Modulation in Ocean Primary Production due to Variability of Photosynthetically Available Radiation under Different Atmospheric Conditions

Abstract

The rate of photosynthesis primarily depends on nutrients and photosynthetically available radiation (PAR) at sea surface. Several ship cruises were carried out to measure optical, biological, and atmospheric parameters in the Arabian Sea and their variability were studied. An analytical nonspectral photosynthesis-irradiance model was used to estimate euphotic primary production (EuPP) to study its variability during cruise periods. PAR was estimated using COART model using in situ measured aerosol optical depth (AOD) to compare with in situ measured PAR. In order to understand the variability of PAR under different types of aerosol and different aerosol loading, a simulation study was carried out using COART model. EuPP was estimated for various PAR values under different aerosol loading and cloud coverage conditions. Sensitivity analysis showed that for maritime, maritime polluted, and desert aerosols, the ratio PAR/PAR0AOD has attenuated to about 11-25%, whereas it has attenuated to 44% for urban aerosol type. PAR/PARclear sky was reduced by ~57% for high aerosol loading and for overcast sky. The decrease in EuPP under various aerosol loading and cloud coverage was observed to depend on the photoadaptation parameter. EuPP/EuPPclear sky was reduced by 38% for maximum maritime aerosol loading and for overcast sky.

(ProQuest: ... denotes non-US-ASCII text omitted.)

Academic Editor:Robert Frouin

Space Applications Centre (ISRO), Ahmedabad 15, India

Received 31 May 2013; Revised 28 October 2013; Accepted 29 October 2013; 5 January 2014

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Introduction

Biological process in the ocean is mediated through the process of photosynthesis, where marine phytoplankton converts inorganic carbon to organic carbon and removes carbon dioxide from the atmosphere. The rate, at which photosynthesis occurs, also termed as primary production, primarily depends on nutrients and photosynthetically available radiation, or PAR, (~0.4-0.7 μ m wavelengths) at sea surface. Productivity varies with the availability of light and takes place within the euphotic zone. This extends from the surface to a depth where there is 1% of the light intensity from the surface. The photosynthetic response of phytoplankton to available light is not linear. It is light dependent at the lower light intensities and becomes independent (saturated) at higher light intensities, producing a curve which is described by its slope ( α ) and the maximum photosynthesis ( _{P m} ) [1].

As solar radiation passes through the earth's atmosphere, some of it gets absorbed or scattered by different atmospheric constituents like aerosols, cloud cover, ozone, water vapor, and various gasses. On a daily level, cloudiness and aerosols have a significant influence on the amount of radiation that reaches the earth surface [2-4]. Arabian Sea and Bay of Bengal basins experience aerosol loadings transported from northern hemispheric landmasses during the Asian dry season (November to April) [5]. The aerosol concentrations have increased over the northern part of India compared to the southern part of India in recent years [3]. The addition of micronutrient iron from mineral dust to sea water can influence ocean productivity [6, 7]. On the other hand, aerosols that remain in the atmosphere and are not deposited in the sea water can reduce the solar energy at the sea surface and can influenced ocean primary production [8, 9]. As a part of IRS P4 OCM I, OCM 2 validation, there were several joint ship cruises by Space Applications Centre and National Institute of Oceanography team to measure optical parameters (radiance/irradiance profile, PAR), biological parameters, and atmospheric parameters (aerosol optical depth) during 2001 to 2011 in different seasons in the Arabian Sea. In the view of above, the variability of PAR, AOD, and ocean primary production was studied during cruise period in the Arabian Sea. In the context of the increased aerosol concentration over the northern part of India, a sensitivity study through COART model was carried out to understand the effect of increased aerosol optical depth on PAR and its role in modulating column primary production in the Arabian Sea.

2. Study Area

The study is carried out in north eastern Arabian Sea (NEAS). The locations of the data collection during ship campaign are shown in Figure 1.

Figure 1: Location of data points of ship cruise in the Arabian Sea (date: 3-17 November, 2001 (SK171), 4-19 January, 2003 (SK186), 16-27 April, 2006 (FORV244), and 7-19 March, 2011 (FORV 286)).

[figure omitted; refer to PDF]

A total of 37 hydrographic stations were sampled during the entire study period and the area covered during the cruises lies within 10-20°N and 66-75°E. During winter monsoon season (December-March), phytoplankton blooms are observed in the entire northern Arabian Sea, covering coastal shelf regions and open Ocean of Oman and Gujarat [10, 11]. However, typical oligotrophic conditions prevail during April and November in the northern Arabian Sea, characteristic of intermonsoon phase.

3. Dataset and Methodology (Cruise Data)

3.1. Brief Description of Radiometers (Surface and Profiler)

An underwater (Satlantic Inc.) radiometer having seven bands centered on 412, 443, 490, 510, 555, 670, and 683 nm was used during 2001 and 2003. Surface PAR was obtained from SMSR (SeaWiFS Multi channel Surface Reference) sensor. The profiler SPMR (SeaWiFs Profiling Multi channel Radiometer) was lowered under water to measure the downwelling irradiance. Another underwater (Satlantic Inc.) radiometer having 1.2 nm resolution was used in 2011. Surface reference _{E s} sensor provided surface PAR. Downloading irradiance at different depth of the ocean was measured from _{E d} sensor of hyperspectral radiometer in free fall mode. In situ data was processed using the software (Prosoft) provided with the instrument. Both radiometers are calibrated every year according to the calibration protocols provided by the company using NIST certified integrity sphere as calibration source. After each measurement, lens of radiometer was washed with fresh water to avoid contamination of salt content.

3.1.1. Estimation of PAR from Radiometer Data

Photosynthetically available radiation is a measure of the number of photons available for photosynthesis by chlorophyll and obtained from reference sensor of radiometer. Reference sensor was kept on the deck of the ship away from the shadow of the ships superstructures and the shadow of the radar dome. Measurement of surface irradiance was carried out between 11:30 am and 12:30 pm. PAR was estimated using the following equation: [figure omitted; refer to PDF] where λ is wavelength, h is Planck constant, c is the speed of light, _{E s} ( λ ) is downwelling surface irradiance in µW cm^-2 nm^-1 obtained from surface PAR sensor of radiometer.

Figure 2(a) shows the variation of downwelling irradiance _{E s} at different wavelength at different time and Figure 2(b) shows PAR in the range 0.4 μ m to 0.7 μ m at different time. PAR was averaged within the time interval. Solar zenith angle was calculated based on NASA report [12] and PAR at local noon was calculated by dividing PAR at observation by cosine of solar zenith angle. The unit of PAR in micromole cm^-2 sec^-1 was converted to W m^-2 unit [13].

(a) Variation of downwelling irradiance _{E s} at different wavelength with time. (b) Variation of PAR with time.

(a) [figure omitted; refer to PDF]

(b) [figure omitted; refer to PDF]

3.2. Estimation of AOD Using EKO Sunphotometer and Microtop II

EKO sunphotometer was used to measure AOD during November 2001 and January 2003. It had five filters at 368 nm, 500 nm, 675 nm, 778 nm, and 865 nm. The function of these filters was to allow only the light corresponding to those wavelengths to pass through them. During March 2011, Microtop II hand held sunphotometer of Solar Light Company USA was used to measure AOD at five different wavelengths (380 nm, 440 nm, 500 nm, 675 nm, and 879 nm). The basic principle was similar to that of EKO Sunphotometer. If _{I 0} was the unattenuated radiation and I was the radiation that reaches the sun photometer after interaction with the air molecules and aerosols, then a straight line was obtained by plotting the logarithm of the voltage values against 1/(cos of solar zenith angle), which is called the Langley plot. The negative slope of Langley plot gave the total optical depth comprising of rayleigh optical depth and aerosol optical depth. Rayleigh optical depth was calculated with inverse relationship between Rayleigh optical depth and fourth power of wavelength [14] at mean sea level. Rayleigh optical depth was subtracted to get the aerosol optical depth. Sun photometer readings were taken every half an hour throughout the day on all days.

3.3. Estimation of EuPP

An analytical nonspectral photosynthesis-irradiance model [1] was used to estimate EuPP. The basic equation of the daily rate of euphotic zone production _{P Z , T} was given as [figure omitted; refer to PDF] where B is chlorophyll-a concentration, _{k par} is vertical diffusion attenuation coefficient for euphotic depth ( _{Z eu} ), and D is the day length given as input to the model. Platt and Sathyendranath [1] have shown that under certain assumptions, a fifth-order polynomial provides an approximation to the analytical solution for daily rate of water column primary production as a function of surface irradiance at local noon. This is given as [figure omitted; refer to PDF] where ^{I 0 m} is surface Irradiance at noon and ^{α B} , ^{P m B} are photo physiological parameters. Dimensionless irradiance = ^{I * m} is given as ^{I 0 m} / _{I k} and _{I k} is calculated as ratio of _{P m} and α . _{I k} was termed as photoadaptation parameter and Ω is weights for fifth-order polynomial fit for x = 5 . Weights were obtained from Platt and Sathyendranath 1993 [1] for the range of 0.2 ...4; ^{I * m} ...4; 20 .

3.3.1. Inputs for the EuPP Model

(i) Chlorophyll-a. Water samples collected during ship cruises were analyzed following ocean optics protocols [15] for field measurements of chlorophyll-a concentration by flurometer.

(ii) Euphotic Depth. Downwelling irradiance at each depth of the Ocean during cruise period was obtained from _{E d} and SPMR sensor of Satlantic radiometer when it was operated in free fall mode. PAR variability at each depth of each station was estimated using [figure omitted; refer to PDF] where _{E d} is downwelling irradiance in micro W cm^-2 nm^-1 at each depth in the ocean. Figure 3 shows depthwise variability of PAR. Euphotic depth was taken as the depth of 1% decrease from sea surface PAR at each station during ship cruise period.

Figure 3: Variability of PAR with depthwise.

[figure omitted; refer to PDF]

(iii) Vertical Diffusion Attenuation Coefficient ( _{k par} ). Water column attenuation up to euphotic depth was calculated following Lambert Beer's relationship _{I Z eu} = _{I sur} exp ( - _{k par} × _{Z eu} ) . _{Z eu} is euphotic depth. _{I Z eu} and _{I sur} were PAR at euphotic depth and at surface. The values of _{I Z eu} and _{I sur} were obtained from _{E d} and SPMR sensor of Satlantic radiometer operated in free fall mode during cruise period.

(iv) Physiological Parameters. Photophysiological parameters α and _{P m} of the photosynthesis-irradiance curve were estimated from PI curve. _{P max} and α in nature are slowly varying properties and can be obtained only from in situ observations. Idealized curve of photosynthetic rate as a function of irradiance is shown in Figure 4(a). A more convenient laboratory based procedure is to measure photosynthesis in combination with a photosynthetron. Different components of photosynthetron are shown in Figure 4(b). This photosynthetron was designed and fabricated at Space Applications Centre, Ahmedabad. Phytoplankton samples were incubated with [ 14 C ] -HCO3 for a period of three hours at the same temperature of the water body and a series of irradiance value designed to correspond to different depths in the euphotic zone was provided from an artificial source (250 W quartz-halogen lamp). The watertight incubation chamber was made with flat acrylic material and was designed to contain a stack of thirteen 300 mL flat rectangular bottles. Bottles were attached to a gearbox unit with a motor to move the rack. A submersible pump was used at the other end of the chamber to circulate water inside the chamber and flow around the rack of bottles. This arrangement kept the algal cells inside the bottle well mixed and prevented their settlement at the bottom of the bottle.

(a) Idealized curve of photosynthetic rate as a function of irradiance. (b) Components of photosynthetron.

(a) [figure omitted; refer to PDF]

(b) [figure omitted; refer to PDF]

Production was computed according to equations in JGOFS protocols [15] and normalized to chlorophyll concentration. The chlorophyll specific α ^B and ^{P m B} were derived by fitting to the experimental data points and hyperbolic tangent function as given in Jassby and Platt [16].

3.4. Day Length

Day length ( D ) in hours was calculated using Brock [17] model.

4. Results

4.1. The Variability of PAR and AOD (Cruise Data) in the Arabian Sea

PAR varied from 344 to 403 Wm^-2 during November 2001, from 290 to 400 Wm^-2 during January 2003, and from 390 to 430 Wm^-2 (Figure 5(a)) during March 2011. The variation of AOD was from 0.05 to 0.2 during November 2001, from 0.08 to 0.55 during January 2003, and from 0.13 to 0.41 (Figure 5(b)) during March 2011. Normally, PAR and AOD values will have a good correlation if they are measured at same locations at different times. PAR varies with solar zenith angle and latitude in addition to AOD. In our study, as PAR has been measured at different latitude, we did not get good correlation between PAR and AOD in the pooled dataset (Figure 5(c)).

Variability of PAR (a) and AOD (b) and the relationship between PAR and AOD (c) during cruise period in the Arabian Sea.

(a) [figure omitted; refer to PDF]

(b) [figure omitted; refer to PDF]

(c) [figure omitted; refer to PDF]

4.2. The Variability of Chlorophyll, k _par , Euphotic Depth, and EuPP (Cruise Data) in the Arabian Sea

During the cruise period the variability of chlorophyll-a, _{K par} , euphotic depth, and EuPP is shown in Figures 6(a)-6(d). Figure 6(e) shows the variation between EuPP with AOD and PAR in the pooled data set during the cruise period.

Variability of chlorophyll (a), _{k par} (b), euphotic depth (c), and EuPP (d) and the variation of EuPP with AOD, PAR, and ∫ PP / ( _{BP m} D / _{k par} ) (e) during cruise period in the Arabian Sea.

(a) [figure omitted; refer to PDF]

(b) [figure omitted; refer to PDF]

(c) [figure omitted; refer to PDF]

(d) [figure omitted; refer to PDF]

(e) [figure omitted; refer to PDF]

The variation of chlorophyll-a was from 0.22 to 1.5 mg m^-3 during November 2001, 0.17-2.6 mg m^-3 during January 2003, and 0.12-3.3 mg m^-3 (Figure 5(a)) during March 2011. _{K par} ranged from 0.06 to 0.25 m^-1 during November 2001, 0.07-0.21 m^-1 during January 2003, and 0.07-0.27 m^-1 (Figure 6(b)) during March 2011. The variation of euphotic depth was from 33 to 64 m during November 2001, 21-66 m during January 2003, and 17-67 m (Figure 6(c)) during March 2011. EuPP was varying from 160 to 305 mg m^-2 day^-1 during November 2001, 135-650 mg m^-2 day^-1 during January 2003, and 180-1705 mg m^-2 day^-1 (Figure 6(d)) during March 2011. Figure 6(e) shows that normalized production ∫ PP / ( _{BP m} D / _{k par} ) (primary production per unit biomass, unit photosynthetic rate, unit hour, and unit vertical diffusion attenuation coefficient) plotted against PAR was found to occur in a region where photosynthesis was maximum and independent of irradiance according to Figure 4(a).

5. Sensitivity Study

In order to understand the effect of AOD on PAR and finally on ocean primary production, the issues coming from the discussion of Sections 4.1 and 4.2 were as follows.

(i) Definite relationship of AOD at 500 nm with PAR and EuPP was not obtained from the pooled in situ data sets.

(ii) Only in situ AOD was obtained from Sunphotometer. The information about the type of aerosol present during the cruise period was not obtained.

(iii): The normalized primary production ∫ PP / ( B _{P m} D / _{k par} ) plotted against PAR was found to occur in a region where photosynthesis was maximum and independent of irradiance.

(iv) Higher value of photoadaptation parameter was estimated during the cruise period which may correspond to different phytoplankton assemblages of phytoplankton. For different PI parameters the variation of EuPP for different aerosol loading was not known.

(v) All the in situ data were obtained under cloud free condition. There was a gap of information about the variability of PAR and EuPP under different cloud coverage conditions.

To get the answers of those issues, we carried out a simulation study to estimate PAR for different types of aerosol model at measured in situ AOD using COART model. In situ PAR was compared with COART model derived PAR. Secondly, a range of PAR values were obtained when AOD was varied from 0 to 1. Similarly, for different cloud coverage, simulated PAR was obtained using nonlinear relationship with cloud coverage [18]. Finally, a study was carried out to estimate EuPP using (3) with measured value of chlorophyll-a, _{K par} , euphotic depth, physiological parameter, and variable value of simulated PAR. The following sections describe the methodology and results for the modulation of PAR and ocean primary production under different aerosol and cloud coverage conditions for different PI parameter.

5.1. Methodology for Estimation of PAR Using COART (Coupled Ocean Atmosphere Radiative Transfer) Model

Estimation of PAR at a single geographic location and its dependence on AOD were studied by COART model. COART is a publicly distributed software and is demonstrated online at (http://www-cave.larc.nasa.gov/cave/). The characteristics of the Coupled Ocean-Atmosphere system for a plane parallel medium are described with the basic equation given in Jin et al. (1994, 2006) [19, 20].

(A) Inputs for PAR Calculation. Latitude and longitude positions of each hydrographic station at 6:30 GMT were used as input to estimate PAR during ship cruise period in the Arabian Sea. Arabian Sea is situated in the tropical belt and all the ship cruise measurements were taken under cloud free condition. Tropical model was used as atmospheric model and no cloud was selected. Stratospheric aerosol was assumed to be zero as there were no reports by volcanic activity or other events that would result in extra aerosol loading during the ship cruise period. Ocean depth was set as zero to neglect upwelling radiance from ocean. PAR was estimated using COART model at in situ aerosol optical depth as input. In order to understand what type of aerosols was present during ship cruise period, in situ PAR was compared for different type of aerosol models mentioned in the COART. In COART model six types of aerosol model, MODTRAN maritime and Urban, OPAC (Optical Properties of Aerosols and Clouds) maritime clean, OPAC maritime polluted and OPAC maritime tropical, and Desert [4], were selected. Maritime aerosol contains sea salt particle. Maritime clean aerosol have no soot, but with certain amount of water-soluble aerosol. Maritime polluted aerosol has highly variable amounts of soot and anthropogenic water-soluble particle. Maritime tropical aerosol has a low density of water-soluble substance and lower number density of sea salt [4]. Desert aerosol consists of the mineral aerosol. Urban aerosol represents strong polluted aerosol that is observed in urban areas. The mass density of soot was very high and both water-soluble and insoluble substances are about twice the continental polluted aerosol found in centre area of large cities. Among all the different types of aerosol, desert aerosol has only mineral composition. The rest of the aerosol types do not have role in adding micronutrient to sea water. In this case, only we studied the changes of ocean primary production due to reduction of surface PAR. Types of aerosol at each station during the ship cruise period are given in Table 1.

Table 1: Different types of aerosol derived from COART model during ship cruise in the Arabian Sea.

Date	Type of aerosol
November 03, 2001	T
November 04, 2001	C
November 05, 2001	D
November 06, 2001	U
November 07, 2001	T
November 08, 2001	C
November 09, 2001	U
November 10, 2001	P
November 11, 2001	U
November 12, 2001	U
November 13, 2001	T
November 14, 2001	U
January 05, 2003	T
January 06, 2003	T
January 09, 2003	T
January 10, 2003	T
January 11, 2003	P
January 13, 2003	U
January 14, 2003	T
January 15, 2003	T
January 16, 2003	T
March 07, 2011	T
March 08, 2011	T
March 09, 2011	T
March 10, 2011	T
March 11, 2011	T
March 12, 2011	T
March 13, 2011	P
March 14, 2011	T
March 15, 2011	T
March 16, 2011	T
March 17, 2011	C
March 18, 2011	M
March 19, 2011	P

M: Maritime aerosol.

T: Maritime tropical aerosol.

P: Maritime polluted aerosol.

C: Maritime clean aerosol.

U: Urban aerosol.

D: Desert aerosol.

From Table 1, it is evident that during cruise period, aerosol distribution was generally maritime tropical type of aerosol. Maritime, maritime tropical, and maritime clean aerosol gave almost same value of PAR whereas maritime polluted aerosol gave lower value of PAR compared to maritime, maritime clean, and maritime tropical aerosol at any AOD for a particular station. That is why in the next sections we categorized maritime, maritime clean, and maritime tropical aerosol as maritime aerosol. The variety of aerosol type and variation in aerosol optical depth during different seasons were due to difference in wind direction during different seasons [5].

(B) Output. The output of the model was integrated flux from 0.4 μ m to 0.7 μ m (PAR) at 0.1 μ m spectral resolution at sea surface at in situ aerosol optical depth. COART model derived PAR was validated with in situ measured PAR (Figure 7). It is expected to find a good validation of the model with in situ data since the aerosol model was selected in such a way that the discrepancies between the model and the measurements are the lowest. To understand the effect of aerosol on PAR and finally on ocean primary production, a sensitive analysis was carried out for maritime, maritime polluted, urban, and desert aerosol.

Figure 7: Comparison of in situ PAR with COART model derived PAR for different type of aerosol.

[figure omitted; refer to PDF]

5.2. Results and Discussion

5.2.1. Sensitivity Analysis: AOD on PAR

Using COART model, variation of PAR/PAR_0AOD under various aerosol loadings for different types of aerosol was studied through a sensitivity analysis. The results are shown in Figure 8.

Figure 8: The variation of PAR with AOD for different types of aerosol.

[figure omitted; refer to PDF]

Direct PAR decreased exponentially as AOD increases according to the Beer-Bouguer-Lamberts law [14]. Diffuse PAR increases as AOD increases at maximum value and then decreases [14]. Direct and diffuse PAR show exponential variation with aerosol optical depth [14]. Mallet et al. [9] fitted a second-order polynomial to the variation of PAR to PAR_{clear sky} with dust optical depth for different single scattering albedo. However, a second-order polynomial was fitted for various types of aerosol and the equation of the relationship between PAR/PAR_0AOD and AOD was estimated for different types of aerosols and shown in Figure 8. Urban type of aerosol attenuated PAR more compared to other type of aerosols. During January 2003, decrease of PAR/PAR_0AOD was more compared with other seasons. The decrease of PAR in percentage for maximum aerosol loading and moderate aerosol loading compared to no aerosol loading was tabulated in Table 2. For maritime type of aerosol, the decrease of PAR/PAR_0AOD for maximum aerosol loading was from 11 to 16% during November 2001, 13-19% during January 2003, and 11-14% during March 2011. The decrease of PAR/PAR_0AOD for moderate aerosol loading was 3-7% during different seasons for maritime aerosol. Similar results were observed at observatory for Atmospheric Radiation Research, Sukhothai, where PAR was reduced ~3% during May 2003 to April 2004 in the polluted conditions [21].

Table 2: Decrease of PAR (%) for maximum and moderate aerosol loadings compared to no aerosol loading for different types of aerosol.

Type of aerosol	Decrease of PAR/PAR0AOD in percentage for maximum aerosol loading ( AOD = 1 )	Decrease of PAR/PAR0AOD in percentage for moderate aerosol loading ( AOD = 0.3 )
November 2001	January 2003	March 2011	November 2001	January 2003	March 2011
Maritime aerosol	11.42 to 13.42	13.88 to 16.37	11.04 to 12.46	3.84 to 4.79	4.79 to 5.84	3.78 to 4.35
Maritime polluted aerosol	~16.36	~18.76	13.05 to 13.88	~5.50	~6.49	3.90
Urban aerosol	37.15 to 39.40	~43.83		11.75 to 12.71	14.78
Desert aerosol	~25.2			7.94

The variation of diffuse PAR with AOD is largely affected by solar zenith angle [14]. The results of the variation of PAR with AOD of Mallet et al. [9] differ from our results, because PAR has been estimated in this at different solar zenith angles. We estimated PAR at noon as in Section 3.1, whereas Mallet et al. [9] estimated PAR at constant solar zenith angle of 30°. We have neglected the contribution of sea surface reflectance from ocean to surface PAR. The influence of sea surface reflectance on PAR is negligible as per Mallet et al. [9].

5.2.2. Sensitivity Analysis: AOD and EuPP

To understand the effect of aerosol on EuPP in the Arabian Sea, a sensitivity study was carried out to estimate EuPP for a range of PAR values when AOD was varied from 0 to maximum 1 for different aerosol types.

Using the analytical model as described in (3), it was observed that EuPP decreased (Figure 9) as aerosol loading increased during different months of the year. The photosynthetic response to available light is not linear [1]. A second-order polynomial was fitted with the variation of ratio EuPP/EuPP_0AOD and equations of the relationship between EuPP/EuPP_0AOD and AOD for different types of aerosol were given in Figure 9. The decrease of EuPP/EuPP_0AOD for different type of aerosol during ship cruise period for maximum aerosol loading and moderate aerosol is tabulated in Table 3.

Table 3: Decrease of EuPP/EuPP_0AOD (%) for maximum and moderate aerosol loadings compared to no aerosol loading for different types of aerosol.

Type of aerosol	Decrease of EuPP/EuPP0AOD in percentage for maximum aerosol loading ( AOD = 1 )	Decrease of EuPP/EuPP0AOD in percentage for moderate aerosol loading ( AOD = 0.3 )
November 2001	January 2003	March 2011	November 2001	January 2003	March 2011
Maritime aerosol	5.68 to 6.64	6.94 to 8.35	5.44 to 6.33	1.84 to 2.17	2.29 to 2.83	1.80 to 2.11
Maritime polluted aerosol	8.26	9.45	6.44 to 6.90	2.63	3.08	2.01 to 2.17
Urban aerosol	20.81 to 22.24	26.04		5.68 to 6.13	7.33
Desert aerosol	13.12			3.77

Figure 9: The variation of EuPP with AOD for different types of aerosol.

[figure omitted; refer to PDF]

For maximum maritime types of aerosol loading, the decrease of EuPP/EuPP_0AOD was from 5 to 10% during ship cruise period. The decrease was from 13 to 26% for maximum urban and desert types of aerosol loading. Ocean primary production decreased by ~35% [8] in the case of intense dust aerosol (AOD > 0.6) in the Atlantic Ocean. The variation of EuPP/EuPP_0AOD with AOD in the Arabian Sea is different from the variation of primary production in the West African Coast [9] for same aerosol optical depth. Nature of variations of euphotic primary production with AOD in the Arabian Sea can be different for same aerosol optical depth as the PI parameters are different in those Oceans. For moderate aerosol loading, EuPP/EuPP_0AOD was decreased from 3-7% for urban and desert type of aerosol loading. The decrease was negligible (1-3%) for moderate maritime type of aerosol. Weak effects of dust on Ocean primary production were also observed in the Atlantic Ocean when dust optical depth was lower that 0.2-0.3 [14]. The variation of ocean primary production for different value of photoadaptation is discussed in the next section.

5.2.3. Sensitivity Analysis: Photoadaptation Parameter and EuPP

A sensitivity study was also carried out to understand how EuPP was varied with increase of aerosol optical depth for different photoadaptation parameters. During the ship cruise period, photoadaptation parameter was varied from 52 to 265 W m^-2 . EuPP was estimated on November 03, 2001 with photoadaptation parameter 71.53 W m^-2 and the variation of EuPP with tropical maritime aerosol has been discussed in Section 5.2.2. For maximum maritime aerosol loading, the decrease in EuPP was 5.68% for the photoadaptation parameter 71.53 W m^-2 . However, some PI parameters were observed during ship cruise period, which had higher value of photoadaptation parameter. Figure 10 shows decrease (%) in EuPP with increase aerosol optical depth for different photoadaptation parameters.

Figure 10: Decrease (%) in EuPP with AOD for different photoadaptation parameters.

[figure omitted; refer to PDF]

Decrease of EuPP with same aerosol optical depth was different for different photoadaptation parameters. With higher value of photoadaptation parameter the decrease of EuPP was high. For maximum maritime aerosol loading, the decrease in EuPP was increased from 5.34% to 9.25% when PI parameter increased from 52.7 W m^-2 to 265.42 W m^-2 . After discussion about the variation of PAR and EuPP under different aerosol loadings for different value of photoadaptation, the variation of PAR and EuPP under different cloud coverage is discussed in the next section.

5.2.4. Sensitivity Analysis: Cloud Coverage, PAR, and EuPP

To understand the variability of PAR under different cloud coverage, direct and diffuse component of PAR was computed using a non-linear relationship for variable cloud coverage [18]. Clear sky is defined as there are no aerosol loading and no cloud. The ratio PAR/PAR_{clear sky} was observed to reduce in a quadratic way with increase in cloud coverage (Figure 11(a)). For no aerosol (AOD = 0) loading PAR/PAR_{clear sky} was reduced up to about 12% from clear sky when cloud coverage was less than 50%. The ratio reduced 52% (Figure 11(a)) for overcast sky. For maximum aerosol loading (AOD = 1) and for overcast sky PAR/PAR_{clear sky} was reduced 57% compared to clear sky (Figure 11(a)). For moderate aerosol loading (AOD = 0.3) and for overcast sky PAR/PAR_{clear sky} was reduced 54% compared to clear sky. Simulation based study also was carried out to understand attenuation of EuPP at different aerosol and cloud coverage conditions and shown in Figure 11(b). For overcast sky and for maritime clean aerosol when AOD varied from no aerosol to maximum aerosol loading, decrease of EuPP/EuPP_{clear sky} was observed from 33% to 38%. For 50% cloud coverage the decrease was from 6% to 11% compared to clear sky. Second-order polynomial was fitted with the variation of PAR/PAR_{clear sky} and EuPP/EuPP_{clear sky} with cloud coverage for AOD values 0, 0.3, and 1, respectively, and equations of the relationship between PAR/PAR_{clear sky} and EuPP/EuPP with cloud coverage for various aerosol loading is shown in Figure 11. Cloud coverage plays dominating role compared to aerosol in attenuating PAR and finally on ocean primary production. Kumar [22] showed that cloud cover has a secondary effect in comparison to turbidity to reduce PAR and primary productivity during summer and fall intermonsoon in the northern Bay of Bengal.

The variation of PAR (a) and EuPP (b) under different cloud coverage (Date: November 04, 2001).

(a) [figure omitted; refer to PDF]

(b) [figure omitted; refer to PDF]

6. Conclusions

Measured value of PAR, AOD at 500 nm, and EuPP varied from 290 to 430 W m^-2 , 0-0.55, and 135-1705 mg m^-2 day^-1 during the ship cruise period (November 2001, January 2003, and March 2011) in the Arabian Sea. In situ PAR was compared with COART model derived PAR for six different types of aerosol models using in situ measured AOD. The type of aerosol model that gave the minimum error compared with insitu PAR was selected for the true representation of that type of aerosol. Dependence of PAR on AOD, and its impact on ocean primary production has been investigated through sensitivity analysis and statistical equations have been generated between PAR, AOD and EuPP in the Arabian Sea.

It is found that for maritime, maritime polluted, and desert aerosol, PAR/PAR_0AOD has attenuated to about 11-25%, whereas it has attenuated to 44% for urban aerosol type. PAR/PAR_{clear sky} was reduced ~57% for high aerosol loading and for overcast sky.

The decrease in EuPP under various aerosol loadings and cloud coverage was observed to depend on the photoadaptation parameter. The decrease in EuPP was observed to be about 10% for higher value of PI parameter when compared with lower value of PI parameter (~5%) for maximum maritime aerosol loading. EuPP/EuPP_0AOD was reduced by about 26% for maximum urban type of aerosol. Moderate maritime, maritime polluted, and desert aerosol have negligible influence (1.8% to 3.7%) on EuPP/ EuPP_0AOD . EuPP/EuPP_{clear sky} was reduced by 38% for maximum maritime aerosol loading and for overcast sky.

Reduction of PAR/PAR_0AOD and EuPP/EuPP_0AOD was more during January compared to other seasons. Cloud coverage plays dominating role compared to aerosol in attenuating PAR and ocean primary production. This sensitivity study demonstrates the effect of varying AOD and aerosol models on PAR and subsequently on PP estimation. It is also observed that aerosol types also play significant role in the PAR estimation. The relationships developed between AOD and PAR and cloud coverage will improve the quantification of EuPP.

Conflict of Interests

The authors do not have any kind of conflict of interests from any personal, financial, professional, political, or legal interest that have a significant chance of interfering with the results and conclusions of the paper. All the results obtained from different instruments (Radiometer, Sunphotometer, etc.) were purchased by our institute Space Applications Centre for scientific research only.

Acknowledgments

The authors are thankful to Shri Kiran Kumar, Director, Space Applications Centre and Dr. J. S. Parihar, Deputy Director, (EPSA), Space Applications Centre, for their valuable suggestions. They are thankful to Zhonghai Jin, Responsible NASA officer, for helping in running COART RT model. They are also grateful to the two anonymous reviewers that have helped them to improve the original version of the paper.

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