The five main influencing factors for lidar errors in complex terrain

Abstract ε ε c ε s φ ε H L H/L and z/L, with z  being the measurement height, are identified as the main scaling factors for the lidar error. Three flow models of different complexity are used to estimate the lidar errors. The outcome of the study provides various findings that enable an assessment of the applicability of these flow models. The study clearly shows that orographic complexity, roughness and forest characteristics, and atmospheric stability have a significant influence on lidar error estimation. Based on the error separation approach it furthermore allows for an in-depth analysis of the influence of reduced half-cone opening angles, explaining contradiction in the previously available literature. The choice and parameterization of flow models and the design of methods for lidar error estimation are found to be essential to achieve accurate results. The use of a Reynolds-averaged Navier–Stokes (RANS) computational fluid dynamics (CFD) model in conjunction with an appropriate forest model is highly recommended for lidar error estimations in complex terrain since forest (and roughness) tends to reduce the lidar error. If atmospheric stability variation at a measurement site plays a vital role, it should also be considered in the modelling. When planning a measurement campaign, an accurate estimation of the predicted lidar error should be carried out in advance to choose a reasonable measurement location. This will decrease measurement uncertainties and maximize the value of the measurement data.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: The five main influencing factors for lidar errors in complex terrain ; volume:7 ; number:1 ; year:2022 ; pages:413-431 ; extent:19 ; Wind energy science ; 7, Heft 1 (2022), 413-431 (gesamt 19)

Contributors, Places and Time

• Creator: Klaas-Witt, Tobias ; Emeis, Stefan

Further information

• DOI: 10.5194/wes-7-413-2022
• URN: urn:nbn:de:101:1-2022030304151546765641
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:23 AM CEST