1. Testing of the Soil, Vegetation, Atmosphere model using the NORUNDA dataset Ivan Kovalets Ukrainian Center for Environmental and Water Projects (UCEWP) Rodolfo Avila Facilia AB

2. The problem of atmospheric transport inside and above the canopy layer 14 C flux Canopy layer Roughness sublayer Surface layer, z0≈h/30 C(z r )=0 Reference height

3. Objectives of the study To test the parameterization and validity of C-14 assessment model developed by Facilia AB To test model’s capability to predict the inside- and above- canopy profiles of CO2 for different stability conditions To evaluate the parameters of model

4. Presentation Layout Description of the Norunda research station Review of the theory and parameterizations Model Results Conclusions

5. The Norunda research station Established in 1994 in frame of NOPEX project for investigation of fluxes of momentum, heat, water, and CO2 between soil, vegetation, and atmosphere Operated by Lund University Located 30 km north of Uppsala mature boreal forest, dominated by Norway spruce and Scots pine Flat topography, H≈25 m, LAI=3÷6 Reference: Lundin et al. (1998) Agricultural and Forest Meteo 98- 99:53-73

6. The Norunda research station 102-m high tower CO2 and CH4 concentration, wind speed, temperature, humidity, measurements from 8 to 102 m Eddy flux, micrometeorological (heat flux, velocity fluctuations, etc) measurements at 35 m Wide range of radiation measurements Automated soil respiration chamber systems Access to data with 30 min resolution through NBECC database http://dbnecc.nateko.lu.se The site participates in FLUXNET: a world-wide network of micrometeorological towers which use eddy covariance methods to measure the exchanges of CO2, water vapor, and energy between terrestrial ecosystems and the atmosphere

7. Model description, general considerations Z=h U(z) z Velocity profile in presence of canopy Surface (logarithmic) layer Exponential decay Inflection point Roughness sublayer The region of inflection in velocity profile is always unstable and acts as the main source of turbulence generation in roughness sublayer Ratio of friction velocity to velocity at canopy height c d – drag coefficient of individual leaf a – frontal leaf area per unit volume Results of Inoue (1963) for inside canopy profile with the constant mixing length l m and infinite canopy depth

8. Model description, roughness correction functions U(z) z Z=h Velocity profile in presence of canopy Surface (logarithmic) layer Exponential decay Inflection point Roughness Sublayer (RSL) - Proposition of Garratt (1980) Account for stability Account for RSL - Proposition of Harman and Finnigan (2008) BLM 129: 323-351

9. Model description, key parameters (which control the above-canopy mixing) By using mixing length hypothesis And requesting continuity of profiles at canopy top Harman and Finnigan (2008) derive RSL correction functions in form: In which coefficients analytically depend on: Ratio of friction velocity to velocity at canopy height: β=u * /U h ≈0.3 – obtained using direct measurements from Norunda station) Drag coefficient of individual leaf: c d ≈0.25 – from literature Leaf level Stanton number: r≈0.1 – from literature Frontal leaf area per unit volume : a≈0.14 – obtained by least squares fitting of the velocity profiles measured at Norunda Turbulent Schmidt number inside canopy layer : Scc=Km/Kc – depend on stability as will be described below

10. Model description, inside-canopy parameterization Drawbacks of the simplified approach of Harman and Finnigan (2008) Limitation of the hypothesis about constant mixing length inside canopy Limitation of the hypothesis of infinite depth of canopy Necessity to obtain the detailed and accurate profiles inside canopy layer (not only above it) Strong dependence of K on β -> very high sensitivity of the results to the parameter value

11. Model description, inside-canopy parameterization Fundamental relationship following from the Taylor’s theory of turbulent diffusion (1921): Empirical parameterization of vertical velocity fluctuation: Empirical parameterization of the Lagrangian time-scale :

12. Model description, key parameters (which control the above-canopy mixing) Ratio of friction velocity to vertical velocity fluctuation at canopy height: c σ ≈1.3 – (obtained using direct measurements from Norunda station) Rate of T L decay with height: c 1 ≈0.4 – from literature Rate of vertical velocity fluctuation decay with height β1=1.5 – obtained by fitting concentration profiles to Norunda data (will be shown below) Vertical profiles of for different values of parameter β1.

13. ReferenceCanopy typeLAIBeta1 Brunet (1994)Wheat0.470.9 Wilson et al. (1982)Corn2.91.03 Denmead and Bradley (1987)PineUnknown1.18 Amiro (1990)Aspen40.76 Amiro (1990)Pine20.7 Amiro (1990)Spruce101.05 Gardiner (1994)Spruce10.22.26 Baldocchi and Meyers (1988)Deciduous forest4.91.29(day), 4.17(night) Aylor (1993)Grass3.8 (PAI)2.33 Finnigan (1978)Wheat1.041.13 Krujt (2000)Tropical forest5.51.5 Shaw (1988)Deciduous forest0.3-4.5from 0.5 for LAI=0.3 to 1.1 for LAI=4.5 Katul and Albertson (1988)Pine4.81.7 Results of least square estimations of the parameter β1 from the published vertical profiles of σ w.

14. Model setup Simulation period: 3 years (2007- 2009) Time resolution: 30 minutes Reference height z r =70 m Stability ranges (approximately correspond to classifications of Golder, 1970): Neutral: |L|> 500 m Slightly stable: 250<L<500 Moderately stable: 70<L<250 Slightly unstable: -500<L<-250 Moderately unstable: -250<L<-70 Diffusion transport equation Setting source term in day time Net flux at canopy top F N is measured Respiration flux from the soil surface is parameterized as function of temperature (Lindroth et al., 1998): Net photosynthesis flux: Photosynthesis flux is distributed through the upper part of canopy layer

15. Averaging and normalizing of measured and calculated concentrations Normalized concentration flux through the top of the canopy If Monin-Obukhov similarity theory was valid such normalization with fixed stability conditions would bring all profiles into single curve Output profile of the following quantity:

16. Results of simulations Day time conditions, neutral stratification

17. Results of simulations Day time conditions, slightly unstable stratification

18. Results of simulations Day time conditions, moderately unstable stratification

19. Results of simulations Night time conditions, neutral stratification

20. Results of simulations Night time conditions, slightly unstable stratification

21. Results of simulations Night time conditions, moderately stable stratification

22. Example calculation of C-14 concentrations Average day-time concentrations of C-14 calculated for the conditions of Norunda during 3 years following the release of 1 Bq/m2/s of C-14

23. Conclusions The model had been successful in reproducing vertical profiles of CO2 concentrations for day-time and night-time conditions and for different stability conditions (from neutral to moderately stable and to moderately unstable) The successful results in reproducing the observed CO2 profiles in day- time conditions could be achieved only by proper assignment of respiration flux Taking into account the unstable stratification during day time conditions reduces the inside canopy concentration up to -25% as compared to neutral case. Thus stability effects probably could be neglected in assessments of C-14 contamination. Application of the model to other canopies could lead to necessity in some tuning of the parameters and additional studies are required in this respect

24. Acknowledgements The present work had been funded by Swedish Nuclear Fuel and Waste Management Company (SKB) We gratefully acknowledge Prof. Andreas Lindroth and his collegues from the Lund University for kindly providing data of the Norunda research station through access to NECC database (http://dbnecc.nateko.lu.se)http://dbnecc.nateko.lu.se

25. Thank you for attention!