Modulation in Direct Radiative Forcing Caused by Wind Generated Sea-Salt Aerosols

Nishi Srivastava1*, S.K. Satheesh2,3

1 Birla Institute of Technology, Mesra, Ranchi-835215, India 2 Centre for Atmospheric and Oceanic Science, Indian Institute of Science, Bangalore-560012, India 3 Divecha Centre for Climate Change, Indian Institute of Science, Bangalore-560012, India

ABSTRACT

Sea-salt aerosols, prominent natural aerosols over the ocean, play a vital role in direct and indirect radiative forcing. Since surface winds are the prime cause of sea-salt generation, we have developed an empirical relationship between aerosol optical depth (AOD) and sea-surface winds over the study region (60–70°E; 40°S–20°N). The latitudinal variation of background aerosol optical depth (τ0) and the wind index (b) are estimated as they are essential inputs for the estimation of the spatial variation of sea-salt aerosols and are used over the Arabian Sea (AS) to generate spatial heterogeneity of sea- salt aerosols. The latitudinal variation of τ0 and b show a nearly exponential and linear increase, respectively, as we moved towards the north. We used an empirical-cum-model approach to construct an aerosol system to reproduce the observed AOD and aerosol optical properties. Utilizing this information as input to a radiative transfer model, we worked out direct radiative forcing (DRF) over the study region in the short wave (0.2–4 µm) and long wave (8–14 µm) region at the surface, top of the atmosphere (TOA) and in the atmosphere. Short wave cooling at the surface, TOA and heating in the atmosphere are estimated as 40 W m–2, 32 W m–2 and 8 W m–2, respectively. Long wave heating due to the sea-salt aerosols estimated at the surface, TOA and in the atmosphere is about 9 W m–2, 6 W m–2 and 15 W m–2 respectively. Long wave forcing (LWF) partly counterbalances the effect of short wave forcing (SWF) and the cooling at the surface and at TOA. The highest value of such an offset at the surface was observed over the AS (~23%) and that at TOA was ~19%, obviously at high wind conditions. This implies that over the AS sea-salt aerosols (in coarse mode) contribute significantly to LWF compared to other adjacent oceanic regions.

Keywords: Sea salt aerosol; Radiative forcing; Aerosol optical depth.

INTRODUCTION 2014). Sea surface temperature is also an important factor in sea salt aerosol production, and investigators have reported The most omnipresent natural aerosols over the oceanic the impact of sea surface temperature on its production (Jaeglé region are sea-salt aerosols (Blanchard and Woodcock, 1980; et al., 2011; Spada et al., 2013; Grythe et al., 2014). Winter and Chylek, 1997; Haywood et al., 1999; Randles For an accurate estimation of the radiative effects of sea- et al., 2004; Satheesh and Moorthy, 2005). Aerosols are one salt aerosols, information about their abundance is required. of the decisive components for the radiative forcing of the Several campaigns and satellite data analyses have been Earth system (IPCC, 2013), and sea-salt aerosols constitute performed to study the concentration and radiative effects of one of its major components. Extensive measurements reveal aerosols (Moorthy and Satheesh, 2000; Vinoj and Satheesh, that processes associated with the bursting of the white-cap 2003; Wai and Tanner, 2004; Satheesh and Moorthy, 2005; and wave breaking primarily generate sea-salt aerosols. Satheesh et al., 2006). Various relationships between these Concentration of sea-salt aerosols strongly depends on parameters have been reported as the outcome of these sea-surface wind speed and its mechanism of generation is studies, which include exponential, linear and power-law type discussed by several investigators, though this dependence relations (Woodcock, 1953, 1957; Monahan, 1968; Lovett, showed large spatial and temporal variability (Stuhlman, 1978; Kulkarni et al., 1982; Gras and Ayers, 1983; Exton 1932; Kohler, 1936, 1941; Nair et al., 2005; Grythe et al., et al., 1985; Marks, 1990; O’Dowd et al., 1997; Moorthy and Satheesh, 2000; Vinoj and Satheesh, 2003; Wai and Tanner, 2004; Satheesh et al., 2006). Over oceanic regions adjacent to the Indian subcontinent also, the dependence of * Corresponding author. sea-salt aerosols mass/number concentration on wind speed E-mail address: [email protected] has been scrutinized by several researchers (Moorthy and

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Satheesh, 2000; Vinoj and Satheesh, 2003; Wai and Tanner, Oceanic aerosols include maritime sources as well as those 2004; Satheesh et al., 2006). Jaeglé et al. (2011) combined from continental regions. Transported continental aerosols station-based observations, satellite-estimated parameters perturb the composition of the oceanic aerosol system, and model simulations to estimate the global distribution of causing spatial and temporal heterogeneity. Consequently, sea salt aerosols. Some investigators have used various real- the radiative impact changes, and these changes have been time measurements and modeled sea salt aerosol distribution widely addressed by several investigators (Johansen and in chemical transport models to estimate the global sea-salt Hoffmann, 2003; Bates et al., 2004; Moorthy et al., 2005; aerosol distribution (Spada et al., 2013). Several investigators Zhu et al., 2007). Most investigators have investigated direct also estimated the sea-salt aerosol mass burden with various as well as indirect radiative forcing primarily owing to model simulations, and an inter-comparison of these results anthropogenic aerosols (e.g., sulfate and black carbon showed large inter-model variations (Textor et al., 2006; aerosol), while some have focused on the radiative effects of Jaeglé et al., 2011). natural aerosols (Charlson et al., 1987; Crutzen and Andreae, Model simulations include various parameterization 1990; Kaufman et al., 1990; Charlson et al., 1991, 1992; schemes, making inter-comparison exercises a challenging Penner et al., 1992; Hegg et al., 1993; Kiehl and Breigleb task (Jaeglé et al., 2011; Jiménez-Guerrero et al., 2011; 1993; Satheesh et al., 1999; Satheesh and Moorthy, 2006). Spada et al., 2013; Struthers et al., 2013; Tsigaridis et al., Studies of the radiative effect from natural aerosols (i.e., 2013; Gythe et al., 2014). Fan and Toon (2011) attempted sea-salt aerosols) are rather sparse over the Indian domain to develop a global parameterization scheme for sea-salt (Moorthy and Satheesh, 2000; Vinoj and Satheesh 2003; aerosol mass/number concentration and optical properties, Vinoj and Satheesh 2004; Nair et al., 2008). Satheesh et al. and they also verified the quadratic dependence of sea-salt (2002) investigated sea-salt aerosol radiative forcing over aerosol optical depth on wind speed. In recent work, Grythe et the tropical Indian Ocean, reporting that radiative forcing at al. (2014) used a Lagrangian particle dispersion model, the surface and top of atmosphere (TOA) were –6.1 W m–2 comprised of observed sea-salt aerosol concentration from and –5.8 W m–2 respectively. Vinoj and Satheesh (2003) various sources, and examined/evaluated various source studied the change in radiation due to the presence of functions. They also demonstrated that wind speed in the aerosols over the Arabian Sea during the summer monsoon 5–14 m s–1 range is responsible for ~80% of global sea-salt season, and reported a decrease of 21 W m–2 at the surface aerosol generation and that sea-salt aerosol production and an increase in TOA reflected radiation by 18 W m–2. exhibited a power law dependence on wind speed. Vinoj and Satheesh (2004) studied indirect radiative forcing Sea-salt aerosols can absorb solar radiation depending due to sea-salt aerosols and demonstrated that its value was on the wavelength (short wave or long wave) and can cool higher than direct radiative forcing (DRF) at TOA. Large or heat the atmosphere accordingly (Satheesh and Moorthy, uncertainties are associated with sea salt aerosol estimates, 2005). Sea salt aerosols can have a direct radiative effect in and thus their unrealistic representation in climate models the visible and infrared regions, and, at the same time, can can cause significant uncertainties in TOA radiative forcing have a role in indirect radiative effect by acting as cloud estimates (Textor et al., 2006; Fan and Toon, 2011; Struthers condensation nuclei (CCN) (Twomey 1977; Twomey et al., et al., 2013). 1984; Charlson et al., 1992; Ayers et al., 1997). With the Most prior work was conducted as part of field campaigns increase in number concentrations of sea-salt aerosols, CCN from specific locations, and hence were constrained by and cloud droplet number concentration also increase, which spatial and temporal coverage. In this work, we study the leads to an enhancement in the reflectivity of the clouds. wind dependence of sea-salt aerosols over a large oceanic Furthermore, for a given amount of moisture, an increase region and the variance of related parameters (i.e., wind in CCN also reduces the effective radius of droplets and independent component of aerosol optical depth τ0; and the causes an increase in the lifetime of clouds. wind index b) with latitude. When the wind direction is from The magnitude of the direct forcing of aerosols depends the continent, an increase in wind speed causes an increase on their scattering and absorbing nature. The cooling and in the concentration of transported continental aerosols along warming effects of aerosols are governed by their optical with an increase in sea-salt aerosols due to local production. properties, which depend primarily on the composition of Hence, it is important to remove the continental influence the aerosol (Chylek and Cookley, 1974; Crutzen and Andreae, when we isolate sea-salt aerosol radiative effects. As 1990; Ramanathan et al., 2001; Randles et al., 2004). It has mentioned earlier, several studies have been carried out on been mentioned that change in wind speed causes a change in the modulation of sea-salt aerosol generation by the wind sea-salt aerosol concentration in the aerosol system. A change where they discuss continental aerosols influence but do in aerosol composition will change the refractive index of the not take into account their impact. In this work, we have aerosols and, consequently their radiative forcing. Our removed the continental influence using back-trajectory incomplete knowledge about spatial and temporal variations analysis. The use of satellite data has improved the spatial and in sea-salt aerosol concentration limit our exact estimation temporal coverage, using MODIS satellite-derived aerosol of its direct and indirect forcing. Along with the direct and optical depth (AOD, τ) with an accuracy of ± 0.03 ± 0.05τ indirect radiative effect and impact of sea salt aerosols; their over global oceans (Remer et al., 2005; Yu et al., 2006). importance has been also noticed in heterogeneous chemistry We first establish an empirical relation between τ and sea- (Lewis and Schwartz, 2004; Jaeglé et al., 2011; Spada et surface wind speed. Thereafter, we estimate the latitudinal al., 2013). variation of the wind index (b), which relates wind speed

Srivastava and Satheesh, Aerosol and Air Quality Research, 16: 2869–2883, 2016 2871 dependence (with a unit of s m–1) and a wind-independent investigated relative to wind speed are the sea-salt aerosols, component of aerosol optical depth (τ0). This variability and these can be assumed to be the major contributors to has been used to generate regional maps of sea-salt aerosol AOD that can be modulated with wind speed (Fitzgerald, optical depth (τs) and its fraction in τ. We use the empirical- 1991; Satheesh et al., 2006). cum-model approach for the estimation of DRF of sea-salt Several studies have reported the wind dependence of aerosols at the short wave and long wave regions. One τ/mass/number concentration in various forms (i.e., linear, notable difference of the present work from previous ones power-law and exponential type) over different parts of the is that the estimation of radiative forcing in the long wave ocean (Moorthy et al., 1997; Moorthy and Satheesh, 2000; region as long wave forcing (LWF) partly counterbalances Jennings et al., 2003; Smirnov et al., 2003; Satheesh et al., the effect of short wave forcing (SWF) and cooling at the 2006; Mulcahy et al., 2008; Glantz et al., 2009). Studies surface and at TOA. Thus, the present work has several over the Arabian Sea and Indian Ocean regions have shown significant differences and advantages. an exponential relationship between τ and wind speed of the form, DATA AND APPROACH τ = τ0 exp(bU), (1) A large oceanic region with a longitudinal span of 10° (i.e., 60–70°E) and a latitudinal span of 60° (from 40°S– where τ is AOD at wind speed U, τ0 is the same at U = 0 20°N), ranging from the Southern Ocean (SO) to the Arabian (i.e., wind independent component of AOD) and ‘b’ is Sea (AS), has been selected to characterize a wind-τ defined as the index for wind speed dependence (s m–1; association. We have divided this region into 6 sub-divisions Moorthy et al., 1997; Moorthy and Satheesh, 2000; Vinoj of 10° × 10° boxes: SO1 (40–30°S; 60–70°E), SO2 (30– and Satheesh, 2003; Satheesh et al., 2006). It has been 20°S; 60–70°E), SO3 (20–10°S; 60–70°E) and SO4 (10°S– shown that the value of b depends on the wavelength. For Equator), respectively, and AS1 (60–70°E; Eq–10°N) and example, b = 0.12 for λ = 0.5 µm and b = 0.18 for λ = 1.02 AS2 (60–70°E; 10–20°N),. We have used MODIS level-3 µm (Hoppel et al., 1990; Moorthy et al., 1997). In ideal daily (on board the Terra satellite) aerosol optical depth conditions, the index of wind, b, which indicates the (AOD, τ) (Remer et al., 2005) and NCEP reanalysis winds dependence of the generation of sea salt aerosols on wind, (for 2008) to derive an association between τ and the wind should depend only on wind (i.e., the generation of sea-salt speed. NCEP data are available with various temporal aerosols should be same over all latitudes for the same resolutions: 4 times daily, daily and monthly time scales, wind condition). But in the practical scenario, this parameter with a spatial resolution of 2.5° × 2.5° on the global grid. is affected by several meteorological and terrain parameters, This data set has been generated with the help of a climate such as salinity, viscosity, friction, sea surface temperature model that has been initialized with various real time and proximity to land. Researchers have reported a linear weather observations (Smith et al., 2001). relationship also between τ and wind speed (Smirnov et al., After establishing the wind-τ speed relationship for the 2003; Jennings et al., 2003). Mulcahy et al. (2008) showed various regions mentioned above, we investigate the a power-law relation between these two parameters for the modulation in DRF owing to a change in sea-salt aerosol west coast of Ireland. Glantz et al., (2009) have studied the concentration caused by the wind. To isolate DRF due to a τ and wind speed relationship over the North Pacific Ocean change in sea-salt aerosols alone, we need to remove the and found a power-law relationship. continental aerosol influence. The hybrid Single Particle Since sea-salt aerosol is the only wind-dependent aerosol, Lagrangian Integrated Trajectory (HYSPLIT) model run in its contribution to AOD is estimated by eliminating back trajectory mode for 7 days, has been used for this background aerosol concentration. Following Eq. (1), sea purpose (Draxler et al., 2003). A hybrid approach connecting salt aerosol optical depth can be derived using the relation, the Lagrangian and Eulerian modes has been used for the estimation of simple parcel trajectories, complex dispersion τs = τ0 [exp(bU) – 1], (2) and depositions. A predictor-corrector advection scheme was used for the forward and backward calculation. We used the 7 where at U = 0, τs will be zero and τ will be τ0 (i.e., optical day back trajectory method for the removal of transported depth due to background aerosol; Satheesh et al., 2006). dust and other anthropogenic aerosols, assuming a life time To incorporate the effect of a change of wind on AOD of aerosols as a week. We generated aerosol trajectories for owing to a change in the mass/number concentration of each grid of MODIS data falling in our study region and aerosols, we estimated τ at different wind speeds from low those data were removed when the corresponding trajectories to high (0–15 m s–1). Following the approach discussed by intersected a significant land mass (continental history). different investigators (Satheesh and Srinivasan, 2002; In rapidly changing meteorological conditions, HYSPLIT Satheesh and Lubin, 2003; Markowicz et al., 2003; Babu et may incorporate significant error. Other sources of error may al., 2004; Moorthy et al., 2005; Satheesh et al., 2006; Nair come from the temporal and spatial interpolation scheme used et al., 2008), we have also used the empirical-cum-model in the model. Removal limits the influence of continental approach for the estimation of the optical properties of aerosols, which may increase due to the effect of wind- aerosols and DRF. borne transport and could contribute to columnar optical The τ values estimated from the wind-τ equations are depth. Thus, over the open ocean, the only aerosols being incorporated in a Mie scattering model, Optical Properties of

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Aerosols and Clouds, OPAC, (Hess et al., 1998) by changing concentration as background aerosols. Also, the presence of a the sea-salt aerosols concentrations in various pre-defined large amounts of phytoplankton over SO is known and may aerosol models. The purpose of such an exercise is to be a source of oceanic sulfate. The percentage contribution of estimate the optical properties of an aerosol system in which τs in τ, increased gradually with increase in wind as we sea-salt aerosol is the only component whose concentration moved towards north (Fig. 2(b)). Contribution of τs in τ changes with wind speed. South of the equator, we adopted showed a variation from 40% (SO1) to 80% (AS2) at high clean marine aerosol models proposed in the OPAC model, wind speed (~15 m s–1) conditions (Fig. 2(b)). while to the north of the equator different aerosol models were used in which the relative abundance of various species Latitude Variation of τ0 and Wind Index b at no wind condition are based on previous observations The relationship between τ and wind speed indicated an over those regions (Satheesh et al., 1999). Over the southern increase in τ0 as moves to the north. Therefore, to estimate oceanic regions (i.e., SO1-3), we selected the Maritime the exact pattern of increase in τ0 with latitudes, we studied Clean model, which is formulated specially for unperturbed the latitudinal variation of τ0 and wind index b for all the remote oceans with no soot and where sea-salt aerosol regions (Figs. 3 and 4). This analysis was also important concentration depended on wind speed. The fourth region because variations in these parameters were essential in (SO4) maritime tropical model was used. order to derive the spatial heterogeneity in sea-salt aerosols. The simulated results from OPAC were used as input The latitudinal variation of τ0 revealed an exponential parameters to a radiative transfer model, SBDART (Santa increase as moving the north, which can be justified by the Barbara DISORT Atmospheric Radiative Transfer Model; fact that, continental aerosol concentration increases due to Ricchiazzi et al., 1998) in conjunction with observed τ, for the proximity to land. The latitudinal variation of τ0 has the calculation of DRF at TOA, the surface and in the been parameterized as, atmosphere. Fluxes at TOA and the surface were estimated for the calculation of radiative forcing and forcing was τ0 (Λ) = 0.194 exp(0.0354 Λ), (4) estimated using (Satheesh 2002; Nair et al., 2008) where Λ indicates latitude. ΔF = FNo Aerosol – FAerosol , (3) Near the southern latitudes in the study region, the value of τ0 was observed to be 0.09 while over the northern AS it was where FNo Aerosol is flux at TOA/surface assuming zero observed to be 0.33. This latitudinal variation is consistent aerosol concentration and FAerosol is flux at TOA/surface with various island and ship-borne investigations (Vinoj and with aerosol. The difference between TOA and surface Satheesh, 2004; Satheesh et al., 2006; Vinoj et al., 2007). forcing is the atmospheric forcing. The present result was more robust as compared to previous ship-based and island measurements, which had limited RESULTS AND DISCUSSIONS spatial and temporal coverage as compared to satellite data. This relationship was subsequently utilized in estimating Wind Dependence of AOD the background AOD (i.e., the wind independent component Fig. 1 shows the scatter plot of daily MODIS τ as a function of τ). of surface wind speed over the six study regions starting In conjunction with τ0 variation, we also studied the from the Southern Ocean (40°S–30°S, 60°E–70°E) to the latitudinal variation of b. Other studies which incorporate Arabian Sea (10°N–20°N, 60°E–70°E). For SO2-4 and the cruise, island measurements and satellite data analysis have AS2, τ shows a clear exponential growth with an increase shown different results regarding the latitudinal variation in wind, though over regions SO1 and AS1 this relationship is of the wind index. Vinoj and Satheesh (2004) show an not as prominent. Still, an exponential relationship between exponential decrease in the wind index as moving the τ and wind speed appears constant. This result is in north, though this result was based only on a few point agreement with earlier studies performed over the Indian sea measurements. Satheesh et al (2006), with the help of and the Arabian Sea region (Moorhty et al., 1997; Vinoj and satellite data analysis, observed no significant variation in Satheesh, 2003, 2004; Satheesh et al., 2006). The correlation the wind index as they moved from the south to the north. coefficients shown between τ and wind speed were significant In our study, we observed a gradual linear increase in b as at a 95% significance level for all the regions. we move from the southern ocean towards the north, which From these exponential fits, we estimated the values of can be expressed as, τ0 and b for each region, which were subsequently used to derive the value of τ at different wind speeds (0–15 m s–1) B = 0.0015 × Λ + 0.096 (5) for the respective regions (Fig. 2(a)). Here, the contribution of wind-generated sea-salt aerosols was not prominent in Out of the several factors discussed earlier in section 2, an increase in τ. But when we eliminated τ0 and estimated the one which causes this change is not clear. Thus, the the contribution of τs in τ with the help of Eq. (2), then its exact reason for the increase in the wind index as we move contribution was seen to be significant ~50%. The increase towards the north is still an open question. in sea salt aerosol concentration discussed here is only that fraction of sea salt aerosols which increased due to the Regional Distribution of Sea-Salt Aerosols increase in wind and not the pre-existing sea salt aerosol In Fig. (2), we observed that among all the six regions,

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Fig. 1. MODIS aerosol optical depth versus NCEP wind speed (a) SO1 (b) SO2 (c) SO3 (d) SO4 (e) AS1 (f) AS2. tAS1 and AS2 showed the highest rate of change in AOD Fig. 5 shows the seasonal maps of sea-salt aerosols for with wind speed. This motivated us to explore the pattern summer (March, April and May) and winter (January, (spatial distribution) of sea-salt AOD. These regions fall in February, November and December). The first panel in the AS, where continental influences are greater due to the Fig. 5 (top to bottom) shows MODIS-derived composite τ, relative proximity of land. To gather information about estimated τs and the fraction of sea salt aerosol (caused heterogeneity in the spatial distribution of τs, we used only by an increase in sea surface wind) in the total aerosol parameterized values of τ0 and b (Eqs. (4) and (5)) in Eq. (2) load for the summer season, and panel 2 is the same for the with NCEP surface wind speed. The monthly mean τ0 and winter season. In the summer, high τ values were observed b values were calculated for each latitude starting from the near the Indian west coast and the northern part of AS, equator to 20°N to preserve their latitudinal variations. while high τs values were found over the Somalia region These monthly latitudinal variations of τ0 and b were used and the highest (~0.2) at the northern edge of the AS. A in conjunction with monthly NCEP wind speed to generate high concentration of sea salt aerosol was observed over monthly regional maps of τs at 1° × 1° resolution. With the these high wind regions as during the summer season, when a help of these calculations, we estimated the seasonal south westerly wind prevails (Gadgil, 2003; Satheesh et variations in sea salt aerosol distribution. al., 2006). During summer, sea salt aerosol fractions in the

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Fig. 2. (a) Variation of total AOD at 0.55 µm as a function of wind speed (b) percentage contribution of sea salt AOD in total AOD. total aerosol load were the highest over the Somalia current Modeled Aerosol Optical Properties region and the south east corner of the Arabian Sea. In The prime objective of this work is to estimate the winter, when wind directions are from the north east, a limb change in atmospheric DRF in short wave as well as in of high τ was observed from the west coast of India with long wave regions due to the modulation in sea-salt aerosol the highest values near the coast (Satheesh et al., 2006). A concentration by surface wind speed. To achieve this, we substantial decrease was noticed moving away from the used the empirical-cum-model approach, as explained coast to the far ocean since the continental influence earlier in Section 2. The calculation of radiative forcing decreases. As compared to the summer season, in winter, from the SBDART model needed the optical properties of aerosol optical thickness was less, and similarly low τs the aerosol system, which have been set based on the values were observed with its peak value (~0.1) over the OPAC model. Depending on the geographical location of Somalia region (Fig. 5(b) for winter). In the winter season the study regions, we selected aerosol models from OPAC. the maximum contribution of sea-salt AOD in the total τ These models provide the concentrations of the various was about 50% while in summer, this contribution was components of the aerosol system, which were used to more than 70% at some locations. Satheesh et al. (2006) derive the optical properties of that specific aerosol model. have also studied the spatial variation of sea-salt aerosols Regions SO1-3 are situated far to the ocean (i.e., they but on a monthly time scale. are the least anthropogenic affected). Hence, we selected a

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Fig. 3. Latitudinal variation of wind independent component of optical depth i.e., τ0.

Fig. 4. Latitudinal Variation of wind index b. maritime clean aerosol model for these regions. For SO4, sea-salt aerosols (accumulation and coarse modes) alone to we chose the maritime tropical aerosol type. Water-soluble generate an estimated τ from the empirical relation. We and sea-salt aerosol (accumulation and coarse modes) are also modeled τ at 11 µm at different wind speeds over the the components of the aerosol model for the southern ocean respective regions (Fig. 6(a)). Over the SO (SO1-4), we region, but the concentration of water soluble aerosols differs observed low values of τ at 11 µm, but at the same time for in SO1-3 and SO4. AS1-2 are in Indian Ocean/Arabian sea AS1-2 relatively high values were observed. An increase in region and observational information regarding aerosol the number concentration of sea-salt aerosol in the coarse concentrations available in the individual aerosol components mode showed the same variation as τ at 11 µm. At high wind prevailing over these regions. Therefore, we used aerosol conditions, τ at 11 µm is enhanced about 2–20 fold from its models based on earlier observations (Satheesh et al., 1999). low wind values over different study regions, whereas τ at Aerosol components for these models are soot, water soluble, 0.55 µm values showed a maximum 6 fold increase in its dust and sea-salt aerosol (in accumulation and coarse modes). values from low wind conditions to high wind conditions. Using these aerosol types for each of the respective Fig. 6(b) shows the contribution of τs at 11 µm to the total τ regions, we reproduced τ, derived from the wind-τ relation at various wind speeds, estimated using Eq. (2). We noticed at different wind speeds, and, simultaneously, other optical that the percentage contribution of sea-salt aerosol optical properties. Concentrations of the aerosol components, other depth to the total τ at 11 µm reached about 100% at moderate than sea-salt aerosol, were kept constant with wind speed wind speed (~5 m s–1) while it was only ~80% in the total τ according to the model. We increased the concentration of at 0.55 µm contribution at 15 m s–1 over AS (AS1-2).

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Fig. 5. Spatial plot of (a) total AOD (b) sea salt AOD (c) sea salt fraction over Arabian Sea region during summer (Mar, Apr, May) season (Panel 1) and winter (Nov, Dec, Jan, Feb) (Panel 2).

In addition to τ, we studied the variation of single respectively. When the number concentration of the sea- scattering albedo (SSA) with an increase in wind speed for salt aerosol showed an exponential growth (for AS1-2), all regions at 0.55 µm and 11 µm (Fig. 7). Extinction then the concentration of the other components of the represents the composite effect of scattering and absorption, system (i.e., water soluble, soot etc.) was constant. As sea- and SSA represents the fraction of scattered light in the salt aerosols are of scattering type, the SSA of the composite total extinction. The SSA of an aerosol depends on its system approached 1 at 0.55 µm. Over SO (SO1-4), the SSA chemical composition and varies from 0 (i.e., completely at 11 µm was constant (~0.23) for all wind speeds, while absorbing) to 1 (i.e., completely scattering). A change in over the AS (AS1-2) the SSA showed a moderate increase wind will change sea-salt aerosol concentration and hence with wind speed where it increased from 0.27 to 0.5. In the the composition of the total aerosol system. Thus, a change infrared region, sea-salt aerosols act as partial scatterers in the contribution of sea-salt aerosol to a particular aerosol and other components like soot as perfect absorbers. Thus, model will influence SSA values. a moderate increase in SSA at 11 µm was observed with The SSA of an aerosol system is the weighted average of wind speed (AS1-2). the individual components of aerosol species. Fig. 7(a) shows the variations of SSA at 0.55 µm and Fig. 7(b) shows the Direct Radiative Forcing in Short Wave and Long Wave same at 11 µm. Over the SO (SO1-4), SSA was close to 1 Region for all wind speeds as the sea-salt aerosol concentration did In this section, we discuss the results for DRF in short- not change drastically. Over the AS (AS1-2), it showed a wave and long wave regions. We estimated LWF and SWF gradual increase from 0.85 to 0.97 and from 0.75 to 0.96 caused due to a rise in sea-salt aerosol concentration owing

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Fig. 6. (a) Variation of total AOD at 11 µm as a function of wind speed (b) percentage contribution of sea salt AOD in total AOD. to increased wind. After estimating aerosol optical properties, from low to high wind conditions. Over the other regions this we estimated the modulation in DRF at the surface, TOA increase was from (~2 W m–2 to 9 W m–2). These results and in the atmosphere (Figs. 8 and 9). The modeled aerosol are in agreement with other studies where radiative forcing properties were used as input in the SBDART model for in the shortwave range has been estimated in the same range the estimation of DRF. Fig. 8 represent DRF at the surface, (Vinoj and Satheesh 2003; Vinoj et al., 2004; Satheesh and TOA, and atmospheric forcing, respectively, in the short Moorthy, 2005). Atmospheric forcing modulation owing to wave region. an increase in sea-salt aerosol is shown in Fig. 8(c). A As the wind speed increased from low to high (~15 m s–1), change in the atmospheric heating over the SO (SO1-4) with a a change in short wave forcing at the surface was observed change in wind speed was about ~1 W m–2, as it varied about (3–10 W m–2) over regions SO1-4 (Fig. 8 (a)). The from 0.4 W m–2 to 1.4 W m–2 with wind speed. Over AS1 highest change in surface radiative forcing from low to and 2, atmospheric forcing changed to about 6 W m–2 and high wind conditions was observed over the Arabian Sea 8 W m–2, respectively from low to high wind conditions. (AS1-2) near ~40 W m–2. Over the AS (AS1-2), SWF at LWF at the surface varied between 0.2–0.7 W m–2 over the surface was several-fold higher than in the other regions. the SO region (SO1-4), but over the AS it was again several Similar to surface SWF, TOA SWF also showed the highest time higher than in other regions. At high wind conditions increase over the AS (~32 W m–2) as wind speed changed (~15 m s–1), it was observed to be as high as ~9 W m–2. At

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Fig. 7. Variation of single scattering albedo as a function of wind speed (a) at 0.55 µm (b) at 11 µm.

TOA also, comparatively little heating due to LWF was important to notice that the rate of increase in LWF is more observed for the SO region, which varied from 0.1–0.4 than the corresponding increase in SWF over AS (AS1-2), W m–2 at 15 m s–1. Over the Arabian Sea it was ~5 W m–2 which indicates the dominance of the coarse mode at at 15 m s–1. Atmospheric forcing in the long wave region was higher wind speeds. LWF counter balanced SWF at the estimated as 0.3–1 W m–2 over SO. Over AS, it observed surface and TOA by about 7% and 5%, respectively, in SO several-fold higher than in other regions, and increased (SO1-4) from calm wind conditions to high wind conditions. approximately 15 times from calm wind conditions to high The maximum offset of SWF at the surface was observed wind conditions. The highest modulation of radiative forcing over AS (AS1-2) where it was about 23%. At TOA, this was observed over the AS (AS1-2), as the highest rate of offset ranged from 4–5% over SO (SO1-4) and over AS generation of sea-salt aerosols (in both modes) was observed (AS1-2), this offset was about 19%. over this region. High values of LWF observed over the AS indicate the dominance of sea-salt aerosols in coarse CONCLUSIONS mode over this region. SWF and LWF have a counter effect at the surface and The generation of sea-salt aerosols by the action of the TOA, as SWF produces a cooling effect while LWF causes wind is a well-established fact. But the dependency of the a heating effect at the surface and TOA, though the mass/number concentration or aerosol optical depth (AOD, magnitude of LWF is usually much smaller than SWF. It is τ) on wind speed does not follow a universal pattern over all

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Fig. 8. Variation of radiative forcing in short wave range (0.2–4 µm) a function of wind speed (a) at surface (b) at TOA (c) in atmosphere.

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Fig. 9. Variation of radiative forcing in long-wave range (8–14 µm) a function of wind speed (a) at surface (b) at TOA (c) in atmosphere.

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