The Effect of Topography and Sea Surface Temperature on ...cml.ust.hk/_sub/_ref/Jung_APJAS2012.pdf · stranded in deep drifts. The cost of the damage was expected ... that blew the

Asia-Pacific J. Atmos. Sci., 48(3), 259-273, 2012

DOI:10.1007/s13143-012-0026-2

The Effect of Topography and Sea Surface Temperature on Heavy Snowfall in the

Yeongdong Region: A Case Study with High Resolution WRF Simulation

Sun-Hee Jung, Eun-Soon Im, and Sang-Ok Han

National Institute of Meteorological Research, Korea Meteorological Administration, Korea

(Manuscript received 4 November 2011; revised 5 April 2012; accepted 6 April 2012)© The Korean Meteorological Society and Springer 2012

Abstract: An analysis of the heavy snowfall that occurred on 11-14

February 2011 in the Yeongdong region along the eastern coast is

presented. Relevant characteristics based on observation and model

simulations are discussed with a focus on the times of maximum

snowfall in Gangneung (GN) and Daegwallyong (DG). This event

was considered part of the typical snowfall pattern that frequently

occurs in the Yeongdong region due to the prevailing northeasterly

flow. The control simulation using the high resolution Weather

Research and Forecasting (WRF) model (1 km × 1 km) showed

reasonable performance in capturing the spatial distribution and

temporal evolution of precipitation. The area of precipitation maxima

appeared to propagate from the plain coastal region further into the

inland mountainous region, in relation to the location of convergence

zone. In addition, a series of sensitivity experiments were performed

to investigate the effect of topography and sea surface temperature

(SST) on the formation of heavy snowfall. The change of topography

tended to modulate the topographically induced mechanical flow,

and thereby modify the precipitation distribution, which highlights

the importance of an elaborate representation of the topography. On

the other hand, the sensitivity experiment to prescribe positive

(negative) SST forcing shows the enhanced (suppressed) precipi-

tation amount due to the change of the sensible and latent heat

fluxes.

Key words: Heavy snowfall, topography and SST effect, WRF

simulation

1. Introduction

The Yeongdong region frequently suffers various severe

weather events such as heavy precipitation and downslope

windstorm, mostly due to the combined effect of its steep

mountain slopes (Taebaek mountain range) and close proximity

to the ocean (East Sea) (Chung et al., 2004; Kim et al., 2005;

Kim and Chung, 2006; Lee et al., 2006; Han and Lee 2007;

Lee and Kim 2008b; Chang et al., 2009; Lee and In, 2009). Of

particular concern is the heavy snowfall during the winter

season because of its frequent occurrence and negative impacts

on the ecosystem and economy. Recently, exceptionally heavy

snowfall occurred on 11-14 February 2011 in the Yeongdong

region along the eastern coast, resulting in tremendous damage

to traffic flow, agriculture, and fishery. The total snow amount

in Donghae (DH) was 134.7 cm (11-14 Feb.), and the 24-hour

accumulated fresh snow in Gangneung (GN) was 77.7 cm (11

Feb.), which is the highest value recorded since observations

started in 1911. This event, considered the heaviest snowfall in a

century on South Korea’s east coast, paralyzed the community

and caused widespread chaos. Hundreds of houses collapsed

under the weight of the snow while hundreds of motorists were

stranded in deep drifts. The cost of the damage was expected

to run to approximately US 65,000,000 dollars (http://www.

safekorea.go.kr).

According to the brief press release by the Korea Meteor-

ological Administration, several typical factors contributed to

this unprecedented event. First, a well developed Siberian High

expanding over the East Sea formed a synoptic pressure pattern

that blew the cold northeasterly winds onto the eastern coastal

region. Secondly, as this continental cold air mass persistently

advected and passed over the relatively warm sea surface, it

was rapidly modified by large oceanic heat and moisture

fluxes, which enhanced the vertical instability. In addition, the

Low pressure located in the southeastern Sea of Japan played a

role in keeping the persistent northeasterly flow in the eastern

coastal region from blocking the closed meso-scale Low

developing at the eastern Sea of the Korean peninsula. These

factors combined to provide a favorable condition for extended

heavy snowfall.

Several previous studies have examined heavy snowfalls in

the Yeongdong region based on both observations and

numerical model experiments. Most of these studies indicated

that the orographic lifting due to the Taebaek mountain range

and the abundant moisture and heat from the East Sea were the

causes of the more frequent and heavier snowfall compared to

other regions. Lee and Kim (2008a) postulated topographic

effect as the key factor in the formation of heavy snowfall in

the Yeongdong region through an experiment that removed the

topography over the Taebaek Mountains. Lee and Lee (1994)

also showed that the height of the topography significantly

affects the amount of snowfall. On the other hand, Ahn and

Cho (1998) highlighted the importance of sea surface tempera-

ture (SST) in the simulation of heavy snowfall events in the

Yeongdong region based on a meso-scale model experiment.

In this study, we attempt to simulate the snowfall event that

occurred on 11-14 February 2011 in the Yeongdong region

Corresponding Author: Eun-Soon Im, 401 Education Service Center,Gangnueng-Wonju National University, 7, Jukheon-gil, Gangneung-si, Gangwon-do 201-702, Korea.E-mail: [email protected]

260 ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES

using the high resolution Weather Research and Forecasting

(WRF) system (1 km × 1 km). The model results are evaluated

by comparison with station observations in terms of spatial

distribution and temporal evolution. Assessing the model sys-

tem’s capability of capturing observed features can provide

some confidence in interpreting the following sensitivity experi-

ments. To better understand the effect of the topography and

SST on the formation of heavy snowfall, a series of ex-

periments are performed. In the sensitivity experiment for

topography effect, the topography is smoothed by using 10-min

United States Geological Survey (USGS) dataset (EXP_T1)

while the control experiment (CONT) uses 30-sec data,

resulting in different topographic features despite the same

resolution of the two experiments (See Fig. 1). In the sensitivity

experiment investigating the SST effect, SST is uniformly

increased (decreased) by 2 K over the ocean areas within the

interior domain when interpolating the initial and lateral

boundary conditions (EXP_S1 & EXP_S2). Additionally, a

sensitivity experiment is performed to prescribe the SST as a

constant in order to examine the effect of horizontal gradient of

the SST distribution (EXP_S3, See Table 1). By comparison

with CONT, EXP_T1 present an ideal of the topography effect

while EXP_S1-3 reveals the influence of SST condition on the

resultant snowfall intensity.

In section 2 we briefly describe the model configuration and

experiment design. The synoptic condition and the relevant

characteristics of the snowfall event are explained in section 3.

The results for the control (CONT) and four kinds of sensitivity

experiment (EXP_T1 and EXP_S1-3) were then validated and

compared in section 4. Finally, the summary and discussion

are presented in section 5.

2. Model configuration and experiment design

The numerical model used in this study is the WRF (version

Fig. 1. The model domain and topography (upper panels), and vertical transects of the surface elevation along the line between points A and B(lower panels) used for the CONT (a, c) and EXP_T1 (b, d) simulations. Topography is represented with shading based on scale at right of the (b).

Table 1. Summary of numerical experiments.

Experiment Topography SST

CONT 30sec. resolution data set Default

EXP_T1 10-min. resolution data set Default

EXP_S1 Same as CONT + 2 K

EXP_S2 Same as CONT − 2 K

EXP_S3 Same as CONT No horizontal gradient (SST = constant)

31 August 2012 Sun-Hee Jung et al. 261

3.2.1) described by Skamarock et al. (2008). The WRF model

is a next-generation meso-scale numerical weather prediction

system designed to serve both operational forecasting and

atmospheric research needs. The Advanced Research WRF

solver developed at the National Center for Atmospheric Re-

search was used for the dynamic core, which is a fully com-

pressible and non-hydrostatic model. The physical parameter-

izations employed in this simulation include the 5-layer thermal

diffusion land-surface model (Chen and Dudhia. 2001), the

Yonsei University (YSU) planetary boundary layer scheme

(Hong et al., 2006), the Rapid Radiative Transfer Model

(RRTMG) longwave radiation scheme (Malwer et al., 1997;

Iacono et al., 2008), Goddard shortwave radiation scheme (Tao

et al., 1989), the Double-Moment (WDM) 6-class microphysics

scheme (Lim and Hong, 2010), and none cumulus parameter-

ization scheme. The WDM 6-class scheme consists of six

hydrometeors: vapor, cloud water, cloud ice, rain, snow, and

graupel. This scheme is considered the most suitable for cloud-

resolving grid. Through various sensitivity experiments, we

determined the optimal selection and combination among the

variety of physical parameterizations.

Figure 1a shows the model domain and topography for the

CONT experiment. The domain focused on the eastern part of

Korean peninsula where the snowfall event selected in this

Fig. 2. Spatial distribution of SST used in (a) CONT, (b) EXP_S1, (c) EXP_S2 and the difference field between CONT and (d) EXP_S3.


study was concentrated. The horizontal resolution was 1 km ×

1 km with 400 × 400 grid points while 31 vertical levels were

employed up to 50 hPa. We also carefully selected the domain

area through several sensitivity tests since the simulation

results may have been affected by the domain size and location

of the lateral boundaries (Seth and Giorgi, 1998). This domain

was determined as a suitable compromise between the accuracy

and computational efficiency.

In addition to the CONT simulation, a series of sensitivity

experiments were performed and major features of the experi-

ments are summarized in Table 1. The first sensitivity

experiment (EXP_T1) used smoothed topography from the 10-

min resolution dataset produced by USGS while CONT used

30-sec data to setup the topography. Since topography exerts a

strong dynamic forcing, accurate representation plays a key

role in intensifying the vertical motion and resultant snowfall.

Both CONT (Fig. 1a) and EXP1_T1 (Fig. 1b) topography

reasonably represented the main mountainous feature with the

most prominent ranges extending from north to south along the

eastern coastal regions (Taebaek Mountains). However, signifi-

cant finer-scale details were only captured by the CONT

topography (a). Therefore, the orographic features were quite

different despite the same resolution (1 km × 1 km) of the two

experiments. Compared to the vertical cross-section of topog-

raphy (Figs. 1c and 1d), this characteristic was more clearly

revealed and further emphasized the necessity of detailed

orographic features in a topographically diverse region. Note

that even the topography in the 1-km resolution of CONT (Fig.

1c) did not fully resolve the fluctuating feature of elevation, as

observed in the 30-sec resolution global dataset produced by

USGS (not shown). However, this is currently considered the

state-of-the-art resolution for numerical simulation.

The second type of sensitivity experiment was performed by

varying the SST condition. We prescribed the SST over the

ocean areas uniformly by adding and subtracting 2 K from the

SST used for the CONT experiment when interpolating the

initial and boundary conditions. Based on the variation of SST

in February during the period 1981-2012 (not shown), the SST

mostly varied in the range of −1 K to 1 K which implied that

abnormally warm (cold) SST was above (below) 2 K. Figure 2

presents the spatial distribution of SST used as the initial

condition for the CONT (a), EXP_S1 (b) and EXP_S2 (c)

experiments. We also performed the sensitivity experiment to

prescribe the SST as constant, which is the area-averaged value

over the ocean area. In case of the initial condition, EXP_S3

prescribed the SST as 280 K without any spatial gradient. In

that case, the SST of the north area was higher than that of

CONT, while the SST of the south area was lower than that of

CONT region (Fig. 2d). SST is an important factor because the

ocean is the source of moisture and heat for snowfall formation.

Higher SST can modify the vertical fluxes of heat and mois-

ture in the atmospheric boundary and produce convection (Cha

et al., 2011), which increases the intensity of the snowfall.

Interpretation of the simulations with different SST conditions

promises to increase our understanding of how higher (lower)

SST affects the simulation of the vertical and horizontal

meteorological fields and the resultant snowfall amount.

The initial and time-dependent lateral boundary conditions

were interpolated using the Korea Local Analysis and Predic-

tion System (KLAPS) with a horizontal resolution of 5 km ×

5 km at 1-hour intervals (Hwang et al., 2011). The integration

spanned from 0000 UTC on 10 February to 0000 UTC on 15

February, 2011, when the record-breaking snowfall event hit

the target region.

3. Observational synoptic condition and general charac-teristics

We begin our analysis with a discussion on the synoptic

overview based on the observation. Figure 3 shows the surface

weather chart at 1500 UTC 11 February (a) and 0000 UTC (b)

12 February 2011 when the snowfall reached the peak in

Gangneung (GN) and Daegwallyong (DG), respectively (Figs.

8a and 8c). A well developed Siberian High was dominant

across the huge continent of East Asia while a Low pressure

accompanied with a front was located over the southeastern Sea

of Japan. Such a synoptic map, the so-called “Northern High

Southern Low”, is a typical pattern to maintain northeasterly

over the Yeongdong region (Lee et al., 2011). Although the

general patterns between two synoptic maps appear to be

similar, several detailed features are different. Compared to

1500 UTC 11 February, the Siberian High extended eastward

and a more intense pressure gradient was found over the

Korean peninsula at 0000 UTC 12 February. The isobars at

0000 UTC were also tilted rather perpendicularly over the East

Sea, which is directly related to the wind direction (See Fig. 9).

The Low pressure around the southeastern Sea of Japan was

deepening and moving toward the Western Pacific. In spite of

the eastward propagation of this Low, the meso-scale Low

developing over the eastern part of the East Sea appeared to be

blocked. This closed Low was a main factor that maintained

the strong and prevailing northeasterly in the Yeongdong

region (Park et al., 2009), and thus caused the long-lasting

snowfall. Since the prevailing northeasterly can reach further

inland, the observed area of the snowfall maxima moved to

inland mountainous region (e.g., DG) from the eastern coastal

region (e.g., GN and DH).

Figure 4 shows observational surface wind fields based on

station data corresponding to the synoptic patterns shown in

Fig. 3. Since the distances between the stations were much

coarser than those of model grid and only several observational

stations were included in the model domain, it was rather

difficult to compare this with simulated wind field (Fig. 9) for

accurate quantitative validation. However, observational wind

fields can provide the reference for the qualitative behavior of

the change of wind direction in the Yeongdong region. The

change of wind direction at 1500 UTC 11 February (a) and

0000 UTC 12 February (b) 2011 well explains the movement

of the maximum snowfall. The northwesterly that appeared in

GN was caused by the northeasterly that was blocked due to


Fig. 3. Synoptic surface weather chart at 1500 UTC 11 February (upper) and 0000 UTC 12 February (lower) 2011.


the mountain barrier when the maximum snowfall occurred

along the plain coastal region (Fig. 4a). However, after 9 hours

(Fig. 4b), the prevailing northeasterly in the Yeongdong region

supported the movement of the snowfall maximum in further

inland.

The intensification of snowfall at 1500 UTC 11 February

and 0000 UTC 12 February can also be explained by the field

of 850 hPa equivalent potential temperature derived from

KLAPS which are used as initial and lateral boundary con-

ditions (Fig. 5). Compared to 9-hour before (0600 UTC 11

February, Fig. 5a), the gradient of the equivalent potential

temperature at 1500 UTC 11 February became more dense

(Fig. 5b). The wedge form of equivalent potential temperature

(especially 276 K) gradually propagated to the east coast over

time. Eventually, the reference line of 276 K became located

toward southeastern part of the Korea peninsula at 0000 UTC

12 February (Fig. 5c). This implies that the encounter area

between the cold air advected from the north and the warm and

humid air advected from the East Sea moved to along the east

coast and thereby provided a favorable condition for heavy

snowfall.

Figure 6 presents the spatial distribution of 3-hour accumu-

Fig. 4. Surface wind field from observation valid at (a) 1500 UTC 11 February and (b) 0000 UTC 12 February 2011.

Fig. 5. 850 hPa equivalent potential temperature (θe) at (a) 0600 UTC, (b) 1500 UTC 11 February, and (c) 0000 UTC 12 February 2011. Blue and

red arrows schematically represent the cold and warm advections, respectively. The red dotted line is the reference line of 276 K.


lated precipitation from 1300 to 1500 UTC 11 February (a),

and 2200 to 2400 UTC 11 February (b), and 4-day accumu-

lated precipitation during 11-14 February 2011 (c). By compari-

son with (a) and (b), the precipitation band evolved over time,

moving to the maximum location from GN to DG, which

corresponded to the synoptic condition shown in Fig. 3. The

distribution of total accumulated precipitation showed a gradient

pattern, with decreasing amount of precipitation towards inland.

This event broke several records. The 24-hour accumulated

fresh snow amounts in GN observational station were 77.7 cm

and 49 cm on 11 and 12 February, respectively, which were the

first and second highest since records began there back in

1911. In particular, the new first rank 77.7 cm snowfall was

much higher than the previous highest of 48.5 cm (12 Dec.

2008). The 24-hour accumulated fresh snow (11 Feb.) in DH

observational station at 70.2 cm was also the highest ever

recorded. The records of maximum depth of snow in GN (12

Feb.) and DH (14 Feb.) were also all-time records.

4. Results

a. Validation of the control experiment

Figure 7 presents the spatial distribution of 3-hour accumu-

lated precipitation at 1300 to 1500 UTC 11 February (a), and

2200 to 2400 UTC 11 February (b), and 4-day accumulated

precipitation during 11-14 February 2011 (c) derived from the

CONT simulation. These model results were qualitatively in

good agreement with the observed estimates as shown in Fig.

6. For the accumulated pattern during 1300 to 1500 UTC 11

February, the model simulated more precipitation at GN than

at DG, showing an intensive precipitation band along the coast

sea. However, after 9 hours, the maximum location of pre-

cipitation moved to DG, in line with the observed distribution.

Also captured is the gradient pattern of precipitation amount

such as less precipitation toward inland for the 4-day total

accumulated precipitation during 11-14 February.

In order to provide a more quantitative measure of the per-

Fig. 6. Spatial distribution of the 3-hour (1300-1500 UTC and 2200-2400 UTC 11 Feb) and 4-day (11-14 Feb) accumulated precipitation derivedfrom observations. Precipitation is represented with shading based on the scale at right of (c). Here, GN, DH, and DG indicate the observationalstations at Gangneung, Donghae, and Daegwallyong, respectively.

Fig. 7. Same as Fig. 6, except for the CONT simulation.


formance of the model, we examined the temporal evolution of

the three stations hit by the heavy snowfall. Figure 8 presents

the time-series of every 3-hour accumulated precipitation GN,

DH, and DG stations, derived from the observations and

CONT simulation. We compared simulated precipitation with

individual station values using the grid points closest to the

stations. The relatively high model resolution (1 km) justified

the comparison between station data (Im et al., 2008) and

closest grid point model data. The temporal evolution exhibited

a bimodal structure having two peaks with different maximum

amounts, regardless of the stations. Generally, the model

showed good phase coherence with the observed variation. The

correlation coefficients at GN, DH, and DG were 0.70, 0.72,

and 0.70, respectively. The model demonstrated the capability

to capture the timing of maximum precipitation despite the

presence of quantitative discrepancies between the observed

and simulated estimates. For GN and DH, the model tended to

underestimate the maximum amount. In particular, the maxi-

mum amount of GN was only approximately half of the

observation. On the other hand, the model exactly captured the

timing and amount of the maximum at DG, while a large error

occurred in the second maximum when the observation

showed very weak intensity.

To explain the synoptic condition to derive this movement of

the precipitation band, we examined the surface wind and

streamline at the same time of the observed surface weather

chart, as shown in Fig. 3 from the CONT simulation (Fig. 9).

The prevailing winds (Figs. 9a and 9c) tended to be approxi-

mately parallel to the isobars presented in the observed surface

weather chart. When the snowfall peaked along the Yeongdong

coastal area (e.g., GN and DH), rather than the ridge of the

mountain (DG) (1500 UTC 11 February, Fig. 9a), the north-

Fig. 8. Time-series of 3-hour accumulated precipitation from 11 to 14 February 2011 derived from the observation and CONT simulation atGangneung (GN; upper), Donghae (DH; middle), and Daegwallyong (DG; lower).


easterly appeared to be blocked due to the mountain barrier

and the wind direction turned to northwesterly along the foot

of the mountains. This cold northwesterly flow then merged

with the relatively warm and moist northeasterly or easterly

advecting from further offshore areas. This collision induced

heavy snowfall along the coast by providing a favorable

condition for the convergence (Alestalo et al., 1985; Yeh and

Chen., 2002). Indeed, the streamline at the same time (Fig. 9b)

clearly reveals the discontinuity line, implying the convergence

zone along the coastal area. Moving to the peak time at DG

(Figs. 9c and 9d), the discontinuity line stepped forward further

inland, possibly due to the change of wind direction and

magnitude. The magnitude of the prevailing northeasterly

became intense approximately perpendicular to the Yeongdong

coast, so that it reached far toward inland. This difference

underlying the synoptic background was attributed to the

change of the area in which the snowfall maxima occurred.

b. Analysis of the sensitivity experiment for topography effect

Figure 10 presents the 4-day total accumulated precipitation

(11-14 Feb.) simulated by EXP_T1 (a) and their differences

from the CONT simulation (b). By comparison, although the

area-averaged amount of precipitation (over the whole domain)

Fig. 9. Surface wind fields (left) and streamline (right) at 1500 UTC 11 February (upper panels) and 0000 UTC 12 February (lower panels) 2011from the CONT simulation.


Fig. 11. Vertical cross-section of the u-w vector derived from the CONT (upper), and EXP_T1 (lower) simulations at 1500 UTC 11 February (left)and 0000 UTC 12 February (right) 2011.

Fig. 10. Spatial distribution of (a) the 4-day (11-14 Feb) total accumulated precipitation derived from the EXP_T1 simulations, and (b) theirdifferences from the CONT simulation. Precipitation is represented with shading based on scale at the right of (a) and (b). Here, GN, DH, and DGindicate the observational stations at Gangneung, Donghae, and Daegwallyong, respectively.


derived from EXP_T1 was mostly similar to that of CONT

(CONT = 25.4 mm and EXP_T1 = 26.1 mm), the difference

field revealed that the spatial details were rather different. The

EXP_T1 with its smoothed topography tended to simulate a

more widespread distribution of the precipitation, but with lower

amounts of localized maximum compared to CONT. Since the

peak of the moderate slope of the EXP_T1 topography was

located further inland (See Fig. 1d), the northeasterly could

reach relatively far from offshore and deliver more moisture

inland. This implies that the change of topography tended to

modulate the topographically induced mechanical flow, resulting

in the modification of the precipitation distribution. Therefore,

the precipitation was enhanced around the mountainous area

and the corresponding reduction was aligned nearly parallel to

the coastal area.

For more detailed analysis, we provide the vertical cross-

sections of the u-w vector (Fig. 11) along the line passing

through the GN and DG stations (See Figs. 1c and 1d) at 1500

UTC 11 February (a, c) and 0000 UTC 12 February (b, d)

2011 when the snowfall reached the peak in GN and DG,

respectively. At the peak time in GN, upward and downward

flows along the mountain ridge and valley are found over

mountains in CONT. In particular, on the windward of the

Taebaek Mountains, the vertical flows lifting along the steep

mountain slope appears to be descent due to blocking effect,

forming the cold air dome on the foot of the mountains. This

cold air encounters the warm and moist air flow from the

ocean, leading to convergence. On the other hand, EXP_T1 do

not develop such a vertical circulation and the flows are

extremely weak over mountains. There is few orographic

lifting on the windward slope of the mountains. It suggests that

the representation of realistic topography can play a critical role

to control the vertical structure of the wind, directly affecting

the resultant snowfall simulation. Moving to the peak time in

DG, the magnitude of the upward motion at the steep mountain

slope became stronger, and thus propagated further inland. The

stronger orographic lifting going over the mountain induced

heavy snowfall in DG station. EXP_T1 also showed an

Fig. 12. Spatial distribution of the divergence field derived from the CONT (upper), EXP_T1(lower) simulations at 1500 UTC 11 February (left)and 0000 UTC 12 February (right) 2011. Convergence (red) and divergence (blue) are represented with shading based on the scale at right.


upward motion along the mountain slope, but the magnitude

was relatively weak and the pattern appeared to be artificial.

This figure again confirmed the importance of an elaborate

representation of the topography by means of the modification

of the topographically induced mechanical flow.

Figure 12 shows the same quantities as Fig. 11 except for the

spatial distribution of the convergence and divergence fields.

Convergence (divergence) is taken as a proxy of the strength

of dynamical distribution. A comparison between the peak

time in GN and DG revealed the westward propagation of the

convergence zone toward inland. This behavior matched the

vertical cross-section of the u-w vector reasonably well. For

CONT, the spatial distribution of the convergence and diver-

gence over the land area were quite inhomogeneous, reflecting

the topographical signal. On the contrary, complex regional

variations mostly disappeared in the EXP_T1 pattern.

c. Analysis of the sensitivity experiment for SST effect

Figure 13 presents the 4-day total accumulated precipitation

(11-14 Feb.) simulated by three kinds of SST sensitivity

experiment (a, b, and c) and their differences from the CONT

simulation (d, e, and f). The spatial distribution and the amount

of precipitation were directly correlated with the SST forcing

in the positive and negative ways. Positive forcing (increasing

SST) enhanced the precipitation while negative forcing (de-

creasing SST) suppressed the precipitation. The difference

fields clearly represent the spatial distribution of the precipita-

tion enhancement or suppression regions compared to the

CONT simulation. In the case of EXP_S1 (EXP_S2), the

higher (lower) SST prescribed over the East Sea effectively

produced more (less) precipitation, showing a dominant

positive (negative) sign. On the other hand, EXP_S3 exhibited

a mixed pattern. Consistently with the SST difference (Fig.

2d), the EXP_S3 simulated more precipitation over the north

area with higher SST than that of CONT and less precipitation

over the south area with lower SST than that of CONT.

Increasing SST tends to enhance the precipitation as

considerable moisture and heat flux are supplied (Kang and

Ahn, 2008; Cha et al., 2011). Therefore, the results shown in

Fig. 13 were somewhat expected. To verify this point, we

investigated the thermodynamical effect due to the change of

Fig. 13. Spatial distribution of the 4-day (11-14 Feb) total accumulated precipitation derived from the EXP_S1, EXP_S2, and EXP_S3 simulations(a, b, and c), and their differences from the CONT simulation (d, e, and f). Precipitation is represented with shading based on the scale at the right of(c) and (f). Here, GN, DH, and DG indicate the observational stations at Gangneung, Donghae, and Daegwallyong, respectively.


the moisture and heat fluxes. Figure 14 displays the spatial

distribution of the sensible and latent heat flux derived from

CONT and three SST sensitivity experiment. Compared to the

SST distribution (Fig. 2), the regions with higher sensible and

latent fluxes generally coincided with the SST pattern. The

sensible and latent heat flux were similar, which was attributed

Fig. 14. Spatial distribution of the time-averaged sensible heat flux (a, c, e, and g) and latent heat flux (b, d, f, and h) from the CONT, EXP_S1,EXP_S2 and EXP_S3 simulations of the 4-day (11-14 Feb) total accumulated precipitation. Sensible heat flux and latent heat flux are representedwith shading based on the scale at the right of (a) and (b).


to the SST pattern. In the experiment with SST gradient

(CONT, EXP_S1 and EXP_S2), rather zonal gradient pre-

dominated with a maximum over warmer ocean area, whereas

EXP_S3 tended to have a northward gradient with the maxi-

mum around the north boundary area. Both maximums

appeared to occur in the region with a larger difference between

SST and the upper air temperature. For instant, in EXP_S3

with the constant SST fields, a more favorable thermal envir-

onment for cold air modification occurred in the north areas

where the upper airflows tended to reach earlier due to the

weakening of the upward transfers of moisture and heat as the

cold upper air passed by the relatively warm ocean and gained

energy. Therefore, the SST condition can thermodynamically

modify the heat fluxes, thereby modulating the main source of

energy for the formation of heavy snowfall.

5. Summary and discussion

In this study, we investigated the synoptic overview and

relevant characteristics of the unprecedented heavy snowfall

that occurred on 11-14 February 2011 in the Yeongdong region.

This event can be explained within the framework of the typical

type of Yeongdong heavy snowfall. When the northeasterly

winds caused by the extension of the Siberian High passed

through the relatively warm sea surface, they brought abundant

heat and moisture fluxes from the ocean. Their subsequent

encounter with the cold and dry air flows that had been turned

down due to the effect of mountain blocking gave rise to a

convergence zone. Furthermore, the closed meso-scale Low

that developed over the eastern part of the East Sea maintained

the strong and prevailing northeasterly in the Yeongdong

region, which produced a favorable condition for long lasting

heavy snowfall. Interestingly, the area of snowfall maxima

tended to move from the plain coastal area to the inland

mountainous area. It is related to the magnitude and direction

of the northeasterly, which affected the location of the con-

vergence zone.

To simulate this snowfall event and extend our understanding

of the key factors for the formation of heavy snowfall, we used

the WRF numerical model with a high resolution (1 km ×

1 km) with a focus on the Yeongdong region. We performed

one control experiment (CONT) and two types of sensitivity

experiment to examine the topography and SST effect for the

heavy snowfall (EXP_T1, and EXP_S1, S2, S3). We first

validated the CONT simulation against the station observations.

The CONT simulation reproduced the spatial distribution and

temporal evolution of the precipitation very well. In particular,

the movement of the snowfall maximum from the coastal

region (e.g., GN and DH) to the Taebaek Mountains (DG) was

well captured in spite of the quantitative discrepancy. Given

this validation of the model performance, we performed two

types of additional sensitivity experiment, one for topography

effect (EXP_T1) and one for SST effect (EXP_S1, S2, S3).

EXP_T1 used the smoothed topography derived from 10-min

USGS dataset while EXP_S1(S2) prescribed SST uniformly by

adding (subtracting) 2 K and EXP_S3 prescribed SST as

constant by removing the spatial gradient as the initial and

boundary conditions; all the other conditions were held

identical. A comparison between CONT and the two types of

sensitivity simulations revealed the role of topography and SST

in the formation of heavy snowfall. EXP_T1 with unrealisti-

cally smoothed topography did not accurately simulate the

vertical circulation with repeated upward and downward motion

along the mountain ridges and valleys. Both the resolution and

the orographic feature critically affected the formation of heavy

snowfall by modifying the topographically induced mechanical

flows, which changed the spatial distribution of snowfall. The

SST sensitivity experiment clearly showed that the higher

(lower) SST tended to enhance (suppress) the precipitation

amount because the SST condition could modulate the inten-

sity of sensible and latent heat fluxes that acted as the source of

energy for the formation of heavy snowfall.

Except for the topography and SST, many factors determine

the snowfall in the Yeongdong region, such as air mass

modification, strength of the northeasterly, and the difference

between air temperature and SST. We will examine the detailed

effects applying to a variety of snowfall events in a future

work, which will generate more robust results. Such a study

will enhance our understanding of the mechanism of the heavy

snowfall event. Eventually, we will develop effective strategies

for preventing or reducing the damage caused by heavy

snowfall.

Acknowledgements. This work was supported by a grant (code

No. 3100-3136-442) funded by the National Institute of

Meteorological Research (NIMR), the Korea Meteorological

Administration (KMA).

REFERENCES

Ahn, J. B., J. H. Oh, and E. H. Cho, 1998: A mesoscale atmosphere/ocean

coupled model experiment for a heavy snowfall event in Korean

peninsula. J. Korean Meteor. Soc., 34, 652-663. (In Korean with

English abstract)

Alestalo, M., and H. Savijärvi, 1985: Mesoscale circulations in a

hydrostatic model: Coastal convergence and orographic lifting. Tellus,

37A, 156-162.

Cha, Y.-M., H.-W. Lee, and S.-H. Lee, 2011: Impacts of the High-

Resolution Sea Surface Temperature Distribution on Modeled Snowfall

Formation over the Yellow Sea during a Cold-Air Outbreak. Wea.

Forecasting, 26, 487-503.

Chang, H., J. Franczyk, and C. Kim, 2009: What is responsible for

increasing flood risks? The case of Gangwon Province, Korea. Nat.

Hazards, 48, 339-354.

Chen, F., and J. Dudhia, 2001: Coupling and advanced Land surface-

hydrology model with the Penn State-NCAR MM5 modeling system.

Part: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569-

585.

Chung, G.-B., J.-Y. Kim, and T.-Y. Kwon, 2004: Characteristics of Lower-

Tropospheric Wind Related with Winter Precipitation in the Yeongdong

Region. J. Korean Meteor. Soc., 40, 369-496. (In Korean with English

abstract)

Han, S.-H., and J.-G. Lee, 2007: Numerical Simulation Study on the


Sensitivity of WRF Model in the Wind Field to the Steepness of

Mountain Slopes. Atmosphere, 17, 349-364. (In Korean with English

abstract)

Hong, S.-Y., Y. Noah, and J. Dudhia, 2006: A new vertical diffusion

package with an explicit treatment of entrainment processes. Mon. Wea.

Rev., 134, 2318-2341.

Hwang, Y.-J., J.-C. Ha, Y.-H. Kim, K.-H. Kim, E.-H. Jeon, and D.-E.

Chang, 2011: Observing System Experiments Using KLAPS and

3DVAR for the Upper-Air Observations over the South and West sea

during ProbeX-2009. Atmosphere, 21, 1-16. (In Korean with English

abstract)

Iacono, M. J., J. Delamere, E. Mlawer, M. Shephard, S. Clough, and W.

Collins, 2008: Radiative forcing by long-lived greenhouse gases:

Calculations with the AER radiative transfer models. J. Geophys. Res.,

113, D13103, doi:10.1029/2008JD009944.

Im, E.-S., W.J. Gutowski Tr., and F. Giorgi, 2008: Consistent changes in

twenty-first century daily precipitation from regional climate simulations

for Korea using two convection parameterizations. Geophys. Res. Lett.,

35, L14706, doi:10.1029/2008GL034126.

Kang, S.-D., and J.-B. Ahn, 2008: Numerical Study on the Formation and

Maintenance Mechanisms of Cloud Street in the East Sea during Cold

Air Outbreak. Asia-Pacific J. Atmos. Sci., 44, 105-119.

Kim, J.-E., T.-Y. Kwon, and B. Y. Lee, 2005: Characteristics of Sensible

Heat and Latent Heat Fluxes over the East Sea Related with Yeongdong

Heavy Snowfall Events. Oce. Pol. Res., 27, 237-250. (In Korean with

English abstract)

Kim, J.-H., and I.-U. Chung, 2006: Study on Mechanisms and Orographic

Effect for the Springtime Downslope Windstorm over the Yeongdong

Region. Atmosphere, 16, 67-83. (In Korean with English abstract)

Lee, H., and T. Y. Lee, 1994: The Governing Factors for Heavy Snowfalls

in Youngdong Area. J. Korean Meteor. Soc., 30, 197-218. (In Korean

with English abstract)

Lee, J. G., and Y. J. Kim, 2008a: A numerical case study examining the

orographic effect of the Taebaek mountains on snowfall distribution

over the Yeongdong Area. Atmosphere, 18, 367-386. (In Korean with

English abstract)

______, and ______, 2008b: A numerical simulation study using WRF of

a heavy snowfall event in the Yeongdong coastal area in relation to the

northeasterly. Atmosphere, 18, 339-354. (In Korean with English

abstract)

______, and S. R. In, 2009: A numerical sensitivity experiment of the

downslope windstorm over the Yeongdong region in relation to the

inversion layer of temperature. Atmosphere, 19, 331-344. (In Korean

with English abstract)

______, S-.D. Kim, and Y. J. Kim, 2011: A Trajectory Study on the Heavy

Snowfall Phenomenon in Yeongdong Region of Korea. Asia-Pacific J.

Atmos. Sci., 47, 45-62.

Lee, J.-S., T.-Y. Kwon, and D.-R. Kim, 2006: Statistical Verification of

Precipitation Forecasts from MM5 for Heavy Snowfall Events in

Yeongdong Region. Atmosphere, 16, 124-139. (In Korean with English

abstract)

Lim, K.-S.S., and S.-Y., Hong, 2010: Development of an effective double-

moment cloud microphysics scheme with prognostic Cloud Condensa-

tion Nuclei (CCN) for weather and climate models. Mon. Wea. Rev.,

138, 1587-1612.

Malwer, E. J., S. J. Taubman, P. D. Brown, M. j. Iacono, and S. A. Clough,

1997: Radiative transfer for on-homogeneous atmospheres: RRTM, a

validated correlated-k model for the longwave. J. Geophys. Res., 102,

16663-16682.

Park, J.-H., K.-E. Kim, and B.-K. Heo, 2009: Comparison of Development

Mechanisms of Two Heavy Snowfall Events Occurred in Yeongnam

and Yeongdong Regions of the Korean Peninsula. Atmosphere, 19, 9-

36. (In Korean with English abstract)

Seth, A., and F. Giorgi, 1998: The effects of domain choice on summer

precipitation simulation and sensitivity in a regional climate model. J.

Climate, 11, 2698-2712.

Skamarock, W. C., and Coauthors, 2008: A Description of the Advanced

Research WRF Version 3. NCAR Tech. Note NCAR/TN-475+STR,

125 pp.

Tao, W.-K., J. Simpson, and M. McCumber, 1989: An ice-water saturation

adjustment, Mon. Wea. Rev., 117, 231-235.

Yeh, H., and Y. Chen, 2002: The role of offshore convergence on coastal

rainfall during TAMEX IOP 3. Mon. Wea. Rev., 130, 2709-2730.

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