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    The location of Davis (solid black circle) in relation to the regional-scale topography. Altitudes of the ice plateau (250-m interval) from the 15-km-resolution AMPS forecast model are shown. The line segment AB marks the cross section in the case study of Fig. 7. The ridgeline northeast of Davis is highlighted by the thick, short, black line. The ERA-Interim grid cell incorporating the ridgeline and downslope region (centered on 68.5°S, 79.5°E) is marked by the dotted rectangle.

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    Davis VHF radar acceptance rates following quality control for the period September 2009–August 2011. The meridional acceptance rate is essentially the same as the zonal acceptance rate, so it is not plotted.

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    The comparison between radiosonde and radar winds for September 2009–August 2011 for (a) wind speed and (b) wind direction. Radar data are averaged within half an hour of the radiosonde launch times. The linear-fit parameters, correlation, and number of data points are detailed in (a). The dashed lines indicate the 1:1 fit, and the solid line in (a) is the linear fit.

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    The vertical wind velocity perturbations, which have ground-based periods of 16 min–12.8 h during May and June 2011. The scale is in the upper right.

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    Vertical wind velocity perturbations with ground-based periods of 16 min–12.8 h (color) and unfiltered horizontal wind velocity (vectors) from the VHF radar for 1200 UT 2 Jun–0000 UT 5 Jun 2011. The wind vector scale is given by the horizontal arrow in the top-right corner (m s−1), along with the north and east directions for reference.

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    (a) The AMPS 10-m forecast horizontal wind velocity field (vectors) at 0000 UT 3 Jun 2011. The color contours indicate the vertical wind velocity at 1.5-km altitude. (b) As in (a), but for the t + 24-h forecast field (0000 UT 4 Jun 2011). In both (a) and (b), Davis is marked by the solid black circle, and the topography with a 500-m interval is marked by the thin black lines. The ridgeline is marked by the thick black line. The lengths of the vectors indicate the wind speed, with the reference vector given in the bottom-right corner (m s−1) of each panel.

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    The cross section along the direction of surface wind propagation upwind of the ice ridgeline (line segment AB in Fig. 1) of the AMPS forecast model at 0000 UT 4 Jun 2011. The locations A and B and the ice ridgeline marked along the x axis are as indicated in Fig. 1. The vertical wind velocities (colors), potential temperature (gray lines, interval of 5 K), and horizontal wind field in this plane (vectors) are displayed. The topography is marked by the solid black line. The wind vector scales are given by the vectors in the top-right corner (m s−1), along with the north and east directions.

  • View in gallery

    The AMPS 10-m forecast horizontal wind velocity field (vectors), along with vertical wind velocity at 1.5-km altitude (color contours) on four different days, as marked in the titles. Other annotations are as given in Fig. 6.

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    The relationship between the ERA-Interim 10-m wind speed above the ridgeline and the Davis radar’s 2.0-km observations. The horizontal dashed lines indicate the active threshold ( m2 s−2) and the quiet threshold ( m2 s−2), while the color bar indicates the number of data points. The correlation coefficient is also given.

  • View in gallery

    The correlation coefficient between the ERA-Interim 10-m wind speed and the logarithm of the Davis VHF radar’s 2.0-km observations (colors). Values of are highlighted by the red contours. The location of Davis is marked by the solid black circle. The ERA-Interim topography is shown by the black lines at every 1000-m altitude.

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    Wind rose of the 2-yr wind speed and direction of the ERA-Interim 10-m wind at 68.5°S, 79.5°E (the ice-ridgeline grid cell; see Fig. 1 for its location).

  • View in gallery

    Monthly-mean ERA-Interim 10-m wind speed above the ice ridgeline. The vertical bars indicate the standard errors, while the two dashed lines indicate plus and minus one standard deviation.

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    The 2.0–3.2-km monthly-mean radar values for the different filter bands, as marked. Vertical bars indicate the standard errors in the means. The monthly standard deviations (not plotted) are 2.0–3.5 m2 s−2 for the different filter bands.

  • View in gallery

    The 2.0–3.2-km monthly-mean radar values for the different filter bands, as marked. Vertical bars indicate the standard errors in the means. The monthly standard deviations (not plotted) are 0.035–0.075 m2 s−2 for the different filter bands.

  • View in gallery

    The correlation coefficient between the ERA-Interim surface pressure and the logarithm of the Davis VHF radar’s 2.0-km values (colors). Values of are highlighted by the red contours. The location of Davis is marked by the solid black circle. The ERA-Interim topography is shown by the black lines at every 1000-m altitude.

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    Composites of the ERA-Interim 10-m horizontal wind speeds (color), horizontal wind velocities (vectors), and surface pressure over the ocean (hPa, black contours) for (a) quiet and (b) active conditions. The location of Davis is marked by the solid red circle. The reference horizontal wind velocity vector is in the bottom-right corner (m s−1).

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The Seasonal Cycle of Lower-Tropospheric Gravity Wave Activity at Davis, Antarctica (69°S, 78°E)

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  • 1 Australian Antarctic Division, Hobart, Tasmania, Australia
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Abstract

A VHF wind-profiling radar located at Davis in coastal East Antarctica (69°S, 78°E) collected data from September 2009 to August 2011 in the lower troposphere. Gravity wave activity is quantified using the radar’s wind velocity variances. ERA-Interim and Antarctic Mesoscale Prediction System (AMPS) forecast output are used to understand the gravity wave activity in the context of the synoptic-scale meteorology and to identify the likely source of the observed gravity waves. The seasonal cycle of lower-tropospheric gravity wave activity (2.0–3.2-km altitude) obtained from the radar data for waves with ground-based periods of 16 min–12.8 h reveals a maximum in winter and a minimum in summer. The largest gravity wave activity corresponds in time to the presence of a surface depression centered north of Davis that directs strong northeasterly winds along the Antarctic coastline. Case studies indicate that these winds interact with an ice ridgeline located around 60 km northeast and upwind of Davis. This interaction between synoptic northeasterly winds and the ridgeline results in the formation of orographic gravity waves, which are observed in the Davis radar data as large wind velocity perturbations.

Corresponding author address: Simon Alexander, Australian Antarctic Division, 203 Channel Highway, Kingston TAS 7050, Australia. E-mail: simon.alexander@aad.gov.au

Abstract

A VHF wind-profiling radar located at Davis in coastal East Antarctica (69°S, 78°E) collected data from September 2009 to August 2011 in the lower troposphere. Gravity wave activity is quantified using the radar’s wind velocity variances. ERA-Interim and Antarctic Mesoscale Prediction System (AMPS) forecast output are used to understand the gravity wave activity in the context of the synoptic-scale meteorology and to identify the likely source of the observed gravity waves. The seasonal cycle of lower-tropospheric gravity wave activity (2.0–3.2-km altitude) obtained from the radar data for waves with ground-based periods of 16 min–12.8 h reveals a maximum in winter and a minimum in summer. The largest gravity wave activity corresponds in time to the presence of a surface depression centered north of Davis that directs strong northeasterly winds along the Antarctic coastline. Case studies indicate that these winds interact with an ice ridgeline located around 60 km northeast and upwind of Davis. This interaction between synoptic northeasterly winds and the ridgeline results in the formation of orographic gravity waves, which are observed in the Davis radar data as large wind velocity perturbations.

Corresponding author address: Simon Alexander, Australian Antarctic Division, 203 Channel Highway, Kingston TAS 7050, Australia. E-mail: simon.alexander@aad.gov.au

1. Introduction

Gravity waves play an important role in driving the general circulation of the middle atmosphere. These waves typically propagate upward from sources in the lower atmosphere, transporting momentum into the middle and upper atmosphere. The gravity wave drag generated upon their breaking closes the mesospheric jet and drives the winter polar stratosphere away from radiative equilibrium (Haynes et al. 1991; Garcia and Boville 1994). The interaction of gravity waves with the background flow, and thus the determination of their breaking altitude, depends upon the wave properties, which are related to the source (Fritts and Alexander 2003).

Gravity waves are generated by orographic and nonorographic processes. Wind flow over mountains results in the production of orographic gravity waves, as demonstrated with observations and models (e.g., Vosper and Worthington 2002; Doyle et al. 2005; Limpasuvan et al. 2007). Mesoscale simulations and observations indicate that orographic gravity waves in the polar regions can influence polar stratospheric cloud formation (Dörnbrack et al. 2002; Höpfner et al. 2006; Alexander et al. 2013a). High-frequency gravity waves show a close correspondence with deep convection (Sato 1993; Tsuda et al. 1994; Alexander et al. 2000, 2008) and the passage of midlatitude cold fronts (Eckermann and Vincent 1993). Gravity waves are emitted spontaneously as an unbalanced flow undergoes readjustment around a front or a jet (O’Sullivan and Dunkerton 1995; Guest et al. 2000; Plougonven et al. 2003; Plougonven and Zhang 2014).

Both orographic and nonorographic gravity waves are present in the southern high latitudes (Alexander and Teitelbaum 2007; Vincent et al. 2007; Hertzog et al. 2008; Hendricks et al. 2014). Radiosonde observations indicate an annual cycle of gravity wave energy in the Antarctic stratosphere, peaking in winter at around 25–30-km altitude before descending downward in a region of high static stability during spring (Yoshiki and Sato 2000). This seasonal gravity wave cycle with winter maximum also occurs in the Antarctic upper stratosphere (Alexander et al. 2011) but merges into a semiannual cycle in the mesosphere, with minima at the equinoxes (Dowdy et al. 2007). However, the seasonal cycle of gravity wave activity in the Antarctic troposphere remains uncharacterized: one of the objectives of this paper is to quantify this in the lower troposphere using radar data.

Strong and persistent katabatic winds occur along the Antarctic coastline. Air above the plateau radiates away its heat during winter and then flows downhill following the contours of the ice plateau before reaching the coast. The wind directions vary around the continental fringe, with the strongest winds occurring at the base of broad valleys (Parish and Bromwich 1987). The coast of East Antarctica is located in the latitude range from 65° to 70°S, which is at the southern edge of the circumpolar belt of depressions (Simmonds and Keay 2000). Therefore, the surface climatological winds in coastal East Antarctica are a combination of influences from katabatic winds draining from the interior of the continent and the transient influences of low pressure synoptic-scale systems traveling eastward, which are centered to the north of the coast. Most of the strongest wind events observed at manned stations along the East Antarctic coastline are associated with an enhancement of the katabatic flow by synoptic-scale meteorological conditions (Turner et al. 2009), and the direction of these strong wind events varies according to the topography inland from each station. Strong katabatic winds can produce orographic gravity waves as they accelerate downhill toward the coastline. Such an event over the western Ross Sea was simulated by Watanabe et al. (2006) in a high-resolution general circulation model, where katabatic flow excited an orographic gravity wave. Orographic waves can also be produced via the interaction of synoptic-scale flow with the katabatic winds and topography (Orr et al. 2014). Because of their low phase speeds (which are nonzero under time-varying background winds), orographic gravity waves drive the background atmospheric flow toward zero when they encounter their critical levels. The strength of the katabatic winds, and the amplitude of the orographic waves produced, may be modulated by the synoptic-scale flow (Orr et al. 2014).

Very-high-frequency (VHF) wind-profiling radars have the capability of monitoring the three wind velocity components at high temporal and vertical resolution from various fixed locations around the world. VHF radars are capable of observing a wide ground-based frequency spectrum of gravity waves as a result of their high sampling rate. The perturbations in the wind speeds from the background state are interpreted as being due to gravity waves (Vincent and Eckermann 1990). Three VHF radars presently operate in Antarctica. Summer case studies using data collected throughout the troposphere and lower stratosphere by a VHF radar at Wasa (73°S, 13°W) attributed vertical velocity perturbations to generation by flow over nearby topography (Valkonen et al. 2010; Arnault and Kirkwood 2012), while a winter case study of large perturbations in the tropospheric wind components at Syowa (69°S, 40°E) coincided with a deep depression located to the north (Sato et al. 2014). A 2-yr dataset of echo return power was used by Alexander et al. (2013b) to investigate the tropopause structure at Davis (69°S, 78°E); here, we use the lower-tropospheric winds obtained simultaneously. We will quantify the seasonal cycle of gravity wave activity in the lower troposphere, calculated from wind observations made with the Davis VHF radar. We will use case-study output from the Antarctic Mesoscale Prediction System (AMPS) forecast (Powers et al. 2003) along with the radar results to investigate the interaction of synoptic winds from an offshore low pressure system with the topography and the katabatic flow. Last, using ERA-Interim data (Dee et al. 2011), we will determine the mean synoptic-scale meteorological conditions when the largest and smallest gravity wave activity is observed at Davis.

2. Data

Figure 1 shows the location of Davis (69°S, 78°E) in the context of its surroundings, taken from the 15-km-resolution terrain used in the AMPS forecast model. A ridgeline in the ice topography located around 60 km to the northeast of Davis is highlighted, as it will be found subsequently to be important for orographic wave generation in the Davis area.

Fig. 1.
Fig. 1.

The location of Davis (solid black circle) in relation to the regional-scale topography. Altitudes of the ice plateau (250-m interval) from the 15-km-resolution AMPS forecast model are shown. The line segment AB marks the cross section in the case study of Fig. 7. The ridgeline northeast of Davis is highlighted by the thick, short, black line. The ERA-Interim grid cell incorporating the ridgeline and downslope region (centered on 68.5°S, 79.5°E) is marked by the dotted rectangle.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

A 55-MHz VHF radar, designed as a hybrid Doppler–full correlation analysis system, is located at sea level at Davis; using this system, a Doppler beam-steering experiment (e.g., Vincent et al. (1987)) was run between August 2009 and October 2011. For this analysis, we use the 2 years of data from September 2009 to August 2011, inclusive. The experimental parameters are listed in Table 1. Radial velocities obtained from vertical and off-vertical beams at zenith angle 7°, pointing toward north and then toward east, were used to calculate the wind components. The full wind vector (u, υ, and w) was obtained once every 8 min, because of interleaving with other experiments performed on the same radar. Only a limited amount of power was sent into the troposphere for this experiment; thus, the height coverage of the winds is restricted to the lower troposphere. The range resolution is 300 m, and the lowest range gate is 2 km. The 8-min-resolution data were subjected to the following quality control procedures. Outliers, defined as data that are two standard deviations outside a 2-h running mean at a particular altitude, are removed. While this likely resulted in the removal of a small amount of genuine wind data, it was found necessary in order to remove data points that were clearly spurious. All data in each 2-h block are subsequently removed if fewer than 50% of possible data points are present.

Table 1.

Radar parameters used in the experiment.

Table 1.

Gravity wave activity is quantified by using VHF radar measurements of wind velocity variances (Vincent and Eckermann 1990; Murayama et al. 1994). It is common for different studies to specify different band limits, varying from minutes up to the inertial period at the location of that particular radar. The Davis wind data are filtered at each altitude to retain perturbations with ground-based periods of 16 min–12.8 h. The lower limit is twice the temporal resolution of the raw data, while the upper limit is the inertial period at Davis. These perturbations are referred to as , , and . We will also investigate a high-frequency (short period) component, which retains waves with 16 min h and a low-frequency (long period) component, which retains waves with 2 h. This separation into high-frequency and low-frequency components permits an analysis of their relative seasonal importance and is useful to quantify, given that high-frequency gravity waves carry a significant proportion of total momentum flux into the middle atmosphere (e.g., Fritts and Vincent 1987). The quality-controlled data acceptance rates are plotted in Fig. 2. While a higher acceptance rate occurs for w than for u, there is still less than 50% of possible w data above 5-km altitude. This analysis will focus on the lowest radar range gates, where the data acceptance rate is highest.

Fig. 2.
Fig. 2.

Davis VHF radar acceptance rates following quality control for the period September 2009–August 2011. The meridional acceptance rate is essentially the same as the zonal acceptance rate, so it is not plotted.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

First, we compare the 2 years of radar winds with collocated radiosonde winds in order to validate the former. Radar data are averaged in the half hour following radiosonde launch (i.e., the approximate time taken for the balloon to ascend to 5–6-km altitude), and the results are in Fig. 3. The radar underestimates the wind speed compared with the radiosonde: the gradient from linear regression is 0.76. The zonal and meridional wind components both exhibit this same underestimate (not shown). The underestimation of wind speeds by the Davis radar is larger than that calculated for other radars, where linear regression gradients were at least 0.93 (Luce et al. 2001; Fukao et al. 2003; Reid et al. 2005). Our radar wind directions are in better agreement with those determined from the radiosondes (Fig. 3b). While there are some isolated outlying points where the directions do not agree, most wind direction points fall along or very close to the 1:1 line.

Fig. 3.
Fig. 3.

The comparison between radiosonde and radar winds for September 2009–August 2011 for (a) wind speed and (b) wind direction. Radar data are averaged within half an hour of the radiosonde launch times. The linear-fit parameters, correlation, and number of data points are detailed in (a). The dashed lines indicate the 1:1 fit, and the solid line in (a) is the linear fit.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

We use data from the AMPS forecast at 15-km horizontal resolution to investigate the interaction between a synoptic-scale offshore low pressure system and the Antarctic topography and katabatic winds during a June 2011 case study. The AMPS provides operational forecasts for the Antarctic region (Powers et al. 2003). The atmospheric model currently used by AMPS is the polar-optimized version of the Weather Research and Forecasting (WRF) Model. Weather forecasts are available on several nested domains. The model has 15-km horizontal resolution for the domain encompassing the whole of Antarctica. Higher-horizontal-resolution forecast model runs result in improved accuracy of near-surface winds due to the improved representation of the terrain (Bromwich et al. 2005; Orr et al. 2014). The 15-km horizontal resolution of AMPS is coarser than that used for specific Antarctic modeling case studies (Plougonven et al. 2008; Arnault and Kirkwood 2012; Orr et al. 2014). However, the purpose here is to determine the regional-scale atmospheric conditions and potential forcing mechanisms for a specific event, rather than performing a detailed model evaluation study. For this purpose, 15-km horizontal resolution is sufficient to investigate the evolution of the flow as it encounters topography, although this resolution will likely underestimate peak wind speeds (Orr et al. 2014).

3. Results

The time series of 16-min–12.8-h filtered for May and June 2011 are plotted in Fig. 4 to illustrate its time-varying nature. On several occasions during this 2-month interval, greater than 1 m s−1 are present and are coherent in altitude, although the data quality-control algorithms have limited the data at altitudes above approximately 4 km. Such large values may persist for several days (e.g., 6–11 May), while at other times they persist for around 1 day (28 May). Bursts of large are observed by radars around the world, (Eckermann and Vincent 1993; Sato 1993; Murayama et al. 1994; Vosper and Worthington 2002; Vincent et al. 2004; Alexander et al. 2008). The sources of these large vertical motions vary at different locations and include cold fronts, jet readjustment, and convection. We shall investigate the sources of large at Davis.

Fig. 4.
Fig. 4.

The vertical wind velocity perturbations, which have ground-based periods of 16 min–12.8 h during May and June 2011. The scale is in the upper right.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

a. June 2011 case study

We investigate one case in detail where values greater than 1 m s−1 were recorded with the radar from 2 to 5 June 2011 (Fig. 5). Vectors indicate that southeasterly winds are present at 2–3 km prior to 0600 UT 3 June and values are approximately −0.2 m s−1. Over the following 6 h, the winds become northeasterly and strengthen to around 20 m s−1, concurrent with an increase in to around 1.5 m s−1. This situation persists until 1200 UT 4 June, after which the winds weaken and turn easterly.

Fig. 5.
Fig. 5.

Vertical wind velocity perturbations with ground-based periods of 16 min–12.8 h (color) and unfiltered horizontal wind velocity (vectors) from the VHF radar for 1200 UT 2 Jun–0000 UT 5 Jun 2011. The wind vector scale is given by the horizontal arrow in the top-right corner (m s−1), along with the north and east directions for reference.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

Figure 6a shows the 10-m horizontal wind field and 1.5-km vertical winds at 0000 UT 3 June from AMPS, which is prior to any large w observed by the radar. An easterly katabatic flow is present over the ice topography. Such flow is typical of the region and corresponds with the climatological winter streamlines over the continent (Parish and Bromwich 1987). The vertical velocities at 1.5 km are around −0.2 m s−1 above the continent but negligible over the sea (Fig. 6a). Such negative (downward) w values are consistent with air flowing downhill off the plateau.

Fig. 6.
Fig. 6.

(a) The AMPS 10-m forecast horizontal wind velocity field (vectors) at 0000 UT 3 Jun 2011. The color contours indicate the vertical wind velocity at 1.5-km altitude. (b) As in (a), but for the t + 24-h forecast field (0000 UT 4 Jun 2011). In both (a) and (b), Davis is marked by the solid black circle, and the topography with a 500-m interval is marked by the thin black lines. The ridgeline is marked by the thick black line. The lengths of the vectors indicate the wind speed, with the reference vector given in the bottom-right corner (m s−1) of each panel.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

The situation changes markedly 24 h later (0000 UT 4 June), at which time the Davis radar observed large . The offshore 10-m northeasterly wind speeds exceed 20 m s−1 (Fig. 6b). A large gradient in horizontal wind speed is apparent, with winds decelerating from 25 m s−1 upward of Davis to less than about 5 m s−1 above and downwind of Davis. The coastal northeasterly winds interact with the ridgeline upwind of Davis, resulting in strong winds of around 25 m s−1 as the flow accelerates downhill. The vertical velocity at 1.5 km indicates large downward motion upwind of Davis (corresponding to the downward slope of the ridge and strongest 10-m horizontal wind speeds) and upward vertical motions above Davis (where the 10-m horizontal wind speeds are smaller). The resultant large values create a pattern that is aligned with the topography. Davis is at the western edge of this large region. The inland katabatic winds change direction slightly and have only a small increase in amplitude (compared with Fig. 6a). Thus, the primary generation mechanism for the large is the synoptic northeasterly winds interacting with the ridgeline, rather than the katabatic winds. Other time steps (every 3 h) reveal similar characteristics, with a large gradient in 10-m horizontal velocity immediately upwind of Davis and a similar 1.5-km pattern.

While the 10-m near-surface flow is easterly upwind of the ridgeline (at 80°–81°E; see Fig. 6b), its direction changes on the descent down the ridgeline and toward the coast at Davis. The cross section in the plane of surface wind propagation incident on the ridge (propagation approximately 65° east of north) is illustrated in Fig. 7. The alternating upward and downward w motions above the downwind region of the ice ridgeline are evident. The wave phases are tilted with altitude into the direction of the prevailing surface wind. Wave energy is thus directed upward and against the propagation direction of the surface wind, indicative of orographic wave activity (Limpasuvan et al. 2007; Plougonven et al. 2008).

Fig. 7.
Fig. 7.

The cross section along the direction of surface wind propagation upwind of the ice ridgeline (line segment AB in Fig. 1) of the AMPS forecast model at 0000 UT 4 Jun 2011. The locations A and B and the ice ridgeline marked along the x axis are as indicated in Fig. 1. The vertical wind velocities (colors), potential temperature (gray lines, interval of 5 K), and horizontal wind field in this plane (vectors) are displayed. The topography is marked by the solid black line. The wind vector scales are given by the vectors in the top-right corner (m s−1), along with the north and east directions.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

Four additional AMPS forecast-output case studies, one in each season, are illustrated in Fig. 8. These additional cases were selected randomly from the numerous days when large w values were recorded by the radar. While there are differences in the details, the main features of the 1.5-km AMPS w field in Fig. 8 are consistent, specifically that the w patterns show strong downward motion above the ice ridgeline and strong upwind motion in the vicinity of Davis. These AMPS results indicate that the large w values observed with the VHF radar throughout the year are likely orographic in origin and occur when strong offshore northeasterly surface winds are present. These cases also show similar vertical wave structure to that illustrated in Fig. 7 for the June 2011 event, although these results are not provided here.

Fig. 8.
Fig. 8.

The AMPS 10-m forecast horizontal wind velocity field (vectors), along with vertical wind velocity at 1.5-km altitude (color contours) on four different days, as marked in the titles. Other annotations are as given in Fig. 6.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

b. Seasonal variation in gravity wave activity

The AMPS case studies indicated the effect that transient offshore meteorological systems have on the occurrence of large at Davis. To investigate the composite synoptic-scale conditions during which the largest values (where the overbar indicates the time mean) were recorded at Davis, we decompose the dataset into “active” and “quiet” conditions, based on a threshold value of . We define a 6-hourly period as being active if its particular value at 2.0 km is in the top 10% of all values recorded during the 2 years (i.e., m2 s−2). Quiet conditions constitute the bottom 10% of all values during the 2 years (i.e., m2 s−2). The selection of this cutoff is somewhat arbitrary; however, similar results to those presented below are evident upon choosing a different cutoff between active and quiet conditions. The purpose of dividing the data into active and quiet regimes is to form composites to understand the synoptic-scale environment. Certainly, a quiet period does not imply no gravity wave activity; rather, this separation allows investigation of the likely origin of the largest values and the background meteorological conditions in which they occur.

The relationship between the radar’s 2.0-km values and the 10-m ERA-Interim wind speeds at the ice ridgeline is shown in Fig. 9. As the near-surface wind speed increases, also increases. The correlation r is 0.64 between the 10-m ERA-Interim winds and the logarithm of the 2.0-km values. The 10-m ERA-Interim winds are 16 ± 4 m s−1 during active conditions and 6 ± 3 m s−1 during quiet conditions (mean and standard deviations given). The smallest ERA-Interim wind speeds during active conditions (<8 m s−1, upper left of Fig. 9) occurred during summer. The correlations between the logarithm of the radar’s 2.0-km values and the 10-m ERA-Interim winds around Davis are shown in Fig. 10. The highest correlations occur northeast of Davis and, more specifically, directly upwind of the ice ridgeline. Figure 10 indicates the impact of the upwind surface flow (upwind considering the prevailing wind direction is northeasterly or easterly; see Fig. 11) on the observed at Davis.

Fig. 9.
Fig. 9.

The relationship between the ERA-Interim 10-m wind speed above the ridgeline and the Davis radar’s 2.0-km observations. The horizontal dashed lines indicate the active threshold ( m2 s−2) and the quiet threshold ( m2 s−2), while the color bar indicates the number of data points. The correlation coefficient is also given.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

Fig. 10.
Fig. 10.

The correlation coefficient between the ERA-Interim 10-m wind speed and the logarithm of the Davis VHF radar’s 2.0-km observations (colors). Values of are highlighted by the red contours. The location of Davis is marked by the solid black circle. The ERA-Interim topography is shown by the black lines at every 1000-m altitude.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

Fig. 11.
Fig. 11.

Wind rose of the 2-yr wind speed and direction of the ERA-Interim 10-m wind at 68.5°S, 79.5°E (the ice-ridgeline grid cell; see Fig. 1 for its location).

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

The wind rose from the ERA-Interim 10-m surface winds above the ice ridgeline is displayed in Fig. 11. Nearly all of the surface winds on the ridgeline are from the easterly quarter, with wind speeds often exceeding 16 m s−1. Such easterly near-surface wind flow is characteristic of the katabatic wind in this location (Parish and Bromwich 1987). The monthly-mean ERA-Interim 10-m wind speeds above the ice ridgeline are illustrated in Fig. 12; greater winter (May–September) wind speeds are evident.

Fig. 12.
Fig. 12.

Monthly-mean ERA-Interim 10-m wind speed above the ice ridgeline. The vertical bars indicate the standard errors, while the two dashed lines indicate plus and minus one standard deviation.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

The monthly-mean radar and values at 2.0–3.2 km are shown in Figs. 13 and 14, respectively, for the data filtered using three different band limits. These results are calculated from the time-averaged variances for the 2-yr dataset. A seasonal cycle is apparent for all cases, with maximum and values in winter and minimum values in summer. The short-period (16 min–2 h) values are consistently larger than the long-period (2–12.8 h) values. This relative contribution is reversed for , where the long-period gravity wave components are larger throughout the year. This indicates that the short-period vertical wind velocities are responsible for a large proportion of the total . Because of the underestimate of the radar’s horizontal wind speeds (Fig. 3), it is likely that the resultant monthly values are also underestimated.

Fig. 13.
Fig. 13.

The 2.0–3.2-km monthly-mean radar values for the different filter bands, as marked. Vertical bars indicate the standard errors in the means. The monthly standard deviations (not plotted) are 2.0–3.5 m2 s−2 for the different filter bands.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

Fig. 14.
Fig. 14.

The 2.0–3.2-km monthly-mean radar values for the different filter bands, as marked. Vertical bars indicate the standard errors in the means. The monthly standard deviations (not plotted) are 0.035–0.075 m2 s−2 for the different filter bands.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

The presence of an offshore synoptic-scale depression is negatively correlated with the logarithm of the 2.0-km Davis radar values over the 2-yr observation period (Fig. 15) so that, as the ERA-Interim offshore surface pressure falls, is likely to increase. The strongest anticorrelation is north of Davis, centered at 64°S, which indicates that the presence of a depression in this region is most likely to result in an increase of the Davis values.

Fig. 15.
Fig. 15.

The correlation coefficient between the ERA-Interim surface pressure and the logarithm of the Davis VHF radar’s 2.0-km values (colors). Values of are highlighted by the red contours. The location of Davis is marked by the solid black circle. The ERA-Interim topography is shown by the black lines at every 1000-m altitude.

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

The composite surface conditions in the Davis region from ERA-Interim are displayed in Fig. 16a for quiet conditions. The katabatic winds are visible over the continent and are aligned following the drainage patterns of Antarctica (Parish and Bromwich 1987). These winds are approximately easterly in the Davis region. The mean 10-m winds close to Davis are 4–6 m s−1. For the composite of active orographic gravity wave conditions at Davis (Fig. 16b), a low pressure system exists offshore and north of Davis, about which the winds circulate cyclonically (clockwise in the Southern Hemisphere). The 10-m winds are stronger over coastal Antarctica during active conditions (14–16 m s−1).

Fig. 16.
Fig. 16.

Composites of the ERA-Interim 10-m horizontal wind speeds (color), horizontal wind velocities (vectors), and surface pressure over the ocean (hPa, black contours) for (a) quiet and (b) active conditions. The location of Davis is marked by the solid red circle. The reference horizontal wind velocity vector is in the bottom-right corner (m s−1).

Citation: Journal of the Atmospheric Sciences 72, 3; 10.1175/JAS-D-14-0171.1

4. Discussion

The seasonal cycle of gravity wave activity in Figs. 13 and 14 for all of the filter bands reveals a winter maximum and low values during summer. Tropospheric (and stratospheric) seasonal variability in gravity wave activity is commonly observed at all latitudes and is due to source variability and filtering by the background atmosphere (Fritts and Alexander 2003). As these Davis results are from the lower troposphere, this seasonal cycle is indicative of stronger, more frequent lower-tropospheric gravity wave sources during winter. The monthly-mean 10-m wind speeds above the ice ridgeline are also strongest in winter (Fig. 12). Stronger-than-usual near-surface northeasterly winds are associated with an increase in gravity wave activity in the lower troposphere above Davis, although the ERA-Interim may not fully capture the small-scale local winds that actually occurred. The strengthening of the near-surface wind is due to the passage of synoptic-scale low pressure systems north of Davis, which direct a strong northeasterly flow over the region around Davis (Fig. 16). The ERA-Interim topographical fields are necessarily smoothed from reality. In coastal East Antarctica where the ice sheet descends steeply, this results in positive model altitudes extending seaward of the actual coastline, which can bias the near-surface winds and temperatures of coastal stations in the model to be more representative of a location at higher altitude (Bromwich et al. 2005). The altitude of the ERA-Interim grid cell that incorporates Davis is 179 m, when in reality Davis is at sea level.

The interaction of the synoptic flow with the topography and katabatic winds is analyzed for a June 2011 case study where the ridgeline immediately upwind of Davis caused a downslope acceleration of the flow and formed an orographic wave. The 10-m AMPS horizontal wind fields before (Fig. 6a) and during (Fig. 6b) observations by the Davis radar of large values (Fig. 5) reveal the interaction of the synoptic-scale meteorological disturbance with the ice topography for this June 2011 case study. The depression’s northeasterly winds are deflected vertically upon encountering the Antarctic topography. Four further AMPS cases on days when large values of Davis radar occur are summarized in Fig. 8. While there are differences in the details, the overall similarities of the AMPS vertical velocity indicate that these synoptic wind–topography interactions occur year-round. Based on these case studies, we conclude that the dominant mechanism for enhancing vertical wind perturbations in the lower troposphere at Davis, and thus increasing gravity wave activity, is the interaction of synoptic-scale-depression winds with the coastal topography. In contrast, during times when offshore winds are light, katabatic winds are still present but only produce very-small-amplitude perturbations. While katabatic winds can generate orographic gravity waves at various locations in the Antarctic (Watanabe et al. 2006), they are not important for doing so at Davis.

However, the interaction of synoptic-scale-depression winds with katabatic winds was documented in a high-resolution-model case study of a strong-wind event at Mawson (68°S, 63°E) by Orr et al. (2014). They reported a low 10-m horizontal wind speed downwind of the station at all model horizontal resolutions (1.5–12 km), similar to that observed in Fig. 6b at Davis, but the location of the maximum wind speed shifted toward Mawson in the higher-resolution model runs. While the amplitudes of the vertical wind velocities at 1.5-km altitude were weaker for lower-resolution runs, the location of the upward and downward components remained fixed relative to ice ridgelines (Orr et al. 2014). Similarly, the ridgeline upwind of Davis (Fig. 1) is responsible for the initiation of strong downslope winds and the formation of orographic waves. Some of the values recorded by the radar may be generated by the synoptic system itself (i.e., have nonorographic sources). Such possibilities will be investigated in the future with high-resolution-model case studies to compare with the Davis radar’s wind profiles.

The results presented here are composited using the full 2-yr dataset. Winter winds are stronger than summer winds (Fig. 12); thus, some seasonal differences in wave generation might be suspected. While the offshore low pressure composite is not as deep during summer as during winter, the same picture of enhanced near-surface flow is observed in both seasons (not shown). Similarly, while the correlation coefficients between the 2.0-km Davis values and the 10-m ERA-Interim wind speeds are lower in summer than in winter, the patterns still follow those illustrated in Fig. 10 for the full 2-yr dataset, with peak correlation above the ice ridgeline northeast of Davis.

The structure of the background wind field dictates how gravity waves will propagate, or at what altitude they will be absorbed into the background flow. All orographic gravity waves are removed when the wind speed in the direction of their propagation is zero (such as when the wind direction turns 180°). Increasingly more orographic waves are absorbed into the background flow as this change in wind direction increases (Dörnbrack et al. 2001; Baumgaertner and McDonald 2007). Case studies in coastal East Antarctica indicate that large values ceased around the upper troposphere (Arnault and Kirkwood 2012; Sato et al. 2014), although the limited height coverage of winds obtained with the VHF radar precludes a similar analysis at Davis. Recent analyses of gravity waves observed in the middle atmosphere above Davis indicate that they were unlikely to be orographic in origin because of lower-level critical filtering (Dowdy et al. 2007; Alexander et al. 2011).

Orographic waves generated by the ridgeline upwind of Davis have a small meridional component. While coastal East Antarctica is oriented approximately zonally, a close inspection of topographical maps reveals numerous ice ridgelines oriented in various directions. The katabatic wind flow along streamlines often has a large meridional component, for example, along the western edge of the Amery Ice Shelf (around 70°S, 70°E; see Fig. 16). Such locations may produce orographic waves that propagate into the middle atmosphere under suitable background wind conditions and would be worth further investigation.

5. Conclusions

The seasonal variability of gravity wave activity is quantified using 2 years of wind data obtained by a VHF wind-profiling radar at Davis from September 2009 to August 2011. Gravity wave activity is calculated using the wind velocity variances from the radar data. A seasonal cycle of lower-tropospheric (2.0–3.2-km altitude) gravity wave activity, for waves with ground-based periods of 16 min–12.8 h, is apparent. Maximum monthly-mean horizontal and vertical wind velocity variances occur during winter, and minimum monthly-mean variances occur during summer. This seasonal cycle, with winter maximum, is also apparent in horizontal and vertical velocity variances where only short-period (16 min–2 h) and long-period (2–12.8 h) components are retained in the temporal filtering. The winter maximum corresponds to the maximum ERA-Interim 10-m horizontal wind speed above a small ice ridgeline located around 60 km northeast and upwind of Davis. Maximum correlations between ERA-Interim 10-m horizontal wind speed and 2.0-km observations at Davis occur along this ridgeline. The times of the largest 10% of vertical velocity variances at Davis correspond to the presence of a depression centered to the north of Davis at 64°S, which directs stronger-than-usual northeasterly winds along the coastline. Case studies using AMPS forecast output indicate that these strong synoptic winds interact with an ice ridgeline to form orographic gravity waves, which manifest themselves in the Davis radar observations as large perturbations in the vertical wind velocity field.

The VHF radar at Davis is currently being upgraded with the goal of providing continuous wind profiles from about 2 km up to the lower stratosphere. Increasing the vertical coverage and temporal resolution will permit the investigation of wave structure and propagation and allow both model evaluations and comparisons with high-resolution-model case studies throughout the upper troposphere and lower stratosphere.

Acknowledgments

We thank the Davis engineers for their efforts in maintaining the VHF radar and the Bureau of Meteorology staff who launched the radiosondes. ERA-Interim data were obtained through the ECMWF data server. Archived AMPS forecast data were obtained from the Earth System Grid. This research was conducted for project 4025 of the Australian Antarctic program. We appreciate the valuable conversations that we have had with Prof. K. Sato, Dr. A. McDonald, and Dr. P. Reid during the course of this study. We thank three anonymous reviewers whose valuable comments improved an earlier version of this manuscript.

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