Determination of the Turbulent Temperature-Humidity Correlation from Scintillometric Measurements

We report on the investigation and successful application of the bichromatic correlation of optical and microwave signals for determining the area-averaged correlation of temperature-humidity fluctuations. The additional technical effort is marginal compared to the common ‘two-wavelength method', which has (in contrast) the restriction that only two of the three relevant meteorological structure parameters can be deduced. Therefore, in the past, it was often assumed that the turbulent humidity and temperature fluctuations are perfectly positively or negatively correlated. However, as shown in this study, over non-homogeneous terrain when the flow conditions are not ideal, this assumption is questionable. The measurements were analysed statistically, and were compared to in situ measurements of the Bowen ratio Bo and the correlation of temperature-humidity fluctuations using eddy-covariance techniques. The latter is in good agreement to that derived by scintillometry. We found that the correlation is not ±1 but as low as −0.6 for Bo smaller than −2, and up to 0.8 for Bo larger than

Scan strategies for wind profiling with Doppler lidar – an large-eddy simulation (LES)-based evaluation

Doppler-lidar scan techniques for wind profiling rely on the assumption of a horizontally homogeneous wind field and stationarity for the duration of the scan. As this condition is mostly violated in reality, detailed knowledge of the resulting measurement error is required. The objective of this study is to quantify and compare the expected error associated with Doppler-lidar wind profiling for different scan strategies and meteorological conditions by performing virtual Doppler-lidar measurements implemented in a large-eddy simulation (LES) model. Various factors influencing the lidar retrieval error are analyzed through comparison of the wind measured by the virtual lidar with the “true” value generated by the LES. These factors include averaging interval length, zenith angle configuration, scan technique and instrument orientation (cardinal direction). For the first time, ensemble simulations are used to determine the statistically expected uncertainty of the lidar error. The analysis reveals a root-mean-square deviation (RMSD) of less than 1 m s−1 for 10 min averages of wind speed measurements in a moderately convective boundary layer, while RMSD exceeds 2 m s−1 in strongly convective conditions. Unlike instrument orientation with respect to the main flow and scanning scheme, the zenith angle configuration proved to have significant effect on the retrieval error. Horizontal wind speed error is reduced when a larger zenith angle configuration is used but is increased for measurements of vertical wind. Furthermore, we find that extending the averaging interval length of lidar measurements reduces the error. In addition, a longer duration of a full scan cycle and hence a smaller number of scans per averaging interval increases the error. Results suggest that the scan strategy has a measurable impact on the lidar retrieval error and that instrument configuration should be chosen depending on the quantity of interest and the flow conditions in which the measurement is performed

On the Discrepancy in Simultaneous Observations of the Structure Parameter of Temperature Using Scintillometers and Unmanned Aircraft

We elaborate on the preliminary results presented in Beyrich et al. (in Boundary-Layer Meteorol 144:83–112, 2012), who compared the structure parameter of temperature (C2T) obtained with the unmanned meteorological mini aerial vehicle ( M 2 AV ) versus C2T obtained with two large-aperture scintillometers (LASs) for a limited dataset from one single experiment (LITFASS-2009). They found that C2T obtained from the M 2 AV data is significantly larger than that obtained from the LAS data. We investigate if similar differences can be found for the flights on the other six days during LITFASS-2009 and LITFASS-2010, and whether these differences can be reduced or explained through a more elaborate processing of both the LAS data and the M 2 AV data. This processing includes different corrections and measures to reduce the differences between the spatial and temporal averaging of the datasets. We conclude that the differences reported in Beyrich et al. can be found for other days as well. For the LAS-derived values the additional processing steps that have the largest effect are the saturation correction and the humidity correction. For the M 2 AV -derived values the most important step is the application of the scintillometer path-weighting function. Using the true air speed of the M 2 AV to convert from a temporal to a spatial structure function rather than the ground speed (as in Beyrich et al.) does not change the mean discrepancy, but it does affect C2T values for individual flights. To investigate whether C2T derived from the M 2 AV data depends on the fact that the underlying temperature dataset combines spatial and temporal sampling, we used large-eddy simulation data to analyze C2T from virtual flights with different mean ground speeds. This analysis shows that C2T does only slightly depends on the true air speed when averaged over many flights.DFG/BA1988/9-1DFG/BE2044/3-1DFG/RA617/20-1Dutch Science Foundation/DN76-274DFG/BE2044/3-3DFG/RA617/20-

Airborne measurements of turbulent fluxes during LITFASS-98: Comparison with ground measurements and remote sensing in a case study

Simultaneous flight measurements with the research aircraft Do 128 and the helicopter-borne turbulence probe Helipod were performed on 18 June 1998 during the LITFASS-98 field experiment. The area-averaged turbulent vertical fluxes of momentum, sensible, and latent heat were determined on a 15 km x 15 km and a 10 km x 10 km flight pattern, respectively. The flights were carried out over heterogeneous terrain at different altitudes within a moderately convective boundary layer with Cumulus clouds. Co-spectra-analysis demonstrated that the small scale turbulent transport was completely sampled, while the comparatively small flight patterns were possibly of critical size regarding the large-scale turbulence. The phygoide of the airplane was identified as a significant peak in some cospectra. The turbulent fluxes of momentum and sensible heat at 80m above the ground showed systematic dependence on the location of the flight legs above the heterogeneous terrain. This was not observed for the latent heat flux, probably due to the vertical distribution of humidity in the boundary layer. Statistical error analysis of the fluxes F showed that the systematic statistical error was one order of magnitude smaller than the standard deviation . The difference between area-averaged fluxes derived from simultaneous Helipod and Do 128 measurements was much smaller than the statistical error, indicating that the systematic statistical error was possibly over-estimated by the usual method. In the upper half of the boundary layer the airborne-measured sensible heat flux agreed well with windprofiler/RASS data. A linear fit was the best approximation for the height dependence of all three fluxes. The linear extrapolations of the latent and sensible heat fluxes to the ground were in good agreement with tower, scintillometer, and averaged groundstation measurements on various surface types. Systematic discrepancies between airborne and ground-based measurements were not found

A New Method for the Determination of Area-Averaged Turbulent Surface Fluxes from Low-Level Flights Using Inverse Models

The low-level flight method (LLF) has been combined with linear inverse models (IM) resulting in an LLF+IM method for the determination of area-averaged turbulent surface fluxes. With this combination, the vertical divergences of the turbulent latent and sensible heat fluxes were calculated from horizontal flights. The statistical errors of the derived turbulent surface fluxes were significantly reduced. The LLF+IM method was tested both in numerical and field experiments. Large-eddy simulations (LES) were performed to compare ‘true’ flux profiles with ‘measurements’ of simulated flights in an idealised convective boundary layer. Small differences between the ‘true’ and the ‘measured’ fluxes were found, but the vertical flux divergences were correctly calculated by the LLF+IM method. The LLF+IM method was then applied to data collected during two flights with the Helipod, a turbulence probe carried by a helicopter, and with the research aircraft Do128 in the LITFASS-98 field campaign. The derived surface fluxes were compared with results from eddy-covariance surface stations and with large-aperture scintillometer data. The comparison showed that the LLF+IM method worked well for the sensible heat flux at 77 and 200m flight levels, and also for the latent heat flux at the lowest level. The model quality control indicated failures for the latent heat flux at the 200m level (and higher), which were probably due to large moisture fluctuations that could not be modelled using linear assumptions. Finally the LLF+IM method was applied to more than twenty low-level flights from the LITFASS-2003 experiment. Comparison with aggregated surface flux data revealed good agreement for the sensible heat flux but larger discrepancies and a higher statistical uncertainty for the latent heat flux

Turbulent fluxes from Helipod flights above quasi-homogeneous patches within the LITFASS area

Turbulent fluxes of sensible and latent heat were measured with the helicopter- borne turbulence probe Helipod over a heterogeneous landscape around the Meteorological Observatory Lindenberg during the STINHO-2 and LITFASS-2003 field experiments. Besides the determination of area-averaged heat fluxes, the analysis focused on different aspects of the response of the turbulent structure of the convective boundary layer (CBL) on the surface heterogeneity. A special flight pattern was designed to study flux profiles both over quasi-homogeneous sub-areas of the study region (representing the major land use types—forest, farmland, water) and over a typical mixture of the different surfaces. Significant differences were found between the heat fluxes over the individual surfaces along flight legs at about 80m above ground level, in agreement with large-aperture scintillometer measurements. This flux separation was still present during some flights at levels near the middle of the CBL. Different scales for the blending height and horizontal heterogeneity were calculated, but none of them could be identified as a reliable indicator of the mixing state of the lower CBL. With the exception of the flights over water, the latent heat flux measurements generally showed a larger statistical error when compared with the sensible heat flux. Correlation coefficients and integral length scales were used to characterise the interplay between the vertical transport of sensible and latent heat, which was found to vary between ‘fairly correlated’ and ‘decoupled’, also depending on the soil moisture conditions

Studying the Boundary Layer Late Afternoon nd Sunset Turbulence (BLLAST)

At the end of the afternoon, when the surface heat fluxes start to sharply decrease, the CBL turns from a convective well-mixed layer to an intermittently turbulent residual layer overlying a stably-stratified boundary layer. This transition raises several observational and modeling issues. Even the definition of the boundary layer during this period is fuzzy, since there is no consensus on what criteria to use and no simple scaling laws to apply. Yet it plays an important role in such diverse atmospheric phenomena as transport and diffusion of trace constituents or wind energy production. This phase of the diurnal cycle remains largely unexplored, partly due to the difficulty of measuring weak and intermittent turbulence, anisotropy, horizontal heterogeneity, and rapid time changes. The Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) project is gathering about thirty research scientists from the European Union and the United States to work on this issue. A field campaign (BLLAST-FE) is planned for spring or summer 2011 in Europe. BLLAST will utilize these observations, as well as previous datasets, large-eddy and direct numerical simulations, and mesoscale modeling to better understand the processes, suggest new parameterizations, and evaluate forecast models during this transitional period. We will present the issues raised by the late afternoon transition and our strategy to study it.Peer ReviewedPostprint (published version

Distributed wind measurements with multiple quadrotor unmanned aerial vehicles in the atmospheric boundary layer

In this study, a fleet of quadrotor unmanned aerial vehicles (UAVs) is presented as a system to measure the spatial distribution of atmospheric boundary layer flow. The big advantage of this approach is that multiple and flexible measurement points in space can be sampled synchronously. The algorithm to obtain horizontal wind speed and direction is designed for hovering flight phases and is based on the principle of aerodynamic drag and the related quadrotor dynamics. During the FESST@MOL campaign at the boundary layer field site (Grenzschichtmessfeld, GM) Falkenberg of the Lindenberg Meteorological Observatory - Richard Assmann Observatory (MOL-RAO), 76 calibration and validation flights were performed. The 99 m tower equipped with cup and sonic anemometers at the site is used as the reference for the calibration of the wind measurements. The validation with an independent dataset against the tower anemometers reveals that an average accuracy of <0.3 m/s for the wind speed and <8° for the wind direction was achieved. Furthermore, we compare the spatial distribution of wind measurements with the fleet of quadrotors to the tower vertical profiles and Doppler wind lidar scans. We show that the observed shear in the vertical profiles matches well with the tower and the fluctuations on short timescales agree between the systems. Flow structures that appear in the time series of a line-of-sight measurement and a two-dimensional vertical scan of the lidar can be observed with the fleet of quadrotors and are even sampled with a higher resolution than the deployed lidar can provide