مورد إلكتروني

Offshore Doppler Wind LiDAR assessment of atmospheric stability

التفاصيل البيبلوغرافية
العنوان: Offshore Doppler Wind LiDAR assessment of atmospheric stability
بيانات النشر: Institute of Electrical and Electronics Engineers (IEEE) 2020
تفاصيل مُضافة: Universitat Politècnica de Catalunya. Doctorat en Teoria del Senyal i Comunicacions
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
Universitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
Silva, Marcos Paulo Araujo da
Salcedo Bosch, Andreu
Gutiérrez Antuñano, Miguel Ángel
Rocadenbosch Burillo, Francisco
نوع الوثيقة: Electronic Resource
مستخلص: This paper tackles atmospheric stability typing using a Zephyr™ 300 offshore Doppler Wind Lidar in the context of its progressive acceptance in the offshore wind-energy industry. The lidar-retrieved wind-shear exponent, which is used as a proxy atmospheric stability, is compared against the wind-shear exponent and the potential temperature gradient both retrieved from reference metmast. A total sample of 4319 measurements is analysed from IJmuiden's test campaign, in the North Sea, from April 1 st to 30 th, 2015. Concerning stability typing, both lidar- and metmast-derived wind-shear indicators overestimated by 4% and 14%, respectively, the most frequent atmospheric stability case, which was convective (48% of the cases) according to the potential temperature reference indicator.
This work was supported via Spanish Government–European Regional Development Funds project PGC2018-094132-B-I00 and EU H2020 ACTRIS-2 (GA 654109). The European Institute of Innovation and Technology (EIT), KIC InnoEnergy project NEPTUNE (Offshore Metocean Data Measuring Equipment and Wind, Wave and Current Analysis and Forecasting Software, call FP7) supported measurements campaigns. CommSensLab is a María-de-Maeztu Unit of Excellence funded by the Agencia Estatal de Investigacion (Spanish National Science Foundation) that also funded the project MDM-2016-0600-18-1. Spanish NSF (Ministry of Science, Innovation and Universities; Ministerio de Ciencia, Innovacion y Universidades) for doctoral grant PRE2018-086054 hold by Ph.D. student Araujo da Silva M.P. at CommSensLab-UPC.
Peer Reviewed
Postprint (author's final draft)
مصطلحات الفهرس: Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció, Optical radar, Wind power, Wind lidar, Wind shear, Atmospheric stability, Offshore wind energy, Radar òptic, Energia eòlica, Conference report
URL: http://hdl.handle.net/2117/340420Test
https://ieeexplore.ieee.org/document/9324044Test
https://ieeexplore.ieee.org/document/9324044Test
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-094132-B-I00/ES/TELEDETECCION ATMOSFERICA MEDIANTE SENSORES COOPERATIVOS LIDAR, RADAR Y PASIVOS: APLICACIONES SOBRE TIERRA Y MAR PARA LA OBSERVACION ATMOSFERICA Y ENERGIA EOLICA OFF-SHORE
info:eu-repo/grantAgreement/EC/H2020/654109/EU/Aerosols, Clouds, and Trace gases Research InfraStructure/ACTRIS-2
info:eu-repo/grantAgreement/MINECO/1PE/MDM-2016-0600
info:eu-repo/grantAgreement/CE/Offshore Metocean Data Measuring Equipment and Wind, Wave and Current Analysis and Forecasting Software/NEPTUNE.EIT/KIC InnoEnergy/FPA/1
الإتاحة: Open access content. Open access content
Open Access
ملاحظة: 4 p.
application/pdf
English
أرقام أخرى: HGF oai:upcommons.upc.edu:2117/340420
Araujo, M. [et al.]. Offshore Doppler Wind LiDAR assessment of atmospheric stability. A: IEEE International Geoscience and Remote Sensing Symposium. "2020 IEEE International Geoscience & Remote Sensing Symposium: September 26–October 2, 2020, virtual: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2020, p. 6081-6084. ISBN 978-1-7281-6374-1. DOI 10.1109/IGARSS39084.2020.9324044.
978-1-7281-6374-1
10.1109/IGARSS39084.2020.9324044
1247082618
المصدر المساهم: UNIV POLITECNICA DE CATALUNYA
From OAIster®, provided by the OCLC Cooperative.
رقم الانضمام: edsoai.on1247082618
قاعدة البيانات: OAIster