1. The Role of Virtual Tall Towers in the Carbon Dioxide Observation Network Martha Butler The Pennsylvania State University ChEAS Meeting June 5-6, 2006

2. Virtual Tall Towers What is a virtual tall tower (VTT)? –At a continental site with continuous CO 2 mixing ratio measurements in the surface layer, estimate the mixing ratio in the mixed layer above during mid-day hours Where/when does a VTT make sense? –Existing site (typically a flux tower) where there is a hole in the existing observation network –Resources to invest in upgrading sampling and calibration procedures How is this done? Testing the correction method What a VTT is not!

3. The Richardson-Miles Package For more information, see www.amerifluxco2.psu.edu

4. Performance Testing Difference between the PSU system and WLEF 76m CO 2 measurements in a test from April-August 2004. [Miles/Richardson/Uliasz, in prep.] Difference of daily averages

5. Global Observation Network in 2002

6. Daily Mixing Ratio Profile from a Tall Tower

7. Is an Adjustment Required at Mid-Day?

8. If You Prefer Numbers… Month CO2 (ppm) at 30m, midday CO2 (ppm) at 396m, midday  CO2 (ppm) 30m-396m, midday σ (396m-30m) CO2 (ppm) at 396m, entire day  CO2 (ppm) 396m(pm) 396m(entire) 1373.16372.510.651.73372.460.05 2375.34374.570.781.72373.960.60 3372.91372.690.220.85372.73-0.04 4370.75370.91-0.160.22371.23-0.32 5363.91364.68-0.770.94366.21-1.53 6358.49359.96-1.471.58362.54-2.59 7352.50353.63-1.130.98354.59-0.97 8355.95356.72-0.770.93356.85-0.13 9364.47364.74-0.270.81364.76-0.02 10371.31370.600.712.70370.490.11 11373.41372.990.410.78372.890.10 12374.19373.630.560.83373.250.38 Annual Mean367.20367.30-0.10367.66-0.36 Monthly Summary for 1998

9. What Is This Adjustment? Following the mixed layer similarity theory of Wyngaard & Brost [1984] and Moeng & Wyngaard [1989], the vertical gradient of a scalar in the boundary layer: where g b and g t are bottom-up and top-down gradient functions scaled by boundary layer depth z i w * is the convective velocity scale wc 0 and wc zi are the surface and entrainment fluxes of the scalar C

10. The Gradient Functions The LES gradient functions are from a study by Patton et al. [2003]. The observed gradient functions will appear in Wang et al. [in review in BLM].

11. Implementation at a Flux Tower We tested the concept at WLEF, adjusting 30m CO 2 mixing ratios to a VTT height of 396m and comparing with the observations at 396m. Required input: displacement height, tower height, VTT height and time series of tower top CO 2 mixing ratio, CO 2 flux, sensible heat flux, and temperature. We estimate the mixing ratio at the VTT height for 3-6 midday hours, depending on time of year. We use the boundary layer depth algorithm from Yi et al. [2001]. We screen for minimum sensible heat flux (20 W m -2 ) and boundary layer depth (700m).

12. The Algorithm As Used Here, - ΔC is the adjustment to the 30m CO 2 mixing ratio - z 0 is the measurement height, 30m - z VTT is the virtual tall tower height, 396m - α is a fraction applied to the surface flux to represent the entrainment flux - d is the displacement height - g b and g t are empirical fits for the gradient functions of Wang et al.

13. Screening to Limit Uncertainties

15. Hourly Adjustment & Bias – Spring/Summer

16. Daily Adjustment & Bias – Spring/Summer

17. A Closer Look at One Month

18. What a VTT is not…. Unlike a tall tower: –Limited number of species observed –Midday observations only –More gaps in the observations –Nocturnal boundary layer not represented –Added uncertainty and bias What if it isn’t a flux tower and/or permanent site? –Sample as high on a tower as possible –Infer the local flux for the micromet adjustment By model By sampling at multiple heights on tower

19. Will VTTs Be Useful? Adding a few more continental observation sites –Density of measurements –Spatial flux variability –Synoptic variability Availability of VTT data Tradeoffs…. –Is the bias and uncertainty a problem? –Can these data help constrain regional budgets?

20. Model Performance at 396m vs. 30m The red lines are time series of hourly samples at WLEF in September 2002 at 396m and 30m from a tracer transport model using analyzed winds and standard “background” fluxes for fossil fuel, air-sea flux and a balanced terrestrial flux. The black lines are the CO 2 time series observations at WLEF. Data are normalized to the beginning of the year 2002.

21. VTT References Davis, K. J., 2003, Well-calibrated CO2 mixing ratio measurements at flux towers: The virtual tall towers approach, 12 th WMO/IAEA Meeting of Experts, Toronto. Davis, K. J. et al., in prep, Methodology for a flux-tower based CO2 observing network: Virtual tall towers. Moeng, C.-H. and J. C. Wyngaard, 1984, Statistics of conservative scalars in the convective boundary layer, JAS, 41(21), 3161-3169. Moeng, C.-H., and J. C. Wyngaard, 1989, Evaluation of turbulent transport and dissipation closure in second-order modeling, JAS, 45, 2311-2330. Patton, E. G., et al., 2003, The influence of forest canopy on top-down and bottom-up diffusion in the planetary boundary layer, QJRMS, 129A, 1415-1434. Wang, W. et al., in review, Observations of the top-down and bottom-up gradient functions in the convective boundary layer from a very tall tower, BLM. Wyngaard, J. C., 1987, A physical mechanism for the asymmetry in top-down and bottom-up diffusion, JAS, 44(7), 1083-1087. Wyngaard, J. C. and R. A. Brost, 1984, Top-down and bottom-up diffusion in the convective boundary layer, JAS, 41, 102-112. Yi, C. et al., 2001, Long-term observations of the dynamics of the continental boundary layer, JAS, 58(10), 1288-1299.

22. Hourly Adjustment & Bias – Fall/Winter

23. Daily Adjustment & Bias – Fall/Winter