Coastal wind from SAR and NWP model for offshore wind power production

• Main Author: Abrahamsen, Malin
• Format: Master Thesis
• Language: English
• Published: University of Tromsø 2013
• Subjects: VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering; visualisering; signalbehandling; bildeanalyse: 429; VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation; visualization; signal processing; image processing: 429; Offshore wind power production; SAR; Earth observation; EOM-3901; Asar; Fakken; Norway; Vannøya; Northern Norway
• Online Access: https://hdl.handle.net/10037/5431

With rising energy demands as well as technological advances, offshore wind power production is becoming an attractive option. However, it is necessary to estimate the wind climate at potential sites in order to achieve optimal siting, and numerical weather prediction models as well as satellite SAR can been used in a first evaluation for this purpose. This study looked the how ASAR and model wind maps compare in terms of estimating coastal wind climates, and whether they can identify local features important to wind farm siting. ASAR images covering Vannøya in northern Norway have been acquired for a period of just over a year, and converted to wind maps using the CMOD-IFR2 algorithm. UM.4km wind model data from MET, covering the same area and time period, have been interpolated to match the resolution of the ASAR wind maps of 450 m. In-situ observations from the on-shore Fakken wind farm have been compared with model predictions for the same location. To get a better idea of how the model and ASAR wind estimates fare in a coastal region, both descriptive statistics and an in-depth analysis of individual ASAR scenes have been made. The in-depth analysis of individual scenes revealed several instances of wind features such as atmospheric gravity waves and wind shadowing which were present in the ASAR wind maps but absent or poorly defined in the model wind maps. Identifying the extent and location of features connected to turbulence or wind shadows can be essential to siting, and it was possible to identify several locations where special care should be taken in estimating the wind climate.