Atmos. Chem. Phys., 16, 7523–7529, 2016www.atmos-chem-phys.net/16/7523/2016/doi:10.5194/acp-16-7523-2016© Author(s) 2016. CC Attribution 3.0 License.

The impacts of moisture transport on drifting snow sublimation inthe saltation layerNing Huang1,2, Xiaoqing Dai1, and Jie Zhang1,2

1Key Laboratory of Mechanics on Disaster and Environment in Western China, Lanzhou University, Lanzhou 730000, China2School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, China

Correspondence to: Ning Huang (huangn@lzu.edu.cn)

Received: 8 October 2015 – Published in Atmos. Chem. Phys. Discuss.: 11 February 2016Revised: 28 May 2016 – Accepted: 31 May 2016 – Published: 20 June 2016

Abstract. Drifting snow sublimation (DSS) is an impor-tant physical process related to moisture and heat transferthat happens in the atmospheric boundary layer, which is ofglaciological and hydrological importance. It is also essentialin order to understand the mass balance of the Antarctic icesheets and the global climate system. Previous studies mainlyfocused on the DSS of suspended snow and ignored that inthe saltation layer. Here, a drifting snow model combinedwith balance equations for heat and moisture is establishedto simulate the physical DSS process in the saltation layer.The simulated results show that DSS can strongly increasehumidity and cooling effects, which in turn can significantlyreduce DSS in the saltation layer. However, effective mois-ture transport can dramatically weaken the feedback effects.Due to moisture advection, DSS rate in the saltation layercan be several orders of magnitude greater than that of thesuspended particles. Thus, DSS in the saltation layer has animportant influence on the distribution and mass–energy bal-ance of snow cover.

1 Introduction

Drifting snow is a special process of mass–energy transportin the hydrological cycle of snow. It not only changes thesnow distribution but also results in phase changes of icecrystals into water vapor, which is known as DSS. Snow sub-limation not only significantly influences the mass–energybalance of snow cover (e.g., Zhou et al., 2014) by chang-ing surface albedo (Allison et al., 1993) and the runoff ofsnowmelt in cold regions (Marks and Winstral, 2001) butalso has a pivotal status on moisture and heat transfer in

the atmospheric boundary layer (Pomeroy and Essery, 1999;Anderson and Neff, 2008). Thus, it is of glaciological andhydrological importance (Sugiura and Ohata, 2008). In highcold areas, the reduction of snow cover may cause the sur-face temperature to increase in the cold season (Huang etal., 2008, 2012). The thickness of seasonally frozen groundhas decreased in response to winter warming (Huang et al.,2012). However, both dust and biomass burning aerosols mayimpact the surface albedo when deposited on snow; sootin particular has large impacts on absorption of radiation(J. Huang et al., 2011). In addition, a large, but unknown,fraction of the snow that falls on Antarctica is removed bythe wind and subsequently sublimates. Therefore, a detailedknowledge of DSS is also essential in order to understandsnow cover distribution in cold high areas as well as the massbalance of the Antarctic ice sheets and, further, the global cli-mate system (Yang et al., 2010).

In drifting snow, snow particles can experience continuoussublimation, which induces a heat flux from the surround-ing air to the particle and a moisture flux in the oppositedirection (Bintanja, 2001a). Thus, DSS can cause increasesin humidity and cooling of the air (Schmidt, 1982; Pomeroyet al., 1993) and has an inherent self-limiting nature due tothe feedback associated with the heat and moisture budgets(Déry and Yau, 1999; Groot Zwaaftink et al., 2011, 2013).On one hand, snow sublimation absorbs heat and decreasesthe temperature of the ambient air, which in turn reduces thesaturation vapor pressure and hence the sublimation rate; onthe other hand, the increment in the moisture content of theambient air decreases the sublimation rate of drifting snow,as it is proportional to the undersaturation of the air.

Published by Copernicus Publications on behalf of the European Geosciences Union.

7524 N. Huang et al.: The impacts of moisture transport on drifting snow sublimation

Saltation is one of the three modes of particle motion,along with suspension and creep. Among the three modes,saltation is important and the DSS in the saltation layermay constitute a significant portion of the total snow sub-limation (Dai and Huang, 2014). Previous studies of DSSmostly focused on the sublimation of suspended snow,which was mainly due to the consideration that sublima-tion will soon vanish in the saltation layer because thefeedback of DSS may lead to a saturated layer near thesurface (Bintanja, 2001b). However, the field observationdata of Schmidt (1982) showed that relative humidity onlyslightly increases during snowdrift events and the maximumhumidity was far below saturation. Further studies (GrootZwaaftink et al., 2011; Vionnet et al., 2014) also showed thatthe relative humidity does not reach saturation even at thelowest atmospheric level after DSS occurs. Some scientistsargued that it was caused by moisture transport, such as diffu-sion and advection of moisture, which inevitably accompanythe drifting snow process (Vionnet et al., 2014). Therefore, itis necessary to study the feedback mechanism of DSS in thesaltation layer and the effect of moisture transport on it.

In this study, we followed previous researches to assumerelative humidity adjacent to snow surface is saturated andignored surface sublimation. However, the particle sublima-tion in saltation layer is considered by taking into account ofmoisture transport in different typical cases, including (1) ne-glecting the effects of moisture transport, (2) consideringmoisture transport due to both moisture diffusion and ad-vection, and (3) considering only moisture diffusion. Here,a wind-blown snow model, balance equations for heat andmoisture of an atmospheric boundary layer, and an equationfor the rate of mass loss of a single ice sphere due to subli-mation were combined to study the sublimation rate of drift-ing snow by tracking each saltating particle in drifting snow.Then, the effects of DSS on the humidity and temperatureprofiles, as well as the effects of diffusion and advection ofmoisture on DSS in the saltation layer, were explored in de-tail.

2 Methods

2.1 Model description

Saltation can be divided into four interactive sub-processes,i.e., aerodynamic entrainment, particle trajectories, particle-bed collisions, and wind modification (N. Huang et al.,2011).

The motion equations for snow particles are (N. Huang etal., 2011)

mpdUp

dt= FD

(Uf−Up

Vr

), (1)

mpdVp

dt=−Wg+FB+FD

(Vf−Vp

Vr

), (2)

dxp

dt= Up, (3)

dyp

dt= Vp, (4)

where mp and Wg are the mass and weight of the snow par-ticle, respectively; Uf, Vf, Up, and Vp are the horizontal andvertical velocities of the airflow and snow particle, respec-

tively; Vr =

√(Uf−Up)2+ (Vf−Vp)2 is the relative veloc-

ity between the airflow and snow particle; xp and yp are thehorizontal position and vertical height of the snow particle,respectively; FB =

16ρfπD

3g and FD =18CDρfπD

2V 2r are

the buoyancy force and the drag force applied on the snowparticle, respectively; ρf is the air density; D is the diameterof the snow particle; g is the acceleration of gravity; and CDis the drag coefficient.

Within the atmospheric boundary layer, the mean hori-zontal wind velocity u satisfies the Navier–Stokes equation(Werner, 1990). According to Prandtl’s mixing length theoryfor the steady flow fully developed over an infinite planarbed, u satisfies

∂

∂y(ρf κ

2y2∣∣∣∣dudy

∣∣∣∣ dudy)+Fx = 0, (5)

where x is the coordinate aligned with the mean wind direc-tion, y is the vertical direction, κ is the von Karman constant,and Fx is the force per unit volume that the snow particlesexert on the fluid in the stream-wise direction and can be ex-pressed as

Fx =

n∑i=1

mpai, (6)

where n is the number of particles per unit volume of fluid atheight y, and ai is the horizontal acceleration of particle i.

When the bed shear stress is greater than the thresholdvalue, snow particles begin lifting off the surface. The num-ber of aerodynamically entrained snow particles Na is (Shaoand Li, 1999)

Na = ςu∗

(1−

u2∗t

u2∗

)D−3, (7)

where ς is a dimensionless coefficient (1× 10−3 in our sim-ulations), u∗ is the friction velocity, and u∗t is the thresh-old friction velocity. Following the previous saltation models(McEwan and Willetts, 1993), the vertical speed of all aero-dynamically entrained particles is

√2gD.

The following three splash functions for drifting snow pro-posed by Sugiura and Maeno (2000) based on experimentsare used to determine the number and motion state of thesplashed particles.

Sv (ev)=1

βα0(α)eα−1

v exp(−ev

β

)(8)

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N. Huang et al.: The impacts of moisture transport on drifting snow sublimation 7525

Sh (eh)=1

√2πσ 2

exp

[−(eh−µ)

2

2σ 2

](9)

Se (ne)=mCnepne(1−p)m−ne (10)

In Eq. (8), Sv is the probability distribution of the verticalrestitution coefficient ev (the ratio of vertical ejection veloc-ity and vertical impact velocity), 0(α) is the gamma func-tion, and α and β are the shape and scale parameters for thegamma distribution function. In Eq. (9), Shis the probabilitydistribution of the horizontal restitution coefficient eh (the ra-tio of horizontal ejection velocity and horizontal impact ve-locity), and µ and σ are the mean and variance, respectively.In Eq. (10), Se is the probability distribution function of thenumber of ejected particles ne, a binomial distribution func-tion with the mean mpand the variance mp(1−p).

The potential temperature θ and specific humidity q ofthe ambient air satisfy the following conservation equations(considering only two dimensions):

∂θ

∂t+ u

∂θ

∂x+ v

∂θ

∂y=∂

∂x

(Kθ ′

∂θ

∂x

)+∂

∂y

(Kθ∂θ

∂y

)+R1, (11)

∂q

∂t+ u

∂q

∂x+ v

∂q

∂y=∂

∂x

(Kq ′

∂q

∂x

)+∂

∂y

(Kq∂q

∂y

)+R2, (12)

where u is the mean horizontal wind velocity which couldbe calculated by Eq. (5) and v the vertical wind velocity isassumed to be zero here; Kθ ′ , Kθ , Kq ′ , and Kq are the heatand moisture diffusivities due to molecular motion and eddydiffusivity, respectively; R1 and R2 are the source terms dueto snow sublimation. In this study, the wind speed is paral-lel to the horizontal direction; moreover, we hypothesize thatthe temperature and specific humidity are linearly distributedalong this direction. Thus, potential temperature and specifichumidity will satisfy the following prognostic equations

∂θ

∂t=∂

∂y

(Kθ∂θ

∂y

)− u

∂θ

∂x−LsS

ρfC, (13)

∂q

∂t=∂

∂y

(Kq∂q

∂y

)− u

∂q

∂x+S

ρf, (14)

where Kθ = κu∗y+KT and Kq = κu∗y+KV (the sum ofeddy diffusivity and molecular diffusivity, respectively); Sis the sublimation rate summed over all particles at eachheight above the surface, here taken as positive for illustra-tion purposes; Ls is the latent heat of sublimation (2.835×106 J kg−1); C is the specific heat of air; ∂θ

∂xand ∂q

∂xrepre-

sent the horizontal gradient in temperature and specific hu-midity. At the edge of snow surface, we considered the ef-fect of advection and hypothesized that the specific humid-ity in the study domain is linearly distributed along the hor-izontal direction from entrance with qin to outlet with qout.

Thus, the horizontal advection of moisture can be simpli-fied to u(qout−qin)/ l, with l being the length of the domain.Except for snow surface edge, the above setup may be (orpartly) suitable for some heterogeneous snow surfaces, suchas patchy mosaic of snow cover. Additionally, these reasonsencourage us to discuss the effect of moisture advection. Forthe case of infinite and homogenous snow surface, we setqin = qout to avoid advection and considered moisture trans-fer via molecular motion and eddy diffusivity. Besides, weset qin = qout and Kq =Kθ to ignore effect of advection andeddy diffusivity, as a reference case. Correspondingly, sim-ilar process was actualized for θ . The variation of tempera-ture will induce some effects on velocity field, which, how-ever, can be ignored by testing. In our study, the variation oftemperature due to snow sublimation is relatively low and itseffect on velocity field is very small. Thus, we did not takethis effect into consideration.

The total DSS rateQS (kg s−1) of the saltation layer withinthe computational domain is obtained by summing the massloss of all saltating particles in the domain.

QS =∑i

(dmdt

)i

, (15)

where(

dmdt

)i

is the mass loss rate corresponding to the ithparticle. At the air temperature T and undersaturation δ(=1−RH), the rate of mass change of a single particle withdiameter D due to sublimation is (Thorpe and Mason, 1966)

dmdt=

πDδ

LsKTNu (

LsRvT− 1)+ RvT

DvShes

, (16)

where RH is the relative humidity of air, K is themolecular thermal conductivity of the atmosphere(0.024 J m−1 s−1 K−1), Dv is the molecular diffusivityof water vapor in the atmosphere, Rv is the gas constantfor water vapor (461.5 J kg−1 K−1), es is saturated vaporpressure with respect to an ice surface, and Nu and Sh arethe Nusselt number and the Sherwood number, respectively,both of which are dimensionless and depend on the windvelocity and particle size (Thorpe and Mason, 1966; Lee,1975).

Nu= Sh={

1.79+ 0.606Re0.5 0.7< Re< 101.88+ 0.580Re0.5 10< Re< 200

, (17)

where Re=DVr/υ is the Reynolds number and υ is thekinematic viscosity of air.

For the purpose of comparison with the sublimation of sus-pended particles, the initial relative humidity profile in accor-dance with that of Xiao et al. (2000) is

RH= 1−RS ln(y/y0), (18)

where y0 is roughness length and RS = 0.039469.

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7526 N. Huang et al.: The impacts of moisture transport on drifting snow sublimation

The conversion relation between relative humidity andspecific humidity is

q = 0.622 ·es

p− es·RH, (19)

where es = 610.78exp[21.78(T − 273.16)/(T − 7.66)].The constant initial potential temperature θ0 is 263.15 K

(but is 253.16 K in the comparison with Xiao et al., 2000)and the initial absolute temperature is

T0 = θ0

(p

p0

)0.286

, (20)

where p is the pressure and its initial distribution is based onthe hypsometric equation

p = p0 exp(−yg

Rdθ0), (21)

where p0 is taken as 1000 hPa and Rd is the gas constant fordry air (287.0 J kg−1 K−1).

2.2 Calculation procedure

The procedure for the calculations is enumerated below.

1. The length, width, and height of the computational do-main sampled from the saltation layer above the sur-face are 1.0, 0.01, and 1.0 m, respectively. The initialand boundary conditions of temperature and humidityare set from Eqs. (18)–(21).

2. Snow particles are considered as spheres with diameterof 200 µm and density of 910 kg m−3. According to theinvestigation of Nemoto and Nishimura (2001) in a coldwind tunnel, the threshold friction velocity of snow isset to be 0.21 m s−1 and the snow bed roughness 3.0×10−5 m.

3. The initial wind field is logarithmic. If the bed shearstress is greater than the threshold value, particles areentrained from their random positions on the snow sur-face at vertical speed

√2gD and the number of aerody-

namically entrained snow particles satisfies Eq. (7).

4. The snow particle trajectory is calculated usingEqs. (1)–(4) every 0.00001 s in order to obtain the ve-locity used in the calculation of sublimation rate and thenew location of each drifting snow particle to determinewhether the snow particle falls on the snow bed.

5. As the snow particles fall on the snow bed, where theyimpart their energy to other snow particles and splashor eject other snow particles, the velocity and angle ofthe ejected particles satisfy the splash functions, i.e.,Eqs. (8)–(10), according to the motion state of the inci-dent particles and the actual wind field at that time. Thenumber of snow particles is re-counted every 0.00001 s.

Figure 1. Temporal evolution of snow transport rate (the inset fig-ure) and the profile of snow particle number density at the steadystate for three wind force levels.

6. The reactive force Fx that the snow particles exert onthe wind field induces wind modification according toEq. (5).

7. Based on the process above, the velocity and location ofeach drifting snow particle are derived and then used inEqs. (15)–(17) to calculate their sublimation rate every0.00001 s. Under the effect of DSS, potential tempera-ture and specific humidity at different heights under thediffusion or advection moisture transport are calculatedevery 0.00001 s.

8. The new values of wind field calculated in step 6 areused in step 3, and then steps 4 to 7 are recalculated.Such a cycle is repeated to finish the calculation of DSSunder thermodynamic effects. Each calculation takes60 s.

3 Results and discussion

3.1 Wind-blown snow development and the structureof snow drifting

Wind-blown snow has a self-regulating feedback mechanismbetween the saltating particles and the wind field; i.e., snowparticles are entrained and transported by the wind, while thedrag force associated with particle acceleration reduces thewind velocity in the saltation layer, thus limiting the entrain-ment of further particles. Figure 1 illustrates the evolution ofsaltating snow particles in air and also the profile of snow par-ticle number density at steady state. The results show that thetransport rate of particles in air increases rapidly and reachesa steady state after 2–3 s. In steady condition, the number ofsnow particles decreases with height and follows a negative

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N. Huang et al.: The impacts of moisture transport on drifting snow sublimation 7527

Figure 2. Temporal evolution of relative humidity (a) and temperature (b) at 1 cm above the surface for three wind force levels neglectingthe effects of moisture transport, considering only moisture diffusion and both moisture diffusion and advection.

exponential law. Except for the particle in air, the ambientrelative humidity and temperature are also important factorsconcern to DSS.

3.2 Relative humidity and temperature

The relative humidity at 1 cm height for different definedwind velocities generally reaches saturation within 10 s whenmoisture transport is not included (Fig. 2a). Snow subli-mation will not occur, and the temperature will not change(Fig. 2b). However, when moisture transport is included, thesnow sublimation occurs throughout the simulation period,and temperature decreases. Moreover, under the same mois-ture transport mechanism, the greater the wind friction veloc-ity, the higher the relative humidity and temperature change(Fig. 2). The relative humidity at 1 cm shows a trend of rapiddecrease, then rapid increase, and finally a slow increasewhen moisture diffusion is included (Fig. 2a), but the relativehumidity does not reach saturation in the simulation periodof 60 s. Early in the wind-blown snow stage, the sublima-tion rate is smaller as only a few saltating particles sublimeand the moisture at the lower height largely moves outwardsdue to the effect of moisture transport, resulting in relativehumidity decrease. With continuing wind-blown snow, moresnow particles leave the surface, which increases the subli-mation rate and hence the relative humidity. When it reachesa steady state, the amount of snow particles in the saltationlayer will no longer increase but instead fluctuate within acertain range. Thereafter, because of the increase in humidityand cooling, DSS weakens (Fig. 3). The results indicate thatDSS in the saltation layer has a self-limiting nature. Whenthe advection of moisture and heat are considered as well,the temperature and relative humidity will reach steady statefinally. In this case, the transport of moisture and heat bal-ances the change of temperature and relative humidity due toDSS.

3.3 Sublimation rate

From Fig. 3, we can see that DSS has reached steady statewith moisture diffusion and advection considered within60 s, but it is not true for only moisture diffusion considered.By considering of the required time of drifting snow develop-ment and the capability of computer, the simulated time wasset as 60 s, which is significantly surpass drifting snow de-velopment time (about 2–3 s) and could be actualized easilyon a computer. Furthermore, the results are enough to exposethe issues that we care about.

Moisture transport could remove some moisture, attenuat-ing the increase of relative humidity and thus negative feed-back, leading to higher sublimation rates with moisture trans-port than without (Fig. 3). With moisture removal only bydiffusion, the sublimation rate at 60 s is roughly the same atthree wind velocities, meaning that sublimation still showsobvious negative feedback. However, with moisture transportby diffusion and advection, the sublimation rate increasessignificantly as the negative feedback effect is effectively re-duced and will reach steady state. Moreover, the sublima-tion rate increases with the friction velocity and can be evengreater than that at the highest wind velocity without advec-tion. For example, the sublimation rate at 60 s with advectionis 0.88× 10−5 kg m−2 s−1 at a friction velocity of 0.3 m s−1,greater than that of 0.44× 10−5 kg m−2 s−1 at a friction ve-locity of 0.5 m s−1 without considering advection. The sub-limation rate even reaches 1.6× 10−5 kg m−2 s−1, equalingthe 1.38 mm d−1 snow water equivalent at a friction velocityof 0.5 m s−1 with advection included (Fig. 3). Furthermore,sublimation continues to occur. Thus, it can be seen that ef-fective moisture transport can weaken the negative feedbackof sublimation, hence significantly affecting DSS. Becausethe occurrence of wind-blown snow must coincide with theairflow, DSS in the saltation layer is not negligible, and the

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7528 N. Huang et al.: The impacts of moisture transport on drifting snow sublimation

Figure 3. Temporal evolution of drifting snow sublimation rate forthree wind force levels neglecting moisture transport, consideringonly moisture diffusion and both moisture diffusion and advection.

assumption that the saltation layer is a saturation boundarylayer is inadvisable.

Air temperature decreases with decreasing height, alongwith air unsaturation degree during wind-blown snow, whichis adverse to sublimation in contrast to higher heights abovethe surface. Nevertheless, the volume sublimation rate in-creases with decreasing height (Fig. 4). This is in agree-ment with the vertical profiles of the horizontal mass fluxof snow particles (N. Huang et al., 2011). That is, there aremore snow particles that can participate in sublimation atlower heights (Fig. 1), leading to higher sublimation rateseven in environments adverse to sublimation. The results in-dicate that the particle number density is an important con-trolling factor for sublimation rate, which is consistent witha previous study (Wever et al., 2009). A comparison betweenour simulated results and that of four models for suspendedsnow, i.e., PIEKTUK-T, WINDBLAST, SNOWSTORM, andPIEKTUK-B, shows that the local sublimation rate of thesuspended snow at 60 s can reach 10−6 kg m−3 s−1 at most(Xiao et al., 2000) (Fig. 4), smaller than that of our calcu-lated results (10−4–10−3 kg m−3 s−1) by 2–3 orders of mag-nitude at the same initial temperature and relative humidity.This result shows that the assumption that sublimation in thesaltation layer can be ignored by considering it a saturationboundary layer is inadvisable. Therefore, DSS in the saltationlayer is of non-negligible importance and requires further de-tailed study.

4 Conclusions

In this study, we established a wind-blown snow model andbalance equations for heat and moisture to study the effect

Figure 4. Comparison of the sublimation rate for the saltation layerand suspension layer (the inset figure) at 60 s as a function of height.The inset figure shows the sublimation rate of four models for thesuspension layer with initial friction velocity of 0.87 m s−1 reportedin Xiao et al. (2000). Our results for the sublimation rate in the salta-tion layer are obtained for three wind force levels (< 0.87 m s−1)with moisture diffusion and advection included with the same initialtemperature (253.16 K) and relative humidity as Xiao et al. (2000).

of different moisture transport mechanisms on DSS in thesaltation layer. As has been reported (e.g., Schmidt, 1982),DSS could lead to strong increases in humidity and cooling,which in turn can significantly reduce the DSS rate; i.e., DSShas an inherently self-limiting nature. Moreover, the rela-tive humidity in the saltation layer quickly reaches saturationwhen moisture transport is not considered. However, effec-tive moisture transport, such as advection, can dramaticallyweaken the negative feedback of sublimation and prolong theduration of the higher DSS rate and hence has a profound ef-fect on DSS. Because of the presence of advection, DSS rateincreases with the friction velocity and the volume sublima-tion rate of saltating particles is several orders of magnitudegreater than that of the suspended particles due to the higherparticle density in the saltation layer. Thus, DSS in the salta-tion layer plays an important part in the energy and massbalance of snow cover and needs to be further studied.

5 Data availability

The underlying data can be found in the Supplement.

The Supplement related to this article is available onlineat doi:10.5194/acp-16-7523-2016-supplement.

Atmos. Chem. Phys., 16, 7523–7529, 2016 www.atmos-chem-phys.net/16/7523/2016/

N. Huang et al.: The impacts of moisture transport on drifting snow sublimation 7529

Acknowledgements. This work is supported by the State Key Pro-gram of National Natural Science Foundation of China (91325203),the National Natural Science Foundation of China (41371034),and Innovative Research Group of the National Natural ScienceFoundation of China (11421062).

Edited by: J. Huang

References

Allison, I., Brandt, R. E., and Warren, S. G., East antarctic sea ice:albedo, thickness distribution, and snow cover, J. Geophy. Res.,98, 12417–12429, 1993.

Anderson, P. S. and Neff, W. D.: Boundary layer physics over snowand ice, Atmos. Chem. Phys., 8, 3563–3582, doi:10.5194/acp-8-3563-2008, 2008.

Bintanja, R.: Modelling snowdrift sublimation and its effect on themoisture budget of the atmospheric boundary layer, Tellus A, 53,215–232, 2001a.

Bintanja, R.: Snowdrift Sublimation in a Katabatic Wind Regionof the Antarctic Ice Sheet, J. Appl. Meteorol., 40, 1952–1966,2001b.

Dai, X. and Huang, N.: Numerical simulation of driftingsnow sublimation in the saltation Layer, Sci. Rep., 4, 6611,doi:10.1038/srep06611, 2014.

Déry, S. and Yau, M.: A bulk blowing snow model, Bound.-Lay.Meteorol., 93, 237–251, 1999.

Groot Zwaaftink, C. D., Löwe, H., Mott, R., Bavay, M., and Lehn-ing, M.: Drifting snow sublimation: A high-resolution 3-D modelwith temperature and moisture feedbacks, J. Geophys. Res., 116,D16107, doi:10.1029/2011jd015754, 2011.

Groot Zwaaftink, C. D., Mott, R., and Lehning, M.: Seasonal sim-ulation of drifting snow sublimation in Alpine terrain, Water Re-sour. Res., 49, 1581–1590, doi:10.1002/wrcr.20137, 2013.

Huang, J., Zhang, W., Zuo, J., Bi, J., Shi, J., Wang, X., Chang,Z., Huang, Z., Yang, S., Zhang, S., Wang, G., Feng, G., Yuan,J., Zhang, L., Zuo, H., Wang, S., Fu, C., and Chou, J.: Anoverview of the semi-arid climate and environment research ob-servatory over the Loess Plateau, Adv. Atmos. Sci., 25, 906–921,doi:10.1007/s00376-008-0906-7, 2008.

Huang, J., Fu, Q., Zhang, W., Wang, X., Zhang, R., Ye, H.,and Warren, S.: Dust and black carbon in seasonal snowacross northern China, B. Am. Meteorol. Soc., 92, 175–181,doi:10.1175/2010BAMS3064.1, 2011.

Huang, J., Guan, X., and Ji, F.: Enhanced cold-season warm-ing in semi-arid regions, Atmos. Chem. Phys., 12, 5391–5398,doi:10.5194/acp-12-5391-2012, 2012.

Huang, N., Sang, J., and Han, K.: A numerical simulation of theeffects of snow particle shapes on blowing snow development, J.Geophys. Res., 116, D22206, doi:10.1029/2011JD016657, 2011.

Lee, L.: Sublimation of snow in a turbulent atmosphere, PhD thesis,Univ. of Wyo., Laramie, 1975.

Marks, D. and Winstral, A.: Comparison of snow deposition, thesnow cover energy balance, and snowmelt at two sites in a semi-arid mountain basin, J. Hydrometeorol., 2, 213–227, 2001.

McEwan, I. K. and Willetts, B. B.: Adaptation of the near-surfacewind to the development of sand transport, J. Fluid Mech., 252,99–115, 1993.

Nemoto, M. and Nishimura, K. Direct measurement of shear stressduring snow saltation, Bound.-Lay. Meteorol., 100, 149–170,2001.

Pomeroy J. W. and Essery R. L. H.: Turbulent fluxes during blow-ing snow: field tests of model sublimation predictions, Hydrol.Process., 13, 2963–2975, 1999.

Pomeroy, J. W., Gray, D. M., and Landine, P. G.: The Prairie Blow-ing Snow Model: characteristics, validation, operation, J. Hy-drol., 144, 165–192, 1993.

Schmidt, R.: Vertical profiles of wind speed, snow concentrationand humidity in blowing snow, Bound.-Lay. Meteorol., 23, 223–246, 1982.

Shao, Y. and Li, A.: Numerical modelling of saltation in the atmo-spheric surface layer, Bound.-Lay. Meteorol., 91, 199–225, 1999.

Sugiura, K. and Maeno, N.: Wind-tunnel measurements of restitu-tion coefficients and ejection number of snow particles in driftingsnow: determination of splash functions, Bound.-Lay. Meteorol.,95, 123–143, 2000.

Sugiura, K. and Ohata, T.: Large-scale characteristics of the distri-bution of blowing-snow sublimation, Ann. Glaciol., 49, 11–16,2008.

Thorpe, A. D. and Mason, B. J.: The evaporation of ice spheres andice crystals, Br. J. Appl. Phys., 17, 541–548, 1966.

Vionnet, V., Martin, E., Masson, V., Guyomarc’h, G., Naaim-Bouvet, F., Prokop, A., Durand, Y., and Lac, C.: Simulationof wind-induced snow transport and sublimation in alpine ter-rain using a fully coupled snowpack/atmosphere model, TheCryosphere, 8, 395–415, doi:10.5194/tc-8-395-2014, 2014.

Werner, B. T.: A steady-state model of wind-blown sand transport,J. Geol., 98, 1–17, 1990.

Wever, N., Lehning, M., Clifton, A., Ruedi, J. D., Nishimura,K., Nemoto, M., Yamaguchi, S., and Sato, A.: Verifica-tion of moisture budgets during drifting snow conditionsin a cold wind tunnel, Water Resour. Res., 45, W07423,doi:10.1029/2008WR007522, 2009.

Xiao, J., Bintanja, R., Déry, S. J., Mann, G. W., and Taylor, P. A.: Anintercomparison among four models of blowing snow, Bound.-Lay. Meteorol., 97, 109–135, 2000.

Yang, J., Yau, M. K., Fang, X., and Pomeroy, J. W.: A triple-moment blowing snow-atmospheric model and its applicationin computing the seasonal wintertime snow mass budget, Hy-drol. Earth Syst. Sci., 14, 1063–1079, doi:10.5194/hess-14-1063-2010, 2010.

Zhou, J., Pomeroy, J. W., Zhang, W., Cheng, G., Wang, G., andChen, C.: Simulating cold regions hydrological processes usinga modular model in the west of China, J. Hydrol., 509, 13–24,2014.

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