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| DC Element | Wert | Sprache |
|---|---|---|
| dc.contributor.author | Watson, Warren | - |
| dc.contributor.author | Wolken-Möhlmann, Gerrit | - |
| dc.contributor.author | Gottschall, Julia | - |
| dc.date.accessioned | 2025-10-22T11:40:11Z | - |
| dc.date.available | 2025-10-22T11:40:11Z | - |
| dc.date.issued | 2025-04-03 | - |
| dc.identifier.uri | https://fordatis.fraunhofer.de/handle/fordatis/457 | - |
| dc.identifier.uri | http://dx.doi.org/10.24406/fordatis/413 | - |
| dc.description.abstract | These datasets accompany the WES preprint: Watson, Wolken-Möhlmann & Gottschall (2025), Evaluating the Impact of Motion Compensation on Turbulence Intensity Measurements from Continuous-Wave and Pulsed Floating Lidars (DOI: 10.5194/wes-2025-45). They cover the FINO3 campaign (German North Sea; 10-min aggregation; wind sector 220°–300°) and compare raw vs motion-compensated TI from a floating ZX300M (cw) and a floating Windcube V2.1 (pulsed) together with a fixed ZX300M reference at 101 m, against Met Mast Cup TI from 101 m. | en |
| dc.description.abstract | File 1 — Binned statistics (public) Title: Binned TI statistics at 101 m (raw vs motion-compensated) with fixed lidar reference What’s inside: Wind-speed–binned (0.5 m s⁻¹) TI metrics from the analysis period 2024-04-06 to 2024-07-09: mean, min, max, std, Q90, count, MBE/RMBE, RMSE/RRMSE, representative TI error. Instruments: Floating ZX300M (cw), floating Windcube V2.1 (pulsed), fixed ZX300M. Columns: WLBZ6_Raw, WLBZ6_Compensated_TI, WLBW4_Raw, WLBW4_Compensated_TI, FINO3_Fixed_Lidar. Processing: Deterministic motion compensation for LoS tilt/rotation and platform surge/sway/heave/tilt. | en |
| dc.description.abstract | File 2 - 10-minute time series data Title: TI time series at 101 m (raw vs motion-compensated) with fixed lidar reference What’s inside: Underlying 10-min TI used for File 1. Instruments: Floating ZX300M (cw), floating Windcube V2.1 (pulsed), fixed ZX300M. Columns: WLBZ6_Raw_TI_101_m, WLBZ6_Compensated_TI_101_m, WLBW4_Raw_TI_101_m, WLBW4_Compensated_TI_101_m, FINO3_Fixed_Lidar_TI_101_m. Processing: Deterministic motion compensation for LoS tilt/rotation and platform surge/sway/heave/tilt. Access: Repository record and metadata are public and citable. Files are temporarily restricted due to ongoing commercial use in a third-party Stage-3 maturity certification. Non-commercial research access may be granted on request under a mutual Data Use Agreement (DUA). Terms will be reviewed after certification completion and, if certification is not granted, annually thereafter. How to request: Email the corresponding author (warren.watson@iwes.fraunhofer.de) with institution, non-commercial purpose, intended analyses/outputs, and requested period. | en |
| dc.language.iso | en | en |
| dc.relation.ispartof | 10.5194/wes-2025-45 | - |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | en |
| dc.subject | Floating-Lidar | en |
| dc.subject | Lidar | en |
| dc.subject | Turbulence intensity | en |
| dc.subject | Remote sensing | en |
| dc.subject | Motion Compensation | en |
| dc.title | Evaluating the Impact of Motion Compensation on Turbulence Intensity Measurements from Continuous-Wave and Pulsed Floating Lidars | en |
| dc.title.alternative | Dataset | en |
| dc.type | Tabular Data | en |
| dc.description.technicalinformation | Python-specific binary format (.pkl) file (written using Python 3.11.9). | en |
| fordatis.group | Energietechnologien und Klimaschutz | en |
| fordatis.institute | IWES Fraunhofer-Institut für Windenergiesysteme | en |
| fordatis.rawdata | false | en |
| fordatis.date.start | 2024-04-06 | - |
| fordatis.date.end | 2024-07-09 | - |
| fordatis.embargo.contactInfo | warren.watson@iwes.fraunhofer.de | en |
| Enthalten in den Sammlungen: | Fraunhofer-Institut für IWES | |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2025-10-07_Statistics.pkl | Binned TI statistics | 21,94 kB | Python Binary Pickle (.pkl) | Öffnen/Download |
| 2025-10-07_Timeseries.pkl Bis 2027-10-14 | 10-minute Lidar TI timeseries data | 145,61 kB | Python Binary Pickle (.pkl) | Öffnen/Download Eine Dokumentkopie anfordern |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons