## 8 Conclusions and Outlook
Parameterizations applied in NWP models can take these observed factors into account [45; 53; 110; 111]. However, based on in situ measurement techniques, it has not been possible to compare the surface-based wind gust forecasting methods with the so-called profile method by [PERSON] (2001) [112], which has been applied in many NWP studies [113; 114; 115; 116; 117], but never assessed based on observations alone. The method assumes that wind gusts observed near the surface are caused by large turbulent eddies bringing high-momentum air aloft down to the surface. An observational study to investigate the validity of this theoretical method would require simultaneous profiles of the mean wind speed, TKE and buoyancy (temperature, humidity). In the future, Doppler lidar technology may provide a possibility for direct evaluation of the Brasseur method with observations, provided that a temperature profile is available simultaneously, for example from a tethered balloon or from UAS (e.g., [118]). In the future, the comparison of gusts from a lidar with model results from Large Eddy Simulations (LES) can potentially provide a possibility to better understand the mechanisms by which the gusts are generated in the atmosphere, and thereby, also new parameterizations for NWP models can potentially be developed to improve wind gust forecasting. The theoretical approach to estimate wind gusts, the so-called Rice theory, has many practical applications. It can be used to convert peak and gust factors when observations are made with different gust time scales \(t_{g}\) and \(T\)[46]. It can also be applied to obtain improved wind gust measurements from a Doppler lidar, which has a limited sampling frequency and the measurements include spatial averaging. In the future, the next step will be to test the applicability of the method to other lidar types and scanning sequences, such as conical scans with many more beams. An open question is, for example, what is a sufficient Doppler lidar measurement frequency for obtaining reliable wind gust estimates? Furthermore, it is important to understand how the horizontal heterogeneity affects the measurements. To understand that, measurements from various environments are needed. Research aircraft can provide information from remote locations, where deployment of other type of wind instrumentation is challenging or even impossible. However, research aircraft are mostly applied in specific campaigns, and even in the future, we cannot expect a high spatial and temporal coverage of observations. However, with the rapidly developing UAS technology, there are better perspectives for extensive gust observations applying UASs. A new application of the peak factor theory is the comparison of temporal and spatial scales used to define wind gusts when measurements are available both from a fixed position (meteorological mast) and a moving platform (research aircraft). The method compares directly the statistical properties of the time series without a need for assuming an advection velocity, which is a prerequisite of the well-known [PERSON]'s hypothesis of frozen turbulence [90]. In fact, the peak factor method can be applied when [PERSON]'s hypothesis is not valid, for example when the mean (advection) velocity is zero. The method could thus provide new insight to understand turbulence in low-wind conditions typical for a stable atmospheric boundary layer. An open question is, for example, could the peak factor method provide new information on how the turbulent time and length scales compare in non-stationary wind speed conditions in different environments and stability conditions, provided that the time series from a fixed point represents the same environment (and period) as the data in terms of distance. Besides being based on measurements, these types of tests could also be based on LES results or on measurements from a wind tunnel where the degree of nonstationarity in the flow field can be controlled.