boxes within the

filaments. From the weighted mean image {Plate 2a), one rnight expect boxes 2, 12, and 18 to be correlated and boxes 5, 14, and 20 to be correlated. This suggests not that the i/la- ments were responding as a single unit simultaneously, but that changes in the nearshore patterns may take several days to propagate seaward. We will discuss this further below.

We note in Table 1 that the lowest coefficients of variation

occurred in the open ocean areas (boxes 17 and 19) and the highest CVs occurred in the coastal area (boxes 3 and 6) and on the edges of the Point Arena filament (boxes 14 and 16). It is not surprising that the open ocean areas showed little variation. The high variability in boxes 3 and 6 may have resulted from the shifts between strong equatorward winds and relaxation events that led to northward advection of high-pigment water near the coast. Evidently, the Point Arena filament must have "wobbled" somewhat so that boxes 14 and 16 were

sometimes within the filament and sometimes not.

The correlation coefficients presented in Figure 3 were calculated for a time lag of 0; we also calculated the autocorrelation coefficient for lags up to 11 days. These results must be interpreted with caution because of the variable number of samples for a particular lag time. For example, there were 10. 4, 3, 4, 9, 8, and 6 samples for lag separations of 1. 2, 3. 4. 5, 6, and 7 days. (Winant et al. [this issue] and BeardsIcy et al. [this issue] noted a definite peak in the wind

w•riance spectrum near 0.25 cycles per day during CODE 1; perhaps this is related to the apparent sampling periodicity of 5 6 days.} At a lag of 1 day, boxes 3, 4, 9, 10, 11, 15, 16, 17, 18, 20. and 21 showed significant autocorrelation. At lags of 5-6 days. boxes 1. 10, 13, 15, and 16 showed significant autocorrelation. We cannot explain the pattern of the 1-day lag correlation: there seemed to be no consistent pattern. Some of the boxes are nearshore, some are at the edge of the coastal band, and some are far off'shore. The 5- to 6-day lag correlation does show some consistency; nearly all of the boxes were located at the fringe of the nearshore band of high pigment in waters with pigment concentrations between 1 and 2 mg m-3. The physical processes behind such a pattern are not clear: current velocities from the Doppler acoustic log showed an energy-weighted decorrelation scale of about 5 days [Kosro, this issue]. Perhaps there was some "pulsing" of the width of this coastal boundary, coincident with the wind- forcing spectral peak at about 4 days. Again, we must use caution in making interpretations from gappy time series.

We also calculated space-time correlations for selected pairs of subareas. There was no evidence of any longshore propagation of patterns as was observed in the SST imagery [Kelly, 1985] or in the large-scale wind field [Halliwell and Allen, this issue]. We looked for evidence of cross-shore propagation within the Cape Mendocino and Point Arena filaments. There were indications of a 5- to 6-day cycle between boxes 5, 15, and 20. That is, there was a significant correlation between 5 and 15 and between 15 and 20 at lags of 5-6 days. The correlation coefficient at these lags was greater than the corresponding correlation at zero lag. This suggests that patterns in phytoplankton pigment that were created nearshore propagated offshore at a speed of between 25 and 35 cm s-•. These values are certainly in the same range as those observed with drifters [Da•.,is, 1985b], current meters [Winant et al., this issue], and Doppler acoustic log measurements [Huyer and Kosro, this issue]. Again. we caution against relying too heavi- ly on results derix, ed from gappy time series, but at least this result is consistent with in situ observations of the filaments. It

does suggest that a simple model of a filament entraining coastal water and moving it offshore may not be unreason- able. However, note that some boxes that were within the

filament (e.g., box 14} did not reveal this simple pattern. Note that box 14 was quite variable {see Table 1), so that it was not always in the filament, while boxes 15 and 20 were almost always in the filament. The lack of a 5-day cycle in the Cape Mendocino filament is more difficult to explain; there were fewer samples at the 5- and 6-day lags.

We do not expect these various correlations to remain constant. As the winds during an upwelling event are by no means spatially or temporally uniform [Kelly, 1985], the intensity or even the sign of the correlation may change. We examined the relationships between three nearshore boxes from each of the three regions described above; box 1, box 5, and box 6. We also included box 15, as it seemed to be correlated with sev-

eral other surrounding subareas. We studied two upwelling e•ents: May 1-12 and July 6-14. Figure 4a shows the time course of the average pigment concentration in these boxes during the May event. Note that prior to day 127 (May 7}, the nearshore boxes I1, 5, and 6} all behaved quite differently. Alter day 127, boxes 5 and 6 (at the southern end of the CODE region} seemed to track each other well. Both the northern subarea Ibox 1} and the off,shore subarea (box 15) did not seem to be correlated with any of the other subareas.

1754 ABBOTT AND ZION' VARIABILITY OF PHYTOPLANKTON PIGMENT

A 12

• 8 I- Z

Q. 4

- • BOX 6 • A

BOX 5 .ox, "./I 1."

_ -- BOX I ............. ß

I i I I I I I I I I I

122 124 126 128 130 I..32

:50 APRIL JULIAN DAY 12 MAY

16-

• 8 I-- Z

Q. 4

)ox _

o 186

5 JULY

•BOX 6

,, / \Eox i .,,. / '. / '\ i • '" • /.. "\

: \ /'/ \ I , /' \ ," \ /'

ß ß

• \"/' BOX 5 188 190 192 194

JULIAN DAY

I

196

15 JULY

Fig. 4. Time series of averaged pigment in boxes 1, 5, 6, and 15 from upwelling events (a) May 1 to May 12 and {b) July 6 to July 14.

Figure 4b shows the time course during the July eventß Note that boxes 5 and 6 were highly correlated during the entire period, while boxes 1 and 15 again did not appear to be correlated with any other subarea.

Obviously, there is not much statistical reliability in any interpretations derived from such short time series, but we are more interested in the temporal patterns than in absolute correlations. If we examine the wind stress EOFs calculated by Kelly [1985], we can partially explain these patterns. Kelly [1985] noted that there was a north-south difference in the wind field, with the dividing line between the two regions located near the CODE Central line. This second wind mode

usually changed from strongly positive early in an upwelling event to strongly negative late in an event. A positive second mode corresponded to strong upwelling-favorable winds in the southern region and downwelling-favorable winds in the northern region. This temporal progression of the second wind mode thus corresponded to upwelling-favorable winds be- ginning in the southern region and propagating northward as the upwelling event continued. The final stages of an upwelling event had upwelling-favorable winds in the northern region and downwelling-favorable winds in the south.

During the May upwelling event (Figure 4a) this second wind mode was initially strongly positive. Around May 7 (day 127) this mode became negative. Note that early in this event, boxes 5 and 6 were quite different and became similar as this mode decreased towards zero. As the winds became more

downwelling-favorable in the south, the pigment concentrations in both boxes 5 and 6 increased, perhaps because these wind conditions were favorable for northward advection

of warm, high-pigment water around Point Reyes. As this poleward flow is concentrated near the coast, we would expect its effects to be visible nearshore (at box 5) and not offshore (at box 15).

During the July upwelling event (Figure 4b) the second wind mode was slightly negative or near zero during the entire period. Unlike the May event, boxes 5 and 6 were similar throughout the event. As the area between box 5 and box 6 is where Kelly [1985] predicted there would be the division between the north and south regions, we expect that box 5 should occasionally be correlated with box 6 and sometimes not. When this second wind mode is small, we expect there to be little difference in wind forcing between the north and south parts of the CODE region. This was the case during this upwelling event. Also, we expect the effects of northward advection not to be pronounced, as in the May event. This apparently was the case, as we did not see any increase in pigment in box 5 or box 6 as we did in May.

5. SUMMARY

The importance of physical forcing at a wide range of space and time scales cannot be ignored in the distribution of phytoplankton pigment in the CODE area. The shelf area, while typically nutrient-rich, showed considerable longshore variability, primarily in response to small-scale changes in the local wind field. The temporal variability in this area also re- sponded to changes in the winds which occasionally result from Kelvin waves propagating northward from off southern California. The width of this coastal boundary varied from 30 km to 70 km, the latter distance being much wider than was expected from Ekman-type upwelling models. The shape of this boundary closely followed the shape of the coastline, implying that coastline topography plays an important role in the dynamics of this area. Large, recurrent filaments at Cape Mendocino and Point Arena may transport large amounts of phytoplankton biomass offshore, resulting in an offshore biomass maximum in zooplankton. The length of these filaments appeared to be related to the location of the wind stress maximum. Thus variations in wind stress curl may affect the dynamics of these filaments. The offshore waters were relatively constant in pigment concentration throughout the CODE 1 period.

There were three well-defined nearshore regions in the study region: a northern area off Cape Mendocino, a central area near the CODE Central line, and a southern nearshore area

off San Francisco. These areas were separated by the patterns of wind forcing. The northern area had relatively light winds and hence high pigment concentrations. It seems to behave in accordance with classic two-dimensional upwelling models. The southern area was weakly negatively correlated with the northern area, although it had relatively light winds (although stronger than the northern area) and had very high pigment concentrations. This area tended to be warm and salty (as well as cloudier) as well; it often moved northward during wind relaxations. The central area where the winds were the

strongest formed another separate region. During wind relaxations the southern inshore portion of the central area appeared to be correlated with the southern area, perhaps because of the poleward current that appears inshore during these relaxation events.

ABBf)TT AND ZION: VARIABILITY OF PHYTOPLANKTON PIGMENT 1755

As the CZCS time series is biased in time and space to periods and areas of high winds, it is not surprising that wind forcing plays a dominant role in the spatial and temporal patterns of phytoplankton pigment variability. However, we have attempted to minimize this problem by proper temporal and spatial weighting. Thus the northern area (which is typically undersampled as a result of low winds} still shows the importance of wind forcing. Finally. note that these interpretations are consistent with the relationship of SST and wind forcing described by Kelly, who used a much larger AVHRR time series.

Processes occurring at mesoscales, such as offshore filaments and small-scale wind events, play an important in role in the patterns of phytoplankton pigment. The large-scale biological patterns observed in CalCOFI are the result of the interactions between these mesoscale processes and larger- scale processes such as wind stress curl. Satellite data can help provide the link between these scales, particularly through the use of long time series. We have seen that one possible interaction. the offshore filaments, is difficult to resolve with large- scale ship surveys, and satellite data are essential. However, we have also shown that high-resolution wind measurements, particularly offshore, are necessary if we are to continue to study the link between the coastal and open oceans.

Acknowled•tments. We thank D. B. Chelton, K. A. Kelly, and K. L. Denman for helpful discussions on many aspects of this research. Satellite data were processed on computer facilities provided by the Pilot Ocean Data System at the Jet Propulsion Laboratory (JPL), California Institute of Technology. The Scripps Satellite Oceanogra- phy Facility is supported by the National Science Foundation, the Office of Naval Research, and the National Aeronautics and Space Administration (NASA). This research was supported by the Ocean Biolog3 Division, Office of Naval Research (contract N00014-85- C0104) to SIO and by NASA to JPL. CODE contribution 41.

REFERENCES

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Abbott, M. R.. and P.M. Zion. Satellite observations of phytoplankton •ariability during an upwelling event, Cont. She!/i Res., 4, 661- 680, 1985.

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Winant, C. D., R. C. Beardsley, and R. E. Davis, Moored wind, temperature, and current observations made during Coastal Ocean D,•namics Experiments 1 and 2 over the northern California conti- nental shelf and upper slope, d. Geophys. Res., this issue.

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P.M. Zion. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109.

(Received March 13, 1986; accepted August 1, 1986.)

Spatial and temporal variability of phytoplankton pigment distributions in the central equatorial...

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