Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)—The Hailuoto 2017 Campaign

Kral, Stephan T.; Reuder, Joachim; Vihma, Timo; Suomi, Irene; O’Connor, Ewan; Kouznetsov, Rostislav; Wrenger, Burkhard; Rautenberg, Alexander; Urbancic, Gabin; Jonassen, Marius O.; Båserud, Line; Maronga, Björn; Mayer, Stephanie; Lorenz, Torge; Holtslag, A.A.M.; Steeneveld, G.J.; Seidl, Andrew; Müller, Martin; Lindenberg, Christian; Langohr, Carsten; Voss, Hendrik; Bange, Jens; Hundhausen, Marie; Hilsheimer, Philipp; Schygulla, Markus

doi:10.3390/atmos9070268

Cited by 52 publications

(60 citation statements)

References 98 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A different kind of lidar system or other measurement technology is necessary in these cases. Remotely piloted aircraft (RPA) are increasingly used in stable ABL research (Kral et al, 2018) as well as for investigations in complex terrains (Wildmann et al, 2017). As such, they are a promising tool to validate and complement remote-sensing data in similar ways as shown in this study.…”

Section: Discussionmentioning

confidence: 84%

“…Recent developments in commercial scanning lidars can provide an assessment of turbulent mixing over a broader region (Smalikho et al, 2013), and many different methods have been introduced to retrieve vertical profiles of turbulence from either vertical stare measurements (O'Connor et al, 2010;Bodini et al, 2018Bodini et al, , 2019Wilczak et al, 2019), six-beam scanning scenarios (Sathe et al, 2015;Bonin et al, 2017), or velocity-azimuth display scans (VAD; Eberhard et al, 1989;Smalikho and Banakh, 2017). Krishnamurthy et al (2011) derived vertical profiles of TKE from horizontal plan-position indicator (PPI) scans (see also Wilczak et al, 2019). Various methods also exist to retrieve vertical profiles of turbulence from rangeheight indicator (RHI) scans in homogeneous, flat terrains (Smalikho et al, 2005;Bonin et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign

et al. 2019

View full text Add to dashboard Cite

Abstract. The understanding of the sources, spatial distribution and temporal variability of turbulence in the atmospheric boundary layer, and improved simulation of its forcing processes require observations in a broad range of terrain types and atmospheric conditions. In this study, we estimate turbulence kinetic energy dissipation rate ε using multiple techniques, including in situ measurements of sonic anemometers on meteorological towers, a hot-wire anemometer on a tethered lifting system and remote-sensing retrievals from a vertically staring lidar and two lidars performing range–height indicator (RHI) scans. For the retrieval of ε from the lidar RHI scans, we introduce a modification of the Doppler spectral width method. This method uses spatiotemporal averages of the variance in the line-of-sight velocity and the turbulent broadening of the Doppler backscatter spectrum. We validate this method against the observations from the other instruments, also including uncertainty estimations for each method. The synthesis of the results from all instruments enables a detailed analysis of the spatial and temporal variability in ε across a valley between two parallel ridges at the Perdigão 2017 campaign. We analyze in detail how ε varies in the night from 13 to 14 June 2017. We find that the shear zones above and below a nighttime low-level jet experience turbulence enhancements. We also show that turbulence in the valley, approximately 11 rotor diameters downstream of an operating wind turbine, is still significantly enhanced by the wind turbine wake.

show abstract

Section: Discussionmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Three flights were chosen for this study. The first flight experiment (in the following referred to as ISOBAR) was conducted during the ISOBAR campaign, which was described by Kral et al [33], presenting the numerous measurement systems of the campaign. The second flight (in the following referred to as COMPLEX) was conducted in complex terrain near Schnittlingen on the Swabian Alp in the South of Germany.…”

Section: Masc and The Methods For Deriving Mean Values And Turbulencementioning

confidence: 99%

“…The ISOBAR flight was conducted in the north of the Bothnian Bay in Finland on the 21 February 2017 between 05:01 and 05:48 UTC, which is 07:01 a.m. local time. The intensive measurement campaign was described by Kral et al [33]. MASC was operated in the dark and started on the lowest flight level of 25 m AMSL and ascended afterwards in steps of 25 m to 150 m AMSL, followed by steps of 50 m. The lower surface layer is sampled denser to capture the ground-based inversion.…”

Section: Low Turbulence In Stably Stratified Nocturnal Polar Boundarymentioning

confidence: 99%

“…Furthermore, flight experiments with large changes in the true airspeed of the UAS can be analyzed. By choosing a flight with very low turbulence in a polar, and stably stratified boundary layer (SBL) from measurements during the ISOBAR campaign [33], and a very turbulent flight from the measurements in complex terrain by [24], deviations can be analyzed and localized. A single event with large changes in airspeed, namely a transect through the wake of a wind turbine, gives insight in the impact of severe turbulence, the accuracy of the wind measurement and the importance of considering changes of the Reynolds number on the probe's tip.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Calibration Procedure and Accuracy of Wind and Turbulence Measurements with Five-Hole Probes on Fixed-Wing Unmanned Aircraft in the Atmospheric Boundary Layer and Wind Turbine Wakes

et al. 2019

Self Cite

View full text Add to dashboard Cite

For research in the atmospheric boundary layer and in the vicinity of wind turbines, the turbulent 3D wind vector can be measured from fixed-wing unmanned aerial systems (UAS) with a five-hole probe and an inertial navigation system. Since non-zero vertical wind and varying horizontal wind causes variations in the airspeed of the UAS, and since it is desirable to sample with a flexible cruising airspeed to match a broad range of operational requirements, the influence of airspeed variations on mean values and turbulence statistics is investigated. Three calibrations of the five-hole probe at three different airspeeds are applied to the data of three flight experiments. Mean values and statistical moments of second order, calculated from horizontal straight level flights are compared between flights in a stably stratified polar boundary layer and flights over complex terrain in high turbulence. Mean values are robust against airspeed variations, but the turbulent kinetic energy, variances and especially covariances, and the integral length scale are strongly influenced. Furthermore, a transect through the wake of a wind turbine and a tip vortex is analyzed, showing the instantaneous influence of the intense variations of the airspeed on the measurement of the turbulent 3D wind vector. For turbulence statistics, flux calculations, and quantitative analysis of turbine wake characteristics, an independent measurement of the true airspeed with a pitot tube and the interpolation of calibration polynomials at different Reynolds numbers of the probe's tip onto the Reynolds number during the measurement, reducing the uncertainty significantly.Atmosphere 2019, 10, 124 2 of 33 attitude, position, and velocity of the vehicle, measured by an inertial navigation system (INS), multiple coordinate transformations finally yield the wind vector. This method is widely used in manned aircraft [1,10] and on fixed-wing UAS [4][5][6][7]. The accuracy of the wind vector measurement is crucial, and the propagation of errors have many influencing factors, originating in the attitude and ground speed measurement of the aircraft, the flow angles and flow magnitude (true airspeed vector) measurement with the multi-hole probe, and also in the measurement of the thermodynamic state of the air. Extensive studies for various systems and subsystems of the wind vector measurement with manned research aircraft [11][12][13][14][15][16], including in-flight calibration procedures and uncertainty analysis [10,17], and with UAS (e.g., for the M 2 AV [7]) were performed.So far, for UAS, calibration maneuvers during flight and the influence of airspeed variations on the wind vector measurement were not addressed in terms of calibration and uncertainty analysis for the 3D wind vector measurement with multi-hole probes. Since a misalignment between the multi-hole probe's orientation and the aircraft cannot be avoided, an in-flight calibration must be applied [16]. Calibration maneuvers during flight such as the "acceleration-deceleration maneuver", the "ya...

show abstract

The stable atmospheric boundary layer over snow‐covered sea ice: Model evaluation with fine‐scale ISOBAR18 observations

Lorenz

Mayer

Kral

et al. 2022

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

A realistic representation of the stable atmospheric boundary layer in numerical weather prediction (NWP) and climate models is still a challenge. We study the evolution of a stable boundary layer over snow‐covered sea ice in Bothnian Bay during wintertime in 2018. We perform high‐resolution model experiments with the Weather Research and Forecasting model in its single‐column model configuration and its default mesoscale configuration to assess which physical processes are essential to predict near‐surface variables correctly. We evaluate our model runs against the unique observational dataset collected during ISOBAR18, which combines novel, upper‐air measurements by an uncrewed aircraft system with wind lidar, sodar, and conventional meteorological mast data. By analysing surface fluxes in the single‐column model, we demonstrate how the atmospheric cooling at the ground can be modelled more realistically than in the mesoscale set‐up. We show that surface albedo and sea‐ice thickness are essential for the surface energy balance in the model, and we demonstrate how the surface fluxes in the mesoscale downscaling with default settings are subject to strong biases. We also show that the ERA5 reanalysis is not capable of representing the observed surface meteorology in the stable atmospheric boundary layer. Our study illustrates the importance of surface albedo and sea‐ice thickness for NWP models. Though a seasonal snow albedo is already in use in many NWP settings, the routine inclusion of sea‐ice thickness, in particular, would be a great step forward for weather forecasts and regional climate simulations.

show abstract

Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)—The Hailuoto 2017 Campaign

Cited by 52 publications

References 98 publications

Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign

Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign

Calibration Procedure and Accuracy of Wind and Turbulence Measurements with Five-Hole Probes on Fixed-Wing Unmanned Aircraft in the Atmospheric Boundary Layer and Wind Turbine Wakes

The stable atmospheric boundary layer over snow‐covered sea ice: Model evaluation with fine‐scale ISOBAR18 observations

Contact Info

Product

Resources

About