Preliminary estimation of black carbon deposition from Nepal Climate Observatory-Pyramid data and its possible impact on snow albedo changes over Himalayan glaciers during the pre-monsoon season

The possible minimal range of reduction in snow surface albedo due to dry deposition of black carbon (BC) in the pre-monsoon period (March-May) was estimated as a lower bound together with the estimation of its accuracy, based on atmospheric observations at the Nepal Climate Observatory-Pyramid (NCO-P) sited at 5079 m a.s.l. in the Himalayan region. We estimated a total BC deposition rate of 2.89 pg m -2 day-1 providing a total deposition of 266 pg m -2 for March-May at the site, based on a cal-over culation with a minimal deposition velocity of 1.0x 10 -4 m s-t with atmospheric data of equivalent BC concentration. Main BC size at NCO-P site was determined as 103.1-T. 669.8 nm by correlation analysis between equivalent BC concentration and particulate size distribution in the atmosphere. We also estimated BC deposition from the size distribution data and found that 8.7% of the estimated dry deposition corresponds to the estimated BC deposition from equivalent BC concentration data. a of BC snow could result in albedo reductions. From a simple numerical calculations and if assuming these albedo reductions continue throughout the year, this would lead to a runoff increases of 70-204 mm of water drainage equivalent of 11.6-33.9% of the annual discharge of a typical Tibetan glacier. Our estimates of BC concentration in snow surface for pre-monsoon season can be considered comparable to those at similar altitude in the Himalayan region, where glaciers and perpetual snow region starts in the vicinity of NCO-P. Our estimates from only BC are likely to


ACPD
The possible minimal range of reduction in snow surface albedo due to dry deposition of black carbon (BC) in the pre-monsoon period (March-May) was estimated as 10,2010 a lower bound together with the estimation of its accuracy, based on atmospheric observations at the Nepal Climate Observatory-Pyramid (NCO-P) sited at 5079 m a.s.l. in

Estimated lower
the Himalayan region. We estimated a total BC deposition rate of 2.89 pg m -2 day-1 bound BC deposition providing a total deposition of 266 pg m -2 for March-May at the site, based on a calover Himalayas culation with a minimal deposition velocity of 1.0x 10-4 m s-t with atmospheric data of equivalent BC concentration. Main BC size at NCO-P site was determined as 103.1-T. J. Yasunari et al. 669.8 nm by correlation analysis between equivalent BC concentration and particulate size distribution in the atmosphere. We also estimated BC deposition from the size distribution data and found that 8.7% of the estimated dry deposition corresponds to Mdh-Title Page the estimated BC deposition from equivalent BC concentration data. If all the BC is bstract Introductio deposited uniformly on the top 2-cm pure snow, the corresponding BC concentration is 26.0-68.2 pg kg -t assuming snow density variations of 195-512 kg m -3 of Yala Glacier Conclusion Veferences close to NCO-P site. Such a concentration of BC in snow could result in 2.0-5.2% Tables Figure albedo reductions. From a simple numerical calculations and if assuming these albedo reductions continue throughout the year, this would lead to a runoff increases of 70-204 mm of water drainage equivalent of 11.6-33.9% of the annual discharge of a typical Tibetan glacier. Our estimates of BC concentration in snow surface for pre-monsoon season can be considered comparable to those at similar altitude in the Himalayan L-B-ack-9 close region, where glaciers and perpetual snow region starts in the vicinity of NCO-P. Our estimates from only BC are likely to represent a lower bound for snow albedo reducn Full screen/ Esc tions, since a fixed slower deposition velocity was used and atmospheric wind and turbulence effects, snow aging, dust deposition, and snow albedo feedbacks were not Printer-friendly Version considered. This study represents the first investigation about BC deposition on snow from atmospheric aerosol data in Himalayas and related albedo effect is especially the Discussion _Interactive first track at the southern slope of Himalayas. 10 15 20 25 ACPD Atmospheric aerosol is an important forcing for the earth's climate through direct and indirect effects (IPCC, 2007). Aerosols generally scatter solar radiation, but black carbon 10,9291-9328,2010 (BC), and mineral dust absorb to a lesser extent solar radiation. Long range transport of BC and dust are well known (e.g., Hadley et al., 2007;Yasunari et al., 2009;Uno et Estimated lower al., 2009). Due to their large amounts present in the Atmospheric Brown Cloud (Rabound BC deposition manathan et al., 2007), these absorbing aerosols may directly warm the atmosphere in over Himalayas the Indian-monsoon region. Lau et al. (2006Lau et al. ( , 2008, proposed the so-called Elevated Heat Pump (EHP) effect, whereby heating of the atmosphere by elevated absorbing T. J. Yasunari et al. aerosols strengthens local atmospheric circulation, leading to a northward shift of the monsoon rain belt, with increased rainfall in northern Indian and the foothills of the Himalayas in the late boreal spring and early summer season. More recently, Lau et

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al. (2010) showed that the EHP effect can also lead to accelerated melting of snow F --bst ract' Ftroductio cover in the Himalayas and Tibetan Plateau, by a transfer of energy from the upper troposphere to the land surface over Tibetan Plateau. In addition, BC and mineral dust Conclusion Veferences depositions onto snow-surface in the cryosphere may reduce the surface albedo (e.g., Tables Figure  Warren and Wiscombe, 1980;Aoki et al., 2006Aoki et al., , 2007Tanikawa et al., 2009). The impurity effect on snow albedo reduction is more important for visible wavelength than that for near infrared radiation (e.g., Warren and Wiscombe, 1980;Flanner et al., 2007). It increases heating of the snow and ice surface, thus accelerating melting, shortening snow duration, and altering mass balance and causing retreat of mountain glaciers, L-B-ack, close which change the amount of available water resource in the region (e.g., Hansen and Nazarenko, 2004;IPCC, 2007;Flanner et al., 2007Flanner et al., , 2009.
n Full Screen/ Esc The southern slope of the Himalaya is directly exposed to Indian emissions and more likely to be impacted by BC than the northern slope. However, the available data of BC deposition (BCD) for studying snow albedo reduction at the southern slopes Printer-friendly Version in Himalayan regions are still very scarce. Moreover, only a few BC concentrations Interactive Discussion (BCC) and morphological properties in snow and ice core in the northern slopes of the Himalaya and Tibetan Plateau region have been measured thus far (Xu et al., 2006(Xu et al., , 2009aMing et al., 2008Ming et al., , 2009Cong et al., 2009Cong et al., , 2010. Studies on BC concen-ACPD tration in snowpack at the southern slope in Himalayas are few compared to those at northern slopes. In addition, glaciers in Himalayas are located in severe topogra- 10,2010 s phy and logistics constraints have severely limited data availability on snow and ice composition, as well as atmospheric composition observations. Hence, an alternative Estimated lower approach to estimate BCD over Himalayan glaciers is necessary for understanding bound BC deposition impact of BCD on melting glaciers.

over Himalayas
Atmospheric data of equivalent BC concentration (egBCC), aerosol particle number ,o concentration and size distribution, as well as meteorological parameters are now con-T. J. Yasunari et al. sites are relatively clean and far from anthropogenic emission sources, they can be considered to study the influence of anthropogenic pollution transported from remote 20 areas.
The Indian sub-continent, especially the Indo-Gangetic Plain is one of the largest BC • I emission sources in the world (Ramanathan et al., 2007) and it is in the vicinity of the Himalayan glaciers. Preliminary work of Bonasoni et al. (2008) has found very elevated L-Back-9 close egBCC under different meteorological conditions, with well defined seasonality show-n Full Screen/ Esc 25 ing a maximum in pre-monsoon season (Marinoni et al., 2010). The aim of this study is to provide a preliminary lower bound estimate of BCD and BCC on and in the snow the related additional snow melt runoff from a typical Tibetan glacier by simple numerical calculations with a glacier mass balance model. These estimations are the first step ACPD of a study finalized to carry out more precise estimations on snow albedos and snow melt runoffs from glaciers using regional model, satellite, and more detailed observa -10,9291-9328,2010 s tions in Himalayan regions, including seasonal variations of atmospheric concentration and deposition of absorbing aerosols. Hopefully, this study will stimulate more work Estimated lower on albedo reduction and accompanied snow melt runoff from glaciers over Himalayan bound BC deposition region.
over Himalayas In this study, a BC concentration range in the snow surface due to the minimal depo-,o sition of BC onto snow surface will be estimated by using NCO-P data with typical snow T. J. Yasunari et al.
density data over a Himalayan glacier (Sect. 3.2) with the discussion on possible dilution and enrichment effect of BCC in snow by precipitation and sublimation (Sect. 3.3). The snow albedo reduction will be assessed based on an empirical relationship be-^ Title Page tween snow albedo reduction rate and BCC in snow (Ming et al., 2009) in Sect. 3.4. Vbstract ' Ftroductio ,5 The possible deviation range as error from our estimated snow albedo reductions will conclusions eference be also discussed in Sect. 3.5. Finally, we will calculate how much the estimated albedo reductions can possibly impact on the increase of snow melt runoff from glaciers. Here Tables  Figure  we carried out some  tical diameter between 0.25 and 32 pm in 31 size channels, on 30 min interval (OPC, optical particle counter, GRIMM#190) and egBCC (MAAP, Multi-Angle Absorption Pho-ACPD tometer, 5012) in the atmosphere on 30 min interval, were recorded. A recommended mass absorption coefficient of 6.6 g m -2 was used for calculating BC concentration 10,9291-9328,201010,9291-9328, 5 (Petzold et al., 2002. Additional information on MAAP measurements and calibration procedures are shown by Marinoni et al. (2010) data at a specific time, the whole set of necessary data on calculation were deleted. We used the middle time of the averaged observation slot time for plotting data.
Tables Figure   Next, with the aim of calculating minimal BCD flux at the surface, here we consider a deposition velocity. The estimated BCD flux will be used to estimate BCC in snow sur-20 face and its impact on snow surface albedo reductions. As deposition velocity, here, we e.
.i consider a constant minimal deposition velocity of 1.Ox 10 -4 ms-1 . In general, detailed • I deposition velocity is considered as: L-B-ack, Close vd = 1 I( ra + rb + r c) +vs (1) n Full Screen /Esc where ra , rb , r,, and vs are aerodynamic resistance above canopy, quasi-laminar 25 layer resistance, surface resistance, and terminal velocity by gravitational settling, re-Printer-friendly Version spectively (Han et al., 2004). Deposition velocity is higher over land than over sea interactive Discussion and the deposition velocities in different particle size over land are mostly faster than 1.0X10 -4 m s-1 (Nho-Kim et al., 2004). Hence, our deposition velocity used in this study will be expected as a slower value than deposition velocities in general diurnal cycles over land and considered as lower bound deposition velocity, minimal value, of ACPD deposition velocity. Using the minimal deposition velocity, the 1-hourly total amount of BC deposition rate 10,9291-9328,2010 5 will be then accumulated over the three-month period to obtain the total mass of BC deposited on snow surface.

Estimated lower bound BC deposition 3 Results and discussions over Himalayas
T. J. Yasunari et al.

Determination of BC size range and deposition rate
While the MAAP instrument specifically measures the aerosol absorption coefficient, Title Page ,o directly related to BCC, both the OPC and SMPS measures total aerosol number con-MM&_ centration and size distributions of all aerosol components including BC. To ascertain Vstract ' Ftroductio the typical size range of BC, the correlation analyses between counts in OPC and conclusions eference SMPS bins and egBCC in the atmosphere were carried out in time series data ( Fig. 2a and b). Higher correlation coefficients (more than 0.8) were seen in the ranges 280r Tables Figure   15 650 nm for OPC-egBCC and 103.1-669.8 nm for SMPS-egBCC, respectively. This confirms that the BC particles at NCO-P preferably have sizes ranging between 100 and 670 nm, as indicated by the high correlation between egBCC and PM, showed by Marinoni et al. (2010). The MAAP measures BCC as egBCC in the atmosphere, since Marinoni et al. (2010) found the negligible dust contribution to aerosol absorption coef-L-Back-M close 20 ficient at NCO-P. In order to reduce any miscounting due to absorbing organic carbon we chose significantly higher correlations (r >0.8) as BC particle existence. In fact, n Full screen/ Esc previous study (Venzac et al., 2008) found much smaller particles (10-20 nm growing up to 40 nm) possibly related to the mode of new particle formation from gaseous or Printer-friendly Version ionic precursors at this site , while larger fraction (>600 nm) of submicron particles is Discussion _Interactive 25 generally present at low concentrations. Less precipitation has been observed in Khumbu valley during pre-monsoon season (Bollasina et al., 2002;Bonasoni et al., 2008Bonasoni et al., , 2010. As deduced by NCO-P data ACPD (Bonasoni et al., 2008(Bonasoni et al., , 2010, in the high Khumbu valley during March-May 2006, precipitation events were only 1.9% of all the available meteorological data during 10,2010 March-May 2006 and the total precipitation amount was very low (6.9 mm). Hence, it is reasonable to assume that the main cause for BC removal in the atmosphere in Estimated lower this season was due to dry deposition.

bound BC deposition
The minimal BC dry deposition flux at the surface was estimated from MAAP and over Himalayas SMPS data, separately. Because enough observation instruments are not always available for field observations, we should consider some ways to estimate BCD from T. J. Yasunari et al.
limited observations. At the NCO-P site, egBCC and SMPS are now available and here we consider two types of BCD estimations. First, the total BC mass deposition flux per 1 h was calculated using egBCC data from MAAP as (egBCC)x(the min-

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imal deposition velocity of 1.Ox 10 -4 m s-1 )x(interval time=3600 s). We summated -4 ms-for each size bin)x(interval time=3600 s). In the calculation, we assumed uniform BCC in the atmospheric layer from the ground to the measurement height of 3.5 m a.g.l. and BC continuously depositing onto the surface. The mass concentrations in the atmosphere in each size bin were calculated from SMPS data, considering spherical particles with a reference particle density (here we used a BC ack 9 Close density of 2000 kg m -3 by Lindstedt, 1994). It is because the SMPS covers wider range of particle size than that of OPC for the small particles, and the correlations n Full Screen/ Esc between egBCC, and OPC -SMPS counts gives similar results as shown in Fig. 2a and b, except for the smaller diameters that are not available by this instrument. The Printer-friendly Version interval of SMPS data was 1 h and continuous depositions during this interval were Interactive Discussion assumed. The values of dlogD in each bin were used for converting size distribution data (dN/dlogD) to number concentration data. Then total dry deposition amount of 10 15 20 25 3059 pg m -2 was obtained for the period of March-May. The SMPS data include more aerosol information than MAAP and this deposition amount may include not only BC ACPD but also other aerosol particles. If we compare the total dry deposition amount from 10,2010 SMPS with the total BC deposition amount of 266 pg m -2 from MAAP, the estimated BC deposition amount from MAAP is 8.7% of the total dry deposition amount from SMPS. This is somewhat consistent with the observed mass contribution of Elemental Carbon

Estimated lower
in aerosol at NCO-P (Decesari et al., 2009) and soot abundance at Mt. Qomolangma bound BC deposition (Everest) (Gong et al., 2010). Hence, we considered that approximately 8.7% of to-over Himalayas tal dry deposition amount from SMPS data is likely composed of BC at NCO-P site.
T. J. Yasunari et al. Then, 1-hourly dry deposition amount from SMPS data was converted to 1-hourly BCD amount multiplied by a coefficient of 0.087. The estimated BCD from MAAP was mainly used for the discussions on BC concentrations in snow and related albedo reductions. The diurnal cycle shows clearly a midnightmorning low and an afternoon high BCD rates, consistent with the diurnal cycle of dry convection in this region during the pre-monsoon periods (Fig. 3b). The same diurnal cycle was seen for aerosol scattering and absorption coefficients at NCO-P site (Marcq et al., 2010). A few acute episode of BC pollution has been observed in this [ gack, close period (egBCC exceeded some thousand of ng m -3 ), leading to an estimated dry deposition of BC larger than 1 µg m -2 h -1 . Although we used a fixed deposition velocity as n Full Screen/ Esc a considered minimal value for the estimated BCD amount, expected faster deposition velocity in actual will likely increase our estimated BCD rate.

ACPD
The total mass of BC deposited on the surface during 2006 pre-monsoon season was estimated as the sum of the BCD integrated the 3-month period with available data. 10,2010 Based on this, we obtained a total BCD amount of 266 pg m -2 for the pre-monsoon season, corresponding to 2.89 pg m -2 day -1 . As indicated in Sect. 3.1, most likely, Estimated lower this value represents the lowest line of the actual BCD. Most of the glaciers in Nepal bound BC deposition generally exist above the altitude of the NCO-P while their ablation basin levels are over Himalayas close to its altitude (Karma et al., 2003). Most of the glacier melting occurs in ablation areas. The equilibrium line altitudes of these glaciers are also above the NCO-P level. T. J. Yasunari et al. Hence, our discussion from the estimated BCD can be applicable to the ablation zone of these glaciers.
The 2-cm top layer (5-cm top layer in Aoki et al., 2000) of snow surface is more

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contaminated than the deeper part of the snow layer because the snow impurities Vbstract ' Ftroductio are derived from direct depositions of atmospheric aerosols (Aoki et al., 2000(Aoki et al., , 2007Tanikawa et al., 2009). Moreover, the surface layer contributes to a large fraction of the Conclusion Veferences semi-infinite albedo in snow contaminated by soot and mineral dust (Tanikawa et al., Tables Figure  2009). In addition, Tanikawa et al. (2009) showed that the mass concentration of snow impurities deposited in the surface layer of -2 cm was about 30-50 ppmw whereas that deposited in 2-10 cm was about 2-6 ppmw. This characteristic between surface layer and lower snow layer was seen for elemental carbon, organic carbon, and dust in their, I study. It indicates that the impurity concentration at the top 2-cm is much more higher L-B-ack-9 close than that below 2 cm and the top snow layer is considered to be the key to assess albedo reductions. Hence, our focus on 2-cm snow surface is reasonable for albedo n Full Screen/ Esc reduction calculations as a preliminary estimate.
To calculate the BCC in the top layer of snow, we assumed that the total BC is Printer-friendly Version uniformly distributed in the top 2 cm pure snow. Since BCC is strongly depends on snow water content and since no data on snow density are available for NCO-P area, Interactive Discussion we used observed surface snow density data at the nearby Yala Glacier by Fujita et al. (1998) (Table 1). The glacier is located in the Nepalese Langtang Valley (28.23° N; 85.60° E; 2.5 km 2 , between 5094-5749 m of altitude) about 123 km away the NCO-P ACPD 10 15 20 25 and at very similar altitude (Fig. 1). A pure snow layer extension deeper than 2 cm can significantly increase the water amount, thus influencing our BCC estimates. However, 10,2010 a similar pure snow layer extension to the deeper later is not realistic based on the studies as mentioned above (Aoki et al., 2000(Aoki et al., , 2007Tanikawa et al., 2009) and snow Estimated lower layers below 2 cm usually include impurities to some extent.

bound BC deposition
As the NCO-P altitude corresponds to the lowest elevation of Yala glacier, our es-over Himalayas timated BCD can be considered to be applicable to the termini of glaciers at similar elevations in Nepal as reported in Karma et al. (2003). In that consideration, we also T. J. Yasunari et al.
assume that transport along valleys and BC source strength can be similar to those at the high Kumbu valley. If the total BC of 266 pg m -2 deposited on 2-cm thickness of pure snow and without pre-existing or other contamination such as dust, BCC in

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the snow surface will vary within the range of 26.0-68.2 pg kg -1 due to snow den-Vstract ' Ftroductio sity variations between 195-512 kg m -3 in Table 1. These estimated concentrations conclusion Veferencee are in good agreement with BCC at other glaciers in the Himalayan region (Table 2). From Table 2, we also note that the upper limit of the NCO-P estimated BC snow conr Tables Figure  centration exceeds the values observed at other locations on the northern slope of the Himalayan range. In particular the East Rongbuk glacier, approximately 16 km to NCO-P but on the opposite side of Mt. Everest, shows the lowest BCC (Table 2). Ming et al. (2008) also found in the same East Rongbuk glacier area the highest level of BCC, 20.3f9.2 pg kg -1 , during the period 1995-2002, exceeding 50 pg kg -1 in the summer of 2001 along a significant increasing trend. Our results together with the mentioned L-Back-9 dose studies suggest that the influence of strong polluted air masses transported from the n Full Screen/ Esc Indo-Gangetic Plain and driven by valley breezes up to high mountain and glaciers, is very large on southern slope of the Himalayas (Bonasoni et al., 2008).

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Interactive Discussion cc Q 9302 3.3 Estimation of dilution effect at the snow surface on BC concentration ACPD Precipitation onto snow surface dilutes BCC in snow; nevertheless pre-monsoon season is well known as dry season in South Asian region and low precipitation amount 10,9291-9328,2010 (6.9 mm) were observed at NCO-P during March-May 2006. Due to the dryness of the s period, we expect that most of the aerosol fallout was due to dry deposition as men-Estimated lower tioned in Sect. 3.1. For strengthen the discussion on BCC in snow without much dilution bound BC deposition effect by precipitation during pre-monsoon season, we also examined the dilution effect over Himalayas on BCC in the snow surface. Assuming that there are not so much differences on precipitation amount between NCO-P site and Yala Glacier because of similar altitude and T. J. Yasunari et al.
,o vicinity, we considered that precipitation at NCO-P are as same as that at Yala Glacier. Then, we assumed same precipitation amount over Yala Glacier. The air temperature over Yala Glacier was also estimated from NCO-P air temperature data ( Fig. 4) with Title Page temperature lapse rate of 6.5 K km -1 . The air temperature at the altitude over Yala Vbstract ' Ftroductio Glacier fell below freezing during most of the time in March-May (Fig. 4). Thus, most ,5 of the precipitations were expected as snowfall. When it snows, snow depth slightly conclusion ^teferences increased with a typical fresh snow density of 110 kg m -3 . As deduced by NCO-P ob- Tables  on 18 May (Fig. 4). However, this could contribute to an increase of only 2 cm of snow depth by fresh snow (hereafter called, Event A). Total precipitation amount dur-20 ing March-May was only 6.9 mm w.e., indicating that the pre-monsoon is very dry in I 2006 and most of the aerosol fallout was considered to be dry deposition as mentioned L-B-ack-9 close in Sect. 3.1. It is noted that the above example cannot be generalized for all the years, because there could be large interannual variability in pre-monsoon snowfall over this n Full screen/ Esc region. 25 For the sake of discussing dilution effect on BCC in snow by precipitation, we also Printer-friendly Version calculated the evaporation amount (E) from the snow surface (sublimation if the snow surface temperature was below 0 degree in Celsius) every 30 min by using a bulk equa-Discussion _Interactive tion. In the calculation, air and snow surface temperature over Yala Glacier at altitude of 9303 5450 m were used, where snow density data in Table 1 were obtained. For estimating snow surface temperature quantitatively, we need irradiance data. However, NCO-P ACPD site did not measure irradiance data during March-May 2006. Hence, we assumed snow surface temperature as -9, -4, and -1 degree in Celsius during 3/1-4/29, 4/30- 10,9291-9328,2010 5/23, and 5/24-5/31, respectively (Fig. 5), compared to the estimated air temperature over Yala Glacier in Figs. 4 and 5. In general, snow temperature fluctuations are much Estimated lower lower than that of air temperature. Based on the characteristics, our values of snow bound BC deposition surface temperature are considered to be realistic.
over Himalayas Then, we calculated the evaporation (sublimation in this study) amount (E) by a bulk equation as follows: T. J. Yasunari et al.
where PAIR , CH , U, QsAT( TS) , QSAT(TA), RH and DT are air density, a bulk coefficient Vstract' Ftroductio (=0.002), wind speed, saturated specific humidity at the snow surface, saturated specific humidity in the atmosphere, relative humidity in percentage divided by 100, and conclusion ^teferences total time in second for 30 min (=1800 s). The fixed air pressure at the altitude of Yala Glacier was also used for this calculation. The direction from the snow surface to the Tables  Figure atmosphere is defined as positive in the equation. The difference between precipitation (P) and evaporation (E) (or sublimation) (P-E) i• ► i shows the amount of water vapor transport between the snow surface and the atmosphere. In Fig. 5, the values of P -E showed negative values over most of the premonsoon periods indicating dominant water vapor transport from the snow surface to

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Abstract 1lntroductiô Conclusions^ jkeference^ Interactive Discussion loss from snow surface was more dominant than precipitation. It implies that higher probability of enrichment of BC at the snow surface due to water loss from the snow surface is expected during March-May rather than the dilution effect by precipitation.
Our estimates of BCC in 2-cm snow surface of 26.0-68.2 pg kg -1 did not include the effect of this enrichment of BC due to the water loss from the snow surface. If we consider this effect, BCC in the snow surface during pre-monsoon period could be even higher. In conclusion, our estimates of BCC are considered to be "lower bound" values without including the enrichment effect of P -E.

Estimation of snow albedo reduction
This was obtained from the relationship between BCC in snow and potential albedo ,5 reductions, derived from a variety of snowpack observations and model calculations.
For the given range of snow density and BCC in snow, we obtained the range of albedo reduction ranging from 2.0 to 5.2% during pre-monsoon period (Fig. 6). This range is significantly higher than the albedo reduction (1%) found by Grenfell et al. (1994) for a uniform distribution of 15 pg kg -1 BC in snow, as indicated by the calculation of 20 Wiscombe (1980). Flanner et al. (2007) indicated that the addition of 500 pg kg -1 of BC to snow decreased its visible albedo approximately 10% in visible wavelengths, and calculated that the instantaneous forcing over the Tibetan Plateau, due to the presence of BC in snow, exceeds 20 Wm -2 in some places. Because snow aging process may also accelerate more BC accumulations onto snow surface (Xu 25 et al., 2006), and because our BCD was determined only considering dry deposition, our numbers are likely to underestimate of the actual albedo reduction for Himalayan glaciers.

ACPD
In reality, the albedo decrease caused by BC depends on a wider range of environmental factors such as snow grain size, solar zenith angle, and snow depth (e.g., Warren 10,9291-9328,2010 andWiscombe, 1980). However, the application of using the regression Eq. (3) is probably adequate for a first estimate of albedo changes because our aim in this study Estimated lower is to determine the minimal level of possible albedo reductions due to BCD. Ice surbound BC deposition face is sometimes come up over glacier surface, but the results obtained by using the over Himalayas Eq. (3) can be applied to the snow surface composed of fresh, compacted, and granular snows, in which the snow density range is similar to that of Yala glacier in Table 1 Vbstract ' Ftroductio The data used in this study were obtained from the Supporting Table 4 in Hansen and Nazarenko (2004)  Jacobson (2004), 1 % albedo reduction by BCC of 15 pg kgby Grenfell et al. (1994) with the model of Warren and Wiscombe (1980). The estimates of albedo reductions from observed BC concentrations in snow by Hansen and Nazarenko (2004) were based on Fig. 2 of Warren and Wiscombe (1985). Hence, the estimated albedo,  1985). They calculated the albedo reductions as external mixture case of BC for new and old snows and also mentioned the importance of internal mixture to n Full Screen/ Esc explain true effect of soot. Therefore, in the study of Hansen and Nazarenko (2004), the estimate for internal mixing increased the BC absorption coefficient, or effective Printer-friendly Version amount, by a factor of two along the descriptions by Warren and Wiscombe (1985). In the calculation of Warren and Wiscombe (1985), new and old snows are considered Interactive Discussion as the grain radius sizes of 0.1 mm and 1.0 mm, respectively. The meteorological con-9306 dition was expected as subarctic summer, clear sky, and solar zenith angle effect of 10 15 20 25 53° at sea level in their estimates. The albedo reduction rates were estimated at the ACPD wavelength of 470 nm in their calculation, at which snow albedo is most sensitive to soot content. Finally, Hansen and Nazarenko (2004) categorized BC and snow into 2 10,2010 types of BC with 2 types of snow condition (4 types) as external mixture of BC with new snow (Ext/New), external mixture of BC with old snow (Ext/Old), internal mixture of BC Estimated lower with new snow (Int/New), and internal mixture of BC with old snow (Int/Old). Therefore, bound BC deposition we used 2 types of BC with 2 types of snow condition and calculated each regression over Himalayas equation from the employed data with the estimated error ( Fig. 7 and Table 3). The data from Jacobson (2004) and Grenfell et al. (1994) with the model of Warren and T. J. Yasunari et al.
Wiscombe (1980) were put into the categories of Int/New and Ext/New, respectively.
The errors between the employed and estimated albedo reduction data from the regression equations are within approximately 1 % (Table 3). There are large differences^ Title Page among the estimated albedo reductions by each type with each equation (Fig. 7a and Vbstract ' Ftroductio b). Warren and Wiscombe (1985) explained that a given amount of soot causes a conclusions eference greater reduction in albedo in old snow than in new snow because the radiation penetrates deeper on average in old coarse grained snow and therefore encounters more actual. If we use the equations of Ext/Old and Int/Old, much more albedo reductions are expected even if we only take BC into account. In those cases with Eqs.
(2) and ACPD (4) in Table 3, the snow albedo for Ext/Old and Int/Old can possibly decrease by 4.6-11.0% and 7.2-16.5%, respectively ( density-based snow albedos were always reduced by applying the albedo reductions of 2.0% or 5.2% related with BCD effect as evaluated in this study. We only changed  The obtained results show a corresponding increase in total annual runoff from 70 to ACPD 204 mm of water equivalent by melt water from the glacier especially due to the June-Au August melting ( melting season ( Fig. 8 . In this study, considered the case that g upper and lower snow layer due to snow meltings, and additional BC depositions by wet deposition may also contribute to snow surface albedo reductions during monsoon season. However, quantitative discussions including all these effects are out of the ACPD scope of this study. In addition, BC flushing effect due to snow melting as discussed in Conway et al. (1996) andFlanner et al. (2007) may also be important for determining 10,2010 s albedo reduction at the snow surface. Due to the different locations, caution should be exercised in applying NCO-P results

Estimated lower
to other mountain sites. However some hints about the sensitivities of these albedo bound BC deposition reductions on snowmelt runoff can be provided by this work. As we mentioned above, over Himalayas our estimation of snow contamination due to BCD and thus albedo reduction range, ,o probably represents a lower estimate. Of course, this is the first step to estimate the T. J. Yasunari et al.
BCD amount in the vicinity of NCO-P site and its concentration in surface snow in Himalayan region. Actually, more increase of snow melt can probably occur due to other atmospheric processes, snow aging, and additional mineral dust deposition. For

Conclusions
We estimated a BCD amount of 266 pg m -2 ( = 2.89 pg m -2 day -1 ) from dry deposition during pre-monsoon season over a Himalayan glacier at similar altitude of NCO-P site. 20 Assuming the BCD is distributed uniformly on a pure 2-cm surface snow layer, we esti-L-B-ack-9 close mated BCC of 26.0-68.2 pg kg -1 within the range of the density at Yala glacier, which is in good agreement with the observations from southwestern China's glaciers. Hence, n Full screen/ Esc our estimated BCC range is considered to be realistic as lower bound BCC level at southern slopes of Himalayas. Assuming that the BCC range in snow is also repre- represents a significant amount of the annual drainage from the glacier. Our results are ACPD applicable to white glaciers only (not for debris cover glacier). However, the estimate is likely to represent a lower bound for snow albedo reductions, since atmospheric wind 10 ,9291-9328,2010 and turbulence effects, snow aging, dust deposition, and snow albedo feedbacks were not considered. When all these processes are included, the actual snow albedo re-Estimated lower duction in Himalayan glaciers is likely to be higher with more consequences on surface bound BC deposition water runoffs from snow-ice melting. For these reasons we need more observations over carry out more detailed studies on dilution and enrichment effects of BC and dust by precipitation, snow surface melting, and combination between the snow surface layer and the snow layer below the snow surface, including the wet depositions of BC and dusts and flushing by melt water and precipitation. Although BC and dust can reduce • I snow surface albedos, we should know the equilibrium albedo reductions in the mixture of the impurities. Namely, we need to discuss the maximal albedo reductions due to BC L-B-ack, close and dust depositions. High-resolution regional and global models with realistic high-n Full Screen/ Esc mountain snow-pack physics are also very helpful to understand the albedo reductions, and related snow processes all over Himalayan and Tibetan regions.

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Abstract 1lntroductiô Conclusions^ jkeference^  10,2010 Estimated lower bound BC deposition   Glacier, respectively. The cross, triangle, and square in sky blue denote the locations of Kangwure Glacier, East Rongbuk Glacier, and Qiangyong Glacier, respectively, where BC concentrations in snow were measured by Xu et al. (2006) and Ming et al. (2008Ming et al. ( , 2009    Air temperature variations at NCO-P site and over Yala Glacier, together with the amount of snowfall and rainfall, and estimated snow depth increases over Yala Glacier. The air temperature over Yala Glacier was estimated with temperature lapse rate of 6.5 K km -1 . If air temperature was below 0 degree in Celsius, precipitation was considered to be snow. The snow depth increases were calculated with a typical fresh snow density of 110 kg m-3.   Fig. 5. Difference between precipitation (P) and estimated evaporation (E) (sublimation in this study). The constant snow surface temperatures of -9, -4, and -1° were used during 3/1-4/29, 4/30-5/23, and 5/24-5/31, respectively. One data in P -E at the time of Event A was located at out of range and plotted in (b) separately. In (b), vertical and horizontal axes have the same units as (a).   Table 3 (2007) and Fujita et al. (2007) for the cases of control run (no forced albedo reduction), 2.0% albedo reduction, and 5.2% albedo reduction, respectively. The lines in sky blue and orange denote the differences of snow melt runoff from the glacier between the cases of 2.0% albedo reduction and control run and between 5.2% albedo reduction and control run, respectively.

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