Eastward shift and maintenance of Arabian Sea oxygen minimum zone: Understanding the paradox

Deep-Sea Research I 115 (2016) 240–252

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Eastward shift and maintenance of Arabian Sea oxygen minimum zone: Understanding the paradox Shiba Shankar Acharya, Mruganka K. Panigrahi n Department of Geology & Geophysics, Indian Institute of Technology, Kharagpur, WB 721302, India

art ic l e i nf o

a b s t r a c t

Article history: Received 5 November 2015 Received in revised form 13 July 2016 Accepted 13 July 2016 Available online 19 July 2016

The dominance of Oxygen Minimum Zone in the eastern part of the Arabian Sea (ASOMZ) instead of the more bio-productive and likely more oxygen consuming western part is the first part of the paradox. The sources of oxygen to the ASOMZ were evaluated through the distributions of different water masses using the extended optimum multiparameter (eOMP) analysis, whereas the sinks of oxygen were evaluated through the organic matter remineralization, using the apparent oxygen utilization (AOU). The contributions of major source waters to the Arabian Sea viz. Indian Deep water (dIDW), Indian Central water (ICW), Persian Gulf Water (PGW) and Red Sea Water (RSW) have been quantified through the eOMP analysis which shows that the PGW and RSW are significant for the eastward shift of ASOMZ instead of voluminous ICW and dIDW. The distribution of Net Primary Production (NPP) and AOU clearly suggest the transport of organic detritus from the highly productive western Arabian Sea to its eastern counterpart which adds to the eastward shifting of ASOMZ. A revised estimate of the seasonal variation of areal extent and volume occupied by ASOMZ through analysis of latest available data reveals a distinct intensification of ASOMZ by 30% and increase in its volume by 5% during the spring-summer transition. However, during this seasonal transition the productivity in the Arabian Sea shows 100% increase in mean NPP. This disparity between ASOMZ and monsoonal variation of productivity is the other part of the paradox, which has been constrained through apparent oxygen utilization, Net Primary Production along with a variation of core depths of source waters. This study reveals a subtle balance between the circulation of marginal oxygen-rich water masses from the western Arabian Sea and organic matter remineralization in the eastern Arabian Sea in different seasons that explains the maintenance of ASOMZ throughout the year. & 2016 Elsevier Ltd. All rights reserved.

Keywords: Arabian Sea Oxygen minimum zone Seasonal maintenance Apparent oxygen utilization Source water mass

1. Introduction Oxygen minimum zones (OMZ) occur at intermediate depths in the water column of world ocean characterized by low dissolved oxygen concentration (r0.5 ml/l, e.g. Helly and Levin, 2004). This suboxic condition in the water column is due to the high oxygen demand and low oxygen supply to the subsurface water. The major OMZs of the global ocean are developed in the upwelling dominated systems or in the regions where ventilation by subsurface currents are restricted. The major OMZs occur in the eastern northern and the southern Pacific Ocean and the northern Arabian Sea, where oxygen concentration drops to r20 mmol/l ( r0.5 ml/ l) (Helly and Levin, 2004; Fuenzalida et al., 2009; Paulmier and Ruiz-Pino, 2009). The OMZs have significant impact on global ecosystem in two ways: (1) they modulate the carbon and n

Corresponding author. E-mail address: [email protected] (M.K. Panigrahi).

http://dx.doi.org/10.1016/j.dsr.2016.07.004 0967-0637/& 2016 Elsevier Ltd. All rights reserved.

nitrogen cycles in ocean and thus regulate the release of greenhouse gases like CO2 and N2O to the atmosphere (Codispoti et al., 2001; Naqvi et al., 2006; Lam and Kuypers, 2011; Bianchi et al., 2012); (2) they influence the ecosystem structure by providing a respiratory barrier in subsurface water (Levin et al., 2009; Stramma et al., 2012; Resplandy et al., 2012). Based on the time series analysis of dissolved oxygen concentration, Stramma et al. (2008) showed an increase in the volume of OMZs in tropical oceanic regions (except the Indian Ocean) over the last fifty years. This expansion may further get intensified with the increase in the rate of global warming (Keeling et al., 2010) which will have a significant impact on coastal ecosystems. Therefore, in order to understand the nature of changes in the oceanic domain that might occur because of the increasing global warming phenomenon, the extent of the major OMZs and the factors influencing their intensity need to be evaluated. In the present study, we focus on Arabian Sea OMZ (ASOMZ) which is inferred to be the third most voluminous OMZ in the world and covers the fourth largest area in

S.S. Acharya, M.K. Panigrahi / Deep-Sea Research I 115 (2016) 240–252

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Fig. 1. Schematic representation of dominant winds (Brown arrow), oceanic circulation (red arrows), and coastal upwelling systems (light blue shading) during (a) NE Monsoon and (b) SW Monsoon (adopted from Prasad et al. (2001) and Resplandy et al. (2012) and references therein). WICC: western Indian Coastal Current; LH: Lakshadweep High; LL: Lakshadweep Low. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

the global ocean (Fuenzalida et al., 2009; Paulmier and Ruiz-Pino, 2009). The monsoonal wind affects both the oceanic circulation pattern and biological activities across seasons in the Arabian Sea. These large scale seasonal variations (Fig. 1) make Arabian Sea as one of the complex system in the global ocean. Despite this considerable spatio-temporal variability in the ocean dynamics and biological activity, no remarkable seasonal and spatial variations has been reported in the oxygen concentrations within the OMZ in the Arabian Sea (Resplandy et al. (2012) and references therein). This is inferred as a spatial and seasonal maintenance of ASOMZ, which is an intriguing aspect to investigate. 1.1. Background The ASOMZ shows near total depletion of oxygen at intermediate water depths from 200 to 1000 m (Morrison et al., 1999), where the dissolved oxygen concentration drops to o10 mmol/l. The upper water column of Arabian Sea (o1200 m) receives water from three major sources. They include Persian Gulf water (PGW), Red Sea water (RSW) and Indian Central Water (ICW) (Rhein et al., 1997). The PGW enters the Arabian Sea just beneath the thermocline (200–400 m, Prasad et al., 2001) and spreads both southward along the Omani coast and around the perimeter of the basin (Shenoi et al., 1993; Prasad et al., 2001), whereas the RSW enters the Arabian Sea at intermediate water depths (300–1000 m, Beal et al., 2000; Bower et al., 2000) and spreads across the basin (Shankar et al., 2005). The dense, saline PGW and RSW enter the Arabian Sea through narrow, shallow straits: the former through the strait of Hormuz and the latter through the Bab-al-Mandeb (BAM). They flow over very shallow sills - the sill depth is nearly 160 m in BAM strait and
80 m in the Strait of Hormuz (Bower et al., 2000). The estimates of the annual mean volume transport of the PGW and RSW across their respective straits,
0.4 Sv (Sv ¼1  106 m3 s  1) and
0.2–0.5 Sv. These values are small as compared to the other marginal sea outflows like
1 Sv for the Mediterranean (Bower et al., 2000 and references therein). Both these water masses (PGW and RSW) show significant seasonal variability in transport due to the effects of the monsoon wind (Donguy and Meyers, 1996; Beal et al., 2000; Bower et al., 2000; Prasad et al., 2001). The details of the flow regimes of RSW and PGW were furnished by Donguy and Meyers (1996), Bower et al. (2000), Beal et al. (2000) and Prasad et al. (2001). Although the physicochemical properties of these oxygenated water masses

have been studied well, their circulation paths in the Arabian Sea are not yet well understood (McCreary et al., 2013). A proper evaluation of the contributions from these sources is expected to provide better insight to the maintenance of ASOMZ across seasons. An interesting characteristic of ASOMZ is that unlike other OMZs it is located well away from the ‘intense’ upwelling zone (Fig. 1(b), Naqvi, 1991) in the western Arabian Sea and best developed in the least productive region of the eastern/central Arabian Sea (Fig. 2, Naqvi, 1991). Various hypotheses proposed to explain this eastward shift include: (i) northward advection of well oxygenated waters by the swift Somali and Omani coastal currents (Sarma, 2002); (ii) rapid sinking of large species (diatoms) in strong upwelling rich regions of western Arabian Sea (Wiggert and Murtugudde, 2007) and (iii) enhanced advection and vertical eddy mixing in the western Arabian Sea which carries small detritus from western to eastern/central basin to provide an additional sink of oxygen (McCreary et al., 2013). The Arabian Sea is an integral part of the monsoon-dominated system, where the surface productivity and mid-depth water circulation respond to this seasonal phenomenon and control the O2

Fig. 2. A map of ASOMZ as demarcated by the 0.5 mmol/l NO2  contour (Redrawn after Naqvi (1991)) depicting the eastward shift.

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concentration in sub-surface water. Although productivity varies significantly across seasons due to the interference of monsoon, the suboxic condition in the eastern/central Arabian Sea prevails in all seasons with little variation (Sarma (2002) and references therein). Numerous hypotheses proposed to explain such balance include: (i) slow advection of oxygen-poor water (Sverdrup et al., 1942), (ii) higher organic matter decomposition rate during monsoonal blooms (Ryther and Menzel, 1965) and (iii) supply of oxygen deficient waters from the South Indian Ocean (Swallow, 1984). Later, Olson et al. (1993) questioned the assumption of slow advection in the Arabian Sea by citing the shorter residence time of oxygen in OMZ (10 74 yr) using transient anthropogenic trace gas, trichlorofluoromethane. This short residence time of water in the suboxic layer of Arabian Sea was later supported by Sarma (2002), who found this value as 6.5 yr from a Modular Ocean Model. Therefore, the actual nature and extent of seasonal variations of ASOMZ need to be worked out more definitively. The earlier spatial and temporal estimates of ASOMZ (e.g. Helly and Levin, 2004: NOAA National Geophysical Data Center; Paulmier and Ruiz-Pino, 2009: World Ocean Atlas (WOA), 2005; Karstensen et al., 2008: GLODAP) are based primarily on historical database which covers a long temporal range of 109 yr (1900– 2009) and hence include oxygen measurements of various sensitivities. Growing evidence suggest that the historical dataset underestimates the volume of suboxic waters in the major OMZs (e.g. Fuenzalida et al., 2009; Banse et al., 2014). One of the reasons for this deviation is the poor sensitivity of past measurements to measure oxygen at a concentration below 0.5 ml/l (or
20 mmol/l) which is the threshold limit for most OMZs (Helly and Levin, 2004; Bianchi et al., 2012). In the early 1960s, Winkler methods were generally used to evaluate the dissolved oxygen concentrations by the visual endpoint detection that generally had poor detection limit at low dissolved oxygen and generally affected by the interference from other chemical species like NO2  (Revsbech et al., 2009). In the early 1970s, membrane oxygen sensors were employed for use in vertical profiling CTDs, which were also later found to be affected by thermal hysteresis that results in large differences in up-casts and down-casts (Atkinson et al., 1995). Recently much lower O2 values ( o2 nmol/l) have been measured with the STOX (Switchable Trace amount Oxygen) sensor in the Peruvian OMZ (Revsbech et al., 2009). Different analytical instruments of varying sensitivities were employed in the measurement dissolved oxygen within the OMZs Therefore, corrections to these historical dissolved O2 data is necessary to reduce this deviation from the real value. Another reason for the disparity in the volumetric estimations of OMZs is the availability of data in a few standard depth levels. The gridded WOA datasets used in the earlier estimations (e.g. Paulmier and Ruiz-Pino, 2009; WOA 2005) up to WOA 2009 covered only 33 standard depth levels. This lack of sufficient data at subsurface depths is possibly the reason for the underestimation of OMZ. 1.2. The present work As outlined above, a number of questions still remain unanswered in regard to ASOMZ. They are as follows: (i) the pathway that RSW and PGW follow in central and northern Arabian Sea is still not well worked out, (ii) the reason for the eastward shift of ASOMZ is not well understood so far, (iii) the magnitude of seasonal scale variation is not assessed as yet, and (iv) the areal and volumetric extent of ASOMZ based on correction to the historical database, are not quantified till date. The present work attempts to improve the understanding of ASOMZ, through (i) evaluation of the annual and seasonal scale variation of the volumetric and areal extent of ASOMZ after applying the correction for oxygen estimations in past

measurements, (ii) assessment of the contribution of major water masses in the Arabian Sea including separate definitions for PGW and RSW in the extended Optimum Multiparameter Analysis (eOMP, Karstensen and Tomczak, 1998), and (iii) evaluation of seasonal disparity between Net Primary Production, OMZ variation and organic matter remineralization through apparent oxygen utilization (AOU) in Arabian Sea. The classification of seasons considered in this study is as follows: Winter Monsoon: JanuaryMarch; Spring inter-monsoon: April-June; Summer monsoon: July-September and Fall inter-monsoon: October-December. We believe that the present study will provide a base for future studies that aim to understand the biophysical interaction of ocean and climate, organic matter preservation, and biogeochemical cycles.

2. Data and methods The in situ measurements from the Global Ocean Data Analysis Project (GLODAP) data set (Key et al., 2004) and gridded (1°  1°) dataset of WOA13 (Garcia et al., 2014) have been used in the present work. The GLODAP database consists of high-quality measurements collected mostly during the 1990s by WOCE program, whereas WOA13 provides the most updated and largest dataset of dissolved oxygen and nutrients ranging from years 1955–2012 that also include the WOCE measurements. We used the ‘analyzed fields’ of theWOA13 dataset which are the arithmetic mean of interpolated values of ‘observed’ depth levels to 102 ‘standard’ depth levels (see Garcia et al. (2014) for details). 2.1. Correction of oxygen concentration data The measurements of low oxygen concentrations made before WOCE shows a severe overestimation of dissolved oxygen at low concentrations and hence underestimates the extent of OMZ (Bianchi et al., 2012; Banse et al., 2014). One of the reasons for this deviation is the poor threshold limits of measurements in the past (2–10 mmol/l, Bianchi et al., 2012). In order to reduce this abnormality, a correction factor for dissolved oxygen in WOA13 gridded data set has been introduced by sampling the gridded data at the locations and month of in situ measurements of WOCE stations from GLODAP database by using linear interpolation technique. This approach is similar to the approach of Bianchi et al. (2012), which successfully reduces the biases in oxygen concentration for WOA 2005 database and applied for major oceans of the world. A scatter of the data above the 1:1 line in Fig. 3 shows the overestimation of WOA13 measurements as compared to GLODAP. The disagreement between these two datasets can be the result of a combination of several factors such as (i) smoothing during objective mapping, (ii) interpolation variability, (iii) poor sensitivity of measurements at low oxygen concentration in past and (iv) combining analytically measured values. Recent evidence cited by Bianchi et al. (2012, and references therein) suggest that the early measurements at low oxygen concentrations (e.g. at suboxic waters) could be biased by up to 5 mmol/l. Therefore, an empirical correction to the gridded WOA13 oxygen values has been applied based on in situ measurements from GLODAP, using a linear fit over the lower range of oxygen values that vary from zero to 60 mmol/l. This procedure resulted in the following equation:

O2Corrected=0. 9353O2WOA13−0. 6672

(1)

where the negative values were considered as zero. This procedure helps us to maintain the geographic structure of WOA13 gridded dataset along with the reduction of biases in low oxygen concentrations. The OMZ characteristics based on this corrected

S.S. Acharya, M.K. Panigrahi / Deep-Sea Research I 115 (2016) 240–252

Fig. 3. Scatter plot of in situ GLODAP and gridded–WOA13 oxygen data. This plot clearly indicates over-estimations of dissolved oxygen concentration of WOA13 as compared to GLODAP database.

oxygen parameter should be considered as the minimum possible value for different estimations (viz. thickness, area, volume, etc.) as complete removal of biases in measurement is not possible in historical dataset. 2.2. Spatial variation of ASOMZ The vertical and horizontal extension of ASOMZ was defined by the oxygen concentrations of o20 mmol/l ( r0.5 ml/l). This threshold value delimited zone will be hereafter described as ‘OMZ core’. This value has been adopted from the study of Kamykowski and Zentara (1990) and the same has been used in several other works on OMZ characterization (e.g. Helly and Levin, 2004; Fuenzalida et al., 2009; Paulmier and Ruiz-Pino, 2009; Bianchi et al., 2012). This threshold value of oxygen concentration is assigned based on the premise that OMZs should allow denitrification and this oxygen value correspond to the maximum oxygen concentration for which water column denitrification has been observed in situ (Smethie, 1987). We determined the OMZ characteristics (viz. upper and lower boundary, thickness, area, and volume) for the annual averages of major OMZs of the world ocean and seasonal averages in the Arabian Sea. The upper and lower boundaries of OMZs ( o20 mmol/l) were defined for each location, difference of which gives the thickness of OMZ. The area covered and the volume occupied by the World Ocean OMZs along with ASOMZ were determined by the average of estimations calculated by means of trapezoidal Rule, extended Simpson's Rule, and extended Simpson's 3/8 Rule (Fuenzalida et al., 2009 and references therein). The trapezoidal rule fits a trapezoid to each successive pair of values and estimates the integral as the sum of the areas of the trapezoids. However, Simpson's rules fit a parabola (quadratic interpolation and cubic interpolation (extended Simpson’s 3/8 rule)) to each interval between two points and calculate the integral as the sum of the areas under the parabolas. The estimations obtained by each rule only differed by less than 1% that indicates the consistency of the dataset and results. 2.3. Optimum multi-parameter analysis Optimum Multiparametric (OMP) analysis (Tomczak and Large, 1989) is a mathematical technique applied on real data that can be

243

used to study the mixing processes between water masses in a certain region. It considers the physical and/or chemical properties measured at each point, to be the result of the mixing of a certain number of water masses, which are called Source Water Masses (SWM) and whose physical and/or chemical characteristics are well-known. These SWMs are assumed to have a common formation history of all components, which can be described as a combination of multiple source water types (SWT) (Tomczak and Large, 1989). An SWT (xi) is a point with specific hydrographic properties of the unmixed source water mass. Therefore, all water masses in the world ocean can mathematically be described through a combination of water types. The contribution of each SWT to these mixing processes is the final objective of the analysis. The OMP analysis is constrained to fulfill two rules: (i) the mass balance equation has to be satisfied at any point and (ii) the mixing contributions of the different SWTs have always to be positive. The contribution of each SWT (Xi) is estimated for each measured point using a non-negative least squares method. The standard OMP analysis assumes that all the parameters are conservative quantities, which is difficult to justify when biogeochemical processes, like remineralization and denitrification, are likely to contribute to the observed parameter distribution. The change of concentration of non-conservative variables by biogeochemical processes can be described by adding a biogeochemical term ( ∆P in this work) related to the non-conservative variables through Redfield ratio (Redfield et al., 1963). In the present work, we have considered the remineralization ratio, given by Hupe and Karstensen (2000) for the Arabian Sea. The remineralization ratio assigned to the subsurface layer of 550–1200 m depth range by Hupe and Karstensen (2000), are extended for the 150–1200 m depth range in the present analysis. This procedure is called extended OMP (eOMP) analysis. The system of equations is as follows: 5

θobs =

∑i = 1 xi × θio + ϵθ

Sobs =

∑i = 1 xi × Sio + ϵS

(2)

5

O2obs =

(3)

5

∑i = 1 xi × O2io − rO/ P∆P + ϵO2 5

NO3obs =

∑i = 1 xi × NO3io + rN / P∆P + ϵ NO3

PO4 obs =

∑i = 1 xi × PO4io + rP / P∆P + ϵ PO4

Siobs =

(5)

5

(6)

5

∑i = 1 xi × Siio + rSi / P∆P + ϵSi

5

1= ∑

(4)

i=1

(7)

xi + ϵ mass θoi ,

Soi ,

(8) O2oi ,

NO3oi ,

PO4oi ,

Sioi

)

where ( represent para and meter definition for source water type i; ( θobs, Sobs , O2obs , NO3obs , PO4obs , and Siobs) stand for the observed parameters in the studied region, and ∆P , the change in phosphate, is related to the other non-conservative parameters through Redfield ratio. In the above equations, ϵ x is the error associated with variable x. In order to control the influence of a certain parameter on the solution, a weighting is applied (Table 1). In the present work, we

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Table 1 Main properties of each of the Source Water Types (SWTs) considered in the study. The correspondent weights of each property equation in the extended OMP (eOMP) analysis are also given, together with the correlation coefficients (R) between the observed and estimated properties and the Standard Errors of the Estimates (SEE). SWTs

Pot. temp (°C)

Salinity (psu)

Oxygen (mmol/l)

Phosphate (mmol/l)

Nitrate (mmol/l)

Silicate (mmol/l)

Mass conservation

PGW RSW dIDW ICW

18.11 12.55 0.92 9 18 36 0.99 0.001

36.5 36.2 34.72 34.54 35.47 36 0.99 0.012

43.75 28 221.47 274.37 253.41 14 0.99 0.06

2.12 2.38 2.12 1.07 0.11 5 0.98 0.001

21.05 30.46 30.53 14.39 0.01 5 0.96 0.05

20.69 45.35 112.7 6.22 1.69 1 0.98 0.21

1 1 1 1 1 36

Lower Upper

Weights R SEE

have adopted the method originally described by Tomczak and Large (1989) that relates the variance of each input parameter among the source waters to the variance of the same parameter within each source-water by the following formula:

Wj =

σj2 δjmax

(9)

where sj measures the ability of parameter j to resolve differences between water sources and δjmax is the largest of source water mass variances for parameter j. Since OMP analysis does not provide a unique method for assigning weights to the mass balance equations, we followed the usual practice (Tomczak and Large, 1989; You and Tomczak, 1993) and assigned the largest of our calculated weights to the mass balance. Following the approach of Hupe and Karstensen (2000) for Arabian Sea eOMP analysis, we have assigned silicate the lowest weight because it is not directly linked with organic matter remineralization. In the present study, four SWMs represented by five SWTs are considered to describe the subsurface layers (4150 m to 4000 m) of Arabian Sea: viz. Persian Gulf Water (PGW), Red Sea Water (RSW) Indian Central Water (ICW) and deep Indian Deep Water (dIDW). The upper boundary is fixed at 150 m that is the top of the ASOMZ. The Persian Gulf and the Red Sea are the source regions for two of the most saline water masses, PGW and RSW respectively. Hupe and Karstensen (2000) and Rixen and Ittekkot (2005) considered RSW and PGW together as a single entity. In the present work, they are treated as separate water masses based on the following three reasons, viz. (1) PGW has a far more northerly source than RSW, (2) PGW appears mostly below 300 m depth while RSW appears between 300 and 900 m depth, and (3) The core densities of PGW and RSW differ widely in potential temperature-salinity diagram (Fig. 4; σθ =26.5kgm−3 and 27.2kgm−3,respectively ). Besides these five water types, other water masses are also identified in Arabian Sea such as mixture of Antarctic Intermediate water (AAIW) with Indonesian Throughflow water (Hupe and Karstensen, 2000), High Salinity Arabian Sea surface water (ASSW) (Shetye et al., 1994; Kumar and Prasad, 1999) etc. We have excluded the above-mentioned water masses because of two reasons: (i) our prime objective of OMP analysis in this present study is to trace the path of RSW and PGW in Arabian Sea which circulate within the depth limits of ASOMZ; and (ii) the combination of four water masses (RSW, PGW, ICW and dIDW) successfully describes the major layers of Arabian Sea (4150 m) which has been confirmed by the mass conservation residuals. A low mass conservation residual, generally considered as below 5%, shows that the properties of the water sample are well represented by the source water types considered (Poole and Tomczak, 1999). The majority (498.5%) of the mass residuals (o0.25%) in the present study indicates that the included source water types can explain the analyzed data (Poole and Tomczak, s 1999). Computation of eOMP was done using the Matlab scripts for eOMP analysis of Karstensen and Tomczak (1999).

Fig. 4. Potential temperature versus salinity distribution in Arabian Sea for depths 4150 m. The source water types are PGW: Persian Gulf water, RSW: Red Sea water, dIDW: deep Indian Deep water and ICW: Indian Central water.

A compilation of source water properties used by several researchers to document the contribution of the different water masses/types are given in Table 2. The comparison of the published source water characteristics (Table 2) and the present estimated values (Table 1) suggests that the estimated properties are well within the range of values reported in the literature. 2.4. Residual apparent oxygen utilization (rAOU) The apparent oxygen utilization (AOU) is the difference between the saturated value of O2 and the measured value, where saturated O2 is the equilibrium saturation concentration of oxygen in the seawater under the same physical and chemical properties. The AOU represents O2 being consumed during the respiration of exported organic matter in the water column. For example, primary production liberates oxygen and increases its concentration while respiration consumes it and decreases its concentration. However, the variation of AOU is also affected by the water mixing processes that reduce its direct applicability as a productivity proxy in an oceanic realm (Garcia et al., 2014; De La Fuente et al., 2014). To remove the influence of water mixing process, i.e. initial condition of each water types, we have used a multiple non-linear regression of AOU with salinity and temperature (De La Fuente et al., 2014) for the ocean interior (0–1500 m, the maximum depth range of ASOMZ). This approach is based on the assumption that a

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Table 2 The literature values of different properties of each of Source Water Types (SWTs). SWTs

References

PGW/RSW

AS-PGW AS-RSW ICW

Lower IDW

Hupe and Karstensen (2000) Rixen and Ittekkot (2005) You and Tomczak (1993) Coatanoan et al. (1999) You and Tomczak (1993) Coatanoan et al. (1999) Rixen and Ittekkot (2005) Hupe and Karstensen (2000)

Pot. temp

Salinity

Oxygen

Phosphate

Nitrate

Silicate

Pot. density

(°C)

(psu)

(mmol/l)

(mmol/l)

(mmol/l)

(mmol/l)

(kg/m3)

18.7 27.41 25.9 15 10 4.39–18.16 10.2 12.45 0.38

37.69 36.33 38.08 35.8 35.3 34.39–35.624 34.8 35.11 34.7

50 146.5 161.9 9 22.33 177.61–278.72 250.1 126.3 216

1.56 0.99 0.372 2.4 2.6 0.145–1.936 0.8 1.46 2.2

19.7 8.67 – 20 30 – 8 21.21 32.1

19.2 – 0.701 30 50 2.921–43.879 8 – 125.3


27.1 – 25.7 26.59 27.18 25.7–27.1 26.76 o 25 427.8

Table 3 Statistical parameters of residual AOU estimations. Seasons

Equation (T ¼Temperature, S¼ Salinity)

 25,440þ 1326*S þ 219.9*T  16.93*S^2  6.114*S*T  0.4918*T^2 Spring  11,750 þ 571.5*S þ185.5*T  6.55*S^2  5.124*S*T  0.4637*T^2 Summer 8870  599.6*S þ143.7*T þ 10.07*S^2 3.88*S*T  0.5981*T^2 Fall 3110 289.4*S þ178.3*T þ 5.917*S^2 4.916*S*T  0.5241*T^2 Winter

Table 5 Seasonal variations of ASOMZ.

Observed AOU Standard deviav/s estimated tion (mmol/l) AOU (R2) AOU rAOU 0.96

99.48

19.86

0.96

99.66

17.36

0.95

91.94

20.96

0.95

91.79

20.12

Seasons

Area (106 km2)

Volume (106 km3)

Mean O2 mmol/l (n ¼ 280)

Maximum thickness (m)

Winter Spring Summer Fall

3.51 3.47 3.31 3.69

2.65 2.61 2.74 2.66

10.09 7 5 12.487 4 8.767 5 9.81 7 5

1230 1150 1290 1240

and Falkowski (1997), using the Moderate Resolution Imaging Spectroradiometer (MODIS) surface chlorophyll concentrations, MODIS 4-micron sea surface temperature data, and MODIS cloudcorrected incident daily photosynthetically active radiation. The monthly data for the global grid of 2160  4320 were retrieved for the time period of January 2003 to December 2014, from the ocean productivity web portal (http://www.science.oregonstate.edu/ ocean.productivity/index.php). The mean seasonal estimates of NPP for the complete dataset were evaluated for the Arabian Sea (Fig. 9).

water type can be identified as a point in temperature-salinity space. We have used seasonally averaged gridded WOA13 dataset in the Arabian Sea to evaluate the “modeled AOU” concentration which can be described by the temperature and salinity variation in the studied region. Thus, the difference between the measured AOU and modeled AOU, hereafter represented by “residual AOU” (rAOU), represents the organic matter remineralization in the Arabian Sea. The equations and statistical parameters are given in Table 3.

3. Results 3.1. Spatial distribution of OMZs The areas and volumes of major OMZs of global ocean computed in the present work are furnished in Table 4 for comparison with previously estimated values. The seasonal estimations (Table 5) of OMZ were done only for the Arabian Sea situation. The OMZ in the Eastern Tropical North Pacific (ETNP) is the largest, contributing

2.5. Net Primary Production (NPP) The estimation of Net Primary Production (NPP) is based on the Vertically Generalized Production Model (VGPM) of Behrenfeld

Table 4 Characteristics of major OMZs of global ocean in terms of Area, Volume, Mean oxygen concentration and maximum thickness. The estimated parameters are also compared with earlier estimations of Fuenzalida et al. (2009). Major OMZs of Global Ocean

Area (106 km2)

Volume (106 km3)

Present

a

Present

a

3.2

2.57

2.51

2.13

1.48

1.58

0.62

0.6

Arabian Sea (AS) (50  77.5°E, 7.5–26°N) Bay of Bengal (BB) (80–100°E, 5–22°N) Eastern South Pacific (ESP) (70–130°W, 0–40°S) Eastern Sub-tropical North Pacific (ESNP) (70–130°W, 0–25°N)

7.07

5.81

1.51

1.46

10.1

9.92

3.6

3.35

Eastern tropical North Pacific (ETNP) (75–180°W, 25–52°N)

13.8

11.86

6.84

5.88

Global Ocean

35.65

a

Fuenzalida et al. (2009).

15.08

Mean

Max.

O2 mmol/l

Thickness (m)

10.45 74 14.51 73 13.45 73 11.46 74 16.74 72 137 4

1230 630 700 730 1080

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Fig. 5. Values of the mass residual error and residuals (measured value – expected value of the property) associated with the extended OMP (eOMP) analysis.

45.36% of total OMZs volume, followed by Eastern Subtropical North Pacific (ESNP, 23.87%), Arabian Sea (Arabian Sea, 16.64%), Eastern South Pacific (ESP, 10.01%) and Bay of Bengal (BB, 4.11%). The major OMZs of the world ocean cover an area of 35.65×106 km2, a significant surface accounting for more than 9% of present day global ocean surface. Based on the area covered by OMZs, ETNP is the largest, covering 38.71% followed by ESNP (28.33%), ESP (19.83%), Arabian Sea (8.98%) and BB (4.15%). The thickest OMZ occurs in the Arabian Sea (1230 m), followed by ETNP (1080 m), ESNP (730 m), ESP (700 m) and BB (630 m). The mean O2 concentrations of OMZ cores suggest that the Arabian Sea has the most intense OMZ followed by ESNP, ESP, BB, and ETNP. We analyzed the seasonal variability of ASOMZ for the areal extent, the core thickness, and O2 concentration in the core. The ASOMZ shows statistically significant differences in terms of the areal extent and volume occupied, during the monsoonal transitions (Table 5). For example, during the spring-summer transition, the volume of ASOMZ core increases by 5%, while the area decreases by 5%. This transition also records intensification of OMZ core by 30% (mean O2 decreases from 12.48 to 8.76 mmol/l). 3.2. Extent of source water masses The mass residuals of the eOMP analysis are almost zero for the entire water column of Arabian Sea except for the shallow surface layer. The residuals of the conservative variables θ and S are lower than the rest, as expected. The Standard Errors of the Estimates (see Table 1) and the individual residual errors of hydrographic properties (Fig. 5) suggest that the eOMP analysis results are adequate to explain the source water characterization in Arabian Sea (Pardo et al., 2012; Kim and Min, 2013; Álvarez et al., 2014).

Fig. 6. Results of eOMP analysis for the (a) N-S and (b) E-W section of Arabian Sea, for different water masses: RSW: Red Sea water, PGW: Persian Gulf water, ICW: Indian Central water and dIDW: deep Indian Deep water. The major contributions of PGW and RSW are confined to the shallow depth having distinct E-W gradient as shown in (b), whereas dIDW is dominated in deeper part of Arabian Sea and ICW in subsurface depths ( o 1500 m), without any significant E-W gradient.

The results of the extended OMP analysis consist of four SWMs contributions along two sections: (1) N-S section (along 66.5°N longitude) and (2) E-W section (along 15.5°E latitude) are shown in Fig. 6. 3.2.1. Persian Gulf Water (PGW) The distribution of PGW along the E-W section (Fig. 6(b)) shows an E-W gradient within the subsurface (o300 m) depths, which marks the maximum concentration along the western coast of Arabian Sea, near its source region. In the central Arabian Sea (60– 67°N longitude), PGW spreads within the intermediate waters, whose contribution decreases to o15% below 1500 m water depth. The N-S section (Fig. 6(a)) along the Arabian Sea shows a decreasing trend in the distribution of PGW contribution towards the southern latitudes. Therefore, two major routes can be assigned to PGW: (i) southward along the Omani coast and (ii) eastward along the north-east Arabian Sea.

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3.2.2. Red Sea Water (RSW) The Red Sea Water shows two maxima in its distribution pattern along the E-W section (Fig. 6(b)), one in the western coast and another on the eastern coast of Arabian Sea, with very little evidence of its presence in central Arabian Sea (o 25%), where possible interference of PGW flow can be observed. Along the N-S section Fig. 6(a), a decreasing trend in the distribution of RSW can be seen towards the northern Arabian Sea, where its contribution is more confined within the depth range of 300–550 m. The presence of RSW in the northernmost Arabian Sea (440%) shows that the RSW must reach the eastern coast of Arabian Sea from farther north, not from the west. This observation supports the conclusion drawn by Babu et al. (1980) and Shankar et al. (2005), who suggested through hydrographic observation that RSW moves northward from the Gulf of Aden along the continental slope off Oman, then westward along the slopes off Iran and Pakistan to the slope off India.

Fig. 7. Schematic diagram of inferred flow paths of different water masses in Arabian Sea. The source water types are PGW: Persian Gulf water, RSW: Red Sea water, dIDW: deep Indian Deep water and ICW: Indian Central water. The dotted lines indicate the traverses used in Fig. 6.

3.2.3. Indian Central Water (ICW) The E-W section (Fig. 6(b)) shows nearly parallel concentration contours of ICW with the depth of the water column, without any E-W gradient. The contribution of ICW decreases with depth along this section. However, the N-S section (Fig. 6(a)) shows a trend of decreasing contribution of ICW towards northern latitudes, which marks the possible mixing of RSW and PGW at subsurface waters.

Fig. 8. Distribution of average residual AOU within upper water column ( o 1500 m) of Arabian Sea for different seasons: (a) Winter (Jan-Mar), (b) Spring (Apr-Jun), (c) Summer (Jul-Sep), (d) Fall (Oct-Dec). These seasonal distributions reflect contrasting east-west variation in organic matter remineralization.

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Fig. 9. Seasonal-mean (n ¼51,332) Net primary Production in Arabian Sea, estimated based on Vertically Generalized Production Model (VGPM) of Behrenfeld and Falkowski (1997). The dotted line reflects approximate boundary of ASOMZ core.

3.3. Relationship between OMZ and productivity

Fig. 10. The primary production (mg C/m2/day) map using measured NPP data (redrawn after Naqvi (1991)).

The resultant distribution pattern of ICW is similar to the result of You (1997) for the northern Arabian Sea. 3.2.4. Deep Indian Deep Water (dIDW) The contribution of dIDW in both the sections (Fig. 6(a) and (b)) shows an increasing trend in distribution with depth. Its contribution to the ASOMZ is minimal as compared to the other water masses. This water mass completely dominates the bottom waters of the Arabian Sea below 1700 m water depth. Nearly paralleled concentration contours in both sections reveal a lack of distribution gradient of dIDW in the Arabian Sea. The flow paths of water masses inferred from the eOMP analysis are sketched in Fig. 7.

The distribution of rAOU in an oceanic realm indicates the oxygen utilized solely by the biochemical processes. Therefore, the relation between rAOU distribution and oxygen concentration will provide a platform to establish the relationship between OMZ and productivity, which is considered as one of the prime drivers for the origin of OMZ in the upwelling rich region like the Arabian Sea. De La Fuente et al. (2014) studied the relation between the distributions of humic-like fluorescent dissolved organic matter (at excitation/emission wavelengths of 340 nm/440 nm) and apparent oxygen utilization (AOU) after removing the influence of water mass mixing and concluded that residual AOU (rAOU) reflects in situ oxidation of organic matter by microbial activity. In the present study, the seasonal variation of rAOU within the upper water column ( o1500 m) of Arabian Sea (Fig. 8) suggests that the organic matter remineralization is more in summer and winter as compared to that of the spring which supports the reduction in ASOMZ intensity during winter-spring transition and intensification of ASOMZ during spring-summer transition as revealed by the spatial distribution of ASOMZ (Table 5). The increase in the magnitude of rAOU towards the eastern Arabian Sea noticeably deviates from the highly productive regions of the western basin as revealed from the seasonal-mean Net primary Production (NPP) maps (Fig. 9). To validate results of this model, the aforementioned distributions of NPP was compared with that of gridded (1°  1°) NPP map presented by Naqvi (1991) using the large database of INODC, IIOE, and data available with the authors (Fig. 10). There are significant similarities exist between the satellite derived NPP distributions (Fig. 9) and measured primary production (Fig. 10); viz. (i) high primary production along the Oman and Arabia offshore, Somalia coast and southwest India, which were earlier identified as upwelling zones (e.g. see Naqvi, 1991); and (ii) low primary production in the central and the eastern Arabian Sea. Therefore, the ASOMZ is definitely located well away from these

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Fig. 11. Seasonal mean distribution of the depth (m) (solid lines) and salinity (psu) (dotted lines) on PGW core ( σθ=26. 5kgm−3).Contour interval for depth is 20 m; for salinity it is 0.15 psu. Note the shoaling of depth contours during spring-summer transition (b-c) in eastern/central Arabian Sea.

highly productive regions and developed within the least productive central and eastern basin of Arabian Sea. The distributions of NPP during the monsoonal blooms (Fig. 9(a) and (c)) are strikingly high than the inter-monsoon seasons (Fig. 9(b) and (d)). The same can also be inferred from the organic matter remineralization map (Fig. 8), where the distributions of rAOU during winter and summer (Fig. 8(a) and (c)) reflect higher oxygen utilization in the eastern and central Arabian Sea as compared to that of the spring and fall (Fig. 8(b) and (d)). These types of monsoonal blooms in the Arabian Sea have previously been reported by many workers. Marra and Barber (2005) reported an increase in the productivity across two monsoons (NE and SW) through the measured chlorophyll-a concentration during the JGOFS program. They proposed that the SW monsoonal bloom (Fig. 9(c)) is a result of wind-driven shear-mixing while the NE monsoonal bloom (Fig. 9(a)) is a response to resource supply through the vertical convective processes.

4. Discussions 4.1. Eastward shift of ASOMZ The eastward shift of ASOMZ may be possible either by greater supply of oxygenated water to the western Arabian Sea which weakens the ASOMZ in the western basin or greater consumption of oxygen in the eastern/central Arabian Sea. The above

observations based on different analysis of WOA13 database support the dominance of both these physical and biogeochemical phenomenon. The E-W section of eOMP analysis (Fig. 6(b)) shows that the supply of ICW and dIDW is nearly same without any significant E-W gradient. However, the contributions of PGW and RSW to the Arabian Sea show significant decreasing E-W gradient, where the PGW response is more dominant. Therefore, the formation of ASOMZ in central/eastern part of the Arabian Sea and its weakening in the western boundary is more likely the result of PGW flow to the Arabian Sea. A comparison of the seasonal distribution of NPP (Fig. 9(a)–(d)) and rAOU (Fig. 8), which acts as an organic matter remineralization proxy, reveals an eastward shift of organic detritus. Therefore, the oxygen utilization is more in the eastern part of the Arabian Sea as compared to its western counterpart (Fig. 8). Recent studies have suggested that low iron and silica concentration in upwelled water during the southwest monsoon may promote bloom of smaller species (Wiggert and Murtugudde, 2007; Hood et al., 2009). Because of the low burial rate of these smaller species, they are possibly driven by the western current, which gives rise to this difference in the zone of bio-production and oxygen consumption in the Arabian Sea. This result is in line with that of Naqvi (1991), who proposed that the degradation of advectively transported organic matter from the zone of high productivity in the western Arabian Sea probably helps to develop the reducing condition in the central and the eastern Arabian Sea, a zone of low productivity.

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Fig. 12. Seasonal mean distribution of the depth (m) (solid lines) and salinity (psu) (dotted lines) on RSW core ( σθ=27. 2kgm−3).Contour interval for depth is 20 m; for salinity it is 0.15 psu. Note the shoaling of depth contours during spring-summer transition in eastern/central Arabian Sea.

Therefore, we conclude that high supply of oxygenated water from the west and greater consumption of oxygen at subsurface depth in central and eastern Arabian Sea are the primary reasons for the eastward shift of ASOMZ. This finding is in line with the result of McCreary et al. (2013), who reported that a significant amount of remineralization in the northeastern basin is fueled by organic detritus driven from the highly productive regions in the western Arabian Sea. 4.2. Maintenance of ASOMZ The changes in the characteristics of an OMZ arise because of the changes in the sources and sinks of oxygen. Such changes in the Arabian Sea may be the results of seasonal variation in the outflow of SWMs and/or changes in the organic matter remineralization in the Arabian Sea. The eOMP analysis shows that dIDW contribution to the upper water column of Arabian Sea is insignificant as compared to other studied SWMs. Besides, the distribution of core density surface of dIDW ( σθ =27.85kgm−3) in different seasons, show negligible variation within the depth range of ASOMZ. Therefore, its role in the seasonal maintenance of ASOMZ can be assumed to be of minimum significance. Though ICW contribution is significant within the depth range of ASOMZ, the OMP analysis of You (1997) shows that the seasonal variation of ICW in the north-eastern part of Arabian Sea is less significant. Besides, it carries oxygen-poor water to the Arabian Sea because it loses most of its oxygen content through organic matter remineralization process on its way through Indian Ocean

(Swallow, 1984; Rixen and Ittekkot, 2005). Because of the lack of sufficient water age data, it is not possible to determine the correlation between the rate of oxygen supply and consumption within the scope of the present work. However, an indirect method was employed to determine the relative decrease in the oxygen concentration within the ICW SWM within its flow path to the Arabian Sea. From the eOMP analysis, the sample points where the ICW contribution was found to be 100%, the measured oxygen concentration was assigned as that of the ICW contribution to the Arabian Sea. The mean oxygen concentration of all these points, which are located at 63.5°E, 6.5°N, was found to be 41 (712) mmol/l. Therefore, a significant decrease in the dissolved O2, from 274.37 to 253.41 mmol/l (Table 1) at the source region (40°–45°S, You, 1997) to 41 mmol/l, has already been occurred by the time ICW reaches the Arabian Sea (6.5°N). Hence, it is expected to be even less at 10–12°N, where the core of the ASOMZ occurs, due to the more intense primary production within the Arabian basin. Therefore, the oxygenated PGW and RSW seem to be the major contributors for the seasonal maintenance of ASOMZ. This is corroborated by the prominent spring-summer transition of ASOMZ. During summer (Fig. 9(c)), the mean NPP of Arabian Sea nearly doubles as compared to that of spring (Fig. 9(b)). This is further supported by the distributions of rAOU in summer (Fig. 8(c)) that shows enhanced organic matter remineralization in eastern part of Arabian Sea as compared to that of spring (Fig. 8(b)). These processes result in the intensification of ASOMZ core by 30% and increase in its volume by 5% (Table 5). The disparity between the increase in productivity and/or organic matter remineralization with ASOMZ intensification might

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be the result of the enhanced flow from marginal SWMs (PGW and RSW). During summer, the wind circulation direction changes throughout the Arabian Sea (Rao et al., 1989) on the onset of south-western monsoon. This brings dramatic changes in the spreading of PGW core ( σθ = 26.5kgm−3, Fig. 11) In the northern Arabian Sea, PGW core becomes shallower by 20 m (decreases from 260 to 240 m; Fig. 11(b) and (c)). During this period, the northward flowing Somali current brings fresh water from the equatorial region and mixes with PGW (Prasad et al., 2001) which can be observed by an eastward tilting of isohalines along the coasts of Somalia and Arabia. Similarly, the core density surface of RSW (27.2kgm−3, Fig. 12) becomes shallower by 20 m in the northeastern Arabian Sea during summer, which was also earlier reported by Gamsakhurdiya et al. (1991). Hence, the enhanced oxygen utilization in eastern part is counterbalanced by the increase flow from the western part of Arabian Sea. In summary, the decrease in the oxygen utilization during the winter-spring transition (Fig. 8(a) and (c)) is counterbalanced by the deepening of PGW and RSW core in the eastern and central Arabian Sea (Figs. 11 and 12). This finding is in line with the results of the biophysical model of Sarma (2002), who inferred a subtle balance between the organic matter oxidation and higher flow of oxygen to maintain the suboxic conditions in the Arabian Sea.

5. Conclusions The following conclusions are drawn in the present work on the characteristics and intriguing aspects of ASOMZ, based on analysis of the most updated database of world ocean atlas (2013): 1. The estimation carried out by corrected oxygen concentration, gives a refined picture of the volume and extent of oxygen minimum zones (OMZs) of the world ocean. 2. The estimations of Arabian Sea OMZ across seasons show distinct variation during spring-summer and winter-spring transition. 3. The extended OMP analysis and salinity distribution along the isopycnal surfaces show that PGW spreads all across the basin at shallow depths whereas RSW is present in a continuous mode towards the eastern longitude at intermediate depths. The contribution of dIDW and ICW to the Arabian Sea is comparatively constant as compared to PGW and RSW. 4. The distribution of residual AOU shows that organic matter remineralization is mostly dominant in the eastern Arabian Sea. This also signifies the eastward advection of organic detritus from the highly productive western coast of Arabian Sea by eastward moving currents. 5. A Greater supply of oxygen to the western coast of Arabian Sea (PGW and RSW) and higher consumption of oxygen in the eastern Arabian Sea cumulatively shifts the OMZ of Arabian Sea towards the eastern boundary. 6. The subtle balance between the flows of marginal oxygen rich water masses (PGW and RSW) and consumption of oxygen by organic matter remineralization play major roles in maintaining the suboxic condition in the Arabian Sea.

Acknowledgements This work forms a part of the Ph.D. thesis of SSA, who acknowledges financial support from the Ministry of HRD, Government of India in the form a research scholarship available through the host Institute. The manuscript has benefitted from thorough and constructive reviews by three anonymous reviewers of the

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Journal. We thank Prof. Igor Belkin, Editor-in-Chief, for his encouragement and support in the course of handling the manuscript.

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