Controlled meteorological (CMET) free balloon profiling of the Arctic atmospheric boundary layer around Spitsbergen compared to ERA-Interim and Arctic System Reanalyses

Abstract

Observations from CMET (Controlled Meteorological) balloons are analysed to provide insights into tropospheric meteorological conditions (temperature, humidity, wind) around Svalbard, European High Arctic. Five Controlled Meteorological (CMET) balloons were launched from Ny-Ålesund in Svalbard (Spitsbergen) over 5-12 May 2011 and measured vertical atmospheric profiles over coastal areas to both the east and west. One notable CMET flight achieved a suite of 18 continuous soundings that probed the Arctic marine boundary layer (ABL) over a period of more than 10h. Profiles from two CMET flights are compared to model output from ECMWF Era-Interim reanalysis (ERA-I) and to a high-resolution (15km) Arctic System Reanalysis (ASR) product. To the east of Svalbard over sea ice, the CMET observed a stable ABL profile with a temperature inversion that was reproduced by ASR but not captured by ERA-I. In a coastal ice-free region to the west of Svalbard, the CMET observed a stable ABL with strong wind shear. The CMET profiles document increases in ABL temperature and humidity that are broadly reproduced by both ASR and ERA-I. The ASR finds a more stably stratified ABL than observed but captured the wind shear in contrast to ERA-I. Detailed analysis of the coastal CMET-automated soundings identifies small-scale temperature and humidity variations with a low-level flow and provides an estimate of local wind fields. We demonstrate that CMET balloons are a valuable approach for profiling the free atmosphere and boundary layer in remote regions such as the Arctic, where few other in situ observations are available for model validation.

Atmos. Chem. Phys., 16, 1238312396, 2016 www.atmos-chem-phys.net/16/12383/2016/ doi:10.5194/acp-16-12383-2016 Author(s) 2016. CC Attribution 3.0 License.

Controlled meteorological (CMET) free balloon proling of the Arctic atmospheric boundary layer around Spitsbergen compared to ERA-Interim and Arctic System Reanalyses

Tjarda J. Roberts1,2, Marina Dtsch3,4, Lars R. Hole3, and Paul B. Voss5

1LPC2E/CNRS, 3A, Avenue de la Recherche Scientique, 45071 Orlans, CEDEX 2, France

2Norwegian Polar Institute, Fram Centre, 9296 Troms, Norway

3Norwegian Meteorological Institute, Bergen, Norway

4Institute for Atmospheric and Climate Science, ETH Zurich, 8092 Zurich, Switzerland

5Smith College, Picker Engineering Program, Northampton, MA, USA Correspondence to: Tjarda J. Roberts ([email protected])

Received: 22 May 2015 Published in Atmos. Chem. Phys. Discuss.: 14 October 2015 Revised: 4 July 2016 Accepted: 18 July 2016 Published: 30 September 2016

Abstract. Observations from CMET (Controlled Meteorological) balloons are analysed to provide insights into tropospheric meteorological conditions (temperature, humidity, wind) around Svalbard, European High Arctic. Five Controlled Meteorological (CMET) balloons were launched from Ny-lesund in Svalbard (Spitsbergen) over 512 May 2011 and measured vertical atmospheric proles over coastal areas to both the east and west. One notable CMET ight achieved a suite of 18 continuous soundings that probed the Arctic marine boundary layer (ABL) over a period of more than 10 h. Proles from two CMET ights are compared to model output from ECMWF Era-Interim reanalysis (ERA-I) and to a high-resolution (15 km) Arctic System Reanalysis (ASR) product. To the east of Svalbard over sea ice, the CMET observed a stable ABL prole with a temperature inversion that was reproduced by ASR but not captured by ERA-I. In a coastal ice-free region to the west of Svalbard, the CMET observed a stable ABL with strong wind shear. The CMET proles document increases in ABL temperature and humidity that are broadly reproduced by both ASR and ERA-I. The ASR nds a more stably stratied ABL than observed but captured the wind shear in contrast to ERAI. Detailed analysis of the coastal CMET-automated soundings identies small-scale temperature and humidity variations with a low-level ow and provides an estimate of local wind elds. We demonstrate that CMET balloons are a valuable approach for proling the free atmosphere and boundary

layer in remote regions such as the Arctic, where few other in situ observations are available for model validation.

1 Introduction

In remote regions such as the Arctic there exists very limited in situ observational data to evaluate atmospheric models.This study demonstrates CMET (Controlled Meteorological) balloons as a new approach for detailed probing of the Arctic atmospheric boundary layer on local-to-regional scales and compares the observations to model reanalysis outputs.

Accurate representation of polar meteorology and small-scale airsea ice interaction processes is essential for meteorological forecast models and to understand climate in the Arctic, a region undergoing rapid change (Vihma et al., 2014). The atmospheric boundary layer in the Arctic is usually strongly stable during winter and only weakly stable to neutral during summer (Persson et al., 2002). Strong temperature inversions can occur as warmer air masses from lower latitudes are advected over the cold polar air masses. This stability acts as a barrier to vertical atmospheric mixing and exchange and can magnify ows over small-scale topography such as channelling and katabatic ows. The Barents Sea near Svalbard is especially implicated in Arctic climate (Smedsrud et al., 2013). To the east of Svalbard, the Barents Sea is typically partially covered by sea ice during winter and

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

12384 T. J. Roberts et al.: Controlled meteorological (CMET) free balloon proling

spring, whilst sea ice is typically absent in the Greenland Sea to the west of Svalbard. This is due to the northward owing warm and saline Atlantic Warm Current (AWC) or North Atlantic Drift, which elevates temperatures along Svalbards west coast, with a secondary branch that enters the Barents Sea. The warm saline AWC releases heat to the atmosphere as it cools to sink beneath the polar waters. The polar waters experience thermodynamic formation, growth and melt of sea ice as well as wind- and oceanic-current-driven advection of sea ice, which can lead to highly variable surface conditions that affect airsea exchange of heat and momentum and the radiative balance, e.g. through albedo. Even at high sea ice density, small patches of open water amongst very close (90100 %) or close (8090 %) drift ice tend to promote seaair exchange, enhancing both temperature and specic humidity at the surface (Andreas et al., 2002). Conversely, snow deposited upon sea ice provides an insulating layer that reduces heat exchange. Hence, heat and energy uxes to the Arctic atmospheric boundary layer can vary by several orders of magnitude, depending on the surface state (Kilpelinen et al., 2011).

Model reanalyses provide temporally consistent representations of atmospheric and surface state and are a valuable tool for understanding Arctic processes and climate.A global model reanalysis product is ERA-Interim (ERA-I) from the European Centre for Medium-Range Weather Forecasts (ECMWF), Dee et al. (2011). At approximately 80 km resolution, ERA-I has been widely used including for Arctic studies, e.g. Rinke et al. (2006). Recently, Arctic System Reanalysis (ASR) products have been developed at higher resolution (1530 km) and specically focused on high latitudes (Bromwich et al., 2016). There is an ongoing effort to validate and compare the ASR and ERA-I reanalyses data sets. The ASR (version 1: 30 km resolution) and ERA-I re-analyses exhibit comparable RMS errors for surface meteorology compared to Arctic-wide collated meteorological station data (December 2006November 2007), (Bromwich et al., 2016). Wind speed biases were signicantly smaller in the ASRv1. North of 60 N, ASRv1 showed smaller precipitation biases than ERA-I except during summer. Moore et al. (2015) showed that the higher-resolution ASRv1 is more able to fully resolve mesoscale features in the atmosphere, such as katabatic wind, to the south-east of Greenland, compared to ERA-I. Wessln et al. (2014) compared ASRv1 and ERA-I reanalyses to surface and radiosonde meteorological data obtained during a 3-week ice drift experiment in summer 2008, a period typically inuenced by clouds. ERA-I was found to have a systematic warm bias in the lowest troposphere, whilst ASRv1 had a systematic cold bias of similar magnitude. The ASR version 2 at 15 km resolution has recently been developed. Moore et al. (2016) demonstrate the added value of ASRv2 compared to ASRv1 in resolving topographically forced winds and capturing mesoscale spatial features around Greenland due to the higher resolution.

In this study we compare ASRv2 (at 15 km resolution) and ERA-I to in situ CMET balloon observations in the Sval-bard region during the 2011 Arctic spring. In this region in situ measurements of the boundary layer and lower troposphere are limited. Meteorological stations provide continuous ground-based data and regular daily meteorological balloon proles, but are sparsely located. In Svalbard, such data sets may be occasionally supplemented by tethered balloon or meteorological mast observations (e.g. Mkiranta et al., 2011). Intensive eld campaigns probe more remote regions of the Arctic by aircraft (e.g. Vihma et al., 2005) or by drifting ice stations (e.g. Rinke et al., 2006, Tjernstrm et al., 2012), but these can only be rarely undertaken due to cost. Remotely piloted aircraft systems (RPAS) also known as unmanned aerial vehicles (UAV) equipped with meteorological sensors provide an alternative cost-effective means to spatially probe the Arctic boundary layer around Svalbard at local scales, Mayer et al. (2012a, b). However, most UAVs are operated over timescales up to a few hours and over ranges typically limited to a few 10s of km. For low-altitude ights the range may be further limited if terrain blocks the signal.

To provide an in situ meteorological data set that samples the wider Svalbard Arctic region we deployed ve Controlled Meteorological (CMET) balloons, launched in May 2011 from Ny-lesund in Svalbard. CMET balloons are capable of performing sustained ights within the troposphere at designated altitudes and can make vertical soundings at any time during the balloon ight on command via satellite link (Voss et al., 2012). The nested dual balloon design ensures very little helium loss, enabling the balloons to make multi-day ights. This gives an opportunity to investigate areas far away from research bases, at greater spatial scales (many hundreds of kilometres from the launch point) than can be obtained by line-of-sight RPAS/UAV approaches, radiosondes or tethered balloons. The study builds upon previous uses of CMET balloons to probe regional-scale meteorology including atmospheric trajectories (Riddle et al., 2006), air ow downwind from a city pollution source (Voss et al., 2010) and Antarctic meteorology on local-to-regional scales (Stenmark et al., 2014; Hole et al., 2016). Here we demonstrate the capability of CMET balloons to repeatedly make in-ight soundings down to low altitudes that reach into the atmospheric boundary layer. We present multiple CMET ights of long duration (up to several days) in the Arctic including a CMET congured to make automated continuous proling into the atmospheric boundary layer. These CMET in situ proles of temperature, humidity and wind are compared to ERA-I and ASR model reanalyses.

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2 Methods

2.1 CMET balloon and payload description

Controlled Meteorological (CMET) balloons can y for multiple days in the troposphere with altitude controlled via satellite link (Voss et al., 2012). Altitude control is achieved by the dual balloon design (high-pressure inner and low-pressure outer balloon) between which helium is transferred by a miniature pumpvalve system. Commands sent through an Iridium satellite link can set target altitude (typically 0 3500 m), control band ( 50500 m with the higher band us

ing less power), vertical velocity ( 0.51.5 m s1), termi

nation countdown timer and numerous other operational parameters. For this study, a new capacity was added to perform automated soundings between two specied pressure altitudes.

The 215 g CMET payload (excluding balloon envelopes) includes the control electronics, GPS receiver, satellite modem, pump-valve system, lithium polymer battery, photo-voltaic panel, aspirated T-RH sensor and a vacuum-insulated pouch for the payload. The payload temperature is maintained within acceptable operating limits (typically +20 C

above ambient) even at altitudes of several kilometres in the Arctic.

An aviation-grade pressure sensor (Freescale MPXH6115A) coupled to a 16 bit analog-to-digital converter (Analog Devices AD7795) provides altitude information to the balloons control algorithm every 10 s during ight. As part of data post-processing, this pressure-derived altitude is corrected for pressure offsets using the in-ight GPS altitude (Inventek ISM300X). GPS latitude and longitude provide the in-ight CMET coordinates and are also further analysed during ight to determine wind speeds in eastward (U) and northward (V ) directions.

Temperature is measured using a thermistor (General Electric MC65F103A) in a 10 k-Ohm divider circuit coupled to the aforementioned analog-to-digital converter. A capacitance humidity sensor (G-TUCN.34 from UPSI, covering 2 to 98 % RH range over 40 to +85 C) generates a signal

which is a function of the ambient relative humidity (RH) with respect to water. Relative humidity was converted to specic humidity (Q) for comparison to the ERA-I and ASR model outputs.

CMETs are relatively simple to launch (requiring just 12 people with standard meteorological balloon skills: launches have been achieved under a wide range of surface winds to date) and are similar in size to a standard meteorological balloon. Further details of the CMET balloon, payload design and balloon ight engineering are described by Voss et al. (2012) and illustrated at http://www.science.smith.edu/cmet/flight.html

Web End =http://www.science.smith.edu/ http://www.science.smith.edu/cmet/flight.html

Web End =cmet/ight.html .

Figure 1. Trajectories of ve CMET balloons launched from Ny-lesund in May 2011. Flight paths are shown on the regional scale of the island Spitsbergen, Svalbard and on the local scale of Kongsfjord. Ny lesund is marked by a yellow circle and lies at the southern side of Kongsfjord. Balloons 4 and 5 performed repeated soundings as shown by the pressure variations in time (marked *). Analysis periods for ights 4 (06:0012:00 UTC) and 5 (full ight) are denoted by x.

2.2 Balloon launches in Svalbard

Five CMET balloons were launched from the research station of the Alfred Wegener Institute and the Polar Institute Paul Emile Victor (AWIPEV) in Ny lesund, over the period 5 to 12 May 2011 (JD 125 to 132) (Fig. 1). Balloons 1 and 2 had short ights due to technical issues encountered at the start of the campaign. Balloon 3 ew far north and was the longest duration ight in this campaign but did not perform any soundings after leaving the coastal area of Svalbard. Balloon 4 ew eastwards, but despite good balloon performance needed to be terminated before encroaching Russian airspace. It performed two closely spaced (ascent and descent) soundings over sea ice in the Barents Sea, east of Svalbard. Balloon 5 undertook a 24 h duration ight that rst exited Kongsfjorden, then ew northwards along the coast. It was placed into an automated sounding mode and achieved a much longer series of 18 consecutive proles of the ABL, before being raised to higher altitudes where winds advected it eastwards. To the best of our knowledge, this was the rst demonstration of a set of extended controlled soundings made using a free balloon.

The data analysis of this study focuses on balloon ights 4 and 5, which made repeated soundings quantifying the following meteorological variables as a function of pressure (altitude): temperature (T ), specic humidity (Q) and northward and eastward winds (V,U). The balloon locations during these ights are shown in Fig. 1. A detailed model

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12386 T. J. Roberts et al.: Controlled meteorological (CMET) free balloon proling

Figure 2. Sea ice concentration eld on 8 May (JD 128) in ERA-I and ASR reanalyses. The ERA-I image shows a map of Svalbard overlain. The ERA-I map coordinates are depicted on the ASR image for ease of comparison. Also shown is the Lance rapid response image (right) from the MODIS satellite (downloaded from http://lance-modis.eosdis.nasa.gov/

Web End =http://lance-modis.eosdis.nasa.gov/ http://lance-modis.eosdis.nasa.gov/

Web End = , land and sea ice are shown in red, cloud cover in white) for 5 May 2011 (JD 125).

comparison is made for ight 4 over time periods 06:00 12:00 UTC on 8 May (JD 128) and for the 24 h ight 5 (21:0021:00 UTC) on 1011 May (JD 130-131).

2.3 Model reanalyses products ERA-I and ASR

The CMET observations are compared to two model re-analyses: ECMWF ERA-Interim (Dee et al., 2011) and the Arctic System Reanalysis (Bromwich et al., 2016). ERAI (available from http://apps.ecmwf.int/

Web End =http://apps.ecmwf.int/ ) has approximately 80 km (T255 spectral) resolution on 60 vertical model levels from the surface up to 0.1 hPa, at 6-hourly resolution. The boundary layer and lower troposphere (> 800 hPa) corre

spond to 14 model levels. For this study, bilinearly interpolated model level data were downloaded at 0.125 spatial resolution, then further linearly interpolated. ASR uses the polar-optimized version of the Weather Research and Forecasting Model (Polar-WRF: Bromwich et al., 2009) with an inner domain that extends over latitudes > 40 N, using

ERA-I output as boundary conditions. ASR (version 2) has 15 km resolution on 70 vertical model levels from the surface up to 0.1 hPa, at 3-hourly resolution (ASR version 1 at 30 km resolution is used in this study only for comparison to a surface station). The boundary layer and lower troposphere (> 800 hPa) correspond to 30 model levels. For

this study, full ASRv2 model level data were made specially available by the ASR team for selected eld dates. Pressure-level data for ASRv2 will soon be publicly available from http://rda.ucar.edu/

Web End =http://rda.ucar.edu/ . The ASR and ERA-I reanalyses were 4-D (latitude, longitude, pressure and time) interpolated to the CMET balloon for direct comparison. A main difference between these two reanalyses is the much higher temporal (3-hourly) and spatial (15 km) resolution of ASR. This provides a more highly resolved simulation of small-scale meteorological processes (especially within the boundary layer) as well as topography. Another difference is that ASR Polar WRF has non-hydrostatic dynamics whilst ERA-I pressure is hydrostatic. Both model reanalyses include assimilation of remotely sensed retrievals and in situ surface and upper

air data, 4-D for ERA-I and 3-D for ASR. ASR uses a high-resolution land data assimilation system and uses Polar WRF which includes the Noah land surface model and a detailed fractional sea ice description including extent, concentration, thickness, albedo and snow cover (see Bromwich et al., 2016 for details). For ERA-I surface properties are less detailed (spatio-temporally) than for ASR, but sea ice is also fractional and updated daily.

Sea ice concentration in ERA-I and ASR models is shown in Fig. 2 for 8 May (JD 128), the date of the CMET ight 4 soundings. Also shown is a satellite image of sea ice coverage (obtained for 5 May, JD 125). The west of Svalbard is ice-free, consistent with sea-surface temperature in this region (see Introduction), whilst dense sea ice occurs east of Svalbard. The satellite image also shows some small-scale features in ice-free areas (polynyas). These are not seen in the ERA-I ice-eld but are represented in ASR as zones of lower ice concentration.

3 Results and discussion

3.1 Meteorological conditions during the campaign

The period of 512 May 2011 was characterized by rapidly changing meteorological conditions, reected in the different CMET ight paths (Fig. 1). The time evolution of the pressure systems driving the winds that advected the CMETs is illustrated by ERA-I model surface pressure maps in Fig. 3. The start of the campaign is inuenced by a high-pressure system that slowly advected balloon 3 northwards. A low-pressure system then developed to the north and east of Sval-bard, which is responsible for the south-eastwards advection of balloon 4. Presence of a high-pressure system causes a slow northwards, followed by an eastwards advection of balloon 5. Surface observations (resolution in minutes) from the AWIPEV meteorological station in Ny-lesund (Maturilli et al., 2013) are shown alongside the ERA-I and ASR model outputs in Fig. 4. The greatest wind speeds during the cam-

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ERA-I sea-level pressure, hPa

Figure 3. Sea-level pressure in ERA-I shown as a function of latitude and longitude at 12-hourly intervals for the duration of the eld campaign, starting on JD 125 (5 May). Overlain in white are Ny-lesund and the CMET ight tracks as a function in time (full extents of ights 3 and 4 are shown at JD 128.5 and for ight 5 at JD 132).

paign are observed on 810 May with the AVIPEV station registering a maximum wind speed of 17.4 m s1 around noon on 9 May. During this period the winds became north-westerly due to the presence of a high-pressure system SW and a lower-pressure system NE of Svalbard. This caused temperature to decrease during this period. This was followed by a period of low wind speed over 1112 May, also reected in the 24 h CMET ight to the east of Svalbard, with low but increasing temperatures recorded at the meteorological station. Both models show good general agreement with the Ny-lesund surface meteorological observations of 2 m temperature, relative humidity and surface pressure (Fig. 4). This is not entirely unexpected given the use of data assimilation in both reanalyses. The models reproduced the variation in 10 m wind speed, but not always the wind direction reported at AWI-PEV (Fig. 4). This is likely due to known along-fjord wind channelling in the Kongsfjorden that oc-curs on ner scales than the resolution of the reanalyses. Indeed, Esau and Repina (2012) found that even a very ne-resolution model (5661 m grid cell) could not fully resolve

near-surface small-scale turbulence in the strongly stratied Kongsfjorden atmosphere, where the valley is surrounded by steep mountain topography.

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Figure 4. Meteorology parameter time series (resolution in minutes) from the Ny-lesund AWIPEV station compared to ERA-I (6-hourly) and ASR (3-hourly) outputs for pressure, temperature, relative humidity, U and V winds. Wind roses compare modelled and observed wind directions.

3.2 CMET proles over sea ice compared to ERA-I and ASR: temperature inversion

The two consecutive CMET proles of temperature, specic humidity, U and V winds over sea ice east of Svalbard (balloon ight 4) on the morning of JD 128 are compared to 4-D interpolated ERA-I and ASR model data (Figs. 5 and 6). The in-ight CMET soundings quantify temperature and humidity proles which increase towards the surface as expected, as well as winds (derived from the balloon ight path) from the north-west. There is good general agreement with ASR and ERA-I. However, the CMET observes a temperature inversion at around 990970 hPa which persists for most of the sounding time series. This temperature inversion is captured by ASR in good agreement with the CMET but is not reproduced by ERA-I. ASR nds a strong gradient in humidity related to this inversion barrier, but the CMET observes a more shallow humidity gradient. ERA-I nds an even shallower gradient in humidity than the CMET. Both models show strengthening westerly winds during the soundings, as observed. The CMET observed a reversal in V winds near the surface (> 1000 hPa). This is better captured by ASR than ERA-I, where it is related in the model to the inversion layer.However, there are differences in V winds at higher altitudes, which are more variable in ASR than in the CMET and ERAI.

The potential temperature and specic humidity proles from the CMET ight are further shown in Fig. 7, alongside

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12388 T. J. Roberts et al.: Controlled meteorological (CMET) free balloon proling

Figure 5. Temperature and specic humidity measured during the CMET ight 4 soundings (lled circles) compared to 4-D interpolated (latitude, longitude, pressure, time) model data from ERA-I and ASR.

Figure 6. U and V winds observed during the CMET ight 4 soundings (lled circles) compared to 4-D interpolated (latitude, longitude, pressure, time) model data from ERA-I and ASR.

equivalent 4-D interpolated model outputs at each CMET latitude, longitude, pressure and time location. The CMET potential temperature prole shows two distinct layers: a strongly stable layer between 990 and 970980 hPa (related to the abovementioned inversion) and a stable layer < 980 hPa. This agrees well with similar layers identied in the ASR, whereas the absence of an inversion layer in ERA-I leads to a more linear potential temperature prole.

The specic humidity prole of ASR shows better agreement with CMET at 980 hPa, whereas ERA-I overestimates it by

0.2 g kg1. At higher altitudes, ERA-I is in better agreement whilst ASR shows greater humidity variability (overestimations by up to 0.3 g kg1) than the trend observed by CMET.

It is difcult to infer any temporal trend in the ight 4

CMET proles over the morning of JD 128. The nal prole (JD > 128.45) shows slightly greater humidity at low al-

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Figure 7. Proles of potential temperature and specic humidity during ight 4 as observed by the CMET balloon and according to the 4-D interpolated ERA-I and ASR model outputs.

titudes but also slightly lower temperature and the inversion is less clear. ERA-I and ASR show a tendency for increasing surface temperature and humidity. In the morning ASR predicts a deepening layer beneath the inversion, but the top remains at constant height. Unfortunately the experiment could not be continued eastwards into the afternoon as the CMET ight had to be terminated to avoid Russian airspace.

3.3 CMET proles in coastal area compared to ERA-I and ASR: wind shear and temperature and humidity trends

Flight 5 provided a series of 18 boundary layer proles over a sea-ice-free region west of Svalbard. With the low wind speeds (< 5 m s1), the 24 h balloon trajectory remained relatively close to the Svalbard coastline. Figures 8 and 9 compare the along-ight proles of temperature, specic humidity and U and V winds measured by the CMET to ERA-I and ASR model reanalyses. From morning to afternoon increases in temperature and humidity at the surface are observed by the CMET and shown by both models. Note that the lowest ERA-I model level intersects the CMET sounding at low altitudes (likely due to non-realistic surface topography), preventing model comparison, whereas this problem does not occur for ASR.

Overall there is good agreement between the reanalyses and CMET observations but some differences remain. During the night of JD 130-131, ERA-I underestimates temperature compared to CMET. This is better reproduced by ASR up until midday on JD 131, although still underpredicted. Both models and the CMET nevertheless show relatively small variations in the temperature proles at this time. Humidity is well reproduced by ASR during the JD 130-131 night and only slightly underestimated by ERA-I. On the morning of JD 131, ERA-I reproduces the observed enhanced humidity near the surface better than ASR. In ASR the vertical humidity transition is sharper than observed by the CMET and humidity is underestimated near the surface. Both ERA-I and ASR capture the observed increase in near-surface temperature and specic humidity up to the mid-afternoon. However, the CMET temperature increase is either stronger or earlier than in the models. These temperature and humidity enhancements are also spatio-temporally more localized for ASR than ERA-I. This leads to closer CMET agreement with ERA-I for mid-afternoon temperature but with ASR for humidity. Temperature is underestimated by both models at high altitudes in the evening of JD 131 whilst humidity is well reproduced (slightly overestimated by ERAI).

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Figure 8. Temperature and specic humidity measured during the CMET ight 5 soundings (lled circles) compared to 4-D interpolated (latitude, longitude, pressure, time) model data from ERA-I and ASR.

There are also differences in the U and V winds between

ASR and ERA-I (Fig. 9). The CMET observes strong V wind shear on the morning of JD 131. This wind shear pattern is reproduced by ASR but is not captured by ERA-I. V winds become southerly (from direction) in mid-afternoon in both models, but are more localized in ASR, leading to better early afternoon model agreement, although ERA-I better reproduces the persistence of southerly V winds to higher altitudes observed during the afternoon on JD 131. Westerly U winds are modelled and observed on the evening of JD 131. ERA-I shows high positive U winds at high altitudes only, whereas ASR shows high positive U winds at almost all levels.

Closer inspection of the CMET temperature shows some signs of hysteresis in this ight with greater temperatures reached during ascents than descents. This is despite the fast time response of the (aspirated) thermistor. A possible explanation might be the heating of the balloon surface by the sun, raising the temperature of the air layer in direct contact with the balloon. This air layer could be transported over the sensor during ascent, but not descent proles. Nevertheless, measurements made during descent only (> 0.1 m s1 vertical descent speed) are consistent with the complete ascent descent in potential temperature and specic humidity proles (Fig. 10). These proles show an overall increase ( 5

6 K) in potential temperature observed close to the surface, which is reproduced by the models except for where ASR underpredicts the temperature rise ( 34 K) and ERA-I ex

hibits a potential temperature bias of 2 K. The observed

trend in surface specic humidity is less clear but with an overall enhancement. ASR specic humidity is in agreement with the CMET on JD 131 morning but is underestimated by up to 0.5 g kg1 during the afternoon. ERA-I better captures the afternoon humidity maximum (and in early morning) but overestimates midday humidity by 0.5 g kg1. The CMET

and model ight 5 proles show less stable conditions than found for ight 4 (which showed an inversion layer).

3.4 CMET soundings in detail: decoupled ows and wind eld estimation

Further analysis of the observations from the CMET ight 5 on JD 131 enables consideration of local-scale patterns at higher resolution than the reanalyses. The observed proles of potential temperature, specic humidity, wind speed and wind direction over 0212.5 UTC (JD 131.08131.52) are

shown with interpolated data between the soundings to highlight temporally consistent features (Fig. 11). The soundings ranged from approximately 150 to 700 m during this period. As mentioned previously, specic humidity tends to increase during the ight, particularly in the lower and middle levels. However, beyond JD 131.40 (9.6 UTC) there is actually a decrease in humidity in the lowermost levels, with maximum humidity in the sounding occurring at around 350 m altitude. Concurrent to this there is also a small increase in potential temperature at low altitudes. The wind speed and direction plots indicate relatively calm conditions, with greatest wind speed in the lower levels from a general southerly direction. In contrast, at the top of the soundings the balloon encountered winds from a northerly direction, above 600 m. From JD 131.35 onwards, the observed winds became broadly southerly also at 600 m. However, a band of rather more west-south-westerly winds developed at mid-altitudes ( 450 m), and low-level winds became (east)-south-easterly

from JD 131.4 onwards. This indicates that the balloon was not strictly sampling a uniform air mass during this period. Whilst previous studies have used CMETs to study Lagrangian air mass trajectories (e.g. Voss et al., 2010), here the ight path is quasi-Lagrangian. As a consequence, the temperature and humidity trends observed along the ight path

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Figure 9. U and V winds observed during the CMET ight 5 soundings (lled circles) compared to 4-D interpolated (latitude, longitude, pressure, time) model data from ERA-I and ASR.

cannot be wholly interpreted in Lagrangian terms (e.g. tracing of diurnal signature on a single air parcel), rather they must also consider the Eularian perspective (e.g. advection of air masses with distinct properties into and out of the CMET ight path and their mixing).

The continuous series of CMET vertical proles provide a more detailed overview of local-scale meteorology than is possible with traditional rawinsondes or constant-altitude free balloons. The CMET observations are consistent with the occurrence of a low-level ow that is decoupled from higher altitudes and at least initially an increase in surface humidity. The surface winds may be inuenced by low-level channel ows. An outow commonly exits from nearby KongsfjordenKongsvegen valley (e.g. Esau and Repina, 2012) but is hard to identify from the ground station in Ny lesund (south side of Kongsfjorden) given the rather low wind speeds during this period. Winds that originate over land are likely to be colder, with lower humidity than marine air masses. Thus, the CMET observations of lower specic humidity between JD 131.40 and 131.5 (9.612 UTC) might be explained by fumigation from or simply sampling of such a channel outow. Alternatively, the CMET location near Kapp Mitra Peninsula at this time may indicate an even more local source of dry air impacting low levels. A nal possibility could be the overturning of air masses in the vertical, bringing less humid air with higher potential temperature to lower altitudes. At mid-levels ( 450 m) a relatively humid

air layer persists, properties which suggest it has origins from the surface. It appears to be advected north-eastwards, potentially replenishing air over Svalbard to replace that which may be lost from the channel outow.

Wind elds are estimated from the CMET balloon 5 ight path for an 8 h period starting in the early morning of 11 May (JD 131) (Fig. 12). As per previous gures, the CMET balloon movement during the soundings has been used to es-

timate wind speed and direction. Here, wind trajectories are derived from the observed winds at 50 m altitude intervals for each up or down prole. The trajectory vectors (of length proportional to the wind speed time elapsed be

tween soundings) are placed end-to-end to estimate the wind eld, shown in Fig. 12 (grey mesh), alongside the CMET ight (red). This approximate technique assumes horizontally uniform ow in the vicinity of the balloon and computed trajectories. The lowermost layer exhibited the greatest wind speed, thus has the longest (and least certain) trajectory, approximately double that of the balloon during the same period. The uppermost layer ows southwards before reversing direction, approximately returning to its initial position at 600 m altitude. The middle layer trajectory is quite similar to that of the overall CMET balloon ight, but is transported initially somewhat more westwards and later somewhat more eastwards, due to the ESE winds experienced in the late morning (see Fig. 11). It is worth noting that this nal direction mirrors ndings from two of the other CMET balloons, which have ight paths out of Kongsfjorden deviating to the north-east into the nearby Krossfjorden (Fig. 1). These balloon-based trajectories provide insight into the complex local dynamics of low-altitude circulation inuenced by complex terrain. Furthermore, the trajectories and prole data can be computed and displayed in near-real time to inform the real-time in-ight decisions on CMET altitude control (e.g. to track specic layers or events of meteorological interest).

3.5 Discussion: ASR and ERA-I model reanalyses in comparison to CMET

Both reanalyses showed good general agreement with the

CMET ights, nding more stable conditions for ight 4 (over sea ice) than ight 5 (coastal). For ight 4, ASR showed

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12392 T. J. Roberts et al.: Controlled meteorological (CMET) free balloon proling

Figure 10. Proles of potential temperature and specic humidity during ight 5 as observed by the CMET balloon and according to the 4-D interpolated ERA-I and ASR model outputs. CMET measurements made during descents only (> 0.1 m s1 vertical descent speed) are shown as lled circles and full data sets are shown as open circles.

a better capability than ERA-I to reproduce a temperature inversion observed over sea ice. ASR and ERA-I broadly reproduced the enhanced humidity near the sea ice surface but showed some discrepancies with the CMET in the vertical-spatial distributions. For ight 5, ASR better reproduced ob-served wind shear near to the Svalbard coast. Both models exhibit increasing specic humidity and temperature in the near-surface atmosphere from morning to afternoon on JD 131, in agreement with the trend observed. However, compared to the CMET the surface temperature and humidity enhancements were underpredicted by ASR. ERA-I underestimated ABL temperature. Whilst increasing humidity and temperature over the daytime might be expected based on the diurnal cycle, Sect. 3.4 highlights the quasi-Lagrangian nature of ight 5 that also requires consideration of air mass advection and mixing. Figure 13 presents ERA-I (regional-scale) and ASR (local-scale) patterns for surface 2 m temperature and humidity for the duration of JD 131, alongside the CMET 5 ight path. A zone of warm and humid air initially to the south-west of Svalbard advects northwards and eastwards. This likely exerted a signicant inuence on the observed and modelled along-ight surface trends. The ASR also clearly shows local diurnal inuences on surface me-

teorology, particularly on 2 m temperature over the elevated topography east of the ight.

The temperature and humidity increases along ight 5 are temporally and spatially broader for ERA-I than for ASR (Fig. 8). This may to some degree reect model diffusion on the larger ERA-I grid size ( 80 km compared to 15 km

for ASR). The poorer ERA-I resolution of Svalbard topography will also affect simulated meteorology in this coastal area, where there may be local mixing, e.g. between marine-and land-inuenced air masses. A major contributing factor to ASR performance in capturing observed wind shear (ight 5) and temperature inversion (ight 4) is likely the higher vertical model resolution of ASR compared to ERAI, with ASR having about double the number of model levels than ERA-I at > 800 hPa, see Methods for descriptions. This improves the representation of the shallow polar ABL with its distinct layers. Noting that higher-resolution models that better capture spatial patterns can nevertheless lead to worse agreement with observations due to slight spatial shifts (Wesselen et al., 2014), we choose not to reduce the ERA-I, ASR and CMET comparison to standard metrics (e.g. a correlation coefcient) here. The representations of Arctic airseaice interaction and parameterization of turbulence uxes in the

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Figure 11. Potential temperature, specic humidity, wind speed and wind direction determined from the CMET balloon observations (131.08 to 131.52 JD, equivalent to 02 to 12.5 UTC on 11 May) of ight 5 during a series of automated soundings between 150 and 700 m altitude.

Data between the balloon soundings has been interpolated.

Figure 12. Wind eld calculated from the CMET balloon ight 5. Air parcel trajectories are calculated over an 8 h period for each 50 m altitude layer according to the winds observed by the CMET soundings. The red line shows the actual balloon track, the black vertical line shows the initialization of the calculation and the derived air parcel trajectories (wind eld grid) are shown in grey. The blue line shows the nal locations after 8 h.

boundary layer schemes will also inuence the model outputs (e.g. Mlders and Kramm, 2010), but they are difcult to assess from this study. In future, this insight could be provided by campaigns in which multiple CMET balloons are sequentially colaunched to horizontally and vertically and probe an atmospheric region, combined with model sensitivity simulations.

4 Conclusions

Five Controlled Meteorological (CMET) balloons were launched from Ny-lesund, Svalbard on 512 May 2011, to measure in situ the meteorological conditions (humidity, temperature, winds, pressure) in the surrounding Arctic region. Repeated soundings were performed along the CMET ights that probed the Arctic atmospheric boundary layer.The CMET data are analysed in comparison to model output from the ERA-Interim and Arctic System Reanalyses.

CMETs are a novel balloon technology capable of multi-day ights in the troposphere and performing in-ight soundings on command. Five CMET balloons were launched in May 2011. Balloons 1 and 2 had only short ights whilst balloon 3 made multi-day ights to the north but did not perform any soundings. Flights 4 and 5 made repeated soundings that proled the ABL. CMET balloon 4 made two soundings of the boundary layer over sea ice to the east of Svalbard. De-spite good performance this ight needed to be terminated to avoid encroaching on Russian territory. CMET balloon 5 was placed in an automated soundings mode and made a suite of 18 continuous soundings along the north-west coast of Sval-bard, during a 24 h ight. To our knowledge, this was the rst automated sounding sequence made by a free balloon.

This study focuses on the two ights that performed repeated proling of the boundary layer. Overall both observations and models identify the ABL as more stable for ight 4 (over sea ice) than ight 5 (coastal). To the east of Svalbard (ight 4), the observed temperature and humidity increases towards the surface are generally well reproduced by ERA-I and ASR. The CMET observed a temperature inversion over sea ice which was reproduced by ASR but was not captured by ERA-I. ASR and ERA-I broadly reproduced the enhanced humidity near the sea ice surface but showed some discrepancies with the CMET in the vertical-spatial distributions.The CMET ight 5 along the north-west coast of Svalbard

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12394 T. J. Roberts et al.: Controlled meteorological (CMET) free balloon proling

Figure 13. Surface 2 m temperature and specic humidity over JD 131 according to ERA-I (upper) and ASR (lower). ERA-I outputs are shown on the regional scale at 6-hourly intervals whilst ASR outputs are shown on a local scale at 3-hourly intervals. The CMET ight 5 trajectory up to each time point is illustrated as a white line.

observed increases in near-surface humidity and temperature and strong wind shear. Detailed analysis of the CMET data identies a low-level ow and provides an estimate of local wind elds. The wind shear was captured by ASR but not ERA-I. Both model reanalyses nd increasing surface specic humidity and temperature from morning to afternoon on JD 131. The enhancements are more spatio-temporally localized in ASR than ERA-I. The temperature enhancement was underpredicted by ASR whilst ERA-I exhibits a negative temperature bias on JD 131. The higher vertical and horizontal resolution of the ASR captures features (temperature inversion in ight 4, wind shear in ight 5) that are not described by ERA-I. However, there are other aspects of the modelobservation comparison that are in better agreement for ERA-I than ASR. This might be due to the different rep-

resentations of processes in the model and could be investigated in future by deploying a suite of CMET balloons over a region combined with model sensitivity studies.

In summary, CMET balloons provide a novel technological means to prole the remote Arctic over multi-day ights, including the capacity to perform continuous automated soundings into the atmospheric boundary layer. CMETs are thus highly complementary to other Arctic observational strategies including xed station, free and tethered balloons, meteorological masts and RPAS/UAVs (drones). Whilst RPAS/UAVs offer full 3-D spatial control for obtaining the meteorological observations, their investigation zone is generally limited to tens of kilometres based on both range and regulatory restrictions. CMET ights provide a relatively low-cost approach to observing the boundary layer at greater

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distances from the launch site (e.g. tens to hundreds of kilometres), from tropospheric altitudes potentially all the way down to the surface, and more remotely from the disturbances of Svalbard topography. CMETs can provide new in situ data sets for for quasi-Lagrangian and long-range transport and process studies.

5 Data availability

The CMET balloon data analysed in this study can be visualized online at http://www.science.smith.edu/cmet/flight.html

Web End =http://www.science.smith.edu/cmet/ight.html and accessed by contacting the CMET balloon principal investigator: Paul Voss at Smith College ([email protected]).Two external model data sets were used in this work and are referenced in the text. ERA-Interim (ERA-I) model reanalysis data are available from http://apps.ecmwf.int/

Web End =http://apps.ecmwf.int/ (Dee et al., 2011). Arctic System Reanalysis (ASR) data v1 and soon v2 are available from http://rda.ucar.edu/

Web End =http://rda.ucar.edu/ (Bromwich et al., 2016).

Acknowledgements. This research was sponsored by the Research Council of Norway and the Svalbard Science Forum. We are very grateful to the joint FrenchGerman Arctic Research Base AWIPEV in Ny-lesund for logistical support and Anniken C.Mentzoni for eldwork assistance. Paul B. Voss also acknowledges Smith College for support. Tjarda J. Roberts acknowledges NSINK, an Arctic Field Grant, CRAICC, and the VOLTAIRE LABEX (VOLatils-Terre Atmosphre Interactions Ressources et Environnement) ANR-10-LABX-100-01 (201120) for funding.This study occurred at the end of the Coordinated Investigation of the Climate-Cryosphere Interactions (CICCI) initiative. We are extremely grateful to the ASR team for providing model-level ASRv2 reanalysis data in advance of public distribution. We thank Chi-Fan Shih for help in accessing the ASR les and David Bromwich for useful comments on the manuscript.

Edited by: S. M. NoeReviewed by: three anonymous referees

Bauer, P., and Bechtold, P.: The ERA-Interim reanalysis: Conguration and performance of the data assimilation system, Q. J.Roy. Meteor. Soc., 137, 553597, doi:http://dx.doi.org/10.1002/qj.828

Web End =10.1002/qj.828 http://dx.doi.org/10.1002/qj.828

Web End = , 2011.Esau, I. and Repina, I.: Wind Climate in Kongsfjorden, Sval-bard, and Attribution of Leading Wind Driving Mechanisms through Turbulence-Resolving Simulations, Adv. Meteorol., 2012, 568454, doi:http://dx.doi.org/10.1155/2012/568454

Web End =10.1155/2012/568454 http://dx.doi.org/10.1155/2012/568454

Web End = , 2012.

Hole L. R., Bello, A. P., Roberts, T. J., Voss, P. B., and Vihma, T.: Measurements by controlled meteorological balloons in coastal areas of Antarctica, Antarct. Sci., CJO2016, doi:http://dx.doi.org/10.1017/S0954102016000213

Web End =10.1017/S0954102016000213 http://dx.doi.org/10.1017/S0954102016000213

Web End = , 2016.

Kilpelinen, T., Vihma, T., and Olafsson, H.: Modelling of spatial variability and topographic effects over arctic fjords in svalbard, Tellus A, 63, 223237, 2011.

Mkiranta, E., Vihma, T., Sjblom, A., and Tastula, E.-M.: Observations and modelling of the atmospheric boundary layer over sea-ice in a svalbard fjord, Bound.-Lay. Meteorol., 140, 105123, 2011.

Maturilli, M., Herber, A., and Knig-Langlo, G.: Climatology and time series of surface meteorology in Ny-lesund, Svalbard, Earth Syst. Sci. Data, 5, 155163, doi:http://dx.doi.org/10.5194/essd-5-155-2013

Web End =10.5194/essd-5-155-2013 http://dx.doi.org/10.5194/essd-5-155-2013

Web End = , 2013.

Mayer, S., Sandvik, A., Jonassen, M., and Reuder, J.: Atmospheric proling with the UAS SUMO: a new perspective for the evaluation of ne-scale atmospheric models, Meteorol. Atmos. Phys., 116, 1526, 2012a.

Mayer, S., Jonassen, M., Sandvik, A., and Reuder, J.: Proling the arctic stable boundary layer in Advent Valley, Svalbard: Measurements and simulations, Bound.-Lay. Meteorol., 143, 507 526, 2012b.

Mlders, N. and Kramm, G.: A case study on wintertime inversions in interior Alaska with WRF, Atmos. Res., 95, 314332, 2010.Moore, G. W. K., Renfrew, I. A., Harden, B. E., and Nernild, S.H.: The impact of resolution on the representation of southeast Greenland barrier winds and katabatic ows, Geophys. Res.Letts., 42, 30113018, doi:http://dx.doi.org/10.1002/2015GL063550

Web End =10.1002/2015GL063550 http://dx.doi.org/10.1002/2015GL063550

Web End = , 2015.Moore, G. W. K., Bromwich, D. H., Wilson, A. B., Renfrew,I., and Bai, L.: Arctic System Reanalysis improvements in topographically-forced winds near Greenland, Q. J. Roy. Meteor.Soc., 142, 20332045, doi:http://dx.doi.org/10.1002/qj.2798

Web End =10.1002/qj.2798 http://dx.doi.org/10.1002/qj.2798

Web End = , 2016.

Persson, P. O. G., Fairall, C. W., Andreas, E. L., Guest, P. S., and Perovich, D. K.: Measurements near the atmospheric surface ux group tower at sheba: Near-surface conditions and surface energy budget, J. Geophys. Res., 107, 80458079, 2002.

Riddle, E. E., Voss, P. B., Stohl, A., Holcomb, D., Maczka, D., Washburn, K., and Talbot, R. W.: Trajectory model validation using newly developed altitude-controlled balloons during the international consortium for atmospheric research on transport and transformations 2004 campaign, J. Geophys. Res., 111, D23S57, doi:http://dx.doi.org/10.1029/2006JD007456

Web End =10.1029/2006JD007456 http://dx.doi.org/10.1029/2006JD007456

Web End = , 2006.

Rinke, A., Dethloff, K., Cassano, J., Christensen, J., Curry, J., Du,P., Girard, E., Haugen, J.-E., Jacob, D., Jones, C., Kltzow, M., Laprise, R., Lynch, A., Pfeifer, S., Serreze, M., Shaw, M., Tjernstrm, M., Wyser, K., and Agar, M.: Evaluation of an ensemble of Arctic regional climate models: spatiotemporal elds during the sheba year, Clim. Dynam., 26, 459472, 2006.

Smedsrud, L. H., Esau, I., Ingvaldsen, R. B., Eldevik, T., Haugan, P. M., Li, C., Lien, V. S., Olsen, A., Omar, A. M., Otter, O. H., and Risebrobakken, B.: The role of the Barents

www.atmos-chem-phys.net/16/12383/2016/ Atmos. Chem. Phys., 16, 1238312396, 2016

References

Andreas, E. L., Guest, P. S, Persson, P. O. G., Fairall, C. W., Horst,T. W., Moritz, R. E., and Semmer, S. R.: Near-surface water vapor over polar sea ice is always near ice saturation, J. Geophys. Res.-Oceans, 107, C10, doi:http://dx.doi.org/10.1029/2000JC000411

Web End =10.1029/2000JC000411 http://dx.doi.org/10.1029/2000JC000411

Web End = , 2002. Bromwich D. H., Hines K. M., and Bai L.-S.: Development and testing of polar weather research and forecasting model: 2. Arctic Ocean, J. Geophys. Res., 114, D08122, doi:http://dx.doi.org/10.1029/2008JD010300

Web End =10.1029/2008JD010300 http://dx.doi.org/10.1029/2008JD010300

Web End = , 2009.

Bromwich, D. H., Wilson, A. B., Bai, L., Moore, G. W. K., and

Bauer, P.: A comparison of the regional Arctic System Reanalysis and the global ERA-Interim Reanalysis for the Arctic, Q. J. Roy. Meteor. Soc., 142, 644658, doi:http://dx.doi.org/10.1002/qj.2527

Web End =10.1002/qj.2527 http://dx.doi.org/10.1002/qj.2527

Web End = , 2016. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli,P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G.,

12396 T. J. Roberts et al.: Controlled meteorological (CMET) free balloon proling

Sea in the Arctic climate system, Rev. Geophys., 51, 415449, doi:10.1002/rog.20017, 2013.

Stenmark, A., Hole, L. R., Voss, P., Reuder, J., and Jonassen,M. O.: The inuence of nunataks on atmospheric boundary layer convection during summer in Dronning Maud Land, Antarctica, J. Geophys. Res. Atmos., 119, 65376548, doi:http://dx.doi.org/10.1002/2013JD021287

Web End =10.1002/2013JD021287 http://dx.doi.org/10.1002/2013JD021287

Web End = , 2014.

Tjernstrm, M., Birch, C. E., Brooks, I. M., Shupe, M. D., Persson, P. O. G., Sedlar, J., Mauritsen, T., Leck, C., Paatero, J., Szczodrak, M., and Wheeler, C. R.: Meteorological conditions in the central Arctic summer during the Arctic Summer Cloud Ocean Study (ASCOS), Atmos. Chem. Phys., 12, 68636889, doi:http://dx.doi.org/10.5194/acp-12-6863-2012

Web End =10.5194/acp-12-6863-2012 http://dx.doi.org/10.5194/acp-12-6863-2012

Web End = , 2012.

Vihma, T., Lpkes, C., Hartmann, J., and Savijrvi, H.: Observations and modelling of cold-air advection over Arctic sea ice in winter, Bound.-Lay. Meteorol., 117, 275300, 2005.

Vihma, T., Pirazzini, R., Fer, I., Renfrew, I. A., Sedlar, J., Tjernstrm, M., Lpkes, C., Nygrd, T., Notz, D., Weiss, J., Marsan,D., Cheng, B., Birnbaum, G., Gerland, S., Chechin, D., and Gascard, J. C.: Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review, Atmos. Chem. Phys., 14, 94039450, doi:http://dx.doi.org/10.5194/acp-14-9403-2014

Web End =10.5194/acp-14-9403-2014 http://dx.doi.org/10.5194/acp-14-9403-2014

Web End = , 2014.

Voss, P. B., Zaveri, R. A., Flocke, F. M., Mao, H., Hartley, T. P., DeAmicis, P., Deonandan, I., Contreras-Jimnez, G., Martnez-Antonio, O., Figueroa Estrada, M., Greenberg, D., Campos, T.L., Weinheimer, A. J., Knapp, D. J., Montzka, D. D., Crounse,J. D., Wennberg, P. O., Apel, E., Madronich, S., and de Foy, B.: Long-range pollution transport during the MILAGRO-2006 campaign: a case study of a major Mexico City outow event using free-oating altitude-controlled balloons, Atmos. Chem. Phys., 10, 71377159, doi:http://dx.doi.org/10.5194/acp-10-7137-2010

Web End =10.5194/acp-10-7137-2010 http://dx.doi.org/10.5194/acp-10-7137-2010

Web End = , 2010.

Voss, P. B., Hole, L. R., Helbling, E., and Roberts, T. J:. Continuous in-situ soundings in the Arctic boundary layer: A new atmospheric measurement technique using controlled meteorological balloons, J. Intell. Robotic Syst., 70, 609, doi:http://dx.doi.org/10.1007/s10846-012-9758-6

Web End =10.1007/s10846- http://dx.doi.org/10.1007/s10846-012-9758-6

Web End =012-9758-6 , 2012.

Wessln, C., Tjernstrm, M., Bromwich, D. H., de Boer, G., Ekman, A. M. L., Bai, L.-S., and Wang, S.-H.: The Arctic summer atmosphere: an evaluation of reanalyses using ASCOS data, Atmos. Chem. Phys., 14, 26052624, doi:http://dx.doi.org/10.5194/acp-14-2605-2014

Web End =10.5194/acp-14-2605- http://dx.doi.org/10.5194/acp-14-2605-2014

Web End =2014 , 2014.

Atmos. Chem. Phys., 16, 1238312396, 2016 www.atmos-chem-phys.net/16/12383/2016/