Implementation of forest canopy in the MIUU mesoscale model

1. Implementation of forest canopy in the MIUU mesoscale model Mattias Mohr, Johan Arnqvist, Hans Bergström Uppsala University (Sweden)

2. 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

3. Ryningsnästest site 140m high mast 18m high mast T1, T2 = windturbines

4. Measurement setup U, T, , Global radiation U, T Sonicane-mometers, LiCor U, T, , q U, T, U, T, q U, T, , Net radiation

5. 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)

6. Windprofile over forests • Bulk versuscanopymodelling • Does it make anydifference at allin mesoscalemodels?

7. Bulk versuscanopymodelling • Resourceassessment benefit?  Not sure • Micro-scalesiting benefit?  Definitely • In MIUU modelwind-mappingsetup: 5 verticallevelswithinforestanyway, so why not includecanopy?

8. Howtoincludethis in the model? • Production/dissipation term in TKE equation LAD | horizontal | 3 - | horizontal | q2 whereq2= turbulent kineticenergy(TKE) βp = 1.0 (canopyproductioncoefficient)βd = 4.0 (canopydissipationcoefficient)  Seemsto make littledifferenceaboveforest. (Main part of TKE produced by strong windshearaboveforest.)

9. Drag term for horizontalwindcomponents (u, v) LAD| horizontal | (same for v-component) , = windcomponent 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: ReidelPublishing 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.

10. ”Elevated” MoninObukhov (MO) theory in model • Replaceelevation abovegroundwithelevation abovezerodisplacement • Replace MO-similaritytheory terms in forestwithsomethingelse (what?) • Lowerboundaryconditionshaveto be modified (energybalance, u*, … )

11. Master lengthscale • Lengthscalewithinforest • Simple modelofInoue (1963): l = 0.47 · (h – d) ≈ 2m • Withincanopy: Lengthscaleconstantwithheight Seemstohaveverylittleinfluence on results.

12. Energy balance • Has to be solved at eachmodellevelwithincanopy • DirectshortwaveradiationfollowsBeer’slawS↓ = S↓0 · exp(-0.5 · ) • Longwaveradiation (Zhao and Qualls, 2006)

13. Start with idealised 1D simulations • Runseveraldays(diurnalcycle) • Parameters used: 10m/s geostr. wind, averagetemperatureprofile, z0 = 1 m, h = 20 m, LAI = 5, pineforest, spring • Compareresultswith bulk version

14. Idealised 1D results – diurnal variation m/s No wind in forest

15. Idealised 1D results – meanprofiles

16. 4 day 1D simulation – Input data • Temperatureprofiles from radio soundingsatRyningsnäs • Global radiation from measurements • Geostrophicwinds from Reanalysis • Forest: hc, LAI, LAD(z), zm best guess

17. 4 day 1D simulation - Ryningsnäs

18. 4 day 1D simulation - shear • Comparisonofshear exponents (4 days): For comparison (annualvalues) 42 Swedish forest site: 0.25 - 0.40 (median value 0.33) (Source: ”Windpower in forests”, final report, Elforsk, publishedMarch2013)

19. Summary & Conclusions • Preliminary 1D resultspromising • Still lotofworkto do (lowerboundaryconditions, canopyenergybalance, lengthscale…) • Vertical resolution of 1D runstootime-consuming for 3D runs? • Is vertical resolution of 3D runsenoughfor canopymodel?

20. Future plans • Refineforestcanopymodule in MIUU model • Implement and run in 3D • Studyeffects on resourceassessment • Implementforestcanopy in WRF