Implementation of forest canopy in the MIUU mesoscale model

Mattias Mohr, Johan Arnqvist, Hans Bergström Uppsala University (Sweden)

Project Goals • Project: Wind power over forests (Vindforsk III) • Better estimation of energy yield (wind resource) • Better estimation of turbine loads (wind shear, turbulence, forest clearings)  Models should be developed for these purposes

Ryningsnäs test site 140m high mast 18m high mast T1, T2 = wind turbines

Measurement setup

U, T, , Global radiation U, T U, T, , q U, T,

Sonic ane mometers, LiCor

U, T, q U, T, , Net radiation U

,

T

MIUU mesoscale model • Used for wind mapping of Sweden (Uppsala University, Weathertech) • Higher order closure, prognostic TKE, no terrain smoothing, 1km resolution (mapping), 100m resolution (forest modelling) • Very high resolution in boundary layer (canopy modelling: 1, 3, 6, 10, 16, 24, 35, 52, … m)

Wind profile over forests • Bulk versus canopy modelling • Does it make any difference at all in mesoscale models?

Bulk versus canopy modelling • Resource assessment benefit?  Not sure • Micro-scale siting benefit?  Definitely • In MIUU model wind-mapping setup: 5 vertical levels within forest anyway, so why not include canopy?

How to include this in the model?

• Production/dissipation term in TKE equation 𝜕𝑞 2 = … 𝜕𝑡 +

C d

·

LAD

· (𝛽 𝑝 · | 𝑢

horizontal

| 3 𝛽 𝑑 · | 𝑢

horizontal

| ·

q 2

where

q 2

=

turbulent kinetic energy

(TKE)

β p

= 1.0 (canopy production coefficient)

β d

= 4.0 (canopy dissipation coefficient)  Seems to make little difference above forest. (Main part of TKE produced by strong wind shear above forest.)

Drag term for horizontal wind components (u, v) 𝜕𝑢 𝜕𝑡 = … −

C d

·

LAD

· | 𝑢

horizontal

| · 𝑢 (same for v-component) 𝑢 = horizontal wind speed, 𝑢 = wind component Halldin, S. (1985): Leaf and bark area distribution in a pine forest. In

The forest atmosphere interaction

, edited by B. A. Hutchison and B. B. Hicks (Dordrecht: Reidel Publishing Company), p. 39 –58.

Lalic, B. and D. T. Mihailovic (2004): An Empirical Relation Describing Leaf-Area Density inside the Forest for Environmental Modeling.

Journal of Applied Meteorology

, Notes and Correspondence, Vol.

43

, p. 641-645.

”Elevated” Monin Obukhov (MO) theory in model • Replace elevation above ground above zero displacement with elevation • Replace MO-similarity theory terms in forest with something else (what?) • Lower boundary conditions have to be modified (energy balance, u *, … )

Master length scale • Length scale within forest • Simple model of Inoue (1963):

l

= 0.47 · (h – d) ≈ 2m • Within canopy: Length scale constant with height  Seems to have very little influence on results.

Energy balance • Has to be solved at each model level within canopy • Direct shortwave radiation follows Beer’s law S↓ = S↓ 0 · exp(-0.5 · 𝑧 ℎ 𝑚𝑜𝑑𝑒𝑙 𝐿𝐴𝐷 𝑧 𝑑𝑧 ) • Longwave radiation (Zhao and Qualls, 2006)

Start with idealised 1D simulations • Run several days (diurnal cycle) • Parameters used: 10m/s geostr. wind, average temperature profile, forest, spring

z 0

= 1 m,

h

= 20 m,

LAI

= 5, pine • Compare results with bulk version

Idealised 1D results – diurnal variation 180 160 140 120 100 7 80 60 40 20 6 5 7

Model-prediced wind speed (fair-weather test case)

9 6 9 9 6 8 7 8 7 5 8 7 8 5 7 6 6 7 6 7 6 7 6 5 5 4 5 6 4 4 6 4 3 4 5 3 1 2 1 2 0 12 0 0 12 0 12 0

Local standard time

0 12 0 0 No wind in forest 0 9 8 11 10 2 1 4 3 7 5 6 m/s

Idealised 1D results – mean profiles

Comparison of Bulk and Canopy Wind Profiles (4 day 1D test run)

200 Bulk forest (z 0 = 1 m) 180 Forest canopy (additional drag terms) Logarithmic wind profile 160 140 120 100 80 60 40 20 0 0 1 2 3 4 5

Mean Wind Speed (m/s)

6 7 8

4 day 1D simulation – Input data • Temperature profiles from radio soundings at Ryningsnäs • Global radiation from measurements • Geostrophic winds from Reanalysis • Forest: h c , LAI, LAD(

z

), z m  best guess

4 day 1D simulation Ryningsnäs

Comparison of Bulk and Canopy Wind Profiles (05/04 - 08/04/2011)

140 Forest canopy (additional drag terms) Measurements Bulk forest (z 0 = 1 m) 120 100 80 60 40 20 0 2 4 6 8

Mean Wind Speed (m/s)

10 12

4 day 1D simulation - shear • Comparison of shear exponents (4 days):

Measurements Forest canopy model Bulk model Shear exponent

0.374

0.365

0.39

For comparison (annual values) 42 Swedish forest site: 0.25 - 0.40 (median value 0.33) (Source: ”Wind power in forests”, final report, Elforsk, published March 2013)

Summary & Conclusions • Preliminary 1D results promising • Still lot of work to do (lower boundary conditions, canopy energy balance, length scale …) • Vertical resolution of 1D runs too time-consuming for 3D runs?

• Is vertical resolution of 3D runs enough for canopy model?

Future plans • Refine forest canopy module in MIUU model • Implement and run in 3D • Study effects on resource assessment • Implement forest canopy in WRF