In this study, 8 years of high-resolution radiosonde data at nine Antarctic
stations are analysed to provide the first large-scale characterization of
the fine vertical structure of the low troposphere up to 3 km altitude over
the coastal margins of East Antarctica. Radiosonde data show a large spatial
variability of wind, temperature and humidity profiles, with different
features between stations in katabatic regions (e.g., Dumont d'Urville and
Mawson stations), stations over two ice shelves (Neumayer and Halley
stations) and regions with complex orography (e.g., McMurdo). At the Dumont
d'Urville, Mawson and Davis stations, the yearly median wind speed profiles
exhibit a clear low-level katabatic jet. During precipitation events, the
low-level flow generally remains of continental origin and its speed is even
reinforced due to the increase in the continent–ocean pressure gradient.
Meanwhile, the relative humidity profiles show a dry low troposphere,
suggesting the occurrence of low-level sublimation of precipitation in
katabatic regions but such a phenomenon does not appreciably occur over the
ice shelves near Halley and Neumayer. Although ERA-Interim and ERA5
reanalyses assimilate radiosoundings at most stations considered here,
substantial – and sometimes large – low-level wind and humidity biases are
revealed but ERA5 shows overall better performance. A free simulation with
the regional polar version of the Weather Research and Forecasting model
(Polar WRF) (at a 35 km resolution) over the entire continent shows
too-strong and too-shallow near-surface jets in katabatic regions especially
in winter. This may be a consequence of an underestimated coastal cold air
bump and associated sea–continent pressure gradient force due to the coarse
35 km resolution of the Polar WRF simulation. Beyond documenting the
vertical structure of the low troposphere over coastal East Antarctica, this
study gives insights into the reliability and accuracy of two major
reanalysis products in this region on the Earth. The paper further underlines
the difficulty of modeling the low-level flow over the margins of the ice
sheet with a state-of-the-art atmospheric model.
Introduction
The margins of East Antarctica are a region of great interest in meteorology
particularly due to the fierce katabatic winds that fascinated and severely
tested the pioneering scientific expeditions in the far south. These
so-called katabatic winds that flow over the sloping surfaces of the ice
sheet can attain very high speeds in confluence regions such as the
Adélie Land or the Lambert
Glacier .
In winter, the strong radiative deficit of the surface leads to persistent,
intense and directionally constant near-surface winds from the interior of
the continent. Beyond the coastal slopes the atmospheric boundary-layer flow
considerably thickens in response to a piling up of cold air downstream over
the sea ice or the ice shelves. This accumulation of cold air is responsible
for a pressure gradient force opposing the katabatic wind that is
particularly intense under weak synoptic forcing . In some regions of the ice sheet, like in Adélie Land
or in Coats Land, the flow regime transition can be abrupt
and is therefore
interpreted as a hydraulic jump, often referred to as a katabatic jump or
Loewe's phenomenon. Such jumps are however rarely important in other sectors
of the Antarctic periphery like Terra Nova Bay .
In summer, the absorption of shortwave radiation by the surface diminishes the
katabatic forcing and the large-scale pressure gradient force dominates the
overall momentum budget of the boundary layer . The lower sea-ice concentration and sea-ice extent generally
diminish the offshore extent of the land flow due to the development of
diurnal sea breezes and because of the thermal and
mechanical erosion of the flow at the ocean surface. In Adélie Land and in
Queen Maud Land, a typical summertime diurnal cycle of the low-level flow has
been evidenced. Nocturnal katabatic forcing alternates with a combination of
thermal wind forcing and surface radiative heating that leads to a weakening
of downslope diurnal flow or even to a diurnal anabatic flow
.
The interactions between the low-level atmospheric flow from the interior of
the ice sheet and the oceanic air masses over – or coming from – the
austral ocean are varied and complex. For instance, it has been shown that
katabatic winds are stronger when an anticyclone sets over the plateau or
when the pressure over the ocean is low as during the approach of deep
cyclones . On the other hand,
katabatic winds have been shown to be a key driver of the mesoscale
cyclogenesis off Adélie Land and the Ross Sea
or over the Weddell Sea
.
From a meteorological and climate perspective, the low-level atmospheric
dynamics over the coastal margins of Antarctica plays a key role for the
energy and mass budgets of the atmosphere over the ice sheet. The low-level
horizontally diverging and northward drainage flow from Antarctica drives a
thermally direct zonal circulation. Subsidence – and associated upper
cyclonic vorticity – takes place over the central ice sheet, while rising
motions occur over the ocean, leading to an active mass exchange between
Antarctica and subpolar latitudes . Moreover,
the low-level circulation over coastal Antarctica is critical for the surface
mass balance of the ice sheet. While transient eddies are responsible for the
moisture transport towards the continent, the export of moisture by the mean
circulation mostly occurs in the low troposphere . This export can be even more
pronounced when considering the moisture export due to blowing snow in the
boundary layer . Using radar measurements and model
simulations, further show that katabatic winds
significantly diminish the precipitation amount that actually reaches the ice
sheet surface. As katabatic winds are relatively dry, they sublimate an
important part of the precipitation before it reaches the ground surface.
This dry layer manifests with low values of relative humidity in the
boundary layer during snowfall events. From a model simulation with the
Integrated Forecast Model (IFS), the authors estimate that sublimation
corresponds to 17 % of the precipitation over the entire continent. This
term reaches up to 35 % when considering only the margins of the ice sheet.
The reliable representation of the Antarctic climate in regional and global
climate models as well as atmospheric reanalyses therefore strongly depends
on their ability to reproduce the low-level atmospheric flow at the Antarctic
periphery. A significant body of literature has focused on the near-surface
atmosphere in Antarctica
and its representation in meteorological reanalyses and models. In
particular, have highlighted an excessive wind speed and a
dry bias in the boundary layer over the Ross Ice Shelf in the Antarctic
Mesoscale Prediction System (AMPS; http://www2.mmm.ucar.edu/rt/amps,
last access: 1 April 2019), which is based on simulations from the polar
version of the Weather Research and Forecasting model (Polar WRF).
have further stressed that the near-surface wind
speed in escarpment areas is strongly underestimated in ERA40 and ERA-Interim
reanalyses, and to a lesser extent in model simulations with the Regional
Atmospheric Climate Model (RACMO). The simulations with the EC-Earth global
climate model in and in the LMDZ general
circulation model in concur with these conclusions,
especially at low horizontal resolutions due to the coarse representation of
terrain slopes.
The vertical structure of the atmosphere over the coastal regions of the ice
sheet and its representation in models have been less documented. Using
radiosonde data, and study the
climatological structure of the whole troposphere and low stratosphere at
the Mawson and Dumont d'Urville (hereafter DDU), Neumayer and Halley stations,
respectively. However, they do not give specific details on the structure of
the boundary layer or on the low troposphere. Significant advances in our
understanding of the low-level flow have been achieved due to the case
studies – often in summer – using a combination of tethersonde and
radiosonde observations (e.g., ) and
thanks to the deployment of sodars in Coats Land , in
Adélie Land and in the Terra Nova Bay
area . A climatological perspective has been provided
by and , who investigated the frequent
temperature and specific humidity surface-based inversions over Antarctica
using radiosonde data from the Integrated Global Radiosonde Archive (IGRA).
In particular, show that over coastal regions, roughly
half of the humidity inversions are associated with temperature inversions, while
the other half is due to a horizontal advection of water vapor increasing
with height.
Nonetheless, little is known about the spatial and temporal variability of
the fine vertical structure of the temperature, humidity and wind over the
coastal margins of Antarctica. Although the lower tropospheric dynamics in
this region is critical for the global climate, its representation in
state-of-the-art climate models and atmospheric reanalyses has not been
assessed hitherto.
The aim of the present paper is twofold: to characterize the vertical
structure of the low atmosphere over several locations of coastal East
Antarctica and to present a first multi-station evaluation of model
simulations and meteorological reanalyses in this region. More specifically,
the main objectives are to
document and decipher the fine vertical structure of the lower tropospheric temperature,
humidity and wind over coastal East Antarctica using radiosonde data; and
evaluate the ability of the ERA-Interim and ERA5 reanalysis products and of the Polar WRF
regional atmospheric model to reproduce the observed mean structure and its variability.
The paper is structured as follows: Sect. introduces the data sets
and details the methodology. Section presents the results, and
the latter are further discussed in Sect. .
Section closes the paper with a conclusion.
Data and methodsRadiosonde data at nine Antarctic stations
The low troposphere over coastal East Antarctica has been sampled for a few
decades by daily radiosoundings at several stations
See
http://amrc.ssec.wisc.edu (last access: 1 April 2019) for a complete
list of Antarctic stations with a continuous radiosounding program.
. In this
study, we analyze daily radiosonde data at seven permanent Antarctic stations
on the coast – McMurdo, Mawson, Davis, Casey, DDU, Neumayer and Halley –
and at two summer stations – Mario Zucchelli and Princess Elizabeth stations
(hereafter MZ and PE stations, respectively) – over the 8-year period
(2010–2017). The specific locations of all the stations are indicated in
Fig. , and the exact coordinates and altitudes are given in
Table S1 in the Supplement. The landscape surrounding the different stations
shows a great morphological diversity.
McMurdo station lies on the southwestern edge of Ross Island, close to the
interface between the Ross Ice Shelf – that extends over 900 km to the
south with a slight rise in elevation – and the Ross Sea to the north. The
topography of the Ross Island region is complex, with steeply rising terrains
corresponding to the two main mountains: Mount Erebus and Mount Terror. Black
Island and White Island with respective maximum elevation of 1040 and 740 m
are located 30 km south of McMurdo. The Transantarctic Mountains, whose
altitude can exceed 2000 m, are located west of Ross Island at a distance of
about 80 km. Mario Zucchelli station is located on the coast of Terra Nova
Bay, 355 km north of McMurdo, at the northeastern side of the confluence
zone of the Priestley and Reeves glaciers and at the south of an orographic
jump of more than 1200 m associated with the abrupt slopes of the
Transantarctic Mountains. Mawson station is situated on the coast of an
isolated horseshoe-shaped rocky area. The ice sheet surface steeply rises
from the coastal ice cliffs surrounding the station towards the plateau.
Davis is a coastal station that lies to the east of the Amery Ice Shelf in
the Vestfold Hills, the largest coastal ice-free area of Antarctica. The land
rises progressively to the southwest towards the ice sheet, and a ridgeline
in the ice topography is located around 60 km to the northeast of the
station . Casey station is located on the coast of the
Wilkes Land, at 12 m altitude. The Law Dome, which lies to the east of Casey
and which rises to an altitude of 1395 m, shields the base from the easterly
winds that predominate in the region. Dumont d'Urville station is located at
41 m altitude on Petrel Island, approximately 5 km off Adélie Land and
the ice sheet proper. The climate at the station is very influenced by strong
katabatic winds blowing from the interior of the ice sheet. Neumayer station
lies on the Ekström Ice Shelf, at a few kilometers from the shoreline.
The shelf extends more than 100 km to the south with an inclination of
approximately 0.1 ‰. Halley station is situated towards the seaward
edge of the Brunt Ice Shelf, Coats Land, on the southeastern shore of the
Weddell Sea at about 30 m altitude. The Brunt Ice Shelf extends to the
southeast of the station for over 40 km, and the uniform surface rises very
gradually over this distance until the hinge zone where the land steeply
rises up to the continental plateau. Unlike all the other stations of
interest here – that are located close to the coast and near sea level – PE
is 220 km away from the coast at 1382 m altitude. The station has been
built on a small granite ridge just north of the Sør Rondane Mountains in
the Dronning Maud Land and it is located at approximately 1 km north of the
Utsteinen Nunatak that culminates at an elevation of 1564 m.
Although fairly short for a climatological study, the 2010–2017 analysis
period was chosen because it fits the period for which ERA5 reanalysis was
available at the time of carrying out the analysis (see Sect. )
and because it corresponds to the period for which the model of radiosonde
used at most stations was Vaisala RS-92. The RS-92 sonde is currently the
most used sonde type over the globe and it is considered the reference
radiosonde by the Global Climate Observing System Reference Upper-Air
Network. This model has also been shown to be slightly affected by common dry
biases in cold and dry environments particularly due
to its two humidity sensors being heated alternately . Note that at the DDU and PE stations, the types of radiosonde
are Modem M2K2-DC and Graw DFM-09, respectively. showed a
low bias in relative humidity between 2 % and 10 % in Modem M2K2-DC
measurements compared to those obtained with RS-92 at the Observatoire de
Haute-Provence, southern France. Since 2013, a correction algorithm on
moisture measurements from DDU has therefore been applied, but this has
limited impacts on the statistics shown in the present paper. Technical
information on all the radiosonde types can be found at
https://www.graw.de (last access: 1 April 2019),
https://www.vaisala.com (last access: 1 April 2019) and
http://www.meteomodem.com (last access: 1 April 2019). The specifics of
the radiosoundings at each station including the sounding times are
summarized in Table . As the aim of this study is to characterize
the fine vertical structure of the low troposphere, we could not make use of
data from IGRA, which are subsets restricted to the so-called “mandatory”
pressure levels completed by a few additional levels with significant
deviation from linearity of temperature and dew point between mandatory
levels (so-called “significant levels”). Here, we rather use data sets
provided by local meteorological organizations or polar institutes that have
a higher vertical resolution. The sole treatment made on the raw data is a
15 s – ≈75 m – smoothing (applied twice) of the wind data, 15 s
being the averaged period of oscillation of the sonde in the first 3000 m
above the surface. This allows to remove the oscillations in the data due to
the natural pendulum motion of the payload after launching. Temperature,
humidity and wind measurements in the first 100 m are also excluded from the
data sets for two main reasons. First, the analysis of temperature and
humidity data potentially affected by thermal lag error – if the radiosonde
was not perfectly equilibrated outdoor before launching, for instance – is
avoided. Second, below an altitude of 100 m, the balloon may have not
reached the flow velocity yet and may thus be still in a transitory state.
shows that, for a typical balloon with an ambient wind
speed of 20 m s-1 (5 m s-1), the adaptation timescale is
approximately 5 s (20 s) corresponding to an altitude range of 25 m
(100 m).
Topography of the Antarctic
continent from the Bedmap2 data set at 10 km resolution
. Black dots indicate stations from which radiosonde
data are used in this study. The blue line delimits the Polar WRF simulation
domain. Red arrows show the 2010–2017 mean wind vector from ERA5
reanalyses.
Characteristics of radiosonde data used in this study. “DDU”
refers to Dumont d'Urville, “MZ” to Mario Zucchelli and “PE” to Princess
Elizabeth station. The indicated time corresponds to the official observation
time. Note that sondes are usually launched 45 min or 1 h before. For
each station, the percentage of data indicates the percentage of available
radiosoundings in the corresponding period. When two numbers are indicated,
the first (second) one corresponds to the percentage of sounding at
00:00 UTC (12:00 UTC). In the Casey and Mawson data sets, measurements
are not provided at constant time or vertical resolution. Subsequently, the
averaged number of vertical levels in the first 3000 m a.g.l. is indicated
in the “resolution” column.
Station nameSonde typePeriodVertical resolutionPercentage of dataUTC time(dd/mm/yyyy)(local time)HalleyVaisala RS-9201/01/2010–12/02/20172 s (≈10 m)90.812:00 (12:00)DDUModem M2K2-DC01/01/2010–31/12/20171 s (≈5 m)90.800:00 (10:00)McMurdoVaisala RS-9201/01/2010–31/12/20172 s (≈10 m)85.0, 50.500:00 (12:00),12:00 (00:00)NeumayerVaisala RS-9201/01/2010–31/12/20175 s (≈25 m)95.612:00 (13:00)MawsonVaisala RS-9201/01/2010–31/12/201723 levels in 3000 m95.212:00 (16:00)CaseyVaisala RS-9201/01/2010–31/12/201723 levels in 3000 m89.3, 86.900:00 (11:00),12:00 (23:00)DavisVaisala RS-9201/01/2010–31/12/20172 s (≈10 m)84.2, 75.600:00 (07:00),12:00 (19:00)MZVaisala RS-92Dec, Jan, Feb 2010–20162 s (≈10 m)67.2, 75.300:00 (11:00),12:00 (23:00)PEGraw DFM-09Dec 2014, 2015, 20175 s (≈25 m)51.912:00 (17:00)and Jan, Feb 2015, 2016ECMWF reanalysis products
Two reanalysis data sets from the European Centre for Medium-Range Weather
Forecasts (ECMWF) will be compared to radiosonde data over
the period 1 January 2010–31 December 2017. Firstly, the ERA-Interim (ERA-I;
) reanalysis is a third-generation reanalysis product with
an averaged horizontal resolution of 79 km and 60 vertical levels up to
0.1 hPa, among which 17 are in the first 3000 m a.g.l. The reanalysis is
based on simulations with the IFS model cycle 31r2 using a 4D-Var
assimilation. Comparing second- and third-generation reanalysis products with
Antarctic station observations, show that ERA-I is
the most reliable for mean sea level pressure and 500 hPa geopotential
height values and trends. ERA-I analyses are available at four times per day:
00:00, 06:00, 12:00 and 18:00 UTC. Secondly, we will use the last-generation
reanalysis product from the ECMWF: ERA5. Major improvements from ERA-I
include a better spatial resolution (31 km on average on the horizontal,
137 vertical levels up to 0.01 hPa among which 33 are in the first
3000 m a.g.l.), a more elaborated model physics (IFS cycle 41r2), more
consistent sea surface temperature, sea-ice cover and additional model inputs
from observations. A summary of the changes between ERA-I and ERA5 can be
found at
https://confluence.ecmwf.int/pages/viewpage.action?pageId=74764925 and
the physics of the IFS model used for ERA5 is described in the technical
notes on the ECMWF website (https://www.ecmwf.int). ERA5 analyses are
available at a 1 h granularity.
It is worth mentioning that radiosonde data at all the considered Antarctic
sites – except PE – have been assimilated by the IFS model to make both
ERA-I and ERA5. The reanalysis data sets are therefore not purely independent
from radiosonde data. Nevertheless, only the meteorological fields at
mandatory and significant levels are assimilated. Hence, the fine-scale
vertical structure of the boundary layer in ERA-I and ERA5 is expected to
remain strongly dependent on the model configuration.
Polar WRF simulations
Numerical simulations were carried out with the regional model Polar WRF
v3.9.1 (e.g., ). The simulation domain size is
5810km×5810km (see blue square in
Fig. ). It is centered over the South Pole and encompasses the
whole Antarctic continent. Simulations are run at 35 km horizontal
resolution over the period (2010–2017) (with a 1-week spinup). Initial
conditions and lateral boundary forcings, as well as sea-ice cover and sea
surface temperature are provided by the ERA5 reanalysis data set. As
recommended in , we use the Bedmap2 topography from
. The model is run with 66 vertical levels, among which
23 are located in the first 3000 m above the ground surface. As in the
standard configuration of the AMPS, the shortwave and longwave radiation
schemes are the Rapid Radiative Transfer Model for general circulation models
(RRTMG) scheme (updated every 15 min) and the cumulus scheme is the
Kain–Fritsch scheme. We use the two-moment microphysical scheme of that leads to the best
Polar WRF simulations compared to cloud and radiation measurements over the
Antarctic Peninsula . For the turbulent diffusion in
the boundary layer, we use the 2.5-level Mellor–Yamada–Nakanishi–Niino
(MYNN) turbulent kinetic energy (TKE) scheme coupled
with the MYNN surface layer scheme, as in .
Notwithstanding that MYNN is an advanced version of the
Mellor–Yamada–Janjic (MYJ) scheme – with improved formulation of mixing
length – noticed better WRF performance in terms of surface
temperature over West Antarctica using the original MYJ parameterization. To
assess the sensitivity to the turbulence scheme and the vertical resolution,
we have also carried out a simulation with the MYJ scheme coupled with the
η-similarity surface layer scheme and one simulation with a refined
vertical resolution close to the surface (see Sect. ).
Analysis methods
Our analysis will focus on the low troposphere that we delimit as the layer
between 0 and 3000 m a.g.l. This atmospheric layer was chosen because it
includes the boundary layer at all stations and because it is slightly deeper
than the mean depth of the equatorward mass flux layer
. Note also that z=3000 m a.g.l. corresponds
approximately to the altitude from which the zonal mean circulation over
coastal Antarctica reverses (from anticyclonic to cyclonic;
see ).
We will compare radiosoundings at each Antarctic station with the simulated
and reanalyzed profiles at the nearest model grid point. Details about the
geographical characteristics of the specific grid points are given in
Table S1. Otherwise mentioned, reanalysis and model profiles will be compared
to radiosonde data at each station at the same time as sonde launchings,
i.e., at 00:00 and/or 12:00 UTC, depending on the station (see Table ). It
is worth mentioning that the World Meteorological Organisation guidelines
state that sondes should be launched at a time such that they reach the
tropopause at the synoptic hour (00:00 or 12:00 UTC). To achieve this in the
Antarctic, where tropopause height is typically between 8000 and 9000 m,
sondes are launched around 45 min before the targeted hour. In the lowest
3000 m a.g.l., one might expect the best comparison with model data 1 h
before the notional synoptic hour. However, the statistical evaluation
in Sect. is not appreciably sensitive to a ±1 h shift
in the time sampling of reanalyses and Polar WRF data sets (not shown).
Three atmospheric variables will be analysed: the wind (speed and direction),
the temperature and the relative humidity calculated with respect to ice, as
temperatures are most of the time below freezing at all stations. We will
mostly focus on the relative humidity and less on the specific humidity (or
mixing ratio) for four reasons. First, the relative humidity is the variable
directly measured by radiosondes. Second, the specific humidity is a variable
that spans several orders of magnitude during the year due to its strong
dependency upon temperature making the annual statistics dominated by high
summer values. The third reason is that the critical variable for cloud and
precipitation formation and subsequently for the surface energy and mass
balance is the relative humidity. Last, the low-level sublimation process –
which is a crucial process over coastal East Antarctica – mostly manifests
in the relative humidity profiles. Information about the specific humidity
profiles will be nevertheless given in Fig. S1 in the Supplement.
In addition to yearly and seasonal statistics, we will consider for each
station a “precipitation events” ensemble, which gathers all profiles for
which substantial precipitation reaches the ground surface (precipitation
rate is greater than 0.1 mm h-1). For radiosounding profiles, the
precipitation conditioning is made using ERA5 reanalyses.
The statistics of wind, humidity and temperature profiles in reanalyses and
Polar WRF have been evaluated by comparing the median profiles as well as the
80–20th and 95–5th interquartiles at every model or reanalyses level
height. The ERA-I and ERA5 performance at the sounding time have also been
evaluated using mean bias and root mean square error calculations at their
respective vertical level heights. The variability in wind direction has also
been evaluated using the directional constancy parameter (DC), defined as
DC=u‾2+v‾21/2u2+v2‾1/2,
where u and v are the zonal and meridional components of the wind,
respectively, and the overbar indicates the time average.
Results
In this section, we present the main features of the vertical structure of
the low troposphere over coastal East Antarctica using radiosonde data and we
assess the ability of reanalyses and Polar WRF in reproducing the profiles
statistics.
General features of the vertical structure of the low troposphere from radiosonde data at nine Antarctic coastal stationsAnnual statistics
A broad view of the yearly vertical structure of the wind speed (U),
temperature (T) and relative humidity with respect to ice (RHi) in the low
troposphere from radiosonde data at each station is depicted in
Fig. . The reader can refer to Fig. S2 for separate statistics of
the zonal and meridional wind components and for further information about
the wind direction. It is worth remembering that only summer data are
available for MZ and PE stations. One particularly striking feature in
Fig. is the diversity of profiles around the coast of East
Antarctica. In the Ross Sea sector (McMurdo and MZ stations), one can notice
the low and nearly constant wind speed. As shown in and
, the atmospheric flow at McMurdo is strongly influenced
by orographic effects like the blocking of the dominant katabatic southerly
flow by the Ross Island. At the MZ station, the observed profiles are often
the results of the confluence of katabatic flows from the Reeves and
Priestley glaciers affected by local mountains . Moving
westward (from left to right in the Fig. ) to Adélie Land and
DDU station, a clear katabatic layer can be seen in the profiles. This layer
is characterized by high wind speeds (with an annual median around
10 m s-1) with a southeasterly direction and capped by a temperature
inversion at about 1000–1500 m altitude. Figure S2 also shows a clear
transition from a low-level easterly flow to a mid-tropospheric westerly flow
at an altitude of about 2300 m. Still more to the west in Fig. 2, Casey
station generally experiences light outflow from the northeast, off Law Dome
. This is visible in radiosonde data with a median wind
speed between 4 and 10 m s-1 monotonically increasing with increasing
height. Note the relatively high value of the 90th percentile in the first
500 m a.g.l. This observation recalls the results of
that explained one extraordinarily very strong wind event (10 m speed
exceeded 50 m s-1) at Casey associated with a deep low north of the
coast in concert with a high surface pressure inland. At the Davis station,
the yearly median wind profile reveals a deep katabatic layer with a moderate
median wind speed maximum of 7 m s-1 at approximately 800 m altitude
and with a northeasterly direction. At the Mawson station, Fig.
shows that both the median wind speed and the variability is maximum close to
the surface. This observation echoes the conclusions of
stating that the near-surface wind at Mawson is driven by shallow surface
drainage flows – thereby explaining the low-level maximum and its
northeasterly direction (Fig. S2) – and modulated by the vertical transfer
of momentum from the mid-troposphere that largely depends on the synoptic
pressure gradient which can strengthen or weaken the surface drainage flow.
Surface-based temperature inversions are a common climatological feature of
the Antarctic troposphere. Interestingly, for all the stations considered, no
surface-based inversion can be pointed out in the yearly median profiles from
radiosoundings. However, surface-based temperature inversions are present in
the first 100 m above the surface in ERA-I, ERA5 and Polar WRF (see
Sect. ). As the first 100 m of radiosonde data are not
analysed here due to the low reliability of radiosonde data in this layer,
this may explain the absence of inversion in the yearly median temperature
profiles at the McMurdo, DDU, Casey, Davis and Mawson stations.
At the DDU, Casey, Davis and Mawson stations, one can further point out that the
yearly median RHi profiles show lower values in the first kilometer above the
ground surface. This bottom layer of drier air corresponds to the advection
of absolutely dry air masses by katabatic winds that adiabatically warm
during their descent from the interior of the continent. At DDU, this process
is sufficiently strong to exhibit a clear signature in the yearly statistical
profiles of specific humidity (Fig. S1). Moving westward and inland towards
PE station, radiosonde data reveal nearly constant median profiles of wind
speed and RHi in summer. underline that the PE station
site is sheltered by the Sør Rondane Mountains in the south and it
is thus protected from strong katabatic jets. Albeit deflected, the flow
originating from the plateau shows a high directional constancy (>0.8)
over a depth exceeding 2000 m (see Sect. ). While the median
temperature linearly decreases with increasing height, the 80th and 90th
percentiles of temperature show constant and slightly increasing values close
to the surface, respectively, evidencing the occurrence of surface-based
inversions in summer during calm wind conditions (not shown). Neumayer and
Halley stations are both located on ice shelves and the respective vertical
structures of the low troposphere are reasonably similar.
shows that the low-level flow at Halley is forced by both synoptic-scale
pressure gradients and the pressure gradient due to the stable air over the
gently sloping surface of the Brunt Ice Shelf. draw
similar conclusions for Neumayer station over the Ekström Ice Shelf,
emphasizing the role of baroclinicity via the thermal wind effect in shaping
the wind structure. Figure shows that the median wind speed at
both stations exhibits a shallow maximum close to the surface that
corresponds to a northeasterly flow. The wind speeds show a large
intra-annual variability and they are slightly stronger at Neumayer than at
Halley, with medians at z=200 m close to 11 and 8 m s-1,
respectively. RHi is nearly constant or slightly decreasing with increasing
height. Unlike stations in coastal katabatic regions, the median temperature
profiles reveal a surface-based inversion in the first kilometer above the
ground.
Vertical profiles of the annual wind speed (top row), temperature
(middle row) and relative humidity with respect to ice (bottom row) from
radiosonde measurements at nine Antarctic stations. Black lines are the
medians, colored lines refer to the 10th, 20th, 30th, 40th, 60th, 70th, 80th
and 90th percentiles. In the legend, “Pctx” refers to the shaded area
that covers x percent of the data greater than the median and x percent
of the data lower than it. The altitude z is above ground level. Numbers in
exponential form next to station names in the title indicate the number of
radiosoundings per day at the corresponding station. The “*” symbol
labels the two stations for which only data from December to February are
shown.
Seasonal statistics
A comparison of the wind, temperature and relative humidity profiles between
the two extreme seasons – summer (December–January–February, DJF) and
winter (June–July–August, JJA) – is depicted in Fig. . We
consider here two stations at which the typical flow is katabatic – DDU and
Mawson – one station over an ice shelf – Halley – and the McMurdo station
where the vertical structure of the troposphere is influenced by the complex
terrain at the foot of the Transantarctic Mountains. One can point out
stronger wind speed at low levels in winter than in summer at the Mawson and
Halley stations, consistent with more stable boundary layers on the plateau
and subsequent stronger katabatic winds as well as stronger large-scale
pressure gradients . Such an increase is not visible
at the DDU station neither in the median nor in the percentiles. The absence of
strong seasonality in the low-level wind speed at DDU is in agreement with
surface observations in , while measurements at
meteorological stations a few tens of kilometers further inland reveal
significantly stronger wind speed in winter than in summer (e.g.,
). This suggests that a slowing down mechanism at the
coast that should be particularly active in winter – like the pressure
gradient force associated with the piling up of cold air over sea ice – may
damp the seasonal cycle. At the Halley, Mawson and DDU stations, the wind
direction at z=500 m is almost constant throughout the year, reflecting
the strong orographic influence in shaping the low-level flow at these three
locations. It is also worth noting that, unlike in summer, the JJA median
profile of wind speed at DDU, Mawson and Halley show a significant increase
with increasing height above 2000 m. This may be explained by the location
of the edge of the polar vortex – which is stronger in winter – that lies
closer to edge of the continent in winter and can be responsible for a
significant vertical gradient of the wind speed even in the mid-troposphere
.
At the McMurdo station, the wind speed is slightly stronger in winter and it
is vertically homogeneous over the first 3000 m in both DJF and JJA seasons.
Temperatures at the four stations are naturally warmer in summer than in
winter, but the capping inversion at DDU and Mawson above the katabatic layer
is more pronounced in JJA. Likewise, the surface-based temperature inversion
over Halley is not present in summer. Note that, due to the diurnal cycle of
the insolation during the summer season, summer vertical profiles may depend
on the local time of the sounding and may not be considered as
climatologically representative. The temporal representativity of
radiosoundings will be further discussed in Sect. . The
relative humidity profile at McMurdo shows a clear seasonality, with more
humid air (relatively) above 2000 m in summer. This is consistent with the
summer wind rose at z=2000 m with more frequent flow from the east
compared to the winter season. Easterly winds at McMurdo generally correspond
to the advection of air masses that transit over the Ross Ice Shelf or Ross
Sea and that do not directly come from the dry atmosphere over the ice sheet.
The relatively dry katabatic layer at the DDU and Mawson stations is well
visible in the summer and winter RHi profiles, with an especially pronounced
“dry concavity” in winter at DDU. Interestingly, the winter median profile
of RHi at the DDU station slightly increases with decreasing height in the
first few hundred meters above the surface.
Stronger water turbulent fluxes at the surface in winter are hardly probable
since there is no open ocean close to the station in winter, while it is
often the case in summer. This local maxima in the profiles may thus be
attributed to the presence of blowing snow in the near-surface flow, which is
more frequent in winter due to stronger katabatic winds on the ice sheet and
to a better snow surface erodibility .
DJF (left panels) and JJA (right panels) vertical profiles of the of
the wind speed (top row), temperature (middle row) and relative humidity with
respect to ice (bottom row) from radiosonde measurements at four Antarctic
stations. Black lines are the medians, colored shadings refer to the 10th,
20th, 30th, 40th, 60th, 70th, 80th and 90th percentiles. In the legend,
“Pctx” refers to the shaded area that covers x percent of the data
greater than the median and x percent of the data lower than it. The
altitude z is above ground level. Wind roses at z=500 and at z=2000 m
are also plotted in the top row panels. Numbers in exponential form next to
station names in the title indicate the number of radiosoundings per day at
the corresponding station.
Statistics during precipitation events
have stressed the role of katabatic winds in
sublimating a significant part of the precipitation falling on the margins of
the ice sheet. In this section, we examine the vertical structure of the wind
and relative humidity during precipitation events at the six stations with
the most intense winds. In agreement with , the second
row of Fig. shows that even during precipitation events, the
atmosphere is unsaturated close to the surface at DDU, Casey, Davis and
Mawson. The first row of Fig. also shows that the wind is
generally enhanced during precipitation events at the latter four stations
(in comparison with the climatology in Fig. ). Moreover, wind roses
at z=500 m in the bottom row of Fig. show that the flow at
this altitude is mostly southeasterly, northeasterly, easterly and
northeasterly at DDU, Casey, Mawson and Davis, respectively. This means that
the low-level flow remains of continental origin during most of the
precipitation events (see map in Fig.). The strengthening of the
continental low-level flow at the Antarctic coast during precipitation events
is consistent with the general picture of moisture advection by synoptic
cyclones documented in . As a synoptic
weather system transits eastward off the Antarctic coast and approaches a
station, it advects oceanic air with clouds towards the continent at its
eastern flank. Note that largest amounts of moisture and precipitation are
brought by large frontal systems not necessarily associated with very intense
cyclones but with low-pressure systems with a large radius
. Meanwhile, the surface pressure over the ocean
decreases, the downslope pressure difference increases, and subsequently the
near-surface wind flow from the continent increases. Strong near-surface
winds and low relative humidity are thus very favorable conditions for the
occurrence of the mechanism of low-level sublimation of precipitation (LSP;
) at the DDU, Mawson, Davis and Casey stations. Note that
even during precipitation events, the relative humidity can be as low as
25 % (26 %) above z=2000 m (below z=500 m) at the DDU
station. These situations often correspond to precipitation from clouds –
associated with northerly warm advection – above 3000 m and moving above a
remaining deep layer of continental flow from the interior of the ice sheet.
The low near-surface humidity values could be partially attributed to the
precipitation conditioning by ERA5 data that may lead to the inclusion of
spurious profiles (i.e., not corresponding to actual precipitation at the
station) in the “precipitation subset”. However, also
show low values of RHi in the first 3000 m a.g.l. at DDU when conditioning
the radiosonde profiles to precipitation and virga events from in situ radar
data, confirming the actual concomitant occurrences of precipitation and
low near-surface relative humidity at DDU.
Figure shows that, despite enhanced wind speed at the Neumayer and
Halley stations, the first 3000 m of atmosphere are completely saturated
during precipitation events, reflecting the likely absence of the LSP
mechanism at these stations. For instance, the wind rose at z=500 m at
Halley shows that the wind at this station during precipitation events is
northeasterly, indicating a flow from the coastal edge of the Brunt Ice Shelf
and not from the interior of the ice sheet. This observation sheds light on
the geographical discrepancies of the LSP around the coast of East
Antarctica.
Vertical profiles of the wind speed (top row) and relative humidity
with respect to ice (bottom row) from radiosonde measurements at five
Antarctic stations along the eastern Antarctic coast. Data sets are
restricted to precipitation cases. Black lines are the medians, colored lines
refer to the 10th, 20th, 30th, 40th, 60th, 70th, 80th and 90th percentiles.
In the legend, “Pctx” refers to the shaded area that covers x percent
of the data greater than the median and x percent of the data lower than
it. The altitude z is above ground level. Wind roses (conditioned to
precipitation events) at z=500 and z=2000 m are plotted in the lower row
panels. Numbers in exponential form next to station names indicate the number
of radiosoundings per day at the corresponding station.
Evaluation of the vertical profile statistics in ERA-I, ERA5 and Polar WRF
In this section, we assess the ability of ERA-I, ERA5 and Polar WRF to
accurately reproduce the vertical structure of the low troposphere at the
nine Antarctic stations. It is worth remembering that, unlike the free-running
Polar WRF simulation, ERA-I and ERA5 reanalyses are not fully independent
from radiosoundings since they frequently assimilate them at low vertical
resolution (except at the PE station). Note also that for complementing the
figures presented in this section, the reader can refer to figures similar to
Fig. for the ERA-I, ERA5 and Polar WRF data sets as well as a
figure showing median and interquartile differences for all stations and all
variables in the Supplement (Figs. S3, S4, S5, S6 and S7).
Wind
Figure shows the differences of yearly median, 80–20th
interquartile and 95–5th interquartile of wind speed with respect to
radiosonde data at the nine stations. This figure can be analysed in parallel
with Fig. , which compares the directional constancy at z=500 m
(dotted axes) and z=2000 m (solid axes) in the different data sets.
Figure S6 also provides the comparison of the statistics for the zonal and
meridional components of the wind separately. Above 2000 m a.g.l., the
median and interquartile absolute differences of the wind speed are generally
less than 3 m s-1 in ERA-I and ERA5. The mid-troposphere circulation
and its variability are thus reasonably well reproduced over the coastal East
Antarctic margins in the reanalyses. Polar WRF often shows slightly higher
values of the interquartile differences and it significantly overestimates
the directional constancy at z=2000 m at all stations and especially in
the Ross sector (McMurdo and MZ stations; see Fig. ). This too
directionally constant flow combined with an overestimation of the variability
of the wind speed at McMurdo (Fig. a) particularly
questions the ability of a model running at 35 km resolution to represent
the local flow, even at z=2000 m, in Antarctic regions with complex
orography. This also suggests that in reanalyses with similar or coarser
horizontal resolution, the data assimilation may play a substantial role in
reproducing the wind statistics at the McMurdo and MZ stations. In katabatic
regions, Polar WRF and reanalyses represent reasonably well the sharp
increase in directional constancy from z=2000 to z=500 m that shows the
contrast between the synoptic and the katabatic flows. However, significant
deficiencies can be noted for the low-level wind speed, especially at DDU,
Casey and Davis stations. At these three stations, the median and the
interquartiles are overestimated in the three data sets. At the Davis and Casey
stations, the simulated median low-level flow has an excessive westward
velocity, while at DDU the median low-level wind has a too-pronounced
southward component (Fig. S6). Smallest differences are generally observed
for ERA5, even though large values of the 95–5th interquartile differences are
noticeable, for instance, at Casey, where the value exceeds 5 m s-1 at
z=500 m in the two ERA reanalyses. The largest differences are noticeable
for Polar WRF, especially near the ground surface. These differences actually
reflect a too-shallow and too-strong katabatic jet. Albeit observed in both
summer and winter seasons, the near-surface wind speed overestimation is more
pronounced in winter at the three stations and it only occurs in winter at
the Mawson station (see Table ). Section will
investigate the possible underlying causes of this strong katabatic wind
deficiencies in Polar WRF. At the Neumayer and Halley stations, the statistics of
the wind structure are well reproduced by the ERA5 reanalysis, while ERA-I
underestimates the variability in the first 500 m above the surface with
interquartile differences around -4 m s-1. Polar WRF shows correct
statistics at Neumayer, but it overestimates the interquartiles as well as
the directional constancy at Halley at both z=500 and z=2000 m
(Fig. ). This suggests an underestimation of the synoptic
variability in the Halley region in the model and particularly an
underestimation of large-scale southwesterly flows from the Weddell Sea (not
shown). At the PE station, the summer distribution of the wind speed in
reanalyses and Polar WRF significantly differs from the one from radiosonde
data. At z=1000 m, the median difference is close to 8 m s-1 for
the three data sets and Polar WRF shows a much stronger median wind speed
overestimated by 4–8 m s-1 up to 3000 m. ERA-I shows a very
excessive median wind speed in the first 1000 m, while in ERA5, the wind
speed and variability are strongly overestimated between z=300 and
z=1500 m. Note that these deficiencies are mostly due to an overestimation
(in absolute value) of the westward component of the flow (Fig. S6). As PE is
the sole station from which radiosonde data are not assimilated, these strong
biases question the ability of the free IFS model at the considered
horizontal resolution in reproducing the dynamics of Antarctic boundary
layer, at least in the PE region where the air flow is strongly affected by
the topography of the Sør Rondane Mountains.
Yearly median differences (solid lines), 80–20th interquartile
difference (dashed lines) and 95–5th interquartile difference (dotted lines)
with respect to radiosoundings for wind speed at nine Antarctic stations.
Red, green and cyan lines refer to Polar WRF, ERA5 and ERA-I, respectively.
Grey strips delimit the first 100 m above the ground surface. Polar WRF and
ERA reanalyses are conditioned to radiosounding times. Numbers in exponential form next to station names in
the title indicate the number of radiosoundings per day at
the corresponding station. The “*” symbol labels the two stations for which
only data from December to February are shown.
Yearly directional constancy at z=500 m (dotted axes) and
z=2000 m (solid axes) at nine Antarctic stations. Polar WRF (PWRF), ERA-I
and ERA5 data are conditioned to radiosounding (RS) times. Numbers in
exponential form next to station names indicate the number of radiosoundings per day at
the corresponding station. The “*” symbol labels the two stations for which
only data from December to February are shown.
Values of the median difference/80–20th interquartile
difference/95–5th interquartile difference with respect to radiosonde wind
speed data at z=250 m (in m s-1) at four Antarctic
stations in katabatic regions. DJF and JJA subsets are distinguished.
Station nameSeasonERA-IERA5Polar WRFDDUDJF0.021/-0.174/-2.031.29/-0.98/-2.40-1.13/0.85/-0.20JJA3.12/1.20/-0.974.02/1.73/0.0268.41/3.76/6.34DavisDJF0.73/1.94/3.011.27/1.94/1.930.97/4.18/6.92JJA3.56/4.77/3.413.20/2.46/3.1912.2/10.3/12.4CaseyDJF2.80/3.43/1.010.41/1.23/-1.373.43/8.69/8.33JJA8.65/7.70/5.441.82/6.02/6.339.03/17.2/17.8MawsonDJF1.23/-1.71/-0.670.36/-0.03/1.23-0.57/-2.14/-0.67JJA1.22/-0.81/0.201.50/-0.11/1.026.20/3.33/5.16Temperature
Figure is similar to Fig. but for temperature
profiles at four stations with very different yearly temperature statistics
(see Fig. ). At Davis, not only the median but also the variability
is well reproduced by ERA-I, ERA5 and Polar WRF. This result can be extended
to the stations in katabatic regions: Mawson, DDU and Casey. A cold median
bias between 2 and 4 ∘C can however be noticed at Mawson in ERA-I
(see Fig. S7), which can be partly explained by the more inland location of the
nearest ERA-I grid point. At the Halley station, ERA-I and ERA5 profiles are very
close to those from radiosonde data. Polar WRF also shows realistic median
profiles, but it overestimates the interquartiles in the first 2000 m.
Similar observations can be made for Neumayer station (Fig. S7). These two
results are actually a consequence of a warm (and moist) bias in summer and a
cold bias in winter that compensate on average over the year (not shown). The
cold winter bias can be explained by too-frequent low-level easterly flows in
the model, whereas the warm summer bias is probably due to the location of the
nearest grid point in Polar WRF, which is closer to the ocean. The model is
hence more prone to oceanic influences when the ocean is free of ice. At the
McMurdo station, ERA-I and ERA5 also show realistic temperature median
profiles and variability, consistently with the bi-daily assimilation of
radiosonde at this station. Polar WRF shows a reasonable median profile, but
it overestimates the variability. This overestimation can be explained by
too-frequent warm (and moist) oceanic influences in spring and autumn (not
shown).
The strongest temperature differences between reanalyses and Polar WRF with
respect to radiosonde data are at the PE station (in summer). Low-level median
profiles are too cold by ≈2∘C in reanalyses and too warm
by slightly higher values in Polar WRF. The interquartile difference –
especially the 95–5th interquartile difference – are underestimated with
absolute values exceeding 10 ∘C at z≈1000 m (out of graph
limits). This observation actually reflects the absence of deep surface-based
inversions in Polar WRF and reanalyses at PE in summer at radiosonde
launching time. In radiosonde data, the summer inversions are mostly observed
in February, i.e., at the end of the summer period, when the length of the day
period has already been reduced. Note that reanalyses and Polar WRF do reproduce
surface-based inversions at the PE station during calm summer nights, but their
timing does not exactly correspond to radiosounding times.
Yearly median differences (solid lines), 80–20th interquartile
difference (dashed lines) and 95–5th interquartile difference (dotted lines)
with respect to radiosoundings for temperature at four Antarctic stations.
Red, green and cyan lines refer to Polar WRF, ERA5 and ERA-I, respectively.
Grey strips delimit the first 100 m above the ground surface. Polar WRF and
ERA reanalyses are conditioned to radiosounding times. Numbers in exponential form next to station names in
the title indicate the number of radiosoundings per day at
the corresponding station. The “*” symbol labels the station for which only
DJF data are shown.
Humidity
ERA reanalyses generally represent well the water vapor content in the low
troposphere at all stations. One exception is at the MZ station, where ERA-I
and ERA5 significantly underestimate the specific humidity in the first
kilometer above the surface in summer, with median differences reaching
approximately -0.50 and -0.85 g kg-1, respectively. Polar WRF show
reasonable yearly median profiles of specific humidity, but the
interquartiles are overestimated in the first 1000 m at almost all stations
(see Fig. S1). This is actually explained by a summertime (DJF)
overestimation of the water vapor content near the surface, with values
reaching, for instance, 0.5, 1.1 and 0.65 g kg-1 at the Davis, DDU and
Mawson stations, respectively. One likely cause for this moist bias is an
overestimation of the surface water fluxes due to overestimated near-surface
wind speed at most stations (see Sect. ). It should also be
noted that near the surface, balloons often sample air coming from the ice
sheet or air in the local boundary layer, i.e., above the station terrain.
However, in the model, meshes encompassing coastal stations are
heterogeneous; i.e., they contain a fraction of land, sometimes sea ice
and/or open ocean (see Table S1). As surface fluxes in a mesh are calculated
as the weighted sum of fluxes over each subsurface, the comparison of surface
water fluxes with those at an isolated station may thus be flawed. The same
conclusion can be drawn for the near-surface specific humidity. Note that the
comparison of observed summer near-surface humidity with that from the
nearest fully continental model grid points is generally more satisfactory
(not shown). It is also worth mentioning that in the versions of IFS used to
make ERA-I and ERA5, grid boxes with a land fraction value above 0.5 are
wholly treated as land, while those with
a value below 0.5 are treated as ocean. Subsequently, when ERA grid boxes
encompassing Antarctic stations are continental, the reanalyzed near-surface
humidity profiles are not directly affected by fluxes from the ocean.
Regarding the relative humidity, the performance of both reanalyses and
Polar WRF is a little less satisfactory. Generally, yearly median and
interquartile differences are comprised between -25 % and +25 % (see
Fig. S7). Figure depicts the difference of RHi statistics at
four stations in four distinct sectors along the East Antarctic rim. At the
Halley station (Fig. b), the median and 80–20th interquartile profiles in
the three data sets are reasonable but the 95–5th interquartile is
underestimated in the two reanalysis products. Similar conclusions hold for
Neumayer station. At the DDU station (Fig. c), one can point out the
overestimation of the median RHi and an underestimation of the interquartiles
at z=1000 m in particular in ERA-I and Polar WRF. The dry layer
corresponding to the katabatic flow is therefore too shallow in the
reanalyses and in Polar WRF. At the Mawson station (Fig. d), the three data sets
show reasonable median RHi values. However, the interquartiles in the first
1000–1500 m above the surface are overestimated likely due to an of excess
of water vapor in the lowest atmospheric layers during the summer season.
Above 2000 m, the interquartiles are underestimated in the three data sets
reaching values up to -23 % in ERA-I and ERA5 for the 95–5th
interquartile. This is explained by an underestimation of very dry conditions
(RHi < 30 %) compared to radiosonde data. Note that the performance of
reanalyses and Polar WRF at the Davis and Casey stations is relatively similar
(see Fig. S7).
At the McMurdo station (Fig. a), the three data sets
overestimate the near-surface RHi close to the surface, and this occurs both
in the summer and winter seasons (not shown). Indeed ERA-I, ERA5 and Polar
WRF show a significant increase in RHi (median and percentiles) with
decreasing height in the first 500 m above the surface while this feature is
much less pronounced in radiosonde data.
A critical point to investigate for the surface mass balance of the ice sheet
is the ability of reanalyses and Polar WRF to represent the RHi profiles
during precipitation events. Figure shows the median and
interquartile differences of RHi during precipitation cases at the Mawson and DDU
stations – i.e., the two stations with the most significant decrease in RHi
in the katabatic layer (see Fig. ) – as well as at the Neumayer
and Halley stations where the lowest layers saturate or are close to
saturation during precipitation events. At Halley and Neumayer, the median
RHi values from ERA-I, ERA5 and Polar WRF are close to radiosonde data. The
variability is also correct, but a significant underestimation of the 95–5th
interquartile can be pointed out in the reanalyses above 1500 m. At the Mawson
station, ERA5 shows a correct representation of the median profiles and of
the variability of RHi, but ERA-I and Polar WRF slightly overestimate the
median in the first 1000 m. At the DDU station, this overestimation is even
further marked, with median differences reaching -12 %, -23 % and
-29% in ERA5, ERA-I and Polar WRF, respectively. Another striking feature
at DDU is the very strong underestimation of the interquartiles in the three
data sets. Indeed, during precipitation events, the simulated and reanalyzed
atmospheres above the katabatic layer is completely, or almost, saturated,
leading to an unrealistically weak RHi variability.
Yearly median differences (solid lines), 80–20th interquartile
difference (dashed lines) and 9–5th interquartile difference (dotted lines)
with respect to radiosoundings of RHi at four Antarctic stations. Panels (a, b)
show the DJF subset, panels (c, d) the JJA subset. Red, green and cyan lines
refer to Polar WRF, ERA5 and ERA-I, respectively. Grey strips delimit the
first 100 m above the ground surface. Numbers in exponential form next to station names in
the title indicate the number of radiosoundings per day at the corresponding
station.
Yearly median differences (solid lines), 80–20th interquartile
difference (dashed lines) and 95–5th interquartile difference (dotted lines)
with respect to radiosoundings for RHi during precipitation events at the Mawson,
DDU, Halley and Neumayer stations. Red, green and cyan lines refer to Polar
WRF, ERA5 and ERA-I, respectively. Grey strips delimit the first 100 m above
the ground surface. Polar WRF and ERA reanalyses are conditioned to
radiosounding times. Mind the different horizontal axis compared to
Fig. .
DiscussionSpatial and temporal representativity of radiosonde data
As radiosoundings sample the atmosphere once or twice a day at a given
specific location, one can question the temporal and spatial representativity
of the statistics presented in Sect. . One can indeed wonder
to what extent an analysis based on radiosonde profiles provide a realistic
picture of the whole – i.e., including the daily variability – temporal
statistics at a given station and to what spatial extent the profiles at the
nine Antarctic stations are representative of the full coastal rim of East
Antarctica.
Figure provides some elements of response about
the temporal representativity by comparing the statistical profiles of wind
speed and temperature at four stations from ERA5 reanalyses considering the
full data set (magenta profiles) or the subset conditioned to radiosonde
times (green profiles). During winter (Fig. c, d, g and h), median and
20–80th interquartile profiles are almost superimposed, suggesting that the
8-year period considered here is sufficiently long so that subsampling at
radiosonde time does not significantly change the winter statistics.
In summer, one could expect a larger difference between both data sets since
the insolation evolves with a diurnal cycle which may affect the diurnal
variability of the boundary layer. At McMurdo (Fig. a), almost no difference
between magenta and green profiles can be underlined, reflecting that the
bi-daily sampling (00:00 and 12:00 UTC) is sufficient to capture most of the
variability at the multi-annual scale. At the Mawson station, the wind and
temperature profiles slightly differ in the first 1000 m above the surface.
Wind and temperature subsampled at sounding times exhibit a lower variability
and they are both higher. This is in agreement with the fact that sondes at
Mawson are launched at 16:00 LT, i.e., during the diurnal warm phase
of the boundary layer. At the Halley station, underlines the
very weak summer diurnal cycle of near-surface temperature and the absence of
diurnal variations of wind speed and boundary-layer height. This is due to
the great partitioning of incoming radiative energy at the surface into
latent heat flux. This leads to a clear diurnal cycle in near-surface
relative humidity which also acts to damp the near-surface
air temperature variations and the thermal mixing in the boundary layer. The
superimposition of green and magenta curves in Fig. d is
consistent with these conclusions. At the DDU station, the summer boundary layer
does evolve with a diurnal cycle in particular due to the
alternation of daytime sea breezes and nocturnal katabatic winds. Particularly
when the DDU island and the nearby ocean are free of snow/ice, convection
can even occur during daytime in calm wind conditions.
In the ERA5 data set, the DDU summer profiles show a diurnal cycle with
warmer near-surface temperatures and weaker wind speed during daytime than
during nighttime. However, Fig. b shows that the 8-year
summer statistics conditioned to the sonde launching time (12:00 UTC,
10:00 LT) are very close to the full summer statistics. This
apparent coincidence may be explained by the timing of the sonde launching
which does not correspond either to the middle part of the nocturnal
katabatic phase or to the most pronounced phase of the diurnal boundary
layer.
To assess the spatial representativity of radiosoundings, we have identified
spatial “footprints” of each station using ERA5 data. In other words, we
have estimated for each station the spatial neighborhood over which the
structure of the low troposphere is similar to that at the station. For this
purpose, we have calculated the overlaps of the 8-year distributions of wind
speed and temperature at two representative vertical levels at every grid
point with those at the station grid point (see details in Appendix A). We
have then made maps associated with each station showing for every grid point
the minimum value among the four independent overlaps (see
Fig. ). We can point out that the statistical properties of
the low troposphere at the nine stations can be reasonably extended to a
significant part of coastal Antarctica. In particular, the structure of the
low troposphere over Halley and Neumayer is representative of those over many
ice shelves and coastal margins, with regions for which the overlap exceeds
85 % even thousands of kilometers away from the stations. On the other
hand, the “footprint” of MZ, PE, Casey and McMurdo is limited to relatively
small areas, indicating that the shape of the profiles at these stations is
quite regional. Dumont d'Urville, Mawson and Davis seem reasonably
representative of a significant part of the coastal edge, but the percentage
overlap rarely exceeds 80 %, indicating that part of their wind and
temperature and wind distributions are explained by regional effects. Note
that our method of footprint determination does not consider the full
profiles but only two representative vertical levels (z=500 and
z=2000 m). Further studies are therefore needed to more precisely
characterize the spatial variability of the full profiles along the Antarctic
rim, making use, for instance, of radiosonde data at extra coastal stations
like Syowa or Novolazarevskaya.
Vertical statistics of temperature (left part of panels) and wind
speed (right part of panels) in DJF (top row) and JJA (bottom row) from ERA5
reanalyses at four Antarctic stations. Dashed green lines (solid
magenta lines) show the medians of the ERA5 data set restricted to
radiosonde launching times (of the full ERA5 data set). Color shadings
delimit the associated 80–20th interquartiles. Numbers in exponential form next to station names in
the title indicate the number of radiosoundings per day at the
corresponding station.
Spatial representativity of the low troposphere at the nine
Antarctic stations. For each station (panel), colors indicate
the minimum value reached by all the
four overlaps between the independent distributions of the 500 m
temperature, 2000 m temperature, 500 m wind speed and 2000 m wind speed at
the ERA5 grid point with those at the station. In each panel, the location of
the corresponding station is indicated with a blue dot.
From ERA-Interim to ERA5: additional insights into the performance of reanalyses
In Sect. , we evaluated the performance of ERA-I and ERA5
reanalyses using median and interquartile differences. With this method, it
could be shown that both reanalysis products have reasonable and comparable
performance in terms of temperature profiles. In terms of wind speed, both
reanalyses show similar results, even though ERA5 was slightly closer to
radiosonde data near the surface at Neumayer and Casey. The comparison of the
performance for the two data sets is more complex for the relative humidity
because of very strong discrepancies from one station to
another.
To better discriminate ERA-I and ERA5, we have plotted the mean biases and
the root mean square errors (RMSEs) with respect to radiosoundings at seven
stations in Fig. . The concomitant comparison inherent to the use
of mean bias and RMSE scores is relevant for these two products since the
timing of the real circulation and the one in reanalyses should be in
principle close to each other, especially near stations where radiosonde data
are assimilated. One can notice that mean bias and RMSE curves are generally
closer to the zero line for the ERA5 data set (bottom row), shedding light on
the overall improvement from ERA-I to ERA5. It is beyond the scope of the
present study to pinpoint the specific changes between the two reanalyses
data sets that led to the reduction of errors. However, one may assume that
the refinement of both horizontal and vertical grids has significantly
contributed to this improvement. However, Fig. also highlights
substantial deficiencies still present in ERA5, particularly the large RMSE
of RHi – exceeding 20 % at Neumayer, McMurdo, Davis and DDU – and of wind
speed that can exceed 5 m s-1 at DDU, Casey and Davis.
Mean bias (solid lines) and root mean square errors (dotted lines)
in ERA-I (top row) and ERA5 (bottom row) with respect to radiosoundings at
seven permanent Antarctic stations. Panels (a) and (d) show
results for the wind speed, panels (b) and (e) results for
the temperature, and panels (c) and (f) results for the
relative humidity with respect to ice.
(a–c) Meridional cross section
(longitude: 140.00∘) of the June–July–August mean potential
temperature around DDU in Polar WRF simulations at 27 km resolution
(a), 9 km resolution (b) and 3 km resolution (c).
June–July–August mean vertical profiles of the wind speed at four locations
along a continent–ocean transect are also plotted. (d–f) Mean JJA
vertical profiles of wind speed at the DDU station. Blue lines refers to the
2010–2017 radiosonde (RS) data set, red lines to Polar WRF simulations at
27 km resolution (d), 9 km resolution (e) and 3 km
resolution (f). In panels (e) and (f), Polar WRF
vertical profiles are computed following the method in Appendix C for more
consistent comparison with radiosonde data.
Sensitivity of Polar WRF simulations
Among the deficiencies identified in Polar WRF in Sect. , the
overly shallow and strong low-level jet at the DDU, Casey, Mawson, Davis,
Neumayer and Halley stations was particularly striking. To gain insights into
the ability of Polar WRF to reproduce the low-level wind profiles over
coastal East Antarctica, we carried out sensitivity tests to the turbulence
scheme and to the vertical resolution with the same setup as the one
described in Sect. . Using the more diffusive MYJ turbulence
scheme instead of MYNN produces a slightly weaker and thicker wind jet but
does not lead to major changes in the simulation. Moreover, increasing the
vertical resolution from 23 to 40 levels in the first 3000 m a.g.l. does
not significantly improve the annual or seasonal statistics of the simulated
profiles (not shown). and have
stressed the importance of the slowing down of katabatic winds at the
Antarctic edges by thermal wind effects due to either sea breezes or the
piling up of cold air over ice shelves or sea ice, leading to a
ocean–continent pressure gradient force. In order to evaluate the ability of
Polar WRF to reproduce this effect and to assess the sensitivity of the
model's horizontal resolution, we have set up a new simulation (see
Appendix B) that focuses on the DDU region. As seen in
Sect. , the regional dynamics at DDU is not completely
representative of the whole East Antarctic coast but
showed that the thermal wind effect occurs along
almost all the edge of Antarctica (see their Fig. 11). This suggests that if
Polar WRF fails in reproducing this process in Adélie Land, it may fail
over many other regions along the ice sheet. The winter latitude–height
cross section of the potential temperature is shown in Fig. for
simulations at 27, 9 and 3 km resolution. The wind speed profiles at four
locations on the continent–ocean transect (among which DDU) are also
plotted. The wind speed profiles at -66.97∘ latitude are relatively
similar for the three resolutions. This suggests that a 27 km resolution
(Fig. a) may be sufficient for modeling the wind over the slopes
of this region of the ice sheet, but further comparison with in situ data is
needed to ascertain this assumption. Moving towards the edge of the
continent, one can also point out that at a resolution of 27 km
(Fig. a) the cold air bump is shallower and does not extend
inland. Indeed, at low resolution, the flow from the ice sheet spreads out
over the sea ice or ocean rather than vertically accumulating particularly
due to the size of the meshes. As a consequence, the associated pressure
gradient force towards the ice sheet, the slowing down of the near-surface
jet over the margins and the subsequent damping and thickening of the
katabatic layer are much weaker in coarse-resolution simulations. Mean
vertical profiles at 3 and 9 km resolution thus compare better with
radiosonde observations (Fig. d, e and f; see also the specific
methodology for high-resolution simulations and radiosonde data in
Appendix C). However, Fig. c and f also show that there is a
shallow wind jet very close to the surface in the mean wind profile at the
DDU station even at 3 km resolution. This jet disappears a few kilometers
downstream. Increasing the horizontal resolution up to 3 km has helped to
reproduce the general behavior of the flow over the coastal margin, but a
near-surface wind bias remains at the specific location of DDU. As DDU is
located on a small rocky island (Petrel Island), one may suspect local
orographic effects on the near-surface flow that cannot be reproduced even at
a resolution of 3 km. This issue should be addressed in the future.
Even though this short analysis does not provide a full explanation of the
wind biases in the Polar WRF simulation over the whole Antarctic coast, it
suggests that the 35 km horizontal resolution is not sufficient to reproduce
the sharp gradients of temperature, pressure and wind at the coastal edge.
This point questions the ability of current general circulation model but
also regional models that run at resolutions of several tens of kilometers
(e.g., ) to correctly reproduce the
structure of the low troposphere over coastal Antarctic margins, the
horizontal extent of katabatic winds and the LSP process.
Conclusions
This study employs high-vertical-resolution data sets of radiosonde data at
nine Antarctic stations to characterize the fine vertical structure of the
low troposphere over the coastal margins of East Antarctica and to assess the
performance of ERA-I, ERA5 and Polar WRF. The examination of radiosonde data
has revealed a large spatial variability of the vertical profiles along the
East Antarctic coast, in particular with strong differences between profiles
at stations over ice shelves, stations in katabatic regions and stations in
the Ross Sea sector with complex orographic influences. The seasonal
variations have been portrayed here by comparing DJF and JJA ensembles. The
analysis has revealed higher wind speeds in winter than in summer at most
stations. This can be explained by more stable boundary layers over the
plateau – and subsequently more intense katabatic flows – and to a lesser
extent by stronger synoptic pressure gradients during winter. However, the
wind profiles at DDU show similar speeds in both winter and summer. This
point underlines the critical role of slowing down mechanisms probably
associated with thermal wind effects, which are particularly intense in
Adélie Land during winter. During precipitation events, winds are
generally stronger due to the increase in the pressure gradient force
associated with the passing synoptic weather system. The inspection of
relative humidity profiles suggests that the LSP frequently occurs at DDU,
Casey, Davis and Mawson stations, but this phenomenon does not appreciably
affect precipitation at Neumayer and Halley. Both reanalysis products, as well
as Polar WRF, overestimate the low-level wind speed in katabatic regions.
Additional Polar WRF simulations at different resolutions over DDU suggest
that this may be a consequence of an underestimated coastal thermal wind
effect associated with the piling up of cold air when the resolution is too
coarse. ERA5 reanalysis overall better compares with radiosonde data than
ERA-I but significant biases remain, particularly for the wind speed and
relative humidity in katabatic regions. Moreover, large wind and temperature
differences with similar amplitude as Polar WRF have been noticed in both
reanalyses at the PE station during summer. This may suggest that the reasonably
correct performance of reanalyses at several stations is in a significant
part due to the assimilation of the local radiosoundings, inviting a
further evaluation of the free IFS model.
Overall, the 8-year radiosounding-based climatology and the thorough
evaluation of reanalyses presented in this article may be relevant for future
climate model evaluations in this extremely important region of the Earth
where intense air mass exchanges between polar and midlatitudes occur and
where atmosphere–ocean interactions control globally relevant processes such
as sea ice and bottom water formation. Although the statistics calculated
from ERA5 vertical profiles at a daily or bi-daily frequency provide a
reasonable view of the complete statistics at the yearly and seasonal scales,
the present paper has not discussed the diurnal evolution of the coastal low
troposphere, which can be particularly marked in summer due to the diurnal
cycle of insolation. The intensive observational campaign associated with the
Year Of Polar Prediction project that took place in the summer of 2018–2019
should provide an unprecedented set of radiosonde data with more than 2000
extra sonde launches. In complement to existing literature on this subject,
these additional radiosoundings could allow us to gain insights into the
subdaily variations of the vertical structure of the low troposphere at many
Antarctic locations.
Finally, the paper has also emphasized the importance of
correctly representing the meridional gradient of temperature and the cold
air bump at the bottom of the ice sheet to satisfactorily simulate the
horizontal extent of the continental flow in atmospheric models. To improve
the cyclogenesis on the shore of the ice sheet , the
formation of sea ice and the creation of oceanic bottom waters in coupled
climate models (e.g., ), observational and modeling
efforts should be made in the future to evaluate and improve horizontal
structure of the coastal Antarctic boundary layer, in line with the IAGO
campaign, for instance .
Data availability
ERA Interim and ERA5 reanalyses are freely distributed on
the ECMWF website (https://www.ecmwf.int, last access: 1 April 2019)
and on the Climate Data Store (https://climate.copernicus.eu, last
access: 1 April 2019). Radiosonde data are either freely distributed or
should be requested to the polar institutes or meteorological services.
Details are given in the Acknowledgments section.
Spatial representativity of temperature and wind at coastal Antarctic stations
To assess the spatial representativity of the temperature and wind in the low
troposphere above given Antarctic stations, we have calculated the spatial
“footprint” of each station. In other words, we have determined the
neighborhoods over which the 8-year statistics of temperature and wind speed
are close to those at the corresponding stations. The method we have employed
is the following. We have calculated the 8-year distributions of wind speed
and temperature at z=500 and z=2000 m a.g.l. (the four variables are
taken separately) at each grid point in the hourly ERA5 reanalyses. The two
heights (z=500 and z=2000 m) were chosen because they correspond to one
level in the core of the boundary layer and to one level slightly above.
Then, overlaps of the distributions of each of the four variables at each
grid point with those at the Antarctic stations were computed. We then
quantify the statistical similarity between one grid point and a station by
the minimum value among the four overlaps corresponding to the four
independent variables. Note that adding the humidity in this method does not
have a significant impact on the definition of the footprints.
Polar WRF simulation over Dumont d'Urville
To investigate the sensitivity of the Polar WRF model over coastal East
Antarctica to the horizontal resolution, we have set up a second simulation.
The model has been run with a downscaling method where a 27 km resolution
domain contains a 9 km resolution nest, which itself contains a smaller nest
at 3 km resolution centered over DDU (see Fig. ). The
nesting is one way; i.e., no information is passed in return from one domain
to its parent. The simulation has been run over the entire year 2016 with a
3-day spinup. External and initial conditions are provided by ERA5
reanalyses. The same physical package as the one used for the Antarctic-scale
simulations (see Sect. ) has been used, except that the cumulus
scheme has been turned off in the 3 km resolution domain.
Map of the three domains of the Polar WRF simulation for the
specific case study over the DDU region.
Radiosonde-following profiles from high-resolution Polar WRF simulations
At high horizontal resolution, it is not appropriate to evaluate the vertical
profiles over a single model grid point with a radiosounding due to the
horizontal drift of the sonde. To make a more consistent comparison, we
simulate the motion of a virtual sonde in the model space. The sonde takes
off at the station and is supposed to rise with a constant vertical velocity
of 5 m s-1. The horizontal advection of the sonde in the model space
is accounting for assuming the stationarity of the horizontal flow during the
ascent. Then, we create an artificial sounding by sampling the model
atmosphere following the trajectory of the virtual sonde (using the nearest
model grid point at each height during the ascent). In Fig. e and f,
the model profiles are generated with this method. It is
however worth noting that, in the first 3000 m above the ground surface, the
virtual balloon has not had the time to drift over a large distance from its
original position (about 15 km at the very maximum). As a consequence, the
new profiles remain relatively close to those right above the station,
especially close to the surface.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-4659-2019-supplement.
Author contributions
EV and AB designed the study, analysed the results and wrote the manuscript.
EV carried out the Polar WRF simulations, processed reanalyses and radiosonde
data and produced the figures. OT provided technical expertise and
contributed to the scientific interpretation of the results.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
This work was funded by the EPFL-LOSUMEA project. We thank Christophe Genthon
and Paul Pettré for insightful comments on a preliminary version of the
manuscript. We also thank Micheal Lehning, Varun Sharma, Josué Gehring,
Lionel Cortes and Richard Forbes for helpful discussions, and
Constantino Listowski for providing the topography data for Polar WRF. We are
grateful to Steve Colwell and the British Antarctic Survey for providing
radiosonde data at the Halley station. For the provision of the radiosounding
data at PE, we thank the Royal Meteorological Institute of Belgium and the
respective operators of the PE station. Radiosoundings during the 2013/2014
summer season were done with the Vaisala Marwin ground receiving system,
provided by the Swiss Federal Institute for Forest, Snow and Landscape
Research. We thank Météo France, the DSO/DOA service for the
acquisition and distribution of radiosonde data at the DDU station. MZ
radiosonde data and information were obtained from the “Meteo Climatological
Observatory at MZS and Victoria Land” of PNRA
(http://www.climantartide.it, last access: 1 April 2019), with the help
of Claudio Scarchilli. Radiosonde measurements at the Neumayer station have
been made freely available on the PANGAEA platform
(https://doi.org/10.1594/PANGAEA.874564) and technical information was
provided by Holger Schmithuesen. Simon Alexander and the Australian Bureau of
Meteorology are also gratefully acknowledged for distributing the radiosonde
data at the Mawson, Davis and Casey stations. The authors appreciate the
support of the University of Wisconsin-Madison Antarctic Meteorological
Research Center and the help of Matthew Lazzara for acquiring and
distributing radiosonde data at McMurdo (http://amrc.ssec.wisc.edu).
The authors also thank John King, Jonathan Wille and one anonymous referee
for their insightful comments on the manuscript. Last but not least, we are
grateful to the scientific and winter-over staffs at Antarctic stations for
acquiring radiosonde data every day in the harsh Antarctic conditions.
Review statement
This paper was edited by Jayanarayanan Kuttippurath and
reviewed by John King, Jonathan Wille, and one anonymous referee.
ReferencesAdams, N.: Identifying the Characteristics of Strong Southerly Wind Events at
Casey Station in East Antarctica Using a Numerical Weather Prediction System,
Mon. Weather Rev., 133, 3548–3561, 10.1175/MWR3050.1, 2005.Agosta, C., Amory, C., Kittel, C., Orsi, A., Favier, V., Gallée, H.,
van den
Broeke, M. R., Lenaerts, J. T. M., van Wessem, J. M., van de Berg, W. J., and
Fettweis, X.: Estimation of the Antarctic surface mass balance using the
regional climate model MAR (1979–2015) and identification of dominant
processes, The Cryosphere, 13, 281–296, 10.5194/tc-13-281-2019, 2019.Alexander, S. and Murphy, D.: The Seasonal Cycle of Lower-Tropospheric
Gravity
Wave Activity at Davis, Antarctica (69∘ S, 78∘ E), J.
Atmos.
Sci., 72, 1010–1021, 10.1175/JAS-D-14-0171.1, 2015.Amory, C., Gallée, H., Naaim-Bouvet, F., Favier, V., Vignon, E., Picard,
G., Trouvilliez, A., Piard, L., Genthon, C., and Bellot, H.: Seasonal
variations in drag coefficients over a sastrugi-covered snowfield of coastal
East Antarctica, Bound.-Lay. Meteorol., 164, 107–133, 10.1007/s10546-017-0242-5, 2017.Argentini, S. and Mastrantonio, G.: Barrier winds recorded during two summer
Antarctic campaigns and their interaction with the katabatic flows as
observed by a tri-axial Doppler sodar, Int. J. Remote
Sens., 15, 455–466, 10.1080/01431169408954086, 1994.Argentini, S., Mastrantonio, G., Viola, A., Pettre, P., and Dargaud, G.:
Sodar
performance and preliminary results after one year of measurements at Adelie
land coast, east Antarctica, Bound.-Lay. Meteorol., 81, 75–103,
10.1007/BF00119401, 1996.Barthélemy, A., Goose, H., Mathiot, P., and Fichefet, T.: Inclusion of a
katabatic wind correction in a coarse-resolution global coupled climate
model, Ocean Modell., 48, 45–54, 10.1007/s10546-017-0304-8, 2012.
Bintanja, R.: Mesoscale Meteorological Conditions in Dronning Maud Land,
Antarctica, during Summer: A Qualitative Analysis of Forcing Mechanisms,
J. Appl. Meteorol., 39, 2348–2370, 2000.Bintanja, R., Severijns, C., Haarsma, R., and Hazeleger, W.: The future of
Antarctica's surface winds simulated by a high-resolution global climate
model: 1. Model description and validation, J. Geophys. Res.-Atmos., 119, 7136–7159, 10.1002/2013JD020847, 2014.Bock, O., Bosser, P., Bourcy, T., David, L., Goutail, F., Hoareau, C.,
Keckhut, P., Legain, D., Pazmino, A., Pelon, J., Pipis, K., Poujol, G.,
Sarkissian, A., Thom, C., Tournois, G., and Tzanos, D.: Accuracy assessment
of water vapour measurements from in situ and remote sensing techniques
during the DEMEVAP 2011 campaign at OHP, Atmos. Meas. Tech., 6, 2777–2802,
10.5194/amt-6-2777-2013, 2013.Bracegirdle, T. J. and Marshall, G. J.: The Reliability of Antarctic
Tropospheric Pressure and Temperature in the Latest Global Reanalyses,
J. Clim., 25, 7138–7146, 10.1175/JCLI-D-11-00685.1, 2012.
Bromwich, D. H., Parish, T., Pellegrini, A., Stearns, C. R., and Weidner,
G. A.: Spatial and temporal variations of the intense katabatic winds at
Terra Nova Bay, Antarctica, Antarctic Meteorology and Climatology: Studies
Based on Automatic Weather Stations, Amer. Geophys. Union, 47–68, 1993.Bromwich, D. H., Steinhoff, D. F., Simmonds, I., Keay, K., and Fogt, R. L.:
Climatological aspects of cyclogenesis near Adélie Land Antarctica, Tellus
A, 63, 921–938, 10.1111/j.1600-0870.2011.00537.x, 2011.Bromwich, D. H., Otieno, F. O., Hines, K. M., Manning, K. W., and Shilo, E.:
Comprehensive evaluation of polar weather research and forecasting model
performance in the Antarctic, J. Geophys. Res.-Atmos.,
118, 274–292, 10.1029/2012JD018139, 2013.Carrasco, J. F., Bromwich, D. H., and Monaghan, A. J.: Distribution and
Characteristics of Mesoscale Cyclones in the Antarctic: Ross Sea Eastward to
the Weddell Sea, Mon. Weather Rev., 131, 289–301,
10.1175/1520-0493(2003)131<0289:DACOMC>2.0.CO;2, 2003.Climate Change Service: ERA Interim and ERA5 reanalyses, available at:
https://climate.copernicus.euTS2, last access: 1 April 2019.Connolley, W. M. and King, J. C.: Atmospheric water-vapour transport to
Antarctica inferred from radiosonde data, Q. J. Roy.
Meteorol. Soc., 119, 325–342, 10.1002/qj.49711951006, 1993.Dare, R. A. and Budd, W. F.: Analysis of Surface Winds at Mawson,
Antarctica, Weather Forecast., 16, 416–431,
10.1175/1520-0434(2001)016<0416:AOSWAM>2.0.CO;2, 2001.Deb, P., Andrew, O., Scott, H. J., Tony, P., John, T., Daniel, B., O., P. J.,
and Steve, C.: An assessment of the Polar Weather Research and Forecasting
(WRF) model representation of near-surface meteorological variables over West
Antarctica, J. Geophys. Res.-Atmos., 121, 1532–1548,
10.1002/2015JD024037, 2016.
Dee, D., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S.,
Andrae, U., Balmaseda, M., Balsamo, G., Bauer, P., Bechtold, P. , Beljaars, A. C., van de Berg, L. , Bidlot,
J. , Bormann, N., Delsol, C., Dragani, R., Fuentes, M. , Geer, A. J.,
Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L.,
Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P.,Monge-Sanz,
B. M., Morcrette, J., Park, B., Peubey, C., de Rosnay, P., Tavolato, C.,
Thépaut, J., and Vitart, F.: The ERA-Interim
reanalysis: Configuration and performance of the data assimilation system,
Q. J. R. Meteorol. Soc., 137, 553–597, 2011.Dufour, A., Charrondière, C., and Zolina, O.: Moisture transport in
observations and reanalyses as a proxy for snow accumulation in East
Antarctica, The Cryosphere, 13, 413–425, 10.5194/tc-13-413-2019, 2019.Durán-Alarcón, C., Boudevillain, B., Genthon, C., Grazioli, J.,
Souverijns,
N., van Lipzig, N. P. M., Gorodetskaya, I. V., and Berne, A.: The vertical
structure of precipitation at two stations in East Antarctica derived from
micro rain radars, The Cryosphere, 13, 247–264,
10.5194/tc-13-247-2019, 2019.ECMWF: Advancing global NWP through international collaboration, available
at: https://www.ecmwf.int, last access: 1 April 2019.Fretwell, P., Pritchard, H. D., Vaughan, D. G., Bamber, J. L., Barrand, N.
E., Bell, R., Bianchi, C., Bingham, R. G., Blankenship, D. D., Casassa, G.,
Catania, G., Callens, D., Conway, H., Cook, A. J., Corr, H. F. J., Damaske,
D., Damm, V., Ferraccioli, F., Forsberg, R., Fujita, S., Gim, Y., Gogineni,
P., Griggs, J. A., Hindmarsh, R. C. A., Holmlund, P., Holt, J. W., Jacobel,
R. W., Jenkins, A., Jokat, W., Jordan, T., King, E. C., Kohler, J., Krabill,
W., Riger-Kusk, M., Langley, K. A., Leitchenkov, G., Leuschen, C., Luyendyk,
B. P., Matsuoka, K., Mouginot, J., Nitsche, F. O., Nogi, Y., Nost, O. A.,
Popov, S. V., Rignot, E., Rippin, D. M., Rivera, A., Roberts, J., Ross, N.,
Siegert, M. J., Smith, A. M., Steinhage, D., Studinger, M., Sun, B., Tinto,
B. K., Welch, B. C., Wilson, D., Young, D. A., Xiangbin, C., and Zirizzotti,
A.: Bedmap2: improved ice bed, surface and thickness datasets for Antarctica,
The Cryosphere, 7, 375–393, 10.5194/tc-7-375-2013, 2013.Gallée, H. and Pettré, P.: Dynamical Constraints on Katabatic Wind
Cessation in Adélie Land, Antarctica, J. Atmos.
Sci., 55, 1755–1770,
10.1175/1520-0469(1998)055<1755:DCOKWC>2.0.CO;2, 1998.
Gallée, H. and Schayes, G.: Development of a three-dimensional meso-gamma
primitive equation model, katabatic winds simulation in the area of Terra
Nova Bay, Antarctica, Mon. Weather Rev., 12, 671–685, 1994.
Gallée, H., Pettré, P., and Schayes, G.: Sudden cessation of
katabatic
winds in Adélie Land, Antarctica, J. Appl. Meteorol.,
35, 1142–1152, 1996.
Genthon, C. and Krinner, G.: Convergence and disposal of energy and moisture
on
the Antarctic polar cap from ECMWFreanalyses and forecasts, J. Clim., 11,
1703–1716, 1998.Gera, B. S., Argentini, S., Mastrantonio, G., Viola, A., and Weill, A.:
Characteristics of the boundary layer thermal structure at a coastal region
of Adélie Land, East Antarctica, Ant. Sci., 10, 89–98,
10.1017/S0954102098000121, 1998.Grazioli, J., Genthon, C., Boudevillain, B., Duran-Alarcon, C., Del Guasta,
M.,
Madeleine, J.-B., and Berne, A.: Measurements of precipitation in Dumont
d'Urville, Adélie Land, East Antarctica, The Cryosphere, 11, 1797–1811,
10.5194/tc-11-1797-2017, 2017a.Grazioli, J., Madeleine, J.-B., Gallée, H., Forbes, R. M., Genthon, C.,
Krinner, G., and Berne, A.: Katabatic winds diminish precipitation
contribution to the Antarctic ice mass balance, P. Natl.
Acad. Sci. USA, 114, 10858–10863, 10.1073/pnas.1707633114,
2017b.
Ingleby, B.: An assessment of different radiosonde type 2015/2016, ECMWF
Technical Memorandum, p. 807, 2017.
King, J. C.: Low-level wind profiles at an Antarctic coastal station,
Antarct.
Sci., 1, 169–178, 1989.
King, J. C. and Anderson, P. S.: A humidity climatology for Halley,
Antarctica, based on frost-point hygrometer measurements, Antarct.
Sci., 11, 100–104, 1999.King, J. C., Argentini, S. A., and Anderson, P. S.: Contrasts between the
summertime surface energy balance and boundary layer structure at Dome C
and Halley stations, Antarctica, J. Geophys. Res., 111, D02105,
10.1029/2005JD006130, 2006.
Kottmeier, C.: The influence of baroclinicity and stability on the wind and
temperature conditions at the Georg von Neumayer Antarctic station,
Tellus A, 38, 263–276, 1986.König-Langlo, G., King, J. C., and Pettré, P.: Climatology of the
three
coastal Antarctic stations Dumont d'Urville, Neumayer, and Halley, J.
Geophys. Res.-Atmos., 103, 10935–10946,
10.1029/97JD00527, 1998.Lenaerts, J. T. M., van den Broeke, M. R., Déry, S. J., van Meijgaard,
E.,
van de Berg, W. J., Palm, S. P., and Sanz Rodrigo, J.: Modeling drifting snow
in Antarctica with a regional climate model: 1. Methods and model
evaluation, J. Geophys. Res.-Atmos., 117, D05108,
10.1029/2011JD016145, d05108, 2012.Listowski, C. and Lachlan-Cope, T.: The microphysics of clouds over the
Antarctic Peninsula – Part 2: modelling aspects within Polar WRF,
Atmos. Chem. Phys., 17, 10195–10221,
10.5194/acp-17-10195-2017, 2017.
Mawson, S. D.: The home of the blizzard, Unabridged, 1915.Milosevich, L. M., Paukkunen, A., Vömel, H., and Oltmans, S. J.:
Development and Validation of a Time-Lag Correction for Vaisala Radiosonde
Humidity Measurements, J. Atmos. Ocean. Technol., 21, 1305–1327,
10.1175/1520-0426(2004)021<1305:DAVOAT>2.0.CO;2, 2004.Monaghan, A. J., Bromwich, D. H., Powers, J. G., and Manning, K. W.: The
Climate of the McMurdo, Antarctica, Region as Represented by One Year
of Forecasts from the Antarctic Mesoscale Prediction System, J.
Clim., 18, 1174–1189, 10.1175/JCLI3336.1, 2005.Morrison, H., Thompson, G., and Tatarskii, V.: Impact of Cloud Microphysics
on
the Development of Trailing Stratiform Precipitation in a Simulated Squall
Line: Comparison of One- and Two-Moment Schemes, Mon. Weather Rev., 137,
991–1007, 10.1175/2008MWR2556.1, 2009.Naithani, J., Gallée, H., and Schayes, G.: Marine air intrusion into the
Adelie Land sector of East Antarctica: A study using the regional
climate model (MAR), J. Geophys. Res.-Atmos., 107, 10.1029/2000JD000274, 2002.
Naithani, J., Argentini, S., and Schayes, G.: Analysis of strong wind events
around Adelie land, East Antarctica, Ann. Geophys., 46, 2003.Nakanishi, M. and Niino, H.: An Improved Mellor–Yamada Level-3 Model: Its
Numerical Stability and Application to a Regional Prediction of Advection
Fog, Bound.-Lay. Meteorol., 119, 397–407,
10.1007/s10546-005-9030-8, 2006.Nicolas, J. P. and Bromwich, D. H.: New Reconstruction of Antarctic
Near-Surface Temperatures: Multidecadal Trends and Reliability of Global
Reanalyses, J. Clim., 27, 8070–8093,
10.1175/JCLI-D-13-00733.1, 2014.Nygård, T., Valkonen, T., and Vihma, T.: Antarctic Low-Tropospheric
Humidity Inversions: 10-Yr Climatology, J. Clim., 26, 5205–5219,
10.1175/JCLI-D-12-00446.1, 2013.Orr, A., Phillips, T., Webster, S., Elvidge, A., Weeks, M., Hosking, S., and
Turner, J.: Met Office Unified Model high-resolution simulations of a strong
wind event in Antarctica, Q. J. Roy. Meteorol.
Soc., 140, 2287–2297, 10.1002/qj.2296, 2014.
Parish, T. R. and Bromwich, D. H.: The surface windfield over the Antarctic
ice sheets, Nature, 328, 51–54, 1987.
Parish, T. R. and Bromwich, D. H.: Instrumented aircraft observations of the
katabatic regime near Terra Nova Bay, Mon. Weather Rev., 117, 1570–1585,
1989.Parish, T. R. and Bromwich, D. H.: A Case Study of Antarctic Katabatic Wind
Interaction with Large-Scale Forcing, Mon. Weather Rev., 126, 199–209,
10.1175/1520-0493(1998)126<0199:ACSOAK>2.0.CO;2, 1998.Parish, T. R. and Bromwich, D. H.: Reexamination of the Near-Surface Airflow
over the Antarctic Continent and Implications of Atmospheric Circulations
at High Southern Latitudes, Mon. Weather Rev., 135, 1961–1973,
10.1175/MWR3374.1, 2007.Parish, T. R. and Cassano, J. J.: The Role of Katabatic Winds on the
Antarctic
Surface Wind Regime, Mon. Weather Rev., 131, 317–333,
10.1175/1520-0493(2003)131<0317:TROKWO>2.0.CO;2, 2003.
Parish, T. R. and Walker, R.: A re-examination of the winds of Adelie
Land,
Antarctica, Aust. Meteorol. Mag., 55, 105–107, 2006.Parish, T. R., Pettré, P., and Wendler, G.: A numerical study of the
diurnal variation of the Adelie Land katabatic wind regime, J.
Geophys. Res.-Atmos., 98, 12933–12947,
10.1029/92JD02080, 1993.Pattyn, F., Matsuoka, K., and Berte, J.: Glacio-meteorological conditions in
the vicinity of the Belgian Princess Elisabeth Station, Antarctica,
Antarct.
Sci., 22, 79–85, 10.1017/S0954102009990344, 2010.Pettré, P. and André, J.-C.: Surface-Pressure Change through Loewe's
Phenomena and Katabatic Flow Jumps: Study of Two Cases in Adélie Land,
Antarctica, J. Atmos. Sci., 48, 557–571,
10.1175/1520-0469(1991)048<0557:SPCTLP>2.0.CO;2, 1991.Pettré, P., Payan, C., and Parish, T. R.: Interaction of katabatic flow
with local thermal effects in a coastal region of Adelie Land, east
Antarctica, J. Geophys. Res.-Atmos., 98,
10429–10440, 10.1029/92JD02969, 1993.Renfrew, I. A.: The dynamics of idealized katabatic flow over a moderate
slope
and ice shelf, Q. J. Roy. Meteorol. Soc., 130,
1023–1045, 10.1256/qj.03.24, 2004.Renfrew, I. A. and Anderson, P. S.: Profiles of katabatic flow in summer and
winter over Coats Land, Antarctica, Q. J. Roy.
Meteorol. Soc., 132, 779–802, 10.1256/qj.05.148, 2007.Sanz Rodrigo, J., Buchlin, J.-M., van Beeck, J., Lenaerts, J. T. M., and
van den Broeke, M. R.: Evaluation of the Antarctic surface wind climate
from ERA reanalyses and RACMO2/ANT simulations based on automatic weather
stations, Clim. Dynam., 40, 353–376, 10.1007/s00382-012-1396-y,
2013.Seefeldt, M. W., Tripoli, G. J., and Stearns, C. R.: A High-Resolution
Numerical Simulation of the Wind Flow in the Ross Island Region, Antarctica,
Mon. Weather Rev., 131, 435–458,
10.1175/1520-0493(2003)131<0435:AHRNSO>2.0.CO;2, 2003.Sorbjan, Z., Kodama, Y., and Wendler, G.: Observational Study of the
Atmospheric Boundary Layer over Antarctica, J. Clim. Appl.
Meteorol., 25, 641–651, 10.1175/1520-0450, 1986.
Streten, N. A.: A review of the climate of Mawson – a representative
strong
wind site in East Antarctica, Antarct. Sci., 2, 79–89, 1990.Tomasi, C., Petkov, B., Benedetti, E., Vitale, V., Pellegrini, A., Dargaud,
G.,
De Silvestri, L., Grigioni, P., Fossat, E., Roth, W. L., and Valenziano, L.:
Characterization of the atmospheric temperature and moisture conditions above
Dome C (Antarctica) during austral summer and fall months, J.
Geophys.
Res., 111, D20305, 10.1029/2005JD006976, 2006.
Turner, J., Lachlan-Cope, T. A., Marshall, G. J., Pendlebury, S., and Adams,
N.: An extreme wind event at Casey Station, Antarctica, J. Geophys. Res.,
106, 7291–7311, 2001.Uotila, P., Vihma, T., Pezza, A. B., Simmonds, I., Keay, K., and Lynch,
A. H.:
Relationships between Antarctic cyclones and surface conditions as derived
from high-resolution numerical weather prediction data, J.
Geophys. Res.-Atmos., 116, D07109, 10.1029/2010JD015358, 2011.
Van den Broeke, M. and Van Lipzig, N. P. M.: Factors Controlling the
Near-Surface Wind Field in Antarctica, Mon. Weather Rev., 21,
1417–1431, 2003.Van den Broeke, M. R., Van Lipzig, N. P. M., and Van Meijgaard , E.:
Momentum Budget of the East Antarctic Atmospheric Boundary Layer: Results
of a Regional Climate Model, J. Atmos. Sci., 59,
3117–3129, 10.1175/1520-0469(2002)059<3117:MBOTEA>2.0.CO;2, 2002.Van Lipzig, N. P. M. and Van Den Broeke, M. R.: A model study on the
relation between atmospheric boundary-layer dynamics and poleward atmospheric
moisture transport in Antarctica, Tellus A, 54, 497–511, 10.3402/tellusa.v54i5.12168, 2002.van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E.,
Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M.,
Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht,
K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den
Broeke, M. R.: Modelling the climate and surface mass balance of polar ice
sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12,
1479–1498, 10.5194/tc-12-1479-2018, 2018.
Vignon, E., Hourdin, F., Genthon, C., Van de Wiel, B. J. H., Gallée, H.,
Madeleine, J.-B., and Beaumet, J.: Modeling the Dynamics of the Atmospheric
Boundary Layer Over the Antarctic Plateau With a General Circulation Model,
J. Adv. Model Earth Sy., 10, 98–125,
10.1002/2017MS001184, 2018.Wendler, G., André, J. C., Pettré, P., Gosink, J., and Parish, T.:
Katabatic winds in Adélie Coast, Antarctica Meteorology and
Climatology: Studies Based on Automatic Weather Stations, american
Geophysical Union, Washington, DC, 10.1029/AR061p0023, 1993.Wille, J. D., Bromwich, D. H., Cassano, J. J., Nigro, M. A., Mateling, M. E.,
and Lazzara, M. A.: Evaluation of the AMPS Boundary Layer Simulations on the
Ross Ice Shelf, Antarctica, with Unmanned Aircraft Observations, J.
Appl. Meteorol. Clim., 56, 2239–2258,
10.1175/JAMC-D-16-0339.1, 2017.
Yurchak, B. S.: An Assessment of Radiosonde Launch Conditions Affected by the
Surface Wind, Russ. Meteorol. Hydrol., 38, 159–167, 2013.Zhang, Y., Seidel, D. J., Golaz, J.-C., Deser, C., and Tomas, R. A.:
Climatological Characteristics of Arctic and Antarctic Surface-Based
Inversions, J. Clim., 24, 5167–5186, 10.1175/2011JCLI4004.1,
2011.