Posters

Abstract

An accurate representation of the atmospheric boundary layer (ABL) is fundamental to offshore wind energy assessments, influencing turbine inflow conditions, wake development, turbulence levels, and the performance of large wind farm clusters. As offshore wind deployment progresses toward multi-gigawatt cluster configurations, the extent to which wind farms interact with and modify the vertical structure of the atmosphere through the formation or alteration of internal boundary layers (IBLs) has emerged as a critical research question. But empirical evidence of such effects in commercial offshore environments remains limited. The BeNeWakes project, initiated by the Netherlands Enterprise Agency (RVO), provides a unique multi-sensor observational basis to address this knowledge gap. The campaign includes a ceilometer deployed within the Borssele offshore wind farm and an array of fixed, floating, and scanning lidars positioned in the downstream region of the wind farm cluster. Together, these instruments enable a comprehensive assessment of boundary-layer structure both within and downstream of a large (3.4 GW) offshore cluster. This contribution presents the methodological framework and initial analysis for investigating ABL height and potential IBL development around the Borssele cluster using the BeNeWakes dataset. The primary objective is to assess whether and under which atmospheric conditions a large offshore wind farm cluster measurably modifies the ABL and induces a downstream internal boundary layer. Continuous ABL height estimates within the wind farm are obtained from ceilometer aerosol backscatter gradients, capturing the stratification directly relevant to turbine inflow. Downstream, scanning lidar observations provide a second vertical measurement of the ABL and spatial information that can reveal the growth, adjustment, or recovery of an IBL as wakes propagate away from the cluster. Fixed and floating lidars surrounding the wind farms supply complementary vertical wind profiles and turbulence indicators. Stability is a key controlling factor for ABL depth, vertical mixing, wake recovery, and IBL development. Established retrieval techniques are applied, including gradient-based ABL detection from ceilometer data and variance- and structure-based methods for scanning lidar observations. Where appropriate, output from the HARMONIE mesoscale model is used to characterize background inflow conditions and to contextualize differences between modelled and observed boundary-layer structure. The analysis focuses on spatial differences in boundary-layer height between in-farm and downstream locations and their dependence on atmospheric stability, wind direction, and wake influence. Although the work is ongoing, the integrated measurement approach is designed to deliver the first empirical characterization of ABL and IBL evolution around a future-scale offshore wind farm cluster. The anticipated outcomes are directly relevant for improving wake modelling frameworks, fatigue load estimation, and the coupling between mesoscale and engineering-scale models in future offshore cluster developments.