Near surface climate of the traverse route from Zhongshan Station to Dome A, East Antarctica

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Antarctic Science 22(4), 443–459 (2010) & Antarctic Science Ltd 2010 doi:10.1017/S0954102010000209

Near surface climate of the traverse route from ZhongshanStation to Dome A, East Antarctica

YONGFENG MA1,2, LINGEN BIAN1*, CUNDE XIAO1,3, IAN ALLISON4 and XIUJI ZHOU1

1Chinese Academy of Meteorological Sciences, Beijing 100081, China2College of Earth Science, Graduate University of Chinese Academy of Sciences, Beijing 100049, China

3Laboratory of Ice Core and Cold Regions Environment, Cold and Arid Regions Environmental and Engineering Research Institute,

Chinese Academy of Sciences, Lanzhou 730000, China4Australian Antarctic Division and Antarctic Climate and Ecosystems CRC, Private Bag 80, Hobart, TAS 7001, Australia

*corresponding author: [email protected]

Abstract: Seasonal variation of temperature, pressure, snow accumulation, winds, and their harmonic

analysis are presented by using the data from Zhongshan Station and three Automatic Weather Stations

deployed between the East Antarctic coast and the summit of the ice sheet at Dome A for the period

2005–07. Results show that: 1) temperature, snow accumulation and specific humidity decrease with

increasing elevation and distance from the coast, with snow accumulation decreasing from 199 mm water

equivalent (w.e.) yr-1 at LGB69 (180 km from the coast) to 31 mm w.e. yr-1 at Dome A, 2) Dome A

experiences an extremely low minimum temperature of -82.58C with the monthly mean temperature below

-508C for eight months in contrast to Zhongshan Station which does not show any monthly mean

temperatures below -208C, 3) mean surface wind speed increases from the coast to the escarpment region,

and then reduces rapidly towards the interior plateau with the strongest winds occurring at katabatic sites

with the greatest surface slopes, 4) temperature and pressure all shows a distinct biannual oscillation with a

main minimum in spring and a secondary minimum in autumn, differing slightly from station to station, and

5) winter temperature corelessness increases as a function of elevation and distance from the coast, from

0.260 at the coastal Zhongshan Station to 0.433 at Dome A.

Received 4 June 2009, accepted 16 January 2010

Key words: Antarctic climate, AWS, corelessness, harmonic analysis, katabatic, snow accumulation

Introduction

There are fewer meteorological measurements in the interior

of Antarctica compared to coastal areas, and hence relatively

few studies of snow/ice-atmosphere interaction on the

continent. Automatic Weather Stations (AWS) provide long-

term unmanned observations in remote areas and where

the weather is extremely adverse. In the past two decades,

about 100 AWS have been deployed in different regions

of Antarctica to form local networks. Many of those were

operated as part of large United States networks on the Ross

Sea Ice Shelf and elsewhere (e.g. Stearns & Savage 1981), but

others were contributed by Australia in East Antarctica, Japan

in eastern Dronning Maud Land (Enomoto et al. 1995), and

the Netherlands in western Dronning Maud Land (Reijmer &

Oerlemans 2002). These AWS provide large volumes of

Antarctic climate data which can contribute substantially to

the study of Antarctic weather and climate, including the

relationships of surface temperature, pressure and wind to

ice sheet terrain (e.g. Allison et al. 1993, Stearns et al. 1993,

Allison 1998, Renfrew & Anderson 2002). Automatic

Weather Stations data have also been used to investigate

ice/snow interactions with the atmosphere. Using four years

of successive data from Dronning Maud Land, Van den

Broeke et al. (2004, 2005) described the seasonal variation

of the surface energy balance, as well as its components,

over different regions including the coastal area, the

katabatic wind zone and the interior of the Antarctic

plateau. As well as regional climate studies using AWS, the

data have been used together with multi-year data from

manned stations to estimate secular trends of surface

temperature, pressure and wind speed for the whole of

Antarctica (Turner et al. 2005).

Some problems arise with AWS (e.g. data gaps owing to

icing/riming on the sensors and errors inherent in unmaintained

radiation sensors or with inadequate ventilation of air

temperature sensors), but the applicability of Antarctic

AWS data have been confirmed by comparison with the

data from manned stations (e.g. Allison & Morrissy 1983).

In this paper we use data from three AWS (LGB69,

Eagle and Dome A, see Fig. 1) deployed during 2002–05

between Zhongshan Station (ZS) and Dome A (the summit

of the East Antarctic ice sheet). The locations and site

characteristics for these stations are given in Table I. The

AWS are operated collaboratively by China and Australia,

and data from them supplement data from another network

in the Lambert Glacier basin, north of 76.48S (Allison,

1998).

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Chen et al. (2007) have used data from LGB69 AWS to

discuss the annual variation of atmospheric parameters in

the near-surface layer over Princess Elizabeth Land in the

East Antarctic, and compared the results to those from ZS.

Xiao et al. (2007) and Hou et al. (2007) studied the annual

mean temperature (represented by the firn temperature at

10 m depth) and the annual mean snow accumulation over

Dome A, reporting values of -58.38C and , 16 mm water

equivalent (w.e.), respectively. Xiao et al. (2008) analysed

the ice sheet characteristics and surface climate on Dome A

using ice core records and AWS measurements, and

showed that Dome A is a potential site for providing the

oldest undisturbed ice-core palaeoclimate record.

Automatic weather station measurements and

data analysis

Zhongshan Station is the second Chinese Antarctic station,

established in 1989 in the Larsemann Hills, Prydz Bay, less

than 2 km from the edge of the Antarctic ice sheet.

Conventional surface meteorological observations have

been made there since then. LGB69, Eagle and Dome A

AWS were installed on the ice sheet in Princess Elizabeth

Land, East Antarctica in January 2002 and January 2005

during the 18th and 21st Chinese Antarctic Research

Expeditions (CHINARE). The three AWS have made

continuous observations since their deployment. Their

locations on the traverse route are shown in Fig. 2. These

AWS were designed by the Australian Antarctic Division

and individually calibrated before deployment. They

measure air temperature at nominal heights above surface

of 1, 2, and 4 m, wind speed at 1, 2, and 4 m, wind direction

at 4 m, atmospheric pressure, global radiation, and firn

temperatures at nominal depths of 0.1, 1, 3, and 10 m, as

well as snow surface height (SSH). Table II lists the major

sensors and their resolutions. Sampling frequency is once

per hour and the data are transmitted in real-time through

the Data Collection System (DCS) on the ARGOS

supporting satellite. The data can be directly downloaded

from the ARGOS website through FTP. In this study, we

also made use of data from some other Antarctic stations

provided by the SCAR READER (REference Antarctic

Data for Environmental Research) project (http://www.

antarctica.ac.uk/met/READER/) and the Australian Antarctic

Fig. 1. Topography and AWS locations along the CHINARE traverse route from ZS to Dome A (left) and the AWS at Dome A

(right). The other AWS have similar designs.

Table I. Location and site characteristics of sites in this study.

Site Latitude Longitude Elevation Distance Slope Data period

(m a.s.l.) from coast (km) (m km-1)

Zhongshan 69822'S 76822'E 14.9 0 - 01.2005–12.2007

LGB69 70850'S 77804'E 1854 180 7.3 01.2002–07.2004

Eagle 76825'S 77801'E 2852 787 2.4 01.2005–12.2007

Dome A 80822'S 77822'E 4093 1228 1.8 01.2005–12.2007

444 YONGFENG MA et al.



Automatic Weather Station Dataset (http://aws.acecrc.

org.au/).

The CHINARE traverse route is approximately along

778E longitude, and stretches from sea level at ZS to the

summit of the inland plateau at Dome A by way of the low-

lying coastal zone, an escarpment region (where katabatic

winds prevail), a low surface-slope area on the plateau

(between c. 2000 and 3000 m elevation), and the interior

of Antarctic plateau (elevation . 3000 m). The AWS are

distributed over these representative surface features (see

Fig. 2) and consequently include almost all the climate

types in East Antarctica.

This paper presents the near surface climate using data

from ZS and the three AWS from January 2005–December

2007. The data were filtered to eliminate anomalous values

due to ARGOS transmission errors, and uncertain data

during the first few days of AWS operation were also

eliminated. The effects of sensor height change due to snow

accumulation or ablation were removed by correcting the

observed air and snow temperatures to a real height/depth

relative to the snow surface. This correction was made

using a temperature profiling method for air temperature

(Ma et al. 2008) and Delaunay triangulation (Lee &

Schachter 1980) with the linear interpolation method for

firn temperature. That is, the 4-level firn temperature time

series was converted into the Delaunay triangular mesh,

onto which interpolation was undertaken for correction.

Since the measured wind speeds are of lower quality, the

change of height had little effect on wind speeds and no

correction was made. Zero wind speed values that occurred

because of icing/riming of the sensors in the winter were

deleted. The Vaisala relative humidity sensors exhibit a

large negative bias at low temperatures, and we corrected

the relative humidity with respect to ice instead of water

when temperatures were , 08C using the method of

Anderson (1994). For LGB69, only data for 2002–04

were utilized because the observations since 2005 were

influenced heavily by snow accumulation.

Meteorological conditions

Annual mean and interannual variability

The AWS have provided us with a fairly complete three-

year dataset (except for LGB69, see below). The records so

far are too short to study atmospheric variability caused

by factors such as El Nino and the Southern Oscillation

(ENSO) or the Southern Annular Mode (SAM), and only

short-term interannual variability of meteorological

elements are addressed here. Table III presents annual

averages of the meteorological variables for all sites along

the CHINARE traverse route. The missing days in January

2005 (Dome A and Eagle), January 2002 (LGB69) and

August–December 2004 (LGB69) were replaced with

corresponding days of the following year. This results in

an addition of 1.5% data to Dome A, 2.5% to Eagle, and

16% to LGB69 in the three year record.

Air temperature

In general, the annual mean air temperature decreases with

elevation: from the near-sea level ZS (14.9 m a.s.l.) to

Dome A (4093 m a.s.l.) the annual mean temperature at

2 m above the surface (Ta) dropped from -9.2 to -51.68C.

However, this is not representative of all parts of the

Antarctic. Van den Broeke et al. (1999) and Bintanja

(2001) showed that air temperature increased with

elevation in some regions of Dronning Maud Land. In

our analysis, however, no such phenomenon was revealed.

Fig. 2. Elevation along the CHINARE traverse route from ZS

(at the coast) to Dome A. LGB59 is an Australian AWS

(73827'S, 76847'E, 2537 m a.s.l.) 420 km from the coast.

Table II. Specifications of the AWS used in this study. Dome A is slightly different (see Xiao et al. 2008).

Sensor Type Range Accuracy

Air temperature FS23D thermistor -85–658C 0.028C

Relative humidity Vaisala HMP45D 0–100% 2% (RH , 90%)

3% (RH . 90%)

Wind speed Young P/L cup anemometer 0–51.1 m s-1 0.1 m s-1

Wind direction Aanderra 3590 vane 0–3608 68

Snow height Campbell Scientific SR50-45 0.5–10 m 0.01 m

Global radiation Middleton EP08 0–204.8 MJ 0.1 MJ m-2

Air pressure Paroscientific Digiquartz 6501A 0.1 hPa

Subsurface temperature FS23D thermistor -85–658C 0.028C

NEAR SURFACE CLIMATE DOME A 445



Budd et al. (1971) found the temperature change with

surface elevation (the topographical lapse rate) on the ice

sheet and defined three distinct regions. Near the coast, the

topographical lapse rate approximates the dry adiabatic

value of 18C 100 m-1, but further inland, on the escarpment

region where the ice sheet surface slope is steeper, the

annual lapse rate increases to twice the adiabatic value. Still

further inland, on the central plateau, it drops again to half

the adiabatic value or less (Allison et al. 1993). Figure 3a

shows the annual mean temperature and 10 m firn

temperature as a function of altitude along the traverse

route. The regions noted by Budd et al. (1971), occur in

these data with a lapse rate of 0.918C 100 m-1 from ZS to

LGB69 where katabatic winds prevail. The value increases

to 1.198C 100 m-1 between LBG69 and LBG59, and

continues to increase with elevation from the zone of

steepest terrain to the interior, reaching 1.978C 100 m-1

between LGB59 and Eagle, almost twice the adiabatic rate.

The surface slope reduces and the lapse rate declines from

Eagle inwards to Dome A (0.898C 100 m-1).

Figure 3b shows the change in potential temperature as a

function of the distance from the coast, indicating that the

annual mean potential temperature increases to a maximum

where the slope and the surface wind speeds are highest.

This feature also occurs in other regions of East Antarctica

(e.g. Van den Broeke et al. 1999), and can be attributed to

the katabatic wind which enhances vertical mixing and

reduces the strength of the surface temperature inversion.

This results in large sensible heat fluxes warming the

surface and relatively high potential temperatures (Van den

Broeke et al. 1999).

The data presented in Table III show that the mean

annual temperature variability between 2005 and 2006 is

small at all the stations (only about 0.58C), but in 2007 they

were warmer than the previous two years (about 1.6, 0.9

and 0.68C for ZS, Eagle and Dome A, respectively). This was

Table III. Annual mean meteorological data for the sites along the ZS–Dome A traverse route.

Site Year 2 m 10 m Temp. 4 m Wind Relative Specific Pres. Accumulation

Air temp. Firn temp. diff. Wind speed direction humidity humidity Snow w.e.

(8C) (8C) (air–firn, 8C) (m s-1) (8T) (%) (g kg-1) (hPa) (m yr-1) (mm yr-1)

2005 -9.9 - - 6.4 70 59 1.21 984.5 - -

ZS 2006 -9.6 - - 6.9 67 57 1.18 983.0 - -

2007 -8.2 - - 7.8 67 58 1.26 986.2 - -

Reliable data rate 100% - 99% 100% 100% 100% -

2002 -25.4 -27.2 1.8 7.9 56 91 0.53 776.0 0.48 195

LGB69 2003 -26.2 -27.0 0.8 9.0 57 89 0.56 776.3 0.50 203

2004 -26.3 -27.0 0.7 - - 89 0.52 773.7 - -

Reliable data rate 98% 98% 72% 97% 98% 100% 99%

2005 -40.7 -43.2 2.5 3.7 54 79 0.18 682.9 0.25 84

Eagle 2006 -40.5 -43.1 2.6 4.8 59 80 0.16 681.7 0.39 131

2007 -39.7 -43.0 3.3 4.0 58 79 0.16 685.9 0.27 91


2005 -51.5 -58.3 6.8 2.2 179 68 0.07 574.3 0.11 32

Dome A 2006 -52.1 -58.2 6.0 3.0 172 68 0.06 573.2 0.05 13

2007 -49.6 -58.1 8.5 2.5 182 70 0.07 576.7 0.19 50


Data gaps in the annual averages are indicated by -.

Fig. 3. a. Annual mean air temperature (2 m above surface) and firn temperature (10 m depth) as a function of surface elevation, b. annual

mean potential temperature as a function of distance from the coast. Data from the Australian AWS LGB59 have been included.




also the case for other stations in East Antarctica, e.g.

Mirny (66833'S, 90801'E, 39.9 m a.s.l.), Progress (69823'S,

76823'E, 64 m a.s.l.), Scott (77.98S, 166.78E, 16 m a.s.l.)

and Vostok (78.58S, 106.98E, 3490 m a.s.l.). The annual

mean temperature in 2007 at these stations (-9.4, -6.5, -17.7

and -53.28C, respectively), was about 1.8, 2.0, 1.9 and

1.38C warmer than the previous two years. This large-scale

short-term warming phenomenon may be most probably

associated with the interannual variation of near-surface

temperature in East Antarctica, which we are unable to

determine in this study due to the lack of observations.

Firn temperature

The firn temperature at c.10 m depth (T10 m) is often used on

the ice sheet as an approximation for the long term annual

mean surface air temperature. At this depth the amplitude of

the annual temperature wave is less than 5% of the surface

value. As shown in Table III, T10 m decreases as a function

of increasing elevation and distance from the coast similarly

to the mean annual air temperature (Ta). The mean value of

T10m over 2005–07 was -27.1, -43.1 and -58.28C for LGB69,

Eagle and Dome A, respectively. However, T10m is

consistently lower than Ta at all sites, with a difference

between Ta and T10m of 1.1, 2.8 and 6.68C for the three AWS.

This occurs because the persistent surface inversions over the

Antarctic ice sheet result in the snow surface temperature

(which determines T10m) being considerably colder than the

air a few metres above the surface.

The surface inversion is particularly extreme at Dome A

compared to the other sites where stronger average wind

speed enhances the vertical mixing of air in the near-

surface layer, weakening the inversion. At Dome A the air

temperature profiles measured by the AWS frequently show

temperature differences between the 1 m and 2 m level (and

between 2 m and 4 m) which average between 1.58C and

2.58C from March–October. The monthly average inversion

strength measured by the air temperature sensors has a

strong seasonal pattern, increasing from zero in January,

and is of similar shape and magnitude in all years. The

3-yearly average difference between Ta (-51.68C) and the

0.1 m firn temperature (T0.1m, -56.68C), which approximates

the snow surface temperature over the period, was 58C.

Snow accumulation

The AWS measure changes in the height of an acoustic ranger

above the surface (snow surface height, or SSH). This

provides information on surface net balance processes such as

snowfall, snow transportation by drift, sublimation, deposition,

and densification of the snow pack (e.g. Reijmer & Van den

Broeke 2001). Because snow accumulation often occurs during

strong winds, it can be difficult to assess whether an

individual accumulation event is due to snowfall or snow

drift transportation, or whether an increase in SSH is due

to densification or ablation. But on an annual or longer time

scale we assume that changes in SSH are due primarily

to net accumulation of snow. Table III presents annual

mean accumulation estimated from the annual mean SSH

changes and converted to water equivalent using the

measured surface snow density at each site. For LGB69,

Eagle and Dome A the annual mean accumulation is 0.49,

0.30, and 0.11 m of snow, respectively, equivalent to 199,

102, and 31 mm w.e. yr-1. Accumulation decreases with

altitude and distance from the coast, in agreement with

the common pattern of Antarctic accumulation and, for

this region of East Antarctica, with Ren et al. (2002). The

year-to-year variability of accumulation is small for all the

stations, differing by up to 0.14 m of snow, although part

of this may be association with snowdrift transport.

Wind speed and direction

Figure 4 presents the annual mean wind speed as a function

of surface slope and distance from the coast (at ZS). The annual

Fig. 4. Annual mean surface wind speed a. as a function of surface slope, and b. as a function of distance from the coast. The annual

mean wind speed at LGB59 is from 1994–96 (Allison 1998).




mean wind speed is 7.0 m s-1 at the coastal station ZS. It

increases rapidly with distance from the coast to 8.5 m s-1 at

LGB69, which is the steepest region on the traverse route with

a surface slope 7.3 m km-1. This is lower than the 10.5 m s-1

reported for LGB59, which has a 4.4 m km-1 surface slope

(Allison 1998). Because of icing/riming on the anemometers,

some data are missing or recorded as zero, particularly during

winter months and the yearly average wind speed may be

underestimated. Further inland from LGB59, the surface slope

diminishes and the average wind speed begins to weaken

significantly. It is only 4.1 m s-1 at Eagle, and continues to

decline to 2.2 m s-1 at Dome A where the terrain is very flat.

Overall, the wind strengthens southward from the East

Antarctic coast into the interior escarpment region, and then

weakens gradually inland (Fig. 4b). This situation is similar to

that in Adelie Land (King & Turner 1997) and in accord with

the pattern of wind speed for 600 km from the coast along

628E in Mac. Robertson Land (Weller 1969).

The wind direction roses for sites along the ZS to Dome A

line are shown against both frequency and wind speed in

Fig. 5. They show strong directional constancy at ZS, LGB69

and Eagle. At ZS, wind directions between north and

east–north–east account for 85.7% of all occurrences, with

north-east winds having the highest frequency (42.1%) and

a mean velocity of 9.4 m s-1. The LGB69 wind direction is

even more constant with a prevalence of east–north-east winds

(54.1%) with an average speed of 9.7 m s-1. Directions between

north-east and east account for 90.3% of the total. The

dominant wind direction at Eagle is north-east (56.3%) with a

mean velocity of 4.9 m s-1, and the secondary direction is

east–north-east with a frequency of 25.2%. For Dome A the

wind direction is more variable with southerly winds

(21.2%) having the highest frequency with a mean wind

speed of 2.4 m s-1, and with a broad spread of winds from

other directions. These results are similar to those reported

by Yang et al. (2007). The direction of prevailing winds at

ZS, LGB69 and Eagle are in agreement with that of

katabatic flows and these three stations are influenced by

katabatic wind. The strongest katabatic wind occurs at

LGB69 situated just downstream of the steepest slope

region of the ice sheet. ZS is on the edge of the ice sheet

and experiences a slightly weaker katabatic effect than at

LGB69. Eagle is on the gentle slope in the interior and

experiences only weak katabatic wind. For Dome A the

irregular directions and weak winds demonstrate that there

is no katabatic effect.

Fig. 5. Wind direction/speed rose charts for all stations along the ZS–Dome A section.

Fig. 6. Annual mean relative humidity (dotted line) and specific

humidity (solid line) as a function of distance from the coast.




Even more remarkable than the strength of the wind

speed in Antarctica is the constancy of the wind direction

(the directional constancy, dc, defined as the ratio of the

magnitude of the mean wind vector to the scalar average

wind speed). A dc value of 1.0 means that the wind blows

from only one direction, whereas a value of 0.0 means that

wind blows from opposite directions with equivalent

strength and frequency. From the AWS observations, the

annual mean dc is 0.86 for LGB69, 0.91 for Eagle, and 0.78

for Dome A. This is close to that reported by Rusin (1964)

with annual mean values of dc of 0.7–0.9 for the coast of

East Antarctica, values close to unity for the slope of the

plateau, and 0.7 or lower for the inland plateau (Xie et al.

1991). Dome C (74.58S, 123.08E, 3280 m a.s.l.), Vostok,

and South Pole (90.08S, 2835 m a.s.l.) have dc values of

0.60, 0.81, and 0.79 (King & Turner 1997), respectively,

which are closer to that for Dome A (0.78). From the above

analysis, the highest dc emerges in the strong katabatic

wind zone with the steepest slope, but is lower in the

interior of the Antarctic plateau.

Pressure

The interannual variability in the annual mean surface

pressure presented in Table III is of the order of 4 hPa. For

the period 2005–07, annual mean surface pressure was

highest in 2007 and lowest in 2006 at ZS, Eagle and Dome A.

This large-scale synoptic effect, perhaps influenced by

modes of variability such as ENSO and the SAM, was

similar at other stations in East Antarctica. For example,

the yearly average surface pressure for 2005, 2006 and

2007 were 985.4, 983.2, and 986.9 hPa at the coastal station

Progress, and 624.4, 623.7, and 626.1 hPa at the inland

plateau station Vostok.

Humidity

Figure 6 shows that the relative humidity increases rapidly

from the coast to the interior of Antarctica, reaching 90% at

LGB69 on the escarpment region, followed by a swift

decline toward the inland plateau, with 69% at Dome A.

The specific humidity initially decreases quickly from the

coast and then reduces gradually towards the plateau. The

annual mean specific humidity was 1.22, 0.54, 0.16, and

0.06 g kg-1 respectively, for ZS, LGB69, Eagle and Dome A.

The value is significantly higher at ZS, which is under the

effect of marine air masses throughout the year, and it is

extremely low at Dome A where the ultra-low temperature

greatly reduces the ability of air to carry moisture. The

inter-annual variability in the annual mean relative

humidity is about 2% for all the stations. However, the

specific humidity variability is largest at ZS (c. 0.05 g kg-1)

and is smallest at Dome A (c. 0.01 g kg-1).

Seasonal cycle (annual variation)

Air temperature

The monthly mean temperature for all the stations along the

traverse line during the observation period is displayed in

Fig. 7. Air temperature warms rapidly in early summer and

cools rapidly at the end of it for all the stations, and is

Fig. 7. Monthly mean air temperature for all the stations along ZS–Dome A section during 2005–07.




preceded and followed by smaller rates of temperature change.

This is typical of the ‘‘coreless’’ winter temperature pattern

(i.e. the winter temperatures do not have distinctive minima

and the temperature traces are rather flat over winter months)

in Antarctica. For ZS, the coldest month of the year had a

monthly mean temperature warmer than -208C during the

observation period while the warmest month at the inland

stations Eagle and Dome A is colder than -20 and -308C,

respectively. The coldest month at Dome A (August 2005) has

a monthly mean air temperature of -65.38C and was 2.88C

warmer than Vostok (-68.18C) and similar to Amundsen-Scott

(-65.28C) at the same time. Although Dome A is 600 m higher

in altitude and 1.58 higher in latitude than Vostok, the

2005–07 yearly mean temperature was 2.68C warmer than that

at Vostok (-51.6 vs -54.28C). We believe that this difference is

real, a result of large-scale atmospheric circulation over the

Antarctic ice sheet, and not an artefact of the measurements.

The consistent air temperature differences between the

different levels and the regular pattern of seasonal change in

inversion strength lends confidence to the accuracy of the

temperature measurements. Because of its setting, near a

region of surface flow divergence and upper air subsidence,

the near surface air temperature is higher at Dome A than in

areas where flow converges (such as Vostok).

The seasonal cycle in air temperature at different latitudes

(Fig. 8) shows that Vostok, Dome A, and Amundsen-Scott,

(the inland plateau stations), have a coreless period between

April and September, whereas the lower latitude stations have

a coreless period that lasts only from about May–September.

The corelessness is defined as the amplitude ratio of the

second to the first harmonic of the annual temperature

wave (Allison et al. 1993, Wendler & Kodama 1993). For

a typical coreless winter, the amplitude of the second

harmonic is more than 25% of the first harmonic. The

corelessness for ZS, LGB69, Eagle, and Dome A is 0.260,

0.273, 0.388, and 0.433, respectively. The Australian AWS

at Law (66.738S, 1366 m a.s.l.) and GF08 (68.498S, 2120 m

a.s.l.) have a corelessness of 0.276 and 0.295, marginally

larger than that of ZS which is at a similar latitude but

lower altitude. Dome C has a corelessness of 0.358 (Allison

et al. 1993), similar to the value at Eagle. The corelessness

Fig. 8. Monthly mean air temperature

(top) and the standard deviation of

daily means within each month,

shown as an average for all sites of

the ZS–Dome A section (bottom).

Latitudes of these sites are as

follows: Zhongshan (69822'S),

Progress (69823'S), LGB69 (70850'S),

LGB59 (73827'S), Eagle (76825'S),

Vostok (78827'S), Dome A (80822'S),

and Amundsen (908S).

Table IV. Monthly mean temperature (8C) and standard deviation (SD)

for all sites along ZS–Dome A section.

Site Zhongshan LBG69 Eagle Dome A

month mean SD mean SD mean SD mean SD

Jan. 0.8 (1.8) -14.5 (1.9) -24.3 (2.8) -34.3 (2.3)

Feb. -3.1 (2.7) -18.6 (3.6) -33.1 (4.5) -43.6 (4.2)

Mar. -7.2 (4.4) -24.7 (4.3) -40.7 (6.1) -54.0 (5.8)

Apr. -10.8 (5.1) -28.9 (6.0) -46.1 (6.4) -57.9 (5.8)

May -14.3 (6.3) -29.6 (5.4) -49.7 (7.7) -59.2 (5.0)

Jun. -13.2 (5.8) -30.5 (5.6) -46.7 (7.9) -58.4 (6.0)

Jul. -16.3 (7.4) -33.6 (6.6) -48.0 (6.4) -61.1 (5.7)

Aug. -14.7 (6.3) -34.2 (3.9) -49.4 (7.9) -61.6 (5.8)

Sep. -14.8 (6.6) -30.6 (4.2) -48.7 (8.6) -60.8 (7.2)

Oct. -12.1 (4.9) -27.8 (4.0) -42.7 (6.3) -53.4 (6.9)

Nov. -4.5 (3.8) -21.3 (2.7) -30.9 (4.6) -42.1 (5.0)

Dec. -0.1 (2.6) -15.8 (2.7) -24.5 (3.4) -33.2 (2.7)

Annual -9.2 (1.7) -25.8 (1.4) -40.3 (1.8) -51.6 (1.4)

SD 7.8 7.8 11.6 11.9




increases from the coast to the interior of Antarctica as a

function of increasing latitude and altitude.

Air temperature in East Antarctica is a very variable

element, especially in winter when the meridional and

local vertical gradients are largest. The standard deviations

(Fig. 8 and Table IV) show that the day-to-day temperature

variability is much higher in winter than in summer. Warming

or cooling of 10–208C often occurs within a few days at ZS,

LGB69, Eagle, and Dome A. Using the observations from six

AWS around the Lambert Glacier basin, Allison (1998) noted

exceptional warming events are a widespread feature over

the region, with surface temperatures rising by 208C or more

for two or three days during high-pressure/high-wind-speed

events in June and July. Likewise, air temperature changes of

20–308C within a few days are not uncommon and often

measured at several stations almost simultaneously over

Dronning Maud Land (Reijmer & Oerlemans 2002). These

large changes in temperature often coincide with changes in

wind speed and direction and may be due to passing low

pressure systems advecting the relative warm and moist

maritime air to the south. The short-term warming events are

mainly related with the high pressure or high wind speed.

These extreme air temperature warm events are at least partly

due to a weakening of the surface inversion, for example from

subsidence of warmer upper air (Wendler & Kodama 1993) or

turbulent mixing, which weakens the surface inversion with

increased wind speed.

The mean monthly temperatures and their standard

deviations for the record period of each station are given

in Table IV. The summer temperature has a pronounced

maximum in January for all the stations except Dome A,

where it occurs in December. Because of the coreless

winter, the lowest temperature was recorded in different

months during different years. The temperature variation

characteristics during March–May and September–November

are similar to those in winter (June, July, August), evidencing

the short Antarctic summer (e.g. Schwerdtfeger 1970). Dome

A at an altitude of 4093 m, has a mean annual temperature of

-51.68C, a mean summer temperature of -43.48C, a mean

temperature of the warmest month (December 2005) of

-31.58C, and eight months (between March and October) with

the monthly mean temperature below -508C. The summer is

limited to times of relatively high solar elevations, especially

in December and January, and already by February there is a

cooling of c. 108C. The mean temperature of winter half year

(April–September) is -59.88C. The coldest temperature yet

recorded at Dome A has been -82.58C (27 July 2007), which

is warmer than the record cold of -89.28C at Vostok (26

August 1982), and warmer than the lowest of -84.68C

observed at Dome C (Allison et al. 1993). This may be

associated with the observational period being too short to

record a minimum temperature lower than that of Vostok or

alternatively Dome A is not the coldest region of the earth.

Figure 9 presents the seasonal variation of the

topographical lapse rate of temperature between ZS and

other AWS sites and between neighbouring sites. The

average topographical lapse rate in midsummer (December

and January) between ZS and all the AWS sites is c.

0.8–0.98C 100 m-1, slightly lower than the adiabatic value

of 18C 100 m-1 (Fig. 9a). In other months it is c. 0.1–0.28C

100 m-1 higher than the dry adiabatic value for all stations

except Dome A. The lapse rates have dual maxima in April

and August, one month earlier than that at the Lambert

Glacier basin sites (Allison 1998) and reach 1.258C 100 m-1

between ZS and LGB59 during April. Figure 9b illustrates

the topographical lapse rates over the differing terrains, i.e.

coastal area, escarpment region, and inland plateau. The

surface lapse rates of the three regions all approximate the

Fig. 9. a. Seasonal variation in the surface lapse rate between ZS and other AWS sites, b. surface lapse rate between the two nearest sites.




dry adiabatic value during midsummer. In other months,

the surface lapse rate approaches the dry adiabatic value

over the escarpment region between ZS and LGB69. From

LGB69 to the inland plateau site, Eagle, the surface slope

decreases rapidly and the lapse rate becomes super-

adiabatic, with a maximum of 2.678C 100 m-1, more than

twice the adiabatic value, between LGB59 and Eagle in

September. The surface lapse rate reduces to the near-dry

adiabatic value from Eagle to Dome A. Similar patterns

occur in the annual mean temperature (Fig. 3a), and was

also found over the ice sheet in Wilkes Land (Allison et al.

1993). The strength of the lapse rate decreased once the

threshold slope exceeded 5 m km-1 (Allison 1998) because

vertical turbulent mixing from stronger katabatic winds

decreased the surface inversion strength.

The observed annual cycle of air temperature as well as

its first and second harmonic waves for all the stations

along the traverse route from ZS to Dome A are displayed

in Fig. 10. The total variance of the annual cycle in air

temperature at all sites can be almost entirely (. 98%)

explained by the first two harmonics, H1(T) and H2(T).

Although the annual cycle is dominated by the first

harmonic, the second harmonic is significant at the four

sites, explaining 8–16% of the total variance. The sites can

be grouped into three regions on the basis of their location,

elevation, mean temperature, and seasonal temperature

cycle: the East Antarctica coastal area (ZS); the East

Antarctica strong katabatic wind zone, or escarpment

region (LGB69); and the East Antarctica inland plateau

region (Eagle and Dome A). The contribution that H1(T)

makes to the variance of air temperature annual variation

reduces from north to south. H2(T) explains 8% of the

variance in the coastal area and escarpment region and

increases to 16% on the plateau, with a greatly increased

harmonic amplitude of 2.0–2.48C in the coastal area and

escarpment region to 4.5–5.68C on the plateau. Van den

Broeke (1998) also found that the percentage of variance of

the annual temperature cycle explained by H2(T) is largest

on the Antarctic Plateau (11–18%), with an amplitude of

roughly 3.5–7.28C, and less for the coastal East Antarctica

(6–12%) with an amplitude of 1.9–2.98C. The phases of

H1(T) and H2(T) at ZS and LGB69 are nearly identical, as is

Fig. 10. Monthly average temperature at a. ZS, b. LGB69, c. Eagle, and d. Dome A (dots, right axis) and the first and second

harmonics (dashed lines) and their sum (solid line, left axis). The numbers are the amplitude and amount of variance explained by

the two harmonics.




the case between Eagle and Dome A, but with the phases

about 10 days ahead of those at ZS and LGB69. This is

associated with the different phase of biannual pressure

oscillation at the different sites.

Pressure

The daily mean surface pressure is variable on time scales

from several days to months. This is shown in Fig. 11 for

all the stations from January 2005–December 2007. The

variations over several days are mainly due to meso-scale

pressure systems (Parish 1982). Figure 11 shows that the

pressure variations at Eagle and Dome A are well

correlated (r 5 0.94), indicative of both sites being under

the influence of the same large-scale synoptic system.

Correlation between the high plateau station and LGB69

and ZS, and between the lower elevation stations, is lower

(r ranges from 0.1–0.5), implying that these stations are

more affected by local circulation than by a single large-

scale system. For example, ZS and LGB69 are only 160 km

apart, but their inter-diurnal pressures differ significantly

perhaps associated with their markedly different topography.

Variations at larger time scales are due to phenomena like

the semiannual oscillation (SAO) in the pressure signal

(Van Loon 1972). The SAO is the main feature of southern

hemisphere extratropical pressure variation (Van Loon 1967).

It consists of a twice-yearly expansion and contraction of

the circumpolar pressure trough around Antarctica in response

to differences in heat storage between Antarctica and the

surrounding oceans. As a result, the surface pressure in middle

and high latitudes shows a clear half-yearly wave. As reported

by Van Loon (1972), and Van Loon & Rogers (1984), the

second harmonic explains 17–36% of the total variance of the

annual cycle in surface pressure in the interior of west

Antarctica and on the Antarctic Plateau, 36–68% along the

East Antarctic coast, and almost 80% on the west coast of the

Antarctic Peninsula. Further to the north, at the sub-Antarctic

islands, both amplitude and explained variance decrease

towards the minimum at 608S.

Figure 12 shows the annual pressure cycle together with the

first, H1(P), and second, H2(P), harmonic for all the stations

along the traverse route. The amplitudes of annual variation in

surface pressure are between 9–18 hPa. A distinct SAO feature

is seen at all the stations, with a predominant maximum in the

summer (December and January), a secondary maximum in

the winter (June), and the predominant smallest value in

August or October with slight differences between stations. In

contrast to air temperature, the dominant period of the

pressure is generally not determined by the first harmonic (i.e.

the annual oscillation signal). Only at LGB69 is the annual

oscillation signal significantly stronger than the SAO, with the

first harmonic accounting for 63.6% of the total variance. At

the other sites, the contribution of first harmonic is close to, or

lower than, the second harmonic for the annual cycle. From

Fig. 12 we see that the explained variance of the first harmonic

for the pressure annual cycle increases rapidly from 24.9% at

ZS of the coastal area to 63.6% at LGB69 in the strong

katabatic wind region (escarpment region), and then reduces

towards the plateau to 41–46% at Eagle and Dome A. The

amplitude also initially experiences an increase and then a

decrease moving inland.

Fig. 11. Daily average surface air

pressure at ZS, LGB69, Eagle, and

Dome A. The thick lines represent

smoothed curves (15 days running

mean).




The contribution of the second harmonic to the annual

pressure variation is opposite to that of the first harmonic.

The contribution reduces to 17.7% at the escarpment region

from 53.1% at the coastal area, followed by rapid increase

to 43–47% on the plateau. This result is c. 10% higher than

that presented in Van Loon (1972) and Van Loon & Rogers

Fig. 12. Monthly average surface pressure at a. ZS, b. LGB69, c. Eagle, and d. Dome A (dots, right axis) and the first and second

harmonics (dashed lines) and their sum (solid line, left axis). The numbers are the amplitude and amount of variance explained by the two

harmonics. At LGB69 the third harmonics and the sum of the first, second and third harmonics are also shown.

Fig. 13. Annual variation of a. wind speed, and b. wind direction constancy (solid line), and wind direction deviation (dashed line).

Inset numbers are annual wind direction at each site.




(1984), which may be the result of interdecadal variation in

the SAO, with a stronger SAO signal in 2005–07 than in

1957–80. The amplitude of the second harmonic increases

gradually from the coastal area and escarpment (c. 2 hPa) to

the interior of the plateau (c. 4 hPa).

At all the stations, the first and second harmonics

together explain 79–89% of the total variance of the annual

cycle in surface pressure. This is significantly smaller than

the 96–99% indicated by Van den Broeke (1998), who used

the harmonic method to analyse the surface pressure from

27 stations distributed all over Antarctica. Our result

demonstrates that the shorter-term pressure variation also

makes specific contributions to the annual variation. At

LGB69 in particular, the third harmonic explains as much

as 14.3% of the variance of the annual cycle, with the

amplitude of 2.0 hPa, and the signal intensity near that of

the second harmonic. For the other three stations, the third

harmonic accounts for 3–4% of variance of the annual

variation, with amplitudes of 0.6–1.1 hPa which, although

rather weak, shows the existence of a 3-wave structure

(seasonal oscillation). Comparing the phase difference

between the second harmonic of temperature (Fig. 10)

and pressure (Fig. 12), H2(T) is c. 10 days ahead of H2(P) at

ZS, H2(T) is c. 10 days behind H2(P) at LGB69 and Eagle,

and H2(T) and H2(P) are approximately coincident at

Dome A. These differences can be explained by the different

locations of the stations with respect to the average position

of the circumpolar pressure trough.

Wind speed and direction

Figure 13 presents the annual variation of wind speed,

directional constancy, and wind direction deviation, for all

the stations along CHINARE traverse route. As seen in

Fig. 13a there is distinct seasonal variation of wind speed for

ZS and LGB69, where wind speed is considerably stronger in

winter (April–September) than summer (October–March).

This is explained by the weaker near-surface inversion that

occurs in summer, leading to a weakened katabatic flow

compared to the winter. At the inland plateau stations Eagle

and Dome A, there is not much variability. The strongest

wind occurs at the site with the greatest surface slope

(LGB69) where the maximum of monthly mean wind speed

exceeds 10 m s-1, followed at the coastal area (ZS) with the

maximum monthly mean of 9 m s-1. The minimum wind

speed is experienced on the inland plateau (Eagle and

Dome A) with a range of 1.6–3.3 m s-1. This is because

LGB69 is in a strong katabatic wind zone and ZS is

downstream of this zone and so experiences the strong winds

caused by katabatic flow compared to Eagle and Dome A

where no katabatic flows form. In addition, the large-scale

pressure gradient (which acts in the same direction, down the

slope) has a significant effect on the forcing of near-surface

winds in East Antarctica, especially in the escarpment region

(Van den Broeke & Van Lipzig 2003). Figure 13b shows that

at LGB69 and Eagle, the wind direction constancy is high

and has relatively small annual variation, with the monthly

mean range of 0.9–1.0 and 0.8–0.9, respectively, and is

slightly higher in winter than summer. For Dome A, the

monthly mean wind direction constancy ranges over 0.7–0.8,

considerably lower than those of LGB69 and Eagle.

Humidity

The annual variation in monthly average specific humidity

is shown in Fig. 14. At all the stations, the maximum occurs

in December or January, and the minimum is in July or

August. The difference in mean specific humidity between

any two adjoining stations is larger in the summer months

(October–March of the next year) than in the winter

(April–September) and particularly between ZS and

LGB69. The maximum (minimum) difference in monthly

mean specific humidity between these two stations reaches

1.21 (0.37) g kg-1 in January (July). LGB69 is 160 km

further inland than ZS and at higher altitude, where air

temperature is relatively lower, leading to the lower

specific humidity. ZS is located on the coast and close to

the open ocean and moist marine air in summer, but in

winter, much of the sea nearby is frozen, thus greatly

reducing vapour in the air, so that the difference in specific

humidity between the two sites becomes very small (also

see Chen et al. 2007). Eagle and Dome A situated in the

inland plateau are barely affected by marine air mass, with

the warmest monthly mean temperature , -20 and -308C,

respectively. Because of high elevation, away from the coast

and cold temperatures, the annual specific humidity is extremely

low throughout the year, with maximum (minimum) monthly

mean specific humidity of 0.45 and 0.18 g kg-1 (0.05 and

0.02 g kg-1) for Eagle and Dome A, respectively.

Accumulation

Global Climate Model (GCM) results suggest that, due to the

nature of the accumulation events, at least five to ten years

accumulation data are necessary to obtain a significant annual

Fig. 14. Monthly mean specific humidity for all sites.




cycle for accumulation (Schlosser 1999). Therefore our two

or three years of accumulation measurements are not

sufficient to determine seasonal patterns. The fact that most

of the accumulation occurs in a few major events per year,

not confined to a particular season, has serious implications

for the analysis of, for example, the d18O in ice cores

(Schlosser 1999). Figure 15a presents the time series of daily

mean snow accumulation for LGB69, Eagle, and Dome A.

The accumulation pattern for the few years of record we do

have is similar for Eagle and Dome A. Between January and

April in most years there appears to be a hiatus in

accumulation with little change in snow surface height, and

most of the accumulation occurs at other times of year. At

both these sites there are large fluctuations in the snow

surface height between about May and mid October during

the coldest period. We suspect that these are due to problems

with the sensors at very low temperature, and do not reflect

real height changes. At LGB69, accumulation can occur at all

times of year and there are no obvious periods of hiatus.

Figure 15 shows that the snow accumulation at LGB69

typically occurs in four or five heavy snowfall events each

year. There are fluctuations in snow surface height at all

Fig. 15. Daily average changes in snow

surface height (top) in metres of

snow and (bottom) in metres of water

equivalent. The surface height is

arbitrarily set at 0 m on the first day.

Fig. 16. Monthly mean firn temperature at different depths over the observation period at LGB69, Eagle and Dome A.




times of year at LGB69, many of which may be related to

wind transport and the movement of surface sastrugi past the

sensor, as well as to compaction after large, new snow falls.

The measured in situ surface snow density at LGB69,

Eagle and Dome A is 406.67, 336.67, and 265.56 kg m-3,

respectively. The water equivalent accumulation record at

the three sites calculated from these average densities is

shown in Fig. 15b. The overall accumulation was 525 mm

w.e. over two and a half years at LGB69, and 306 and

93 mm w.e. over the three years at Eagle and Dome A,

respectively.

Snow temperature

The time series of 2005–07 monthly mean snow

temperatures for LGB69, Eagle, and Dome A are given

in Fig. 16. This figure indicates that the snow temperature

cools (warms) from the surface layer to the deep layer in

the summer (winter), indicates rapid warming at the

beginning of summer (September–October), and rapid

cooling at the end of the summer (except 10 m depth),

and is preceded and followed by smaller rates of snow

temperature change, similar to air temperature features.

Among the three AWS sites, Dome A (LGB69) experiences

the greatest (smallest) variability in the annual variation of

snow temperature, with amplitudes of 28, 17, and 78C (18,

12, and 58C) at 0.1, 1, and 3 m depths, respectively, and

Eagle temperature varying in between, but at 10 m depth

the yearly amplitude is only c. 0.48C for all the three sites.

For LGB69, Eagle and Dome A the amplitudes of the

annual cycle at 10 m depth is only 1.4–2.2% of the amplitude

at 0.1 m depth, so the 10 m depth can be assumed to be a

layer with constant temperature. Longwave radiative fluxes

and turbulent fluxes influence only the top few millimetres of

the snow/ice, while a significant part of the absorption

(. 50%) shortwave radiation also occurs in the top few

millimetres of the snow/ice and the residue exponentially

decreases towards the deep layer (Brandt & Warren 1993).

Therefore, the exponential attenuation in the temperature

cycle with depth is a result of thermal conduction. The

amplitude at 10 m depth is typically about 2.3% of that at the

snow surface (Xie et al. 1991). The phase of the temperature

cycle is also lagged with depth, and the maximum monthly

mean firn temperature which occurs in January at 0.1 m

depth, does not occur until February at 3 m.

Figure 17 illustrates the monthly mean firn temperature

as a function of depth for the three AWS during the

observation period. The near surface temperatures warm

rapidly between October and December (by 11.1, 16.4 and

19.68C at LGB69, Eagle and Dome A), and cool rapidly

from February–April at rates similar to spring warming. In

both cases the rate of change increases with the elevation

and distance from the coast. The changes are slower at

other times of year. This is similar to observations at

Plateau station (Weller & Schwerdtfeger 1970). At all sites

the surface layer is warmest in January and coldest in

August or September. At Eagle and Dome A the 0.1 m firn

temperature rises sharply in October, with an increase of

4.1 and 4.78C respectively over September. The variation

of firn temperature below 3 m depth is similar at all sites.

Cooling occurs from January–May and warming from

June–December, with the nearly constant temperature at

10 m depth. The depth-dependent curves of firn temperature

in Fig. 17 are asymmetric as a result of the attenuation of

temperature amplitude and the shift in phase during the

process of heat conduction with depth.

Conclusions

Using data from ZS and three AWS to investigate the near

surface climate of the East Antarctic ice sheet along the

traverse route from ZS to Dome A, we find that:

1) Air and firn temperature, accumulation and specific

humidity decrease with increasing elevation and distance

Fig. 17. Monthly mean firn temperature as a function of depth at LGB69, Eagle, and Dome A.




from the coast. Annual mean air temperature decreases

from -9.28C at ZS to -51.68C at Dome A, and the specific

humidity decreases from 1.22 g kg-1 to 0.06 g kg-1. The

snow accumulation declines from 199 mm w.e. yr-1 at

LGB69 to 31 mm w.e. yr-1 at Dome A.

2) Annual mean surface wind speed is strongest at LGB69

and weakest at Dome A (2.1 m s-1). It increases rapidly

from the coastal area to the escarpment region, and then

drops quickly towards the interior of the plateau. The

strongest wind occurs at the site with the greatest

surface slope.

3) A strong coreless winter temperature regime exists at

all the stations. The corelessness factor increases with

elevation and distance from the coast, from 0.260 at

ZS to 0.433 at Dome A.

4) The surface temperature lapse rate is close to the dry

adiabatic value between the coast and the escarpment

region (ZS to LGB69). Between LGB69 and the

inland plateau site, Eagle, the surface slope decreases

rapidly and the lapse rate increases to super adiabatic,

reaching a value twice the adiabatic value (1.978C

100 m-1). The surface lapse rate then reduces to

0.878C 100 m-1 between Eagle and Dome A and is

slightly smaller than the dry adiabatic value.

5) Both temperature and pressure all show a distinct semi-

annual oscillation signal with a primary minimum in

spring (September or October) and a secondary

minimum in autumn (March or April). The second

harmonic of temperature annual cycle explains 8% of

the variance in the coastal and the escarpment region,

and 16% on the plateau. The amplitude of the second

temperature harmonic increases from 2.0–2.48C in

the coastal and escarpment region to 4.5–5.68C on the

plateau. The contribution of the second harmonic to

the annual pressure variation decreases from 53% at the

coast to 18% at the escarpment region, then increases

again to 43–47% on the inland plateau. The seasonal

cycle of pressure (the third harmonic wave) contributes

to some extent to the annual pressure variation. In other

words, the pressure annual oscillation signal exists as a

3-wave structure (seasonal oscillation).

6) The depth-dependent temporal curve of snow

temperature exhibits an asymmetric structure due

entirely to the attenuation of temperature amplitude

and is lagged in phase with increased depth during the

process of heat conduction through the snow/ice.

Acknowledgements

We thank M. Sparrow and J. Burgess for carefully reviewing

the original manuscript. Special recognition is given to all

personnel involved in the CHINAREN traverse program. This

work was supported by the National Key Technologies R&D

Program of China (2006BAB18B05), National Natural Science

Foundation of China (40575033, 40776002, 40620120112),

and Chinese Arctic and Antarctic Administration (CAA) IPY

(2008–09) Program. The involvement of IA was supported by

the Australian Government’s Cooperative Research Centre

program through the Antarctic Climate and Ecosystems

Cooperative Research Centre (ACE CRC). The constructive

comments of the reviewers and editor are also gratefully

acknowledged.

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Near surface climate of the traverse route from Zhongshan Station to Dome A, East Antarctica

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