Comparison of wind climatology from dynamical downscaling with
other methodologies. E. Avolio 1,2, S. Federico 1, Claudia
Calidonna 1, C.Transerici 1, Birgitte Furevik 3 Anna M. Sempreviva
1,4, 1. Institute of Atmospheric Sciences and Climate, ISAC-CNR,
Lamezia Terme, Italy 2. CRATI s.c.r.l., Lamezia Terme, Italy 3.
Norwegian Meteorological office, met.no, Bergen, Norway 4. DTU,
Wind Division, Risoe Campus, Roskilde, Denmark Lamezia Terme
OFFSHORE WIND RESOURCE ASSESSMENT IN THE CENTRAL MEDITERRANEAN
AREA.
Slide 2
Motivation Wind resources assessment methodologies Dynamical
downscaling Results and comparisons Concluding remarks Outline of
the presentation
Slide 3
Also Coastal waters are deep with environmental constraints.
There is strong need of reliable data: Buoys are sparse and with
missing data Vertical wind profiles are missing Coastal
methodologies tested in the North Sea can not be applied due to
Stability effects and Sea-Breeze recirculation FP7 EU ORECCA
PROJECT Offshore Renewable Energy Conversion Coordination Action
www.orecca.euwww.orecca.eu BUT THERE ARE OPPORTUNITIES:
Technological progress in buoyant deep offshore wind farms Less
harsh meteorological conditions Motivations : Challenges in the
Mediterranean QUESTION: How the Mediterranean wind potential
compares to the North Sea? ANSWER: The Mediterranean is less windy
than the North Sea.
Slide 4
Are at least 5 year local wind data available? To design a wind
farm the local wind climatology is needed YES NO So far so good
What shall we do? Develop methodologies to generate data
Motivations Plan local measurement For N years Cost money and
TIME!!
Slide 5
1. STATISTICAL : Correlations with coastal data 2. DIAGNOSTIC
MODELS: WAsP 3. DATABASES FROM ANALYSIS O RE-ANALYSIS PROGRAMMES
ECMWF (EUROPEAN) i.e. ERA - 40 NCEP-NCAR (USA) 50 years 4.
SPACE-BORN Observations 5. DYNAMICAL DOWNSCALING FROM GENERAL
CIRCULATION MODELS Methodologies
Slide 6
Advantages: Spatial and temporal coverage Spatial resolution:
10 - 2 km Weak points: Super-computer and skilled staff needed!
Uncertainties under evaluation, need data Modeling: Dynamical
downscaling THE RAMS MODEL: 30 years (1975-2004)
Slide 7
Annual average wind speed: 80 mAnnual average wind speed: 150 m
Meand Wind Climatology 80m 150m
Slide 8
MODEL: Intra - annual Cycle
Slide 9
IA=IA= year Total Period North GRID South GRID MODEL: Inter -
annual Indices 12 %
Slide 10
Availability: 10 Years, 01/08/1999 - 31/10/2009 Two passes per
day Wind speed U retrieved from radar backscatter at surface and
extrapolated to 10 m using a neutral log profile Space-born remote
sensing: QuikSCAT SeaWinds microwave radar onboard QuikSCAT:
Slide 11
11 QuikScat mean wind speed (m s 1 ) (20002007) and mean wind
direction. The wind speeds are reduced using the correction of the
ECMWF for winds above 19 m s 1 B.R. Furevik, A. M. Sempreviva, L.
Cavaleri., J.M. Lefvre, C. Transerici, Eight years of wind
measurements from scatterometer for wind resource mapping in the
Mediterranean Sea, Wind Energ. (2011), DOI: 10.1002/we QuikSCAT:
Offshore Wind Map
