1. Talents of tomorrow: Wind meteorology

2. Mean wind speed profiles in conditionally neutral boundary layer: a new similarity theory that predicts wind speeds up to 80% of the atmospheric boundary layer height
Pitch by Roberto Alessio Cersosimo, MSc, DTU Wind Energy Errors within 5% in the prediction of the mean speed profile are obtained for neutral inversion capped ABL (conditionally neutral) for the 80 % of the ABL height. A new similarity theory for the mean wind speed profile is obtained and tested with data from 18 LES NCAR simulations. This results in a new equation that reduces the prediction error of wind profile at turbine sites from 10% - 15% of the log-law to 1% - 5%.

3. Extreme variance vs. turbulence: What can the IEC cover?
Pitch by Ásta Hannesdóttir, PhD student, DTU Wind Energy Here we demonstrate the effect of extreme variance events on wind turbine loads. From ten years of data, we analyze periods with variance exceeding the IEC extreme turbulence prescription. The variance is mainly due to coherent gust-like events, and not turbulence, and these events additionally incur extreme shear. Loads from simulations of these events are compared with the extreme turbulence design load case of the IEC standard, with the latter generally giving higher loads.

4. Analysis of Wake Detection using LIDARs
Pitch by Sayantan Chattopadhyay, MSc, DTU Wind Energy The study presents a quantitative estimation of the wake characteristics using LIDAR measurements. The methodology exhibits an unique relationship between the wake turbulence, as observed at a downstream wind turbine by a nacelle-mounted 4-beam LIDAR through the measurement of line of sight velocity and doppler spectrum, and correspondingly relates it to the velocity deficit applicable to both full wake and partial wake condition. The study finds its relevance in a simple, quick and precise determination of the wake velocity deficit which can be used for performance estimation, yaw correction and wind farm control.

5. Satellite SAR measurements for Offshore Wind Farm Development
Pitch by Tobias Ahsbahs, PhD student, DTU Wind Energy SAR satellites can assist in (pre)feasibility phases of offshore wind farm planning by offering a high resolution glimpse into the large scale wind condition– global and for free! This complements reanalysis data and local measurements with an independent measure of wind speed. The challenges are to validate and estimate uncertainties, create acceptance from the developers, and demonstrate applications that can generate value. We can show the potential of large SAR archives at the location of the Anholt wind farm for wake detection and coastal wind speed gradients.

6. Modeling of rough weather over the North Sea
Pitch by Marc Imberger, MSc, DTU Wind Energy Within the scope of wind forecasting for offshore wind energy applications, special care has to be taken of the prediction of rough weather events, since inaccurate prediction is connected to major financial losses due to large day-ahead wind power forecast errors, unforeseen shut-downs of wind farms or rescheduling of onsite O&M activities. Using the Weather Research and Forecast (WRF) software environment, a systematic way to determine suitable temporal parameters and grid specific parameters (domain size, location and resolution) for the simulation of rough weather events is developed and presented considering an exemplary area of interest over the North Sea.