JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 117, C04005, doi:10.1029/2011JC007604, 2012
Effects of mesoscale processes on phytoplankton chlorophyll
off Baja California
T. Leticia Espinosa-Carreón,1 Gilberto Gaxiola-Castro,2 Emilio Beier,3 P. Ted Strub,4
and J. A. Kurczyn5
Received 19 September 2011; revised 11 February 2012; accepted 14 February 2012; published 3 April 2012.
[1] Using satellite sea surface height (SSH) and chlorophyll (CHL), the year 2000 is
analyzed to characterize the effects of mesoscale circulation patterns on phytoplankton
spatial variability in the California Current (CC) off Baja California. Satellite data are
combined with and compared to in situ field measurements (chlorophyll-a and
hydrographic variables) along vertical alongshore sections located 130 km offshore
between 24.5 33 N. Monthly average maps of SSH and surface geostrophic velocities
depict the characteristics of mesoscale meanders and eddies, which correspond well with
the subsurface hydrographic and velocity fields. Satellite-derived pigment (CHL)
represent in situ fields in the upper 0–20 m (overall r = 0.53; p < 0.05), but their
representation of peak values in Deep Chlorophyll Maxima (DCM) at 50 m depth are
inaccurate. DCM are traced in all three seasons (January–July), descending from near
the surface (north of 31 N) to 50 m over a large extent of the transect to the south,
approximately following the 24.7–25.1 isopycnals as they and the isotherms deepen to
the south. In January, phytoplankton chlorophyll concentrations in the DCM are
relatively uniform, originating during upwelling events that occur farther north, then
following the equatorward flow of the CC. During April and July, the discrete maxima
in the DCM occur at the centers of cyclonic meanders and the chlorophyll
concentrations inside these maxima are enhanced as a result of local coastal upwelling
off Baja California. Phytoplankton blooms created by coastal upwelling spread
offshore and subduct along the 24.7–25.1 isopycnals, creating the DCM along the
inner part of the meandering jet.
Citation: Espinosa-Carreón, T. L., G. Gaxiola-Castro, E. Beier, P. T. Strub, and J. A. Kurczyn (2012), Effects of mesoscale
processes on phytoplankton chlorophyll off Baja California, J. Geophys. Res., 117, C04005, doi:10.1029/2011JC007604.
1. Introduction
[2] Although the pelagic ecosystem of the California
Current (CC) is well studied, aspects of the interaction
between its mesoscale circulation features and biology
remain to be clarified by combinations of satellite and in situ
data—the topic of this paper. The California Current System
(CCS) connects the SubArctic gyre in the north to the North
Equatorial Current in the south [Favorite et al., 1976; ParésSierra et al., 1997]. In the southern part of the California
1
Instituto Politénico Nacional, Departamento de Medio Ambiente,
Centro Interdisciplinario de Investigación para el Desarrollo Integral
Regional Unidad Sinaloa, Guasave, Sinaloa, Mexico.
2
Departamento de Oceanografía Biológica, Centro de Investigación
Científica y de Educación Superior de Ensenada, Ensenada, Mexico.
3
Centro de Investigación Científica y de Educación Superior de
Ensenada, Unidad La Paz, Mexico.
4
College of Earth, Ocean and Atmospheric Sciences, Oregon State
University, Corvallis, Oregon, USA.
5
Departamento de Oceanografía Física, Centro de Investigación
Científica y de Educación Superior de Ensenada, Ensenada, Mexico.
Copyright 2012 by the American Geophysical Union.
0148-0227/12/2011JC007604
Current off Baja California, the equatorward flow takes the
form of an intensified jet. The core of this jet separates from
the coast and is often found 100–200 km offshore, strongest
during late winter and spring. The jet often divides the inshore
biologically productive waters from offshore low-production
waters, creating strong mesoscale variability in the form of
eddies and meanders that affect the biological productivity of
the area [Henson and Thomas, 2007a, 2007b].
[3] Physical-biological interactions in the southern CC region
have been reported in numerous field studies and (more recently)
analysis of satellite fields [Strub et al., 1990; Hayward et al.,
1999; Bograd et al., 2000; Durazo et al., 2001; EspinosaCarreon et al., 2004; Henson and Thomas, 2007a, 2007b]. In
particular, Legaard and Thomas [2007] use satellite data to
describe the spatial pattern and intraseasonal variability of chlorophyll and sea surface temperature. However, papers that combine coincident satellite and in situ data are less common and we
use this combination to explore the relationship between mesoscale circulation features and phytoplankton distributions, as
represented by satellite and in situ chlorophyll-a concentrations.
[4] Three processes have been suggested in the generation
of meanders and eddies off Baja California: wind-forcing,
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instabilities of the coastal flow, and coastal geometry
[Haidvogel et al., 1991; Parés-Sierra et al., 1993; Barth
et al., 2000]. The aspects of wind forcing most commonly
described are coastal upwelling/downwelling due to alongshore wind stress and upwelling/downwelling in offshore
regions caused by the curl of the wind stress [Chelton, 1982;
Bakun and Nelson, 1991]. Upwelling is needed to increase
the phytoplankton concentrations, by bringing the nutrients
that originate in the deeper ocean up into the euphotic zone,
where solar radiation drives photosynthesis. A third type of
wind forcing that accomplishes the same result is direct wind
stirring, proportional to the cube of the wind speed [Strub
et al., 1990]. Dynamical instabilities that convert the linear
momentum of jets into mesoscale meanders and eddies may
be barotropic (due to horizontal shear of strong currents) or
baroclinic (due to vertical shear and horizontal density gradients). In this region, vertical shear is created by the interaction of the equatorward surface flow of the California
Current with the poleward California Undercurrent [Barth
et al., 2000; Jerónimo and Gómez-Valdés, 2007]. Coastal
geometry may be in the form of bottom bathymetry or
coastline morphology (capes and bays). Simpson and Lynn
[1990] have documented mesoscale structures off Baja
California and suggested that the ocean’s bottom bathymetry
induces instabilities in the seasonal intensification of the
California Undercurrent, which generates meanders and
eddies that are also influenced by the geometry of the
coastline [Soto-Mardones et al., 2004].
[5] The processes discussed above usually act in combination to create meanders and eddies on time scales of weeks
to seasons. On longer time scales, Gaxiola-Castro et al.
[2008] illustrate temporal links between lower trophic biological levels and physical processes in the southern region
of the California Current off Baja California. They concluded that diminishing near-surface salinity and water column integrated phytoplankton biomass have been associated
with variations in the Pacific Decadal Oscillation (PDO).
[6] The year 2000 has been distinguished by the CC’s
strong shift in location away from the coast of Baja California, with sea surface temperatures close to the long-term
mean [Bograd et al., 2000]. The main goal of this work is to
characterize the effects of mesoscale processes (jets, eddies,
and meanders) on surface and subsurface phytoplanktonchlorophyll distribution during three months of the 2000
year off Baja California. We utilize a combination of satellite-derived data (SSH and CHL) with field information
obtained from the sea-ongoing CalCOFI (California Cooperative Oceanic Fisheries Investigations) and IMECOCAL
(Investigaciones Mexicanas de la Corriente de California)
programs. We selected an alongshore transect located at a
distance of 130 km offshore, where the transitional core of
the CC is usually found, and also where field data are routinely collected by CalCOFI and IMECOCAL. One consequent research question is: Is there an association between
circulation processes and water column phytoplanktonchlorophyll distributions in the CC along Baja California?
2. Data and Methods
2.1. Satellite-Derived Data
[7] High-resolution sea surface height anomalies (hereafter sea level anomalies, SLA) have been produced by
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Segment Sol Multimissions d’Altimétrie, d’Orbitographie
et de Localisation Précise (Ssalto)/Developing Use of
Altimetry for Climate Studies (DUACS) and distributed by
Archiving Validation and Interpretation of Satellite Oceanographic Data (AVISO), at 7 day intervals on a 1/3 Mercator
grid and objectively interpolated onto a uniform 1/4 grid. A
7 year mean (1993–1999) of the SSH at each point is
subtracted to remove the unknown geoid and the mean
height, creating the SLA from the SSH (see http://www.aviso.
oceanobs.com) [Ducet et al., 2000; Le Traon et al., 2003].
Our time series spans from October 1992 to September 2007,
and represent the updated multimission gridded product
referred to as the Delayed Time maps of sea level anomaly.
[8] To examine the representative mesoscale nature of the
year 2000, we calculated the nonseasonal anomalies of the
SLA data by removing the temporal mean and seasonal signal estimated from the harmonic analysis of the AVISO time
series (as in the work of Espinosa-Carreon et al. [2004]):
Fðx; tÞ ¼ A0 ðxÞ þ A1 ðxÞ cosðwt 81 Þ þ A2 ðxÞ cosð2wt 82 Þ;
ð1Þ
where A0, A1, and A2 are the temporal mean, annual amplitude, and semiannual amplitude for each time series at each
pixel; x(x, y); w= 2p/365.25 is the annual radian frequency;
81, 82 are the phases of annual and semiannual harmonics,
respectively, relative to the beginning of year; and t is time.
Fitted errors of amplitudes and phases (calculated as
described by Beron-Vera and Ripa [2002]) were very low in
value (not shown). After removal of the temporal mean and
seasonal signals, the nonseasonal sea level anomalies retain
only the subseasonal and interannual variability.
[9] Empirical Orthogonal Functions (EOFs) are calculated
for the nonseasonal SLA described above. In the analysis
below, results are shown only for the first EOF mode of
nonseasonal SLA, which describes the most coherent pattern
of the nonseasonal variance. The bimonthly Multivariate
ENSO Index (MEI) values (in 1/1000 of standard deviations) were obtained from http://www.cdc.noaa.gov/people/
klaus.wolter/MEI/table.html and are compared to the nonseasonal SLA EOF in Figure 2.
[10] To reconstruct the dynamic sea surface height (SSH),
we added the long-term mean of sea surface dynamic height
(calculated from the surface geopotential anomalies of the
World Ocean Database 2001, WOD01) to the SLA from
AVISO, using 500 dbar as reference level. The WOD01
represents the climatological, high-resolution 1/4 gridded
temperature and salinity fields at standard depths [Boyer
et al., 2005] and were obtained from the National Oceanographic Data Center web site (see http://www.nodc.noaa.
gov). This replaces the actual mean SSH with the mean
hydrographic dynamic height, converting SLA back to an
estimated dynamic SSH.
[11] SeaWiFS (Sea Viewing Wide Field of View Sensor)
ocean color data (chlorophyll concentrations, CHL) were
provided by A. Thomas of the University of Maine. After
initial processing [Barnes et al., 1994], the 8 day composites were remapped to 4 km resolution. Weekly CHL
imagery, were obtained from December 1999 to January
2001 for the California Current region (22–33 N, 112–
120 W) (Figure 1). From the weekly CHL and SSH data we
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Figure 1. Study area showing the 200 m isobath for CalCOFI-IMECOCAL regions. Points show the
*0.50s hydrographic stations from which in situ temperature ( C), salinity, and chlorophyll-a (mg m3)
data are obtained.
obtained the discrete surface values for all the stations,
sampled by CalCOFI and IMECOCAL programs in our
study area (grids not shown). We are particularly interested in
the stations numbered *0.50, which form a transect along a
line parallel to the coast (located 130 km offshore)
(Figure 1). Finally we estimated the monthly average of the
dynamic sea surface height fields, from which the surface
geostrophic velocities were calculated. Dynamic SSH fields
were very similar to those obtained by Strub and James
[2002].
2.2. In Situ Data
[12] In situ temperature, salinity, and phytoplankton
chlorophyll-a data were acquired from the monitoring programs of CalCOFI (stations 90.53 and 93.50; http://www.
calcofi.org/data.html) and IMECOCAL (stations *0.50 from
lines 100 through 137; http://imecocal.cicese.mx/) during
January (14 January to 2 February), April (4 to 23 April),
and July (10 to 31 July), 2000 (transect line in Figure 1). At
each station, a CTD/Rosette cast was made to the 1000 m
depth to measure pressure, temperature, and salinity. Density
was determined from temperature and salinity data, following the United Nations Educational, Scientific and Cultural
Organization [1983] and Millero and Poisson [1981] algorithms. Geostrophic velocities were calculated following
Pond and Pickard [1986], and referenced to the 500 dbar
depth estimated from the geopotential anomalies.
[13] Phytoplankton chlorophyll-a concentrations were
measured from discrete water samples collected in 5 L
Niskin bottles at 0, 10, 20, 50, 100, 150, 200 m depths. For
chlorophyll-a analyses, 1 L of seawater was filtered onto
Whatman GF/F filters and chlorophyll-a was determined by
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Figure 2. First non-seasonal EOF mode of dynamic Sea Level Anomalies (SLA) from AVISO, for
October 1992 to September 2007. (a) Spatial pattern (in cm) and (b) time series (relative units, green line)
and Multivariate ENSO Index (MEI, blue line).
the fluorometric method [Yentsch and Menzel, 1963; Holm
Hansen et al., 1965], following Venrick and Hayward’s
[1984] procedure. Data from these discrete depths are used
to calculate the water column integrated phytoplankton
chlorophyll-a (0–100 m, in mg m2), and to create vertical
sections along the CalCOFI and IMECOCAL stations *0.50
in Figures 5–7.
3. Results
3.1. Mesoscale Processes for the Year 2000
[14] The spatial and temporal pattern for the first EOF of
nonseasonal monthly average SLA is shown in Figure 2. This
EOF mode explains 35% of the nonseasonal SLA variability
and represents mainly the El Niño/La Niña interannual
events. These strongly affect the Baja California Peninsula
coast, with diminishing effects offshore. The mean circulation pattern during strong interannual events consists of
meandering poleward flow during El Niño and equatorward
flow for the duration of La Niña. The correlation between the
time series of the first EOF mode (in green) and the Multivariate ENSO index (MEI) (in blue) is significant (r = 0.56;
p = 0.01). Within the context of the weak La Niña conditions, we examine biophysical interactions associated with
mesoscale features off Baja California during January, April,
and July 2000.
[15] Dynamic height fields (SSH) in the year 2000 for
January, April, and July, show mesoscale features characterized by eddies and meanders (Figure 3). During January
and April, the lowest dynamic SSH values (<90 cm) are
observed in the northernmost part of the study area and in
the coastal zone. In January, the prominent features are the
extensive region of low dynamic SSH over most of the
region within the persistent Southern California Bight
cyclonic eddy north of 30 N, the large cyclonic eddy off
Punta Eugenia (26 –28 N), and the other mesoscale structures with low dynamic SSH extending west offshore of
24 N. In April, a low dynamic SSH feature is located north
of Punta Eugenia, which appears to spread out southwestward. In the southwest corner of the region, an area with
high dynamic SSH is depicted, increasing from January to
July. These fields suggest an intensification of an anticyclonic eddy situated 29.0 N–116.5 W in January that
moved to 29 N–118 W in April and merged with the
offshore region of high dynamic SSH in July.
[16] Chlorophyll-a monthly images for January, April, and
July are shown in Figure 4. In the north, high chlorophyll
concentrations are observed offshore, advected from the
north and extending farthest south (30 N) in January,
representing the Ensenada Front off Baja California. In January, the cyclonic eddy located at 27 N–116 W shows an
offshore chlorophyll concentration greater than 0.3 mg m3.
In the three sampled months along the transect, high chlorophyll concentrations (>0.5 mg m3) are inversely and
significantly correlated with lower dynamic SSH values
(r = 0.83 for January; r = 0.43 for April; r = 0.61 for
July). The relationship between satellite chlorophyll (mg
m3) and geostrophic velocities (cm s1) are shows in
Figure 4. We can observe that the surface chlorophyll distributions are well related to the mesoscale structures.
[17] The circulation patterns described by satellite data in
Figure 3 agree in general with the more spatially limited
IMECOCAL hydrographic dynamic height fields (with
500 dbar as the reference level) presented by Bograd et al.
[2000]. The question is how to relate the more complete
surface fields constructed from satellite data (Figure 3 and
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Figure 3. Monthly average dynamic Sea Surface Height (cm) calculated as the sum of AVISO anomalies
plus the temporal mean of the dynamic height field of WOD01 [Boyer et al., 2005] during (a) January
2000, (b) April 2000, and (c) July 2000. Vectors correspond to the associated geostrophic velocity
(cm s1). The thick black line represents the transect formed by *0.50s hydrographic stations. Dynamic
SSH images represent the temporal average of the weeks that corresponds to each cruise time period.
Henson and Thomas [2007a, 2007b]) to the sparse subsurface in situ data?
3.2. Mesoscale Circulation, SSH, and Chlorophyll
Relationships
[18] In order to study the relationship of phytoplankton
biomass to mesoscale circulation features, we use in situ and
satellite-derived chlorophyll-a concentrations as proxies for
phytoplankton biomass. These are compared to the ocean’s
mesoscale structure, as represented by satellite-derived
dynamic SSH (anomalies plus mean dynamic height), and to
the hydrographic distribution of water properties and geostrophic velocities along the transects shown in Figure 3.
These transect run parallel to, and approximately 130 km
from the coast, mostly in the transition area between the CC
core flow and the coastal upwelling zone. The in situ data
along the transects help to characterize the subsurface fields
Figure 4. SeaWiFS Chlorophyll-a monthly composites for (a) January 2000, (b) April 2000, and (c) July
2000. Vectors correspond to the geostrophic velocities (cm s1) associated with the altimeter dynamic
SSH. The thick black line represents the transect formed by *0.50s hydrographic stations. Chlorophyll-a
images represent the temporal average of the weeks that corresponds to each cruise time period.
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Figure 5. Descriptive contours of the transect formed by the *0.50 hydrographic lines for January 2000.
(a) Dynamic Sea Surface Height (SSH; cm), Geopotential anomaly (Geop. anom.; cm), SeaWiFS chlorophyll-a concentration (CHL; mg m3) from weekly data extracted at transect stations, and in situ integrated chlorophyll-a (mg m2). Vertical distributions of (b) temperature ( C), (c) geostrophic current
velocity (cm s1, positive eastward), (d) salinity, (e) phytoplankton chlorophyll-a (mg m3), and (f) density (kg m3).
associated with the surface properties sampled by the
satellites.
[19] The IMECOCAL cruises during 2000 had duration of
three weeks. In our correlation analysis, we use the weekly
satellite chlorophyll data that corresponds to each station’s
date, comparing satellite chlorophyll (CHL) to in situ data
(chl) for all cruises (Lines 90 and 93 from CalCOFI and
100–137 IMECOCAL programs). Using chl(sup) to represent
surface values of chl, for January our findings are: CHL
versus chl(sup) r = 0.38 (p = 0.05) and CHL versus chl(10m)
r = 0.12 (p not significant); April: CHL versus chl(sup) r =
0.75 (p = 0.05) and CHL versus chl(10m) r = 0.65 (p = 0.05);
July: CHL versus chl(sup) r = 0.48 (p = 0.05) and CHL versus
chl(10m) r = 0.49 (p = 0.05). Only during January were the
satellite CHL and subsurface chl(10m) uncorrelated.
[20] In January, dynamic SSH (cm) and satellite CHL
concentrations (mg m3) show an inverse relationship (r =
0.83; p < 0.05) along the transect line (Figure 5a). Within
the water column, the vertically integrated chlorophyll concentrations (0–100 m, in mg m2) remain nearly constant at
40 mg m2, except for a drop to 20 mg m2 at the most
southern stations (130–137, Figure 5a). Comparing dynamic
SSH and cross-transect velocities, dynamic SSH minima at
stations 100–103 and 123–127 fall inside cyclonic eddies,
while the dynamic SSH maxima at stations 107–117 fall
inside an anticyclonic eddy, as depicted by the geostrophic
dynamics (Figures 3a, 5a and 5c).
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Figure 6. As in Figure 5 but for April 2000.
[21] Distributions of isothermals (Figure 5b) and isopycnals (Figure 5f) along the transect show a gradual deepening toward the south, as expected when moving toward
warmer (subtropical) water masses. Isohalines also deepen
slightly toward the south until stations 117–120, where they
shoal abruptly (Figure 5d), indicating the transition from
subarctic to more saline subtropical water masses. The crosssection geostrophic current flow depicts two cyclones centered at stations 100 and 123 (Figure 5c), separated by an
anticyclonic eddy that crosses the transect line at stations
107–117 (Figure 3a). The current flow inside the cyclones is
offshore in the north and onshore in the south of each
cyclonic eddy center.
[22] In spite of the presence of mesoscale structures along
this section, the integrated in situ chlorophyll signal shows
little variability in Figure 5a, while the satellite-derived
chlorophyll appears more responsive. This is explained by
the chlorophyll section in Figure 5e, which reveals chlorophyll maxima (0.4–0.6 mg m3) that deepen from near the
surface at the north, to 50 m depth between stations 107–
127. The integration from 0 to 100 m captures all of this
DCM (Deep Chlorophyll Maximum) at each station, despite
its changing depth. This creates a nearly uniform integrated
values of 40 mg m2 at all stations except along the
southern end of the transect, where the subsurface maximum
disappears.
[23] The satellite’s CHL color sensor only detects the
first optical depth of the upper water column, which is
shallower for higher subsurface concentrations. While it is
able to see the enhanced near-surface chlorophyll maximum
of 0.6–0.8 mg m3 located in the north (stations 90–103),
the satellite CHL values underestimate the in situ concentrations, giving values of 0.4–0.5 mg m3. When the
subsurface maximum of 0.4–0.6 mg m3 descends to 50 m
depth at station 107 and farther south, the satellite CHL
values of chlorophyll concentrations drop to values between
0.1–0.2 mg m3. Maximum in situ chlorophyll-a subsurface observations rise above 0.6 mg m3 at stations 120–
127, causing only a minor increase in the satellite CHL
values. This demonstrates that in situ observations provide
more information about the bio-physical interactions of
mesoscale eddies with chlorophyll concentrations. The highsurface chlorophyll values at the northern stations (90–100)
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Figure 7. As in Figure 5 but for July 2000.
are being advected offshore by the northern branch of the
cyclonic eddy located between stations 90–107. The circulation pattern depicted by the southern cyclonic eddy (station
123, Figure 3a) produces a vertical distribution of chlorophyll that is different from the northern chlorophyll vertical
distribution at 50 m, the higher-subsurface values of
chlorophyll concentration located at the center of the
cyclonic eddy (between stations 120–127) are moving offshore in the northern half of the eddy and onshore in the
southern half of the eddy. Note that there is no value of
integrated in situ chlorophyll-a at station 123 (Figure 5a),
so the apparent separation of the subsurface maxima at stations 120 and 127 is an artifact of the contouring routine.
[24] Figures 6 and 7 show the distributions of the same
variables as presented in Figure 5, but for the transects
sampled in April and July, respectively. In April, the in situ
integrated chlorophyll-a values display an inverse relationship to the dynamic SSH values (Figure 6a). The integrated
chlorophyll-a maxima are caused by the discrete maxima in
the DCM values at stations 100 and 113–120 (Figures 6a
and 6e). These stations correspond exactly to the minima
in the dynamic SSH (Figure 6a), also depicted by the zero
lines in the cross-sectional geostrophic velocity (Figure 6c).
Thus, these maxima in the DCM are inside the strongest
cyclonic meanders along the section (also confirmed in
Figure 3b).
[25] The difference between April and January is that the
DCM is not continuous in April; instead it is confined to the
cyclonic meanders. Note that although there are no in situ
chlorophyll-a data at station 107 in April (Figure 6a), the low
values at the neighboring stations 110 and 103 confirm the
diminished values of the subsurface chlorophyll-a core
under the anticyclone and the lack of a continuous DCM.
The satellite CHL are relatively low everywhere south of
station 100, but they do show a relative maximum at station
117, located at the center of the southernmost DCM.
[26] The surface and subsurface chlorophyll-a fields from
July show similar patterns to those of April from station 100
to the south, except that the isolated DCM cores are at stations 103 and 120 and the values are much higher than in
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April. Although the peaks and troughs of the dynamic SSH
in July are not as well correlated with the in situ integrated
chlorophyll-a values (Figure 7a) as they are in April, their
values do depict an inverse relationship north of station 107.
4. Discussion
[27] During the year 2000, the MEI and the first EOF SSH
time series off Baja California have minor negative values
(Figure 2b), indicating that during this particular year the La
Niña conditions are weak, as was described by Bograd et al.
[2000] and Espinosa-Carreon et al. [2004]. The latter
authors postulate that off Baja California during the 1997–
2000 El Niño/La Niña cycles, local conditions increased the
distinctive effects of the 1997–1998 El Niño event, but
deaden the effects of the 1999–2000 La Niña event.
[28] Lynn and Simpson [1987] state that the strongest CC
equatorward flow is present in spring and summer, whereas
the strongest poleward coastal counterflow (the Inshore
Countercurrent, IC) is most evident during fall and winter.
During our short period of study, monthly dynamic SSH data
do not show poleward flow in January nor an increase in
equatorward CC flow from January to April (both periods
have very similar current patterns in Figures 3a and 3b). This
may indicate that the IC is inshore of the domain of the maps,
i.e., in coastal areas not resolved by the altimeter dynamic
surface height. During spring and summer the highest CC
flow velocities are associated with the seasonal maxima of
the pycnocline tilt [Collins et al., 2003; Pennington et al.,
2009]. Durazo et al. [2010] show that the region north of
Punta Eugenia (28 N) is influenced by SubArtic Water
(SAW) all year, while the southern region is influenced by
Transitional Surface Water (TSW) and Subtropical Surface
Water (StSW), mainly during summer and autumn. These
two water masses were present in our results during July,
associated with the large high-SSH area that occupies almost
half of the southwestern portion of our study area.
[29] Soto-Mardones et al. [2004] describe mesoscale
structures during 2000 off Baja California, using ADCP
currents and hydrographic data from the IMECOCAL
observations. In their analyses, the spring circulation was
more uniform and without eddies, except for a meander
located off Punta Eugenia. Using the finer spatial resolution
of the satellite data, we verify that this meander is a portion
of a cyclonic eddy extending offshore. Soto-Mardones et al.
[2004] explained the generation and propagation of eddies at
28.5 N from January 2000 to July 2001, following the displacement of a cyclonic eddy that was originally situated off
Punta Eugenia. Goerike et al. [2004] established that quarterly observations in the California Current are appropriate
to delineate the effects of the major ocean climate events in
this region. Despite the fact that there is not a distinctive
seasonal periodicity in eddy generation off Baja California,
we suggest that the lower SSH area situated at 24.5 N–
117.5 W in January has moved to 26.5 N–119.0 W in
April, while a water mass with high SSH develops in the
southwestern corner of our domain (Figure 3). The summer
season is characterized by the presence of small eddies close
to the coastal region, which interact with the equatorward
CC flow and with the TSW and StSW in the southern region.
Previous studies by Durazo and Baumgartner [2002], SotoMardones et al. [2004], Jerónimo and Gómez-Valdés
C04005
[2007], Durazo et al. [2010] and others have shown vertical sections of temperature, salinity, potential density,
velocity and spiciness along lines perpendicular to coast in
the IMECOCAL region. The alongshore transect examined
here lies in the transitional zone, which divides the coastal
zone from the oceanic zones, and is characterized by strong
mesoscale structures. This zone has also been described by
Lynn and Simpson [1987] and has been used by MartínezGaxiola et al. [2010] as the offshore boundary to estimate
the geostrophic transport of phosphates in an area extending
from Ensenada to Punta Eugenia. Our emphasis is different
from the above studies in that we use the alongshore transect
to characterize the subsurface fields associated with the
surface properties observed by the satellites.
[30] Soto-Mardones et al. [2004] show that the offshore
Ekman transport in the study region increases the equatorward flow and changes the structure of eddies and meanders,
reinforcing the circulation in the eastern branch of an anticyclonic eddy and in the western part of a cyclonic eddy.
This can be seen in the westward flow near stations 117–127
(Figure 5c) and in the boundaries between the anticyclonic
and cyclonic eddies located at the end of the transect
(Figure 3a). Again, the horizontal 2-D surfaces fields from
the satellite and the vertical 2-D subsurface transects provide
complementary information.
[31] From the January results, we propose the following
interpretation of the processes controlling phytoplankton
distributions: (1) The 2-D surface fields in Figure 3a shows
that the transect depicted in Figure 5 cuts through a field
composed mainly of mesoscale meanders and eddies; (2)
The surface CHL concentrations are representative (r = 0.37;
p < 0.05) of the pattern of the in situ surface chlorophyll-a
concentrations (although lower in magnitude); but they do
not represent (r = 0.50; p < 0.05) the relatively uniform
amounts of integrated chlorophyll-a pigment in the upper
100 m; (3) In the north, the strong covariability between
high values of satellite-derived CHL and gradients of satellite-derived SSH in Figure 5a could be interpreted to indicate
a greater offshore transport of phytoplankton in the northern
half of the eddy than onshore transport in the southern half
of the cyclonic eddy; (4) The in situ measurements in
Figure 5c, however, indicate that the onshore transport of
phytoplankton in the southern half of the eddy may be
similar in magnitude to the offshore transport, differing only
in the depth of the returning phytoplankton (which is misinterpreted in the satellite data); (5) Likewise, higher values
(>0.6 mg m3) of chlorophyll-a concentrations are also
found in the subsurface (50 m) maximum at the center of the
southern cyclonic eddy in the in situ section, which are only
weakly detected in the satellite CHL field (not significant at
p < 0.05); (6) The higher chlorophyll values on the inshore
side of the equatorward flow around the southern cyclonic
eddy (Figures 4 and 5) suggest that phytoplankton biomass
has increased due to coastal upwelling entrainment, similar
to the situation found in the CC farther north by numerous
authors [Brink and Cowles,1991]; (7) The vertical sections
show a gradual deepening toward the south of isotherms,
along with a deepening of the subsurface chlorophyll maximum (with values of >0.4 mg m3), which approximately
follows the 24.7–25.1 isopycnals; (8) Salinity distributions
along the section are consistent with the equatorward CC
flow of SubArctic Water (SAW) in the north, with an abrupt
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shoaling of isohalines at stations 117–120, indicating the
influence of the TSW and StSW south of Punta Eugenia
[Durazo et al., 2010].
[32] The 2-D satellite-derived SSH and surface velocity
fields in Figure 3c provide an explanation for the differences
observed in the results of July from those of January and
April. First, the spatial scales of the meanders are shorter in
July than in January and April. The alternating onshore and
offshore bands of currents in Figure 7c between stations
100–107 are barely captured by the station’s transects. Second, the meandering jet has moved further offshore in July
(Figure 3c) and the transect itself lies along the inshore
boundary of the mesoscale features, missing their peaks and
troughs.
[33] With regard to the north-south gradients in the chlorophyll-a, temperature, salinity and density fields, the pattern
seen in January is generally repeated in April and July:
Isotherms and isopycnals deepen to the south, while isohalines shoal abruptly between stations 117–120. Salinities
greater than 33.8 and an increase in temperature of the upper
ocean (of 0.3 C) indicate the presence of the TSW (Transitional Surface Water) and StSW (Subtropical Surface
Water) south of Punta Eugenia. SAW (SubArtic Water)
characteristics (subsurface salinity minima <33.5) are evident both north and south of Punta Eugenia. The DCM near
50 m, following the 24.7–25.1 isopycnal, also indicates the
presence of SAW in the core of the CC, as it continues
equatorward.
[34] The other common feature in all three months is the
northern maxima of satellite CHL (with values of 0.4–
0.8 mg m3 in the north), dropping to values of 0.2 mg m3
south of stations 97–103 (off northern Baja California,
31 N). This may represent the seasonal variability of the
Ensenada Front, describing richer CC water to the north and
more oligotrophic subtropical water to the south of the front
[Peláez and McGowan, 1986; Espinosa-Carreon et al.,
2004]. The integrated chlorophyll-a values and the subsurface chlorophyll-a transects in Figures 5–7 show that high
chlorophyll-a pigment concentrations are also found south
of the Ensenada Front next to the coast within the equatorward meanders jet. However, the high chlorophyll values
only appear in the DCM (50 m depth), producing a signal
of only 0.1 mg m3 in the satellite-derived CHL. Subsurface values increase to >1.0 mg m3 in April and >2.0 mg
m3 in July. Due to the seasonal increases in upwellingfavorable winds [Soto-Mardones et al., 2004], we suggest
that the high values of chlorophyll-a concentrations in the
DCM are an indication of local wind-driven coastal upwelling, resulting in nearshore phytoplankton blooms that are
entrained into the inshore side of the expanding equatorward
jet, subducting with the 24.7–25.1 isopycnal to form the
DCM.
[35] The data presented above demonstrate that mesoscale
cyclonic eddies and meanders with low dynamic SSH
anomalies off Baja California are not necessarily always
associated with high chlorophyll-a concentrations (in the
surface or subsurface). The existences of a strong equatorward CC flow with coastal wind-driven upwelling events
help establish a good correspondence between chlorophyll
concentrations and mesoscale circulation features. These
conditions are not found during January (winter), when the
CC flow is weak [Lynn and Simpson, 1987] and the
C04005
biological signal along our transects shows a weak DCM
(0.4–0.6 mg m3), characteristic of a mesotrophic ecosystem [Kahru and Mitchell, 2002; Gaxiola-Castro et al.,
2010]. In April (spring), the CC flow increases and the
coastal upwelling system is amplified [Espinosa-Carreon
et al., 2004; Durazo et al., 2010], promoting a strengthened biological response. Chlorophyll-a pigment concentrations reach 1.0 mg m3 (eutrophic conditions) in the
DCM at 50 m depth. Still, the only high satellite-derived
CHL signal (>0.4 mg m3) occurs north of the Ensenada
Front. During July (summer), local coastal upwelling processes reach their maximum intensity [Zaytsev et al., 2003]
and the surface geostrophic currents move offshore, developing smaller-scale meanders. At this time, chlorophyll-a
concentrations increase to > 2 mg m3 in the DCM, inshore
of the cyclonic meandering jet, although the satellitederived CHL barely detects these DCM values. The
Ensenada Front is more evident, with high chlorophyll
concentrations (0.8 mg m3) at the north of the front
attributed to nutrient-rich waters [Gaxiola-Castro and Alvarez
Borrego, 1991] that are upwelled farther north and advected
southward by the CC flow.
[36] Off central California, sea surface water transported
along the core of the CC shows lower nutrient concentrations than the locally upwelled waters. This allows the
upwelled, high-phytoplankton biomass to be clearly seen in
satellite images, as it extends offshore [Chavez et al., 2002].
This has also been seen off Baja California, in a narrow
region within 50 km off the coast (data not shown). In the
case of the transects used in our study (located at 130 km
offshore), the high chlorophyll-a concentrations were usually observed at subsurface depths and satellite-derived CHL
data registered relatively uniform, low concentrations.
[37] These results are consistent with the findings of
Espinosa-Carreon et al. [2004], who determined that for the
same study area there is not a clear relationship between
satellite-derived CHL and SSH cyclonic eddies. The authors
propose that the offshore surface nutrients are depleted by
phytoplankton, creating a nutricline that is too deep to allow
nutrients to be raised by cyclonic eddies into the euphotic
zone. The results of our study reveal that the relationships
between satellite values of CHL and SSH can be misleading
or difficult to interpret, without the companionship of the
subsurface distributions of chlorophyll-a and velocities
within the water column.
5. Conclusions
[38] Satellite-derived SSH and CHL are combined with
subsurface in situ data collected along a transect located
130 km offshore, parallel to the coast of Baja California
(Figure 1), to describe the mesoscale processes that affect
phytoplankton distributions during January, April, and July
2000. Meanders and eddies were observed in this region
during the three sampling months, their velocity distributions
were well depicted in the surface (by the satellite-derived
SSH dynamic fields) and in the water column (by the geopotential anomalies) (Figures 3, 4, 5, 6, and 7). On the other
hand, the biological response to mesoscale processes of the
satellite-derived chlorophyll (CHL) is more difficult to
interpret due to changes in the phytoplankton vertical distribution. North of 31 N, CHL values were moderately high
10 of 12
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ESPINOSA-CARREÓN ET AL.: CHLOROPHYLL OFF BAJA CALIFORNIA
(0.4–0.8 mg m3) in all three months, dropping to 0.2–
0.4 mg m3 south of 31 N. Subsurface chlorophyll-a concentrations produce a Deep Chlorophyll Maxima (DCM),
with higher values at the center of the two cyclonic eddies,
after the onset of an upwelling event in April and July. In
January, there is a more uniform DCM, creating nearly
constant values of integrated chlorophyll-a concentrations.
Values in the DCM increase from January (0.4–0.6 mg m3)
to April (>1.0 mg m3) to July (>2.0 mg m3).
[39] In January we interpret the moderate chlorophyll-a
concentrations values in the DCM to indicate a general
inflow from the north, from upwelling off California and
advection of phytoplankton equatorward by the CC. The
influence of this equatorward flow continues to create a
moderate surface chlorophyll-a concentrations north of 31 N
during April and July, while local wind-driven upwelling
causes phytoplankton blooms and high chlorophyll-a concentrations inshore of the meandering jet. The later increases
its strength between winter and spring and then moves offshore in the summer. The blooms created by the coastal
upwelling spread offshore, depleting surface nutrients and
subducting along the 24.7–25.1 isopycnals, creating the
DCM along the inner part of the meandering jet.
[40] Subsurface data are necessary to fully describe the
bio-physical interactions between chlorophyll concentrations and the mesoscale features observed in the SSH. Our
study reveals that the relationships between satellite values
of CHL and SSH can be misleading or difficult to interpret,
without the addition of subsurface distributions of chlorophyll-a and velocities within the water column. Subsurface
data also document the influence of the Subarctic Water
mass at the north of our study area and the Subtropical
Surface Water mass south of Punta Eugenia.
[41] Acknowledgments. The first author had a fellowship from
CONACYT and support through several other projects: Fase 1-Oceanografía por Satelite (DAJ J002/750/00), G35326T; CICESE Biological Oceanography Department; IAI-CRN 062; IOCCG; COAS-OSU (JPL-1206714,
OCE-0000900), CECYT, IPN-SIP 20060413, and a fellowship from
COFAA and EDI. SeaWiFS pigment data were processed and made
available by Andrew Thomas at the University of Maine. First author,
E.B. and J.A.K. are part of CONACYT/CB project (SEP-2008-103898),
Investigaciones Oceanográficas del Sistema Frontal de Baja California
(PI, E. Beier). P.T.S. was supported by NASA grant NNX08AR40G,
NOAA grant NA08NES440003 and NSF grant OCE-0815007. This is also
a contribution of the IMECOCAL-CICESE research program to the scientific agenda of the Eastern Pacific Consortium of the InterAmerican Institute for Global Change Research (IAI-EPCOR). In situ data were
obtained from the CalCOFI and IMECOCAL oceanographic programs.
The altimeter product were produced by Ssalto/DUACS and distributed
by AVISO, with support from CNES.
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