High resolution aircraft measurements on three days over Wijdefjorden, Svalbard during the STABLE campaign in March 2013

The data set consists of high resolution airborne measurements that were obtained mainly over Svalbard and near the sea ice edge north of Svalbard on three days in March 2013 during the campaign "SpringTime Atmospheric Boundary Layer Experiment (STABLE). STABLE was led by the Alfred Wegener Institue (AWI) and by the Finnish Meteorological Institute (FMI). The measurements were performed using the POLAR 5 research aircraft, where all research flights of 5-6 hours duration started and ended at Longyearbyen airport. During STABLE, observations focused on the vertical structure of the lower troposphere as well as boundary layer modifications, e.g. during marine cold-air outbreaks and by convection over leads in sea ice. The data set presented here predominantly consists of measurements that were obtained over the Wijdefjorden, which is a North-South oriented fjord with a length of more than 100km in the northern part of Spitsbergen. The measurements were carried out to study the boundary layer structure in the fjord as well as for analyses of the role of the topography on the atmospheric conditions. In its southern part, the fjord was covered by land-fast sea ice until about 72.5km north of the fjord's head. In its northern part, there was open water. On all three days, the corresponding flight patterns mainly consisted of vertical aircraft profiles between 30m and 1000-1500m height during saw-tooth patterns and of low- and high-level horizontal flight legs from the marginal ice zone towards the fjord and vice versa. Each file consists of measurements from one flight leg, where in each file name we include start and end time (in UTC) and the following abbreviations: • h: low-level horizontal flight leg (below 1000m flight altitude) • H: high-level horizontal flight leg (above 1000m flight altitude) • t: ascent or descent with an altitude difference 1500m (or ascent/descent at high altitudes)

The airborne measurements were obtained by instruments installed in and at a turbulence nose-boom. The following variables are included in the data set (see Table 1): air pressure (static & dynamic) and wind obtained from a Rosemount 858 five-hole probe as well as temperature (Pt100 resistance thermometer), all with 100 Hz sampling rate, relative humidity (Vaisala HUMICAP in a Rosemount housing, 1Hz), radar altimeter (1Hz), and surface temperature (KT-19 radiation thermometer, 10Hz). Global Position System (GPS) and Inertial Navigation System (INS) were used to derive the aircraft's height, velocity, and position, and also for the calculation of the three wind components. Besides the GPS-based height, we provide also the more reliable pressure-based altitude. All variables are provided with 100Hz in each file. Air pressure and air temperature data were corrected as described in detail by Michaelis et al. (2022). Relative humidity data were corrected for adiabatic heating, which occurs due to compression of the air entering the Vaisala HUMICAP sensor situated in the Rosemount housing (see Smit et al., 2013). More detailed description on the measurements including the instruments' accuracies and the quality-processing of the measurements is provided by Suomi et al. (2023), for which this data set is a supplement, as well as by Michaelis et al. (2021, 2022) and Tetzlaff et al. (2014, 2015). In the latter four publications, data from the STABLE campaign is used as well but mainly from flight days other than in this data set. The corresponding data are available at Lüpkes et al. (2021a, b). Master tracks for all STABLE research flights can be found at Steinhage (2015). Finally, Hartmann et al. (2018) provide more details on the quality of such airborne measurements in general including instrument calibrations and the determination of related measurement accuracies. Note that for the wind measurements the full accuracy is only achieved and the estimates on uncertainty are only valid for straight level flight sections (Hartmann et al., 2018).