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Seasonal and spatial variability of remotely sensed chlorophyll and physical fields in the SAZ-Sense region
Deep-Sea Research II 58 (2011) 2082–2093
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Deep-Sea Research II journal homepage: www.elsevier.com/locate/dsr2
Seasonal and spatial variability of remotely sensed chlorophyll and physical fields in the SAZ-Sense region Mathieu Mongin a,b,, Richard Matear b,c, Matthew Chamberlain b,c a
Antarctic Climate and Ecosystems CRC, Hobart 7001, Australia CSIRO Marine and Atmospheric Research, Hobart 7001, Australia c Centre for Australian Weather and Climate Research (CAWCR), A partnership between CSIRO and the Bureau of Meteorology, Australia b
a r t i c l e i n f o
a b s t r a c t
Available online 12 June 2011
The Sub Antarctic Zone Sensitivity to environmental change (SAZ-Sense) project focused on the northern boundary of the Southern Ocean south of Tasmania where there is a persistent and large summer zonal gradient in remote sensed ocean color surface chlorophyll (Chl). This paper presents the seasonality and spatial variability of surface Chl, nutrients, temperature, light availability in the region. First, we verify that remotely sensed ocean color zonal gradient reflects a real gradient in Chl. From seasonal and spatial patterns in the region, we conclude that neither temperature, macronutrients nor light availability can account for the observed large zonal gradient in the surface Chl. Other factors such as iron or ecosystem structure must explain the gradient. We also explore variability in the remote sensed observations during the cruise. At the SAZ east station, there is high mesoscale variability with corresponding high variability in Chl concentrations, with the spatial variability around the station exceeding the expected difference between the SAZ east and SAZ west processes stations. The interpretation of the collected cruise station data, particularly at the SAZ east site needs to consider mesoscale variability. Comparison of Seawifs images with cruise data shows good agreement, particularly for low Chl values (less than 1.5 mg m 3). & 2011 Elsevier Ltd. All rights reserved.
Keywords: Sub-Antarctic Zone High nutrient low chlorophyll Chlorophyll-a Sea surface temperature Mesoscale variability
1. Introduction The SAZ-Sense project, Sub-Antarctic Zone Sensitivity to environmental change, focused on the Sub-Antarctic Zone south of Tasmania located in the Australian sector of the Southern Ocean (Fig. 1), which we refers to as the (SAZ) region. Globally, the SAZ is an important zone for carbon exchange and anthropogenic carbon uptake (Roy et al., 2003; Borges et al., 2007), and McNeil et al. (2001) estimated that the entire Southern Ocean SAZ accounts for 10% of the global anthropogenic CO2 uptake. The SAZ is the zone in the Southern Ocean where mode and intermediate water forms (Herraiz-Borreguero and Rintoul, 2011). It is also the zone that displays high biological production and high export production (Lourey and Trull, 2001), which has an important influence on the global nutrient distributions (Sarmiento et al., 2004). Previous biogeochemical studies in this sector of the Southern Ocean have investigated the differences between the Sub Antarctic Zone (SAZ) and the Polar Front Zone (PFZ) (Smith et al., 2000; Trull et al., 2001; Wang et al., 2001), with emphasis on mixed layer depth, iron and silicic acid limitation, and carbon export. For SAZ-Sense, we
Corresponding author at: CSIRO Marine and Atmospheric Research, Hobart, 7001, Australia. E-mail address: [email protected] (M. Mongin).
0967-0645/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.dsr2.2011.06.002
directed our attention at investigating the spatial and temporal variabilities in the biogeochemical fields within the Tasman Sea SAZ region. Within the Tasman Sea SAZ, there are large, and persistent zonal and meridional gradients in the remotely sensed ocean color Chl. The SAZ-Sense cruise occurred during January and February 2007 on the RSV Aurora Australis. This multidisciplinary cruise examined the microbial ecosystem structure and biogeochemical processes in SAZ and PFZ, with the emphasis on explaining the spatial pattern observed in the remotely sensed ocean color Chl observations (Fig. 1). During the cruise, three process (P) stations were each occupied for 6–7 days (P1 45.51S 140.51E ; P2 541S 146.51E ; P3 46.51S 1521E ). The strategy was to compare the typically low summer phytoplankton concentrations in the SAZ west station (P1) with the typically higher summer phytoplankton concentrations in the SAZ east station (P3), with further comparisons were made between the PFZ station (P2) and the two SAZ stations. Since the cruise captures only a short period of the biogeochemical seasonal cycle, to fully understand the ecosystem structure and biogeochemical processes we do need to consider the full seasonality of the main biogeochemical fields. In fact, part of the observed spatial variability can usually be explained by differences in the seasonality in the study region. While a plausible explanation for the observed Chl gradient is iron limitation, we feel that other possible hypotheses need to be
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Fig. 1. (A) SeaWiFS chlorophyll summer mean (October 2006–March 2007), and Fronts (as defined by Sokolov and Rintoul, 2007). The white line represents the Subtropical Front, the yellow line the Subantarctic Front and the red line the Polar Front, from climatological records. (B) MODIS 8 day Summer mean (2006–2007) sea surface temperature, the white line shows the 10 c and 15 c isotherm. (C) Ocean atlas (CARS) annual NO3, the white line shows the 1 mmol m 3 contour. (D) Ocean atlas (CARS) annual SiðOHÞ4 the white line shows the 1 mmol m 3 contour. The red dots on the four panels show the SAZ-Sense Cruise sampling locations. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
examined as well. Those includes differences in nutrient supplies and light availability which could be related to vertical and horizontal mixing and, therefore, to mesoscale activity and eddy transport. We also need to explore the inter-annual variability to address whether the cruise dataset is representative of the long-term mean situation. To present the background information, our paper has the following structure. The next section briefly describes the observations we use to characterize the SAZ-Sense region. In the first part of the results section, we present the climatological fields of surface Chl, sea surface temperature (SST), macro-nutrients (nitrate and silicic acid), mixed layer depth (MLD) and eddy kinetic energy (EKE). We use these fields in the discussion to explore the relationship between the Chl and the environmental fields important to phytoplankton growth. In particular, we will try to answer whether the observed environmental variability in the SAZ region can explain the observed west to east increase in sea surface Chl in this region. In the second part of the results, we present the spatial and temporal variability during the SAZ Sense cruise to provide a larger spatial and temporal context from which to interpret the cruise data.
Meteorology [www.godae.bom.gov.au]. The SST data consists of 8-day composites with a 1/41 spatial resolution. The sea surface height anomaly used is the merged TOPEX/ Poseidon Jason 1, ENVISAT, and GFO dataset provided by the Archiving Validation and Interpretation of Satellite Data in Oceanography (AVISO) project (http://www.aviso.oceanobs.com/duacs). The surface height is computed from the sea surface height anomalies combined with the mean dynamic height (1993–1999) relative to 2000 dbar estimated from in-situ observations (derived from the Rio05 product which was produced by CLS Space Oceanography Division and distributed by Aviso (http://www.aviso.oceanobs.com/)). The surface height fields were re-gridded onto a 1/31 Mercator grid. The absolute surface geostrophic velocity field was then estimated from the sea surface height fields. From the surface geostrophic velocities, we computed the eddy kinetic energy (EKE) using the following equation (as in Waugh et al., 2006). EKE ¼ 12½½uu2 þ½vv2
ð1Þ
where u and v represent the zonal and meridional velocities, respectively, and u and v denotes the mean zonal and meridional velocities from the dataset (climatology for years 2001–2008).
2. Materials and methods 2.2. Regional ocean properties 2.1. Remotely sensed observations We use the Level-3 Standard Mapped HDF Chl data provided by the SeaWiFS Project, NASA/Goddard Space Flight Center and GeoEye. The SeaWiFS Chl dataset consists of 8-day composites with a 9 km spatial resolution. The time series of Chl at the three process stations were computed by averaging a 11 by 11 region around the average location of the process stations (Bowie et al., 2011). The SST used in the study comes from the global high-resolution sea surface temperature (GHRSST) dataset for the Australian region provided by the Australian Bureau of
The seasonal water properties were based on the CSIRO Atlas of Regional Seas (CARS, Dunn and Ridgway, 2002). CARS contains seasonal mixed layer depths, temperature, salinity, oxygen, nitrate, silicate and phosphate at 1/21 spatial resolution for the Australian region. The CARS mixed layer depth is computed using a density change from the ocean surface of 0.05 (sigma units) following Rintoul and Trull (2001). Seasonal mixed layer depths at the three process sites were also estimated using Argo floats (Salle et al., 2009) and ship-based salinity and temperature profiles from the SAZ-Sense cruise in the same an
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manner as CARS. With the ARGO data, only profiles obtained within a 11 by 11 region around the process stations were used. Based on this criteria, we had 19 profiles for P1, 7 for P2 and 36 for P3. Finally, simulated temperature and salinity profiles from an eddy-resolving ocean forecasting and assimilation model (OFAM), (Mongin et al., 2011; Oke et al., 2005; Dietze et al., 2009), were used to compute the daily mixed layer depth (using the same criteria as used in CARS). For details on the ocean model simulation please refer to the Mongin et al. (2011) manuscript.
3. Results 3.1. Climatological/seasonal record 3.1.1. Water masses The SAZ-Sense project took place in a region including the southern part of the oligotrophic subtropical Pacific Ocean, the northern extreme of the PFZ (Fig. 1A) and the Subantarctic Zone itself. Separating these three zones are the Sub-Tropical Front (STF) and the Sub-Antarctic Front (SAF). Although the location of the STF is difficult to characterize with remotely sensed observations because the front has a small impact on sea surface elevation, (Sokolov and
Rintoul, 2007), it is generally found just south of Tasmania and New Zealand. North of the STF, the main process driving the phytoplankton seasonal concentration is the supply of nutrients to the euphotic zone via vertical mixing, either through seasonal mixed layer deepening or enhanced vertical mixing due to eddy activity (Tilburg et al., 2002). Along the STF, the bloom dynamics are complex because of the strong north–south gradient in macro-nutrient concentrations and the highly variable physical environment. The highly variable physical environment involves the interaction of subtropical and Sub-Antarctic water masses in an eddy rich region (HerraizBorreguero and Rintoul, 2011), which is further complicated east of Tasmania by the extension of the East Australia Current and the eddies associated with this current (Ridgway, 2007a). 3.1.2. Chlorophyll-a In this section, we briefly describe the summer time Chl distribution in the SAZ-Sense region and the seasonal evolution of Chl in the region and at the three process stations. The Chl summer climatology (October 2006–March 2007) in the SAZ-Sense region is shown in Fig. 1A. Aside from the elevated Chl observed along the coast, the highest Chl occurs between Tasmania and New Zealand along latitude 46.51S. This bloom that
Fig. 2. (A) Seasonal evolution of Chl a at the SAZ-Sense cruise process stations P1 (46.5S, 140.5E); P2 (54S, 145E); and P3 (45.5S, 152.5E) using the 8 day SeaWiFs climatology. (B) Seasonal evolution oft the GHRSST sea surface temperature (SST) at the three process stations. (C) Seasonal evolution of nitrate from the CARS Ocean Atlas with nitrate (dots) measured during SAZ-Sense voyage shown as dots. (D) Seasonal evolution of SiðOHÞ4 from the CARS Ocean Atlas with SiðOHÞ4 measured during SAZ-Sense voyage shown as dots.
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develops in the Tasman Sea SAZ is one of the largest noncoastal phytoplankton blooms observed from space (Tilburg et al., 2002). In the SAZ, the high summer Chl concentrations appear bounded by the 10 1C isotherm in the south and the 15 1C isotherm in the north (Fig. 1B). Similar to the Kerguelen island plume bloom (Moore and Abbott, 2000; Mongin et al., 2009), the SAZ bloom displays a zonal gradient in Chl. However, unlike the Kerguelen bloom, the Chl concentrations increases as one moves eastward from Tasmania. The seasonal climatology of the bloom in the SAZ-Sense region can be described as follows: (1) A late winter (August–September) bloom occurs in the oligotrophic waters north of the STF associated with the seasonal mixed layer deepening. While this bloom seems to propagate southward, this is not due to advection rather it reflects the timing of deep winter mixing, which occurs later in the winter as one goes south. (2) Following the winter bloom, high Chl concentrations are found in cyclonic eddies that spin-off the EAC and propagate southward along the southeast Australian and Tasmanian coasts and then head to the west as they go south of Tasmania (Sokolov and Rintoul, 2000; Ridgway and Dunn, 2003). These eddy-related high Chl features continue until late October. (3) Starting in late October Chl levels start to rise in the SAZ. West of Tasmania, the SAZ Chl concentrations peak in the months
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of December and January. East of Tasmania, the SAZ Chl concentrations peak in the months of February and March, with maximum summer surface Chl concentrations that are double the values observed in the SAZ west of Tasmania. In the SAZ-East SAZ, the summer phytoplankton peak occurs first near Tasmania in early December and progressively occurs later in the season as one move moves eastward toward New Zealand. Off New Zealand, the timing of the SAZ bloom is coincident with the coastal bloom that occurs on the south west coast of New Zealand. The seasonal climatology of the Chl at the three process stations is shown in Fig. 2A. At all three process stations, the pattern of minimum Chl is similar but timing, duration and magnitude of the Chl bloom varies. At P3, the timing of the Chl peak occurs later in the summer with the highest peak concentration and the longest duration of elevated concentrations. P2 has the earliest peak in Chl concentrations (late December), while P1 peaks in mid-January and P3 peaks in mid February. Although the summer peak in Chl is later in the season at P3 than P1, P3 always maintains higher Chl concentrations throughout the summer period than P1.
3.1.3. Macro-nutrient fields Within the SAZ-Sense region, both nitrate (Fig. 1C) and silicate mean distribution (Fig. 1D) display a strong north–south gradient,
Fig. 3. Seasonal mixed layer depth for P1, P2 and P3 from: (A) ARGO. (B) OFAM. (C) CARS. In all panels, P1 is a solid line, P2 is a dotted line and P3 is a dashed line.
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with generally macro-nutrient limited conditions north of the STF and macro-nutrient replete conditions south of the STF. The lower panels of Fig. 2 display the seasonal cycle of both nitrate and silicate from CARS. At all three stations, we find nitrate replete conditions year around. When compared to measurements made during the cruise there is a better agreement with nitrate than for silicate (CARS tends to over-estimate the silicate concentrations at all three process stations). At P1 and P3, the nutrient concentrations are similar at the end of the winter suggesting similar winter maximum MLD setting the initial nutrient concentration at the start of the growing season. It seems that there is always more nitrate throughout the year at P1 than P3, but the seasonal evolution is somewhat different with a more pronounced cycle at P3 that P1. The minimum nitrate concentration at P3 is less than P1, consistent with the differences in Chl concentrations, but the difference in the nutrient draw-down is less than the factor two difference observed in the Chl. 3.1.4. Sea surface temperature The seasonality of the SST displays some similarity to Chl. Station P3 is the warmest, with summer SSTs that are 2 1C greater than what is observed at station P1 (Fig. 2B). The polar front station (P2) is the coolest, with SSTS between 4 and 6 1C cooler than P3 (Fig. 2B). At both P1 and P2, the maximum SST occurs in mid-February, while at P3 it is about a month later. The higher temperature at station P3
reflects a greater input of sub-tropical waters into this station than at station P1. The input of sub-tropical waters is visible in the SST field (Fig. 1B) but tends to be confined near the coast of Tasmania. This reflects the movement of eddies that are shed off the EAC, which then propagate down the east coast of Tasmania and move west once they are south of Tasmania (Sokolov and Rintoul, 2000; Ridgway and Dunn, 2003). With the exception of the eddies just discussed, most of the influence of the EAC occurs about 101 north of the STF where the EAC separates from the continental shelf and flows eastward, hence it has no direct influence on the high Chl in the SAZ. Within the Tasman Sea SAZ, the summer SST spatial pattern is different to that of Chl with no zonal gradient. 3.1.5. Light availability vertical mixing The light availability is a function of the incident light (itself dependent on the latitude and cloud cover), and the mixed layer depth. The summer averaged incident solar radiation into the surface ocean did not reveal a zonal pattern that increases across the SAZ (data not shown). The mixed layer depth (MLD) seasonality is a difficult field to estimate, because of the lack of winter ship-based observations, especially in the Southern Ocean and the high spatial heterogeneity due to mesoscale variability. To determine the MLD at the process stations, we use three different estimates. MLD estimated from (1) the ARGO temperature and salinity profiles, (Fig. 3A),
Fig. 4. Simulated MLD from OFAM. (A) in the winter (September 93) and (B) during the time period of the cruise (January 94).
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Fig. 5. (A) Map of sea surface anomalies (21–28 February 2008) around the SAZ-Sense cruise region.
(2) simulated temperature and salinity profiles of OFAM (Fig. 3B) (3) CARS temperature and salinity profiles (Fig. 3C). Despite the inconsistencies between these three measurements of MLD, there are several important features to emerge from the MLD estimates. First, if we omit the CARS dataset at P3, the winter MLD at P2 in the polar front zone is much less than P1 and P3. This agrees with previous analysis which showed the SAZ winter mixed layer depths to be much deeper than the PFZ (Rintoul and Trull, 2001). The simulated MLD from OFAM (Oke et al., 2005) produces deep winter mixed layers at both SAZ process stations (500 m) and moderate winter mixed layer depths (200 m) at the PFZ station, consistent with the winter observations of Rintoul and Trull (2001). Second, at P2 all three estimates show a steady deepening of the MLD from January onward, with maximum MLD of between 150 and 250 m occurring by the end of winter and this is followed by a relatively fast re-stratification from September to December to a MLD of 50 m. Third, the MLD estimates at the two SAZ stations show the greatest differences in the winter period. The ARGO data gave a greater winter mixing at P1 (as deep as 500 m) than at P3 (only 250 m), which was opposite to the CARS and OFAM estimates. The deep MLD in the ARGO dataset for P1 is linked to an anticyclonic eddy which provides a over-estimate of the MLD. We know the CARS and OFAM MLD represent averages over a 11 by 11 square, while the limited ARGO profiles are biased by mesoscale features like fronts and eddies (Salle et al., 2009). Hence we feel the ARGO MLD were not representative of the 11 by 11 area that we use for delimiting the process stations, and the CARS and OFAM MLD provide a better estimate of the climatological evolution of the MLD at the process stations. Based on this, the maximum MLD is similar at P1 and P3 which is consistent with a similar winter nitrate concentration at the two sites. Fourth, mesoscale eddies can influence the seasonal cycle of mixing, but they will only be important over short time and space scales, which would be insufficient to explain the persistent summer zonal Chl gradient in the SAZ. The OFAM simulation can provide some insight into the mesoscale variability in the SAZ-Sense region in both the summer and winter (Fig. 4). Both the summer and winter mixed layer depths display high variability associated with mesoscale features. In the Tasman Sea SAZ, mesoscale variability causes the September MLD to vary between 200 and 400 m, and the January MLD to vary between 30 and 60 m.
Fig. 6. Comparison between SeaWiFS Chl-a 8 days composite extracted at the SAZ Sense station (at the time and location of the sampling) and in-situ measured (HPLC) Chl. (A) SeaWiFS Chl versus HPLC Chl (B) SeaWiFS Chl and HPLC Chl for the different region of the cruise.
Fifth, the summer MLD at P1 and P3 is similar for the three estimates with a depth of approximately 50 m. In comparison during the SAZ-Sense cruise, the CTD estimate of the MLD at the process stations were 50 m at P1 and P2 and 30 m at P3.
3.1.6. Horizontal mixing As noted by McNeil et al. (2007) lateral mixing can have a strong influence on the pCO2 cycle within the SAZ. P2 located near the main branches of the Antarctic Circumpolar Current (ACC) shows the greatest variability in sea surface anomaly (SSA) of the three process stations (Fig. 5), P3 also has relatively high SSA due to mesoscale eddies that spin-off the EAC. In comparison, P1 EKE is almost 10 times less than either P2 or P3. Although there is a large EKE difference between stations P3 and P1 this difference is not sustained across the entire Tasman Sea SAZ region. The greater eddy activity at P3 than P1 would not influence the light availability, but could play a role in the exchange of iron-rich macronutrient-poor sub-tropical water with macronutrient-rich but iron-poor SAZ water, which is the hypothesis used by Bowie et al. (2009) to build an iron budget. Mesoscale eddies are known to influence the rate of mixing in the ocean which affects
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Fig. 7. SeaWiFS Chl 8 days composite overlay with sea surface height anomaly (SSHA) (black contour are positive, magenta are negative) around P1. (A) Prior to the cruise. (B) During P1 sampling. (C) During P2 sampling. (D) During P3 sampling, dashed line represent the 1 to 1 ratio. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
horizontal mixing, vertical nutrient supply and light availability (review in Martin, 2003). The increased eddy activity could be associated with increased vertical mixing but the lack of a vertical gradient to the iron profiles measured during SAZ-Sense (Lannuzel et al., 2011; Bowie et al., 2009) do not support the idea of an increased vertical iron supply rate. The iron supply to the Tasman Sea SAZ region will be explored in more detail in Mongin et al. (2011).
3.2. Conditions during the SAZ-Sense cruise 3.2.1. Fronts location During the cruise, the STF was crossed between CTD station 1 and 2 on the leg from Hobart to station P1 (in the SAZ east of Tasmania) at 1441E 441S. The location of the STF was marked by a strong surface Chl gradient, which appeared to be a permanent summer feature and was a good indicator of the location of the STF. On the return leg to Hobart from P3, the STF was crossed just after leaving the P3 sampling site, at 451S 152.51E. Again it was associated with a large gradient in Chl. Generally, the STF is a difficult feature to locate due to the presence of Tasmania, the relative weakness of the temperature and salinity gradients, and
the occurrence of large eddies, but by looking at the summer Chl concentrations we can estimate that it is located at about 42.51S. To locate the mean climatological position of the SAF we use sea surface height (Sokolov and Rintoul, 2007). Most of the CTD casts are located north of the SAF (represented by the yellow contours on Fig. 1A), except for the CTDs around P2, and the first three casts of the P2 to P3 leg. However, during the cruise, from the sea surface height criteria (Sokolov and Rintoul, 2007), P2 is located just north of the SAF (red lines), which differs from the temperature and salinity criteria (Bowie et al., 2011), which locates P2 south of SAZ and inside the PFZ. The different locations of the SAF is not that surprising since the sea surface height estimate is based on a 10-day composite that misses short-term meanders in the front, which are observed in a CTD casts. This further demonstrates that the position of SAF was highly variable, which may explain some of the spatial variability in the observed Chl and nutrient fields in the vicinity of P2.
3.2.2. Ocean color During the cruise, (Wright, 2009, personal communications) measured chlorophyll-a pigment using high performance liquid chromatography (HPLC). We compared this dataset with SeaWiFs chlorophyll-a (by extracting the pixel corresponding to the cruise
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Fig. 8. SeaWiFS Chl 8 days composite overlay with sea surface height anomaly (SSHA) (black contour are positive, magenta are negative) around P2. (A) Prior to the cruise. (B) During P1 sampling. (C) During P2 sampling. (D) During P3 sampling. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
station). We used 8 days composite images because cloud cover a comparison using daily images. The aims of this section is not to do a complete evaluation of the SeaWiFS bio-optical algorithms but more to explore the variability of the signal in both datasets and compare with other studies. There are many uncertainties underlying this comparison: some in-situ samples were not strictly taken at the surface (but down to 5 m due to wave motion, S. Wright personal communication), the in-situ and satellite measurements are not strictly concurrent in time and space due to high cloud coverage, and the resolution may not resolve the high spatial variability around the sites (particularly P3). Despite those uncertainties, the agreement is quite remarkable especially around station P1, while the in-situ measurements at P3 are 50% higher (Fig. 6). Previous studies found out that SeaWiFS usually underestimate chlorophyll-a (Moore et al., 1999), our results suggest that is not the case for the region of low concentrations (i.e. P1 and P2), which is in line with the (Marrari et al., 2006) study that found that ocean color image agree with those determined from water samples for chlorophyll-a value ranging from 0.05 and 1.5 mg.
However, at P3 (high chlorophyll) the SeaWiFS estimate generally is too low. 3.3. Mesoscale features during the cruise Sea surface height anomalies (SSHA) are overlain on the 8-day SeaWiFS Chl image to link the Chl variability to mesoscale eddies (Fig. 7). Around P1, the Chl concentrations show an increased trend from south to north (Fig. 7). P1 is not located in an obvious mesoscale feature. Over the four images, the eddy field appears nearly stationary. In the vicinity of P1, the largest eddy in the images was a quasistationary cyclonic eddy south east of P1 that was slowly moving west with a low Chl concentration in its center. Over the four images the Chl concentrations in the vicinity of P1 show a slight decline (Fig. 7). The images show no clear relationship between SSHA and Chl, with more spatial variability in Chl than in the SSHA. Around P2 (Fig. 8), the link between SSHA and Chl is clear, with anticyclonic eddies (positive SSHA) being associated with high Chl. In the first two images, the two anticyclonic eddies north of
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Fig. 9. SeaWiFS Chl 8 days composite overlay with sea surface height anomaly (SSHA) (black contour are positive, magenta are negative) around P3. (A) Prior to the cruise. (B) during P1 sampling. (C) during P2 sampling. (D) during P3 sampling. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
P2 contain high Chl concentrations and as these eddies move westward the eddies are stretched and the region of high Chl also stretches. Originally P2 is located in a weak anticyclonic eddy, which slowly weakens with time and by the end of the sequence of images a cyclonic eddy has propagated into the region just to the northeast of the station. Although the images are cloudy there is no substantial change in Chl concentrations at P2 with the change in the mesoscale features around the station and the Chl concentration remains low ranging between 0.1 and 0:25 mg m3 Chla. Around P3, the Chl concentrations show a gradual increase with time without a clear link between SSHA and Chl (Fig. 9). At the location of P3 there is large variability in both the Chl concentrations and the SSHA. Sampling at this process station was made in both a weak cyclonic and anticyclonic eddy, and in the region between these two eddies. The sampling taken between the two eddies show low concentrations in the first three images and only the last image shows elevated concentra1 tions of greater than 1 mgl Chla. Sampling located in both the anticyclonic and cyclonic eddies to the northwest and southeast of this trough of low Chl show much higher concentrations of Chl. By the time of the P3 occupation (2–11 February 2007 image, Fig. 9) the casts, in the two eddy features, show Chl concentra1 tions greater than 1 mgl Chla.
4. Discussion 4.1. Link between environmental fields and the zonal variability of Chl The Tasman Sea SAZ region displays a prominent summer zonal increase in Chl going from south of Tasmania to south of New Zealand. The remotely sensed zonal gradient is a real feature and is supported by in-situ HPLC chlorophyll data. The increasing west to east gradient in the SAZ is associated with a greater and prolonged summer Chl bloom. The zonal increase in the SAZ is as great as the difference in Chl concentrations between the SAZ and PFZ. This large zonal gradient in the summer Chl in the Tasman Sea SAZ was a key feature that motivated SAZ-Sense. We presented the environmental variability in the SAZ-Sense region and are now exploring how these fields could relate to the zonal pattern of Chl. Our goal is to assess whether the environmental fields can explain the observed spatial structure of the climatological Chl signal. Here, we focus on environmental fields that control phytoplankton concentrations while Kidson et al. (2011) use data assimilation and ecosystem simulations to explore whether ecosystem differences in structure and dynamics can reproduce the increased Chl in the west. The potential processes controlling the chla bloom dynamics include temperature, light levels, iron
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Fig. 10. SeaWiFS Chl climatology (thick solid line) and SeaWifs Chl for the 2006–2007 period (solid line with dots) at (A) P1. (B) P2. (C) P3. The gray vertical line denotes the date the station was sampled.
concentrations, phytoplankton composition and biomass loss terms including zooplankton grazing and mortality. The analysis of the remotely sensed and in-situ observations shows the entire SAZ region is nitrate replete with minor zonal differences in light availability and temperature. In the Tasman Sea SAZ, one finds nitrate and phosphate (data not shown) replete 1 1 conditions ð \ 2 mmol l \ 0:12 mmol l respectively). Both the winter MLD and the dissolved iron concentrations (Bowie et al., 2009) at the base of the winter mixed layer were similar at the SAZ process stations, P1 and P3. Similarly winter level of iron both in surface and subsurface did not display high values (Sedwick et al., 2008). The SAZ west region does present signs of colimitation with silicic acid in the late summer (Sedwick et al., 2008), but this will only affect diatoms at the end of the growing season. The main information that we can extract from the MLD estimates is that the maximum of the mixed layer is similar at P1 and P3, with similar behavior for the re-stratification period, which is consistent with the nutrient field observations. Hence the effect of the mixed layer depth, by either supplying nutrients or limiting light availability (through the Sverdrup critical depth) cannot explain the difference in Chl concentrations between P1 and P3. Using the Eppley (1972) temperature dependent phytoplankton growth, a 2 1C difference between P1 and P3 would only increase phytoplankton growth by 10%. Phytoplankton growth, remineralization processes and grazing all are affected by changes
in temperature, but in our case the 2 1C increase is not sufficient to modify significantly those physiological processes, and hence the phytoplankton biomass. Other hypothesis include a change in the phytoplankton carbon to chlorophyll ratio, which could be reflected in different chlorophyll signal underlying similar phytoplankton biomass. But the carbon to chlorophyll is mostly driven by nutrient and light levels. Furthermore, iron limitation leads to reduced ability to use light which means an increase chlorophyll per amount carbon in the phytoplankton (Sunda and Huntsman, 1997). This would mean a lower chlorophyll/C in the area where the is more iron as observed at P3 (Mongin et al., 2011; Bowie et al., 2009)
4.2. Spatial and temporal variability around the processes stations While SAZ-Sense sought to explain the recurrence of the zonal Chl gradient in the Tasman Sea SAZ, for the interpretation of the cruise data we need to address the following points: (1) Does the time of the collection of the data at P1 and P3 affect our interpretation of the observations? (2) What is the spatial variability around the three process stations? There is a difference in the timing of the summer bloom at P1 and P3 of several weeks. P1 was sampled at the approximate time of the peak Chl bloom (Fig. 10), while P3 was sampled on a still rising Chl bloom. The peak in the P3 Chl occurs approximately
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two weeks after the P3 sampling, during which time the Chl can increase by about 20%. The 8-day Chl composites provide an indication of the spatial and temporal variability around the process stations during the cruise. Figs. 7–9 show the 8-day composite images around P1, P2 and P3, respectively, for before, and while these three stations were sampled. The Chl images display filament like patterns, that are probably a consequence of both horizontal stirring (of either nutrients or Chl) and alteration of the light mixing regime due to mesoscale activity. The occurrence of small scale structures makes the analysis of the cruise data, which are based on discrete CTD profiles more difficult, as variability between casts could be related to the mesoscale variability rather than differences between process stations. The high Chl mesoscale variability around P3 will make the interpretation of the cruise data challenging.
4.3. Interannual variability In the previous sections, we discussed the seasonal and spatial variability in the SAZ-Sense region and images of the Chl concentrations during the summer of the SAZ-Sense cruise. To gauge the representativeness of the year of the SAZ-Sense cruise, we compare the Chl concentrations of the seasonal climatology with the 2006–2007 season at the three process stations (Fig. 10). During the SAZ Sense cruise of January–February, 2007, the two SAZ process stations, P1 and P3, had anomalous high Chl concentrations with a summer maxima that occur more than a month later than normal. While at P2, Chl concentrations of 2007 reflected the averaged conditions. Although higher than average Chl concentrations were observed during SAZ-Sense at P3 and P1, more of an issue is the large spatial variability around these two process sites which was large and generally exceeded the expected mean difference between P1 and P3. In particular, at P3, the variability was large and the casts obtained during the 1 week occupation sampled a cyclonic and anticyclonic eddy, and the water between these two eddies all of which displayed different Chl concentrations.
5. Conclusions In the SAZ south of Australia, the spatial pattern of SST, macronutrient and light availability does not reflect the pattern of Chl variability. Where the environmental fields exhibited zonal gradients (e.g. SST and EKE), the gradients were weak, and not sustained across the entire Tasman Sea. Therefore, environmental gradients could not explain the two-fold difference in Chla in surface waters across the SAZ in the Tasman Sea. The spatial complexity in the vicinity of P1 and P3 needs to be considered in the interpretation of the cruise data. In particular, the CTD casts at P3 (east) process station exhibit high spatial variability in the Chl concentrations associated with mesoscale features that exceeds the expected differences in Chl between P1 and P3.
Acknowledgments We thank Andrew Bowie, Brian Griffiths and Thomas Trull for insightful discussions, as well as Andrew Lenton and 3 anonymous reviewers for constructive comments. This work was funded by the Australian Commonwealth Cooperative Research Centres Program the CSIRO Wealth from Ocean Flagship and Australian Climate change science programme.
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Contents lists available at ScienceDirect
Deep-Sea Research II journal homepage: www.elsevier.com/locate/dsr2
Seasonal and spatial variability of remotely sensed chlorophyll and physical fields in the SAZ-Sense region Mathieu Mongin a,b,, Richard Matear b,c, Matthew Chamberlain b,c a
Antarctic Climate and Ecosystems CRC, Hobart 7001, Australia CSIRO Marine and Atmospheric Research, Hobart 7001, Australia c Centre for Australian Weather and Climate Research (CAWCR), A partnership between CSIRO and the Bureau of Meteorology, Australia b
a r t i c l e i n f o
a b s t r a c t
Available online 12 June 2011
The Sub Antarctic Zone Sensitivity to environmental change (SAZ-Sense) project focused on the northern boundary of the Southern Ocean south of Tasmania where there is a persistent and large summer zonal gradient in remote sensed ocean color surface chlorophyll (Chl). This paper presents the seasonality and spatial variability of surface Chl, nutrients, temperature, light availability in the region. First, we verify that remotely sensed ocean color zonal gradient reflects a real gradient in Chl. From seasonal and spatial patterns in the region, we conclude that neither temperature, macronutrients nor light availability can account for the observed large zonal gradient in the surface Chl. Other factors such as iron or ecosystem structure must explain the gradient. We also explore variability in the remote sensed observations during the cruise. At the SAZ east station, there is high mesoscale variability with corresponding high variability in Chl concentrations, with the spatial variability around the station exceeding the expected difference between the SAZ east and SAZ west processes stations. The interpretation of the collected cruise station data, particularly at the SAZ east site needs to consider mesoscale variability. Comparison of Seawifs images with cruise data shows good agreement, particularly for low Chl values (less than 1.5 mg m 3). & 2011 Elsevier Ltd. All rights reserved.
Keywords: Sub-Antarctic Zone High nutrient low chlorophyll Chlorophyll-a Sea surface temperature Mesoscale variability
1. Introduction The SAZ-Sense project, Sub-Antarctic Zone Sensitivity to environmental change, focused on the Sub-Antarctic Zone south of Tasmania located in the Australian sector of the Southern Ocean (Fig. 1), which we refers to as the (SAZ) region. Globally, the SAZ is an important zone for carbon exchange and anthropogenic carbon uptake (Roy et al., 2003; Borges et al., 2007), and McNeil et al. (2001) estimated that the entire Southern Ocean SAZ accounts for 10% of the global anthropogenic CO2 uptake. The SAZ is the zone in the Southern Ocean where mode and intermediate water forms (Herraiz-Borreguero and Rintoul, 2011). It is also the zone that displays high biological production and high export production (Lourey and Trull, 2001), which has an important influence on the global nutrient distributions (Sarmiento et al., 2004). Previous biogeochemical studies in this sector of the Southern Ocean have investigated the differences between the Sub Antarctic Zone (SAZ) and the Polar Front Zone (PFZ) (Smith et al., 2000; Trull et al., 2001; Wang et al., 2001), with emphasis on mixed layer depth, iron and silicic acid limitation, and carbon export. For SAZ-Sense, we
Corresponding author at: CSIRO Marine and Atmospheric Research, Hobart, 7001, Australia. E-mail address: [email protected] (M. Mongin).
0967-0645/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.dsr2.2011.06.002
directed our attention at investigating the spatial and temporal variabilities in the biogeochemical fields within the Tasman Sea SAZ region. Within the Tasman Sea SAZ, there are large, and persistent zonal and meridional gradients in the remotely sensed ocean color Chl. The SAZ-Sense cruise occurred during January and February 2007 on the RSV Aurora Australis. This multidisciplinary cruise examined the microbial ecosystem structure and biogeochemical processes in SAZ and PFZ, with the emphasis on explaining the spatial pattern observed in the remotely sensed ocean color Chl observations (Fig. 1). During the cruise, three process (P) stations were each occupied for 6–7 days (P1 45.51S 140.51E ; P2 541S 146.51E ; P3 46.51S 1521E ). The strategy was to compare the typically low summer phytoplankton concentrations in the SAZ west station (P1) with the typically higher summer phytoplankton concentrations in the SAZ east station (P3), with further comparisons were made between the PFZ station (P2) and the two SAZ stations. Since the cruise captures only a short period of the biogeochemical seasonal cycle, to fully understand the ecosystem structure and biogeochemical processes we do need to consider the full seasonality of the main biogeochemical fields. In fact, part of the observed spatial variability can usually be explained by differences in the seasonality in the study region. While a plausible explanation for the observed Chl gradient is iron limitation, we feel that other possible hypotheses need to be
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Fig. 1. (A) SeaWiFS chlorophyll summer mean (October 2006–March 2007), and Fronts (as defined by Sokolov and Rintoul, 2007). The white line represents the Subtropical Front, the yellow line the Subantarctic Front and the red line the Polar Front, from climatological records. (B) MODIS 8 day Summer mean (2006–2007) sea surface temperature, the white line shows the 10 c and 15 c isotherm. (C) Ocean atlas (CARS) annual NO3, the white line shows the 1 mmol m 3 contour. (D) Ocean atlas (CARS) annual SiðOHÞ4 the white line shows the 1 mmol m 3 contour. The red dots on the four panels show the SAZ-Sense Cruise sampling locations. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
examined as well. Those includes differences in nutrient supplies and light availability which could be related to vertical and horizontal mixing and, therefore, to mesoscale activity and eddy transport. We also need to explore the inter-annual variability to address whether the cruise dataset is representative of the long-term mean situation. To present the background information, our paper has the following structure. The next section briefly describes the observations we use to characterize the SAZ-Sense region. In the first part of the results section, we present the climatological fields of surface Chl, sea surface temperature (SST), macro-nutrients (nitrate and silicic acid), mixed layer depth (MLD) and eddy kinetic energy (EKE). We use these fields in the discussion to explore the relationship between the Chl and the environmental fields important to phytoplankton growth. In particular, we will try to answer whether the observed environmental variability in the SAZ region can explain the observed west to east increase in sea surface Chl in this region. In the second part of the results, we present the spatial and temporal variability during the SAZ Sense cruise to provide a larger spatial and temporal context from which to interpret the cruise data.
Meteorology [www.godae.bom.gov.au]. The SST data consists of 8-day composites with a 1/41 spatial resolution. The sea surface height anomaly used is the merged TOPEX/ Poseidon Jason 1, ENVISAT, and GFO dataset provided by the Archiving Validation and Interpretation of Satellite Data in Oceanography (AVISO) project (http://www.aviso.oceanobs.com/duacs). The surface height is computed from the sea surface height anomalies combined with the mean dynamic height (1993–1999) relative to 2000 dbar estimated from in-situ observations (derived from the Rio05 product which was produced by CLS Space Oceanography Division and distributed by Aviso (http://www.aviso.oceanobs.com/)). The surface height fields were re-gridded onto a 1/31 Mercator grid. The absolute surface geostrophic velocity field was then estimated from the sea surface height fields. From the surface geostrophic velocities, we computed the eddy kinetic energy (EKE) using the following equation (as in Waugh et al., 2006). EKE ¼ 12½½uu2 þ½vv2
ð1Þ
where u and v represent the zonal and meridional velocities, respectively, and u and v denotes the mean zonal and meridional velocities from the dataset (climatology for years 2001–2008).
2. Materials and methods 2.2. Regional ocean properties 2.1. Remotely sensed observations We use the Level-3 Standard Mapped HDF Chl data provided by the SeaWiFS Project, NASA/Goddard Space Flight Center and GeoEye. The SeaWiFS Chl dataset consists of 8-day composites with a 9 km spatial resolution. The time series of Chl at the three process stations were computed by averaging a 11 by 11 region around the average location of the process stations (Bowie et al., 2011). The SST used in the study comes from the global high-resolution sea surface temperature (GHRSST) dataset for the Australian region provided by the Australian Bureau of
The seasonal water properties were based on the CSIRO Atlas of Regional Seas (CARS, Dunn and Ridgway, 2002). CARS contains seasonal mixed layer depths, temperature, salinity, oxygen, nitrate, silicate and phosphate at 1/21 spatial resolution for the Australian region. The CARS mixed layer depth is computed using a density change from the ocean surface of 0.05 (sigma units) following Rintoul and Trull (2001). Seasonal mixed layer depths at the three process sites were also estimated using Argo floats (Salle et al., 2009) and ship-based salinity and temperature profiles from the SAZ-Sense cruise in the same an
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manner as CARS. With the ARGO data, only profiles obtained within a 11 by 11 region around the process stations were used. Based on this criteria, we had 19 profiles for P1, 7 for P2 and 36 for P3. Finally, simulated temperature and salinity profiles from an eddy-resolving ocean forecasting and assimilation model (OFAM), (Mongin et al., 2011; Oke et al., 2005; Dietze et al., 2009), were used to compute the daily mixed layer depth (using the same criteria as used in CARS). For details on the ocean model simulation please refer to the Mongin et al. (2011) manuscript.
3. Results 3.1. Climatological/seasonal record 3.1.1. Water masses The SAZ-Sense project took place in a region including the southern part of the oligotrophic subtropical Pacific Ocean, the northern extreme of the PFZ (Fig. 1A) and the Subantarctic Zone itself. Separating these three zones are the Sub-Tropical Front (STF) and the Sub-Antarctic Front (SAF). Although the location of the STF is difficult to characterize with remotely sensed observations because the front has a small impact on sea surface elevation, (Sokolov and
Rintoul, 2007), it is generally found just south of Tasmania and New Zealand. North of the STF, the main process driving the phytoplankton seasonal concentration is the supply of nutrients to the euphotic zone via vertical mixing, either through seasonal mixed layer deepening or enhanced vertical mixing due to eddy activity (Tilburg et al., 2002). Along the STF, the bloom dynamics are complex because of the strong north–south gradient in macro-nutrient concentrations and the highly variable physical environment. The highly variable physical environment involves the interaction of subtropical and Sub-Antarctic water masses in an eddy rich region (HerraizBorreguero and Rintoul, 2011), which is further complicated east of Tasmania by the extension of the East Australia Current and the eddies associated with this current (Ridgway, 2007a). 3.1.2. Chlorophyll-a In this section, we briefly describe the summer time Chl distribution in the SAZ-Sense region and the seasonal evolution of Chl in the region and at the three process stations. The Chl summer climatology (October 2006–March 2007) in the SAZ-Sense region is shown in Fig. 1A. Aside from the elevated Chl observed along the coast, the highest Chl occurs between Tasmania and New Zealand along latitude 46.51S. This bloom that
Fig. 2. (A) Seasonal evolution of Chl a at the SAZ-Sense cruise process stations P1 (46.5S, 140.5E); P2 (54S, 145E); and P3 (45.5S, 152.5E) using the 8 day SeaWiFs climatology. (B) Seasonal evolution oft the GHRSST sea surface temperature (SST) at the three process stations. (C) Seasonal evolution of nitrate from the CARS Ocean Atlas with nitrate (dots) measured during SAZ-Sense voyage shown as dots. (D) Seasonal evolution of SiðOHÞ4 from the CARS Ocean Atlas with SiðOHÞ4 measured during SAZ-Sense voyage shown as dots.
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develops in the Tasman Sea SAZ is one of the largest noncoastal phytoplankton blooms observed from space (Tilburg et al., 2002). In the SAZ, the high summer Chl concentrations appear bounded by the 10 1C isotherm in the south and the 15 1C isotherm in the north (Fig. 1B). Similar to the Kerguelen island plume bloom (Moore and Abbott, 2000; Mongin et al., 2009), the SAZ bloom displays a zonal gradient in Chl. However, unlike the Kerguelen bloom, the Chl concentrations increases as one moves eastward from Tasmania. The seasonal climatology of the bloom in the SAZ-Sense region can be described as follows: (1) A late winter (August–September) bloom occurs in the oligotrophic waters north of the STF associated with the seasonal mixed layer deepening. While this bloom seems to propagate southward, this is not due to advection rather it reflects the timing of deep winter mixing, which occurs later in the winter as one goes south. (2) Following the winter bloom, high Chl concentrations are found in cyclonic eddies that spin-off the EAC and propagate southward along the southeast Australian and Tasmanian coasts and then head to the west as they go south of Tasmania (Sokolov and Rintoul, 2000; Ridgway and Dunn, 2003). These eddy-related high Chl features continue until late October. (3) Starting in late October Chl levels start to rise in the SAZ. West of Tasmania, the SAZ Chl concentrations peak in the months
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of December and January. East of Tasmania, the SAZ Chl concentrations peak in the months of February and March, with maximum summer surface Chl concentrations that are double the values observed in the SAZ west of Tasmania. In the SAZ-East SAZ, the summer phytoplankton peak occurs first near Tasmania in early December and progressively occurs later in the season as one move moves eastward toward New Zealand. Off New Zealand, the timing of the SAZ bloom is coincident with the coastal bloom that occurs on the south west coast of New Zealand. The seasonal climatology of the Chl at the three process stations is shown in Fig. 2A. At all three process stations, the pattern of minimum Chl is similar but timing, duration and magnitude of the Chl bloom varies. At P3, the timing of the Chl peak occurs later in the summer with the highest peak concentration and the longest duration of elevated concentrations. P2 has the earliest peak in Chl concentrations (late December), while P1 peaks in mid-January and P3 peaks in mid February. Although the summer peak in Chl is later in the season at P3 than P1, P3 always maintains higher Chl concentrations throughout the summer period than P1.
3.1.3. Macro-nutrient fields Within the SAZ-Sense region, both nitrate (Fig. 1C) and silicate mean distribution (Fig. 1D) display a strong north–south gradient,
Fig. 3. Seasonal mixed layer depth for P1, P2 and P3 from: (A) ARGO. (B) OFAM. (C) CARS. In all panels, P1 is a solid line, P2 is a dotted line and P3 is a dashed line.
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with generally macro-nutrient limited conditions north of the STF and macro-nutrient replete conditions south of the STF. The lower panels of Fig. 2 display the seasonal cycle of both nitrate and silicate from CARS. At all three stations, we find nitrate replete conditions year around. When compared to measurements made during the cruise there is a better agreement with nitrate than for silicate (CARS tends to over-estimate the silicate concentrations at all three process stations). At P1 and P3, the nutrient concentrations are similar at the end of the winter suggesting similar winter maximum MLD setting the initial nutrient concentration at the start of the growing season. It seems that there is always more nitrate throughout the year at P1 than P3, but the seasonal evolution is somewhat different with a more pronounced cycle at P3 that P1. The minimum nitrate concentration at P3 is less than P1, consistent with the differences in Chl concentrations, but the difference in the nutrient draw-down is less than the factor two difference observed in the Chl. 3.1.4. Sea surface temperature The seasonality of the SST displays some similarity to Chl. Station P3 is the warmest, with summer SSTs that are 2 1C greater than what is observed at station P1 (Fig. 2B). The polar front station (P2) is the coolest, with SSTS between 4 and 6 1C cooler than P3 (Fig. 2B). At both P1 and P2, the maximum SST occurs in mid-February, while at P3 it is about a month later. The higher temperature at station P3
reflects a greater input of sub-tropical waters into this station than at station P1. The input of sub-tropical waters is visible in the SST field (Fig. 1B) but tends to be confined near the coast of Tasmania. This reflects the movement of eddies that are shed off the EAC, which then propagate down the east coast of Tasmania and move west once they are south of Tasmania (Sokolov and Rintoul, 2000; Ridgway and Dunn, 2003). With the exception of the eddies just discussed, most of the influence of the EAC occurs about 101 north of the STF where the EAC separates from the continental shelf and flows eastward, hence it has no direct influence on the high Chl in the SAZ. Within the Tasman Sea SAZ, the summer SST spatial pattern is different to that of Chl with no zonal gradient. 3.1.5. Light availability vertical mixing The light availability is a function of the incident light (itself dependent on the latitude and cloud cover), and the mixed layer depth. The summer averaged incident solar radiation into the surface ocean did not reveal a zonal pattern that increases across the SAZ (data not shown). The mixed layer depth (MLD) seasonality is a difficult field to estimate, because of the lack of winter ship-based observations, especially in the Southern Ocean and the high spatial heterogeneity due to mesoscale variability. To determine the MLD at the process stations, we use three different estimates. MLD estimated from (1) the ARGO temperature and salinity profiles, (Fig. 3A),
Fig. 4. Simulated MLD from OFAM. (A) in the winter (September 93) and (B) during the time period of the cruise (January 94).
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Fig. 5. (A) Map of sea surface anomalies (21–28 February 2008) around the SAZ-Sense cruise region.
(2) simulated temperature and salinity profiles of OFAM (Fig. 3B) (3) CARS temperature and salinity profiles (Fig. 3C). Despite the inconsistencies between these three measurements of MLD, there are several important features to emerge from the MLD estimates. First, if we omit the CARS dataset at P3, the winter MLD at P2 in the polar front zone is much less than P1 and P3. This agrees with previous analysis which showed the SAZ winter mixed layer depths to be much deeper than the PFZ (Rintoul and Trull, 2001). The simulated MLD from OFAM (Oke et al., 2005) produces deep winter mixed layers at both SAZ process stations (500 m) and moderate winter mixed layer depths (200 m) at the PFZ station, consistent with the winter observations of Rintoul and Trull (2001). Second, at P2 all three estimates show a steady deepening of the MLD from January onward, with maximum MLD of between 150 and 250 m occurring by the end of winter and this is followed by a relatively fast re-stratification from September to December to a MLD of 50 m. Third, the MLD estimates at the two SAZ stations show the greatest differences in the winter period. The ARGO data gave a greater winter mixing at P1 (as deep as 500 m) than at P3 (only 250 m), which was opposite to the CARS and OFAM estimates. The deep MLD in the ARGO dataset for P1 is linked to an anticyclonic eddy which provides a over-estimate of the MLD. We know the CARS and OFAM MLD represent averages over a 11 by 11 square, while the limited ARGO profiles are biased by mesoscale features like fronts and eddies (Salle et al., 2009). Hence we feel the ARGO MLD were not representative of the 11 by 11 area that we use for delimiting the process stations, and the CARS and OFAM MLD provide a better estimate of the climatological evolution of the MLD at the process stations. Based on this, the maximum MLD is similar at P1 and P3 which is consistent with a similar winter nitrate concentration at the two sites. Fourth, mesoscale eddies can influence the seasonal cycle of mixing, but they will only be important over short time and space scales, which would be insufficient to explain the persistent summer zonal Chl gradient in the SAZ. The OFAM simulation can provide some insight into the mesoscale variability in the SAZ-Sense region in both the summer and winter (Fig. 4). Both the summer and winter mixed layer depths display high variability associated with mesoscale features. In the Tasman Sea SAZ, mesoscale variability causes the September MLD to vary between 200 and 400 m, and the January MLD to vary between 30 and 60 m.
Fig. 6. Comparison between SeaWiFS Chl-a 8 days composite extracted at the SAZ Sense station (at the time and location of the sampling) and in-situ measured (HPLC) Chl. (A) SeaWiFS Chl versus HPLC Chl (B) SeaWiFS Chl and HPLC Chl for the different region of the cruise.
Fifth, the summer MLD at P1 and P3 is similar for the three estimates with a depth of approximately 50 m. In comparison during the SAZ-Sense cruise, the CTD estimate of the MLD at the process stations were 50 m at P1 and P2 and 30 m at P3.
3.1.6. Horizontal mixing As noted by McNeil et al. (2007) lateral mixing can have a strong influence on the pCO2 cycle within the SAZ. P2 located near the main branches of the Antarctic Circumpolar Current (ACC) shows the greatest variability in sea surface anomaly (SSA) of the three process stations (Fig. 5), P3 also has relatively high SSA due to mesoscale eddies that spin-off the EAC. In comparison, P1 EKE is almost 10 times less than either P2 or P3. Although there is a large EKE difference between stations P3 and P1 this difference is not sustained across the entire Tasman Sea SAZ region. The greater eddy activity at P3 than P1 would not influence the light availability, but could play a role in the exchange of iron-rich macronutrient-poor sub-tropical water with macronutrient-rich but iron-poor SAZ water, which is the hypothesis used by Bowie et al. (2009) to build an iron budget. Mesoscale eddies are known to influence the rate of mixing in the ocean which affects
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Fig. 7. SeaWiFS Chl 8 days composite overlay with sea surface height anomaly (SSHA) (black contour are positive, magenta are negative) around P1. (A) Prior to the cruise. (B) During P1 sampling. (C) During P2 sampling. (D) During P3 sampling, dashed line represent the 1 to 1 ratio. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
horizontal mixing, vertical nutrient supply and light availability (review in Martin, 2003). The increased eddy activity could be associated with increased vertical mixing but the lack of a vertical gradient to the iron profiles measured during SAZ-Sense (Lannuzel et al., 2011; Bowie et al., 2009) do not support the idea of an increased vertical iron supply rate. The iron supply to the Tasman Sea SAZ region will be explored in more detail in Mongin et al. (2011).
3.2. Conditions during the SAZ-Sense cruise 3.2.1. Fronts location During the cruise, the STF was crossed between CTD station 1 and 2 on the leg from Hobart to station P1 (in the SAZ east of Tasmania) at 1441E 441S. The location of the STF was marked by a strong surface Chl gradient, which appeared to be a permanent summer feature and was a good indicator of the location of the STF. On the return leg to Hobart from P3, the STF was crossed just after leaving the P3 sampling site, at 451S 152.51E. Again it was associated with a large gradient in Chl. Generally, the STF is a difficult feature to locate due to the presence of Tasmania, the relative weakness of the temperature and salinity gradients, and
the occurrence of large eddies, but by looking at the summer Chl concentrations we can estimate that it is located at about 42.51S. To locate the mean climatological position of the SAF we use sea surface height (Sokolov and Rintoul, 2007). Most of the CTD casts are located north of the SAF (represented by the yellow contours on Fig. 1A), except for the CTDs around P2, and the first three casts of the P2 to P3 leg. However, during the cruise, from the sea surface height criteria (Sokolov and Rintoul, 2007), P2 is located just north of the SAF (red lines), which differs from the temperature and salinity criteria (Bowie et al., 2011), which locates P2 south of SAZ and inside the PFZ. The different locations of the SAF is not that surprising since the sea surface height estimate is based on a 10-day composite that misses short-term meanders in the front, which are observed in a CTD casts. This further demonstrates that the position of SAF was highly variable, which may explain some of the spatial variability in the observed Chl and nutrient fields in the vicinity of P2.
3.2.2. Ocean color During the cruise, (Wright, 2009, personal communications) measured chlorophyll-a pigment using high performance liquid chromatography (HPLC). We compared this dataset with SeaWiFs chlorophyll-a (by extracting the pixel corresponding to the cruise
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Fig. 8. SeaWiFS Chl 8 days composite overlay with sea surface height anomaly (SSHA) (black contour are positive, magenta are negative) around P2. (A) Prior to the cruise. (B) During P1 sampling. (C) During P2 sampling. (D) During P3 sampling. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
station). We used 8 days composite images because cloud cover a comparison using daily images. The aims of this section is not to do a complete evaluation of the SeaWiFS bio-optical algorithms but more to explore the variability of the signal in both datasets and compare with other studies. There are many uncertainties underlying this comparison: some in-situ samples were not strictly taken at the surface (but down to 5 m due to wave motion, S. Wright personal communication), the in-situ and satellite measurements are not strictly concurrent in time and space due to high cloud coverage, and the resolution may not resolve the high spatial variability around the sites (particularly P3). Despite those uncertainties, the agreement is quite remarkable especially around station P1, while the in-situ measurements at P3 are 50% higher (Fig. 6). Previous studies found out that SeaWiFS usually underestimate chlorophyll-a (Moore et al., 1999), our results suggest that is not the case for the region of low concentrations (i.e. P1 and P2), which is in line with the (Marrari et al., 2006) study that found that ocean color image agree with those determined from water samples for chlorophyll-a value ranging from 0.05 and 1.5 mg.
However, at P3 (high chlorophyll) the SeaWiFS estimate generally is too low. 3.3. Mesoscale features during the cruise Sea surface height anomalies (SSHA) are overlain on the 8-day SeaWiFS Chl image to link the Chl variability to mesoscale eddies (Fig. 7). Around P1, the Chl concentrations show an increased trend from south to north (Fig. 7). P1 is not located in an obvious mesoscale feature. Over the four images, the eddy field appears nearly stationary. In the vicinity of P1, the largest eddy in the images was a quasistationary cyclonic eddy south east of P1 that was slowly moving west with a low Chl concentration in its center. Over the four images the Chl concentrations in the vicinity of P1 show a slight decline (Fig. 7). The images show no clear relationship between SSHA and Chl, with more spatial variability in Chl than in the SSHA. Around P2 (Fig. 8), the link between SSHA and Chl is clear, with anticyclonic eddies (positive SSHA) being associated with high Chl. In the first two images, the two anticyclonic eddies north of
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Fig. 9. SeaWiFS Chl 8 days composite overlay with sea surface height anomaly (SSHA) (black contour are positive, magenta are negative) around P3. (A) Prior to the cruise. (B) during P1 sampling. (C) during P2 sampling. (D) during P3 sampling. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
P2 contain high Chl concentrations and as these eddies move westward the eddies are stretched and the region of high Chl also stretches. Originally P2 is located in a weak anticyclonic eddy, which slowly weakens with time and by the end of the sequence of images a cyclonic eddy has propagated into the region just to the northeast of the station. Although the images are cloudy there is no substantial change in Chl concentrations at P2 with the change in the mesoscale features around the station and the Chl concentration remains low ranging between 0.1 and 0:25 mg m3 Chla. Around P3, the Chl concentrations show a gradual increase with time without a clear link between SSHA and Chl (Fig. 9). At the location of P3 there is large variability in both the Chl concentrations and the SSHA. Sampling at this process station was made in both a weak cyclonic and anticyclonic eddy, and in the region between these two eddies. The sampling taken between the two eddies show low concentrations in the first three images and only the last image shows elevated concentra1 tions of greater than 1 mgl Chla. Sampling located in both the anticyclonic and cyclonic eddies to the northwest and southeast of this trough of low Chl show much higher concentrations of Chl. By the time of the P3 occupation (2–11 February 2007 image, Fig. 9) the casts, in the two eddy features, show Chl concentra1 tions greater than 1 mgl Chla.
4. Discussion 4.1. Link between environmental fields and the zonal variability of Chl The Tasman Sea SAZ region displays a prominent summer zonal increase in Chl going from south of Tasmania to south of New Zealand. The remotely sensed zonal gradient is a real feature and is supported by in-situ HPLC chlorophyll data. The increasing west to east gradient in the SAZ is associated with a greater and prolonged summer Chl bloom. The zonal increase in the SAZ is as great as the difference in Chl concentrations between the SAZ and PFZ. This large zonal gradient in the summer Chl in the Tasman Sea SAZ was a key feature that motivated SAZ-Sense. We presented the environmental variability in the SAZ-Sense region and are now exploring how these fields could relate to the zonal pattern of Chl. Our goal is to assess whether the environmental fields can explain the observed spatial structure of the climatological Chl signal. Here, we focus on environmental fields that control phytoplankton concentrations while Kidson et al. (2011) use data assimilation and ecosystem simulations to explore whether ecosystem differences in structure and dynamics can reproduce the increased Chl in the west. The potential processes controlling the chla bloom dynamics include temperature, light levels, iron
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Fig. 10. SeaWiFS Chl climatology (thick solid line) and SeaWifs Chl for the 2006–2007 period (solid line with dots) at (A) P1. (B) P2. (C) P3. The gray vertical line denotes the date the station was sampled.
concentrations, phytoplankton composition and biomass loss terms including zooplankton grazing and mortality. The analysis of the remotely sensed and in-situ observations shows the entire SAZ region is nitrate replete with minor zonal differences in light availability and temperature. In the Tasman Sea SAZ, one finds nitrate and phosphate (data not shown) replete 1 1 conditions ð \ 2 mmol l \ 0:12 mmol l respectively). Both the winter MLD and the dissolved iron concentrations (Bowie et al., 2009) at the base of the winter mixed layer were similar at the SAZ process stations, P1 and P3. Similarly winter level of iron both in surface and subsurface did not display high values (Sedwick et al., 2008). The SAZ west region does present signs of colimitation with silicic acid in the late summer (Sedwick et al., 2008), but this will only affect diatoms at the end of the growing season. The main information that we can extract from the MLD estimates is that the maximum of the mixed layer is similar at P1 and P3, with similar behavior for the re-stratification period, which is consistent with the nutrient field observations. Hence the effect of the mixed layer depth, by either supplying nutrients or limiting light availability (through the Sverdrup critical depth) cannot explain the difference in Chl concentrations between P1 and P3. Using the Eppley (1972) temperature dependent phytoplankton growth, a 2 1C difference between P1 and P3 would only increase phytoplankton growth by 10%. Phytoplankton growth, remineralization processes and grazing all are affected by changes
in temperature, but in our case the 2 1C increase is not sufficient to modify significantly those physiological processes, and hence the phytoplankton biomass. Other hypothesis include a change in the phytoplankton carbon to chlorophyll ratio, which could be reflected in different chlorophyll signal underlying similar phytoplankton biomass. But the carbon to chlorophyll is mostly driven by nutrient and light levels. Furthermore, iron limitation leads to reduced ability to use light which means an increase chlorophyll per amount carbon in the phytoplankton (Sunda and Huntsman, 1997). This would mean a lower chlorophyll/C in the area where the is more iron as observed at P3 (Mongin et al., 2011; Bowie et al., 2009)
4.2. Spatial and temporal variability around the processes stations While SAZ-Sense sought to explain the recurrence of the zonal Chl gradient in the Tasman Sea SAZ, for the interpretation of the cruise data we need to address the following points: (1) Does the time of the collection of the data at P1 and P3 affect our interpretation of the observations? (2) What is the spatial variability around the three process stations? There is a difference in the timing of the summer bloom at P1 and P3 of several weeks. P1 was sampled at the approximate time of the peak Chl bloom (Fig. 10), while P3 was sampled on a still rising Chl bloom. The peak in the P3 Chl occurs approximately
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two weeks after the P3 sampling, during which time the Chl can increase by about 20%. The 8-day Chl composites provide an indication of the spatial and temporal variability around the process stations during the cruise. Figs. 7–9 show the 8-day composite images around P1, P2 and P3, respectively, for before, and while these three stations were sampled. The Chl images display filament like patterns, that are probably a consequence of both horizontal stirring (of either nutrients or Chl) and alteration of the light mixing regime due to mesoscale activity. The occurrence of small scale structures makes the analysis of the cruise data, which are based on discrete CTD profiles more difficult, as variability between casts could be related to the mesoscale variability rather than differences between process stations. The high Chl mesoscale variability around P3 will make the interpretation of the cruise data challenging.
4.3. Interannual variability In the previous sections, we discussed the seasonal and spatial variability in the SAZ-Sense region and images of the Chl concentrations during the summer of the SAZ-Sense cruise. To gauge the representativeness of the year of the SAZ-Sense cruise, we compare the Chl concentrations of the seasonal climatology with the 2006–2007 season at the three process stations (Fig. 10). During the SAZ Sense cruise of January–February, 2007, the two SAZ process stations, P1 and P3, had anomalous high Chl concentrations with a summer maxima that occur more than a month later than normal. While at P2, Chl concentrations of 2007 reflected the averaged conditions. Although higher than average Chl concentrations were observed during SAZ-Sense at P3 and P1, more of an issue is the large spatial variability around these two process sites which was large and generally exceeded the expected mean difference between P1 and P3. In particular, at P3, the variability was large and the casts obtained during the 1 week occupation sampled a cyclonic and anticyclonic eddy, and the water between these two eddies all of which displayed different Chl concentrations.
5. Conclusions In the SAZ south of Australia, the spatial pattern of SST, macronutrient and light availability does not reflect the pattern of Chl variability. Where the environmental fields exhibited zonal gradients (e.g. SST and EKE), the gradients were weak, and not sustained across the entire Tasman Sea. Therefore, environmental gradients could not explain the two-fold difference in Chla in surface waters across the SAZ in the Tasman Sea. The spatial complexity in the vicinity of P1 and P3 needs to be considered in the interpretation of the cruise data. In particular, the CTD casts at P3 (east) process station exhibit high spatial variability in the Chl concentrations associated with mesoscale features that exceeds the expected differences in Chl between P1 and P3.
Acknowledgments We thank Andrew Bowie, Brian Griffiths and Thomas Trull for insightful discussions, as well as Andrew Lenton and 3 anonymous reviewers for constructive comments. This work was funded by the Australian Commonwealth Cooperative Research Centres Program the CSIRO Wealth from Ocean Flagship and Australian Climate change science programme.
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