The aerodynamic roughness length of forested areas, forest areas forest IBL and how IBL and how to to proceed with canopy flow research… Ebba Dellwik, Jakob Mann, Ferhat Bingöl, Andrey Sogachev, Andrey Sogachev, Ole Rathmann Scope • Definition Definition and issues and issues concerning the the estimation of surface roughness from measured data • ”WAsP in the forest” • New internal boundary layer experiment in Sorø • Analysis of WAsP, Weng and SCADIS results • Future canopy flow research Aerodynamic surface roughness is a property of the surface/surface cover that g flat surfaces can be assessed at homogeneous through the wind profile in the inertial sublayer. sublayer Aerodynamic surface roughness, the inertial sublayer and the roughness sublayer φ m = ∂u κ ≡1 ∂ ln( z − d ) u* ⇒ u= u* κ ln (z − d ) z0 1 φ There is a risk of underestimating z0 when using data from measurements, which data from measurements which are taken too close to the canopy. log‐z scalle m < But close But close to the forest to the forest due to the roughness sublayer influence Aerodynamic surface roughness, the inertial sublayer and the internal boundary layer φ • Forests are characterized by large scale inhomogeneities (clearings and lakes). ∂u κ >1 = • At a smooth At th to rough transition t ht iti ∂ ln( z − d ) u m * There is a risk of underestimating z0 when using measurement data taken too far from the canopy. Example from tall mast in large forest near Uppsala 0 z = z−d ⎛ uκ ⎞ ⎟⎟ p⎜⎜ exp ⎝ u* ⎠ d = 22m Thanks to Meelis Mölder and Anders Lindroth at Lund University for data The aerodynamic surface roughness The aerodynamic … is a ”constant”, but may depend on ‐ wind speed (Bosveld 1997; Dellwik and Jensen, 2005) / leaf area index (i.e. Nakai (i.e. Nakai et al. 2008) et al. 2008) ‐ seasonality / leaf ‐ stability (Harman and Finnigan, 2007) ”WAsP WAsP in the forest in the forest” • The aerodynamic roughness was changed from 0.4m to more realistic values (0.7m‐2m). • A drag partitioning model using the frontal area index for estimation of z of z0 and d, was and d was tested and found and found to work to work well for for WAsP modelling. • However: limited measurement height in small forests. Wind Energ. 2006; 9:211–218 Conclusion 1 • Th The aerodyanmic d i roughness h i diffi lt to estimate is difficult t ti t using i measurements for forested areas. Alternative 1: Use models to estimate the roughness and displacement height (see i.e. Crockford and Hui, 2007, “Validation of Wind Resource Assessment Methodologies g Including the Effects of Forests”). Alternative 2: Measure Alternative 2: Measure within canopy leaf area / wind / wind speed profiles speed profiles for estimation of the drag profile. Alternative 3: Estimate simplified f leaff area within the canopy from f models. Forest and wind profiles‐ new measurements Internal boundary layer height hi where u* = u*1 Constant flux layer height he Roughness sublayer height h* d u *1 u *2 u* m φ = ∂u κ ∂ ln( z − d ) u* Internal boundary layer height hi Constant flux layer height he Roughness sublayer height h* The measurements The measurements – overspeed corrected The measurements – u The measurements u* 240° 240 270° The models The models • SCADIS (distributed drag force) ‐ dynamic IBL ‐ dynamic ABL ( g model)) • WAsP (roughness ‐ parameterized IBL is slightly stable ‐ upwind/background profile is slightly • WEng (roughness model) ‐ dynamic IBL ‐ upwind/background profile is neutral IBL in WAsP IBL in WAsP log(z‐d) g( ) hi hi /3 he z0, forest z0, upstream U Model settings Model settings • WAsP and WENG: d z0,forest = 1.8m, z0,upstream = 0.1m, dforest = 21m • SCADIS: z0,upstream = 0.1m , LAIforest is 5m2/m2 WAsP results WEng and WAsP WAsP and Weng and SCADIS Conclusions 2 • The The mean mean wind profile in the IBL was in the IBL was near near‐ logarithmic with regards to z0 ≈2m and d = 21m up to 100m for a 500m long fetch! 100m for a 500m long fetch! • The double kink IBL model in WAsP was not confirmed by measurements. by measurements • The IBL growth in WEng was slow in comparison to measurements. t • None of the models was perfect, but the SCADIS results were closest to the measurements. Future canopy flow research Future canopy flow research • New Swedish project ”Vindforsk” • Proposed P d flow center fl t ‐ merge SCADIS with EllipSys ‐ develop linearized model with a distributed drag force