1. Estimating scalar fluxes in tropical forests using higher-order closure models Mario Siqueira 1, Humberto R Rocha 2, Michael L Goulden 3, Scott D Miller 3, Renato Silva 4, and Gabriel Katul 1 1 Nicholas School of the Environment and Earth Sciences, Duke University, Durham, NC, USA 2 Departamento de Ciências Atmosféricas,Universidade de São Paulo, São Paulo, Brazil 3 Department of Earth System Science, University of California, Irvine, CA, USA 4 Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA Introduction Eddy Covariance (EC) flux measurements are now widely used for estimating long-term biosphere-atmosphere gas exchange. However, gap-filling and constraining these EC estimates using other techniques that are sensitive to different assumptions remains a high priority. Improved ability to recover fluxes from concentration and temperature profile data could serve as one such constraining and gap-filling method. Furthermore, if successful, concentration profiles permit estimating fluxes of chemical fluxes for which high frequency gas analyzers are not currently available. We investigate the ability of higher order closure models to estimate CO 2 fluxes from a tropical forest in Amazon, Brazil. To this end, we extended the 2 nd order Eulerian approach described in Siqueira and Katul, 2001 for CO 2 along with the appropriate stability correction regimes. For comparison, we also performed calculations using a 1 st order closure model and a “dummy” model where perfect similarity between heat and CO 2 transfer is assumed. Budget Equation for scalar flux: Closure Approximations: With some manipulation, the flux can be written as: Above canopy: 1 st Order Closure Model For consistency with 2 nd order: Dummy Model2 nd Order Closure Model Flux Gradient approach Similarity between sensible heat and CO 2 transfer Velocity Statistics The required velocity statistics for these models were computed using the 2 nd order closure model of Wilson and Shaw, 1997. Stability corrections described in Leuning, 2000 and Hsieh and Katul, 1997 were applied in a manner similar to Leuning, 2000. Models Results Discussion Constants C 4 and C 4 ’ were optimized here due to the wide literature range. Neglecting the transport term provided better statistics (not shown). This is indicative of small flux divergence, consistent with the fact above the canopy near field effects may be negligible. Increasingly higher scatter for higher fluxes for both sensible heat and CO 2 fluxes. It seems that the higher fluxes are associated with high diffusivity and small gradient. For these conditions, the uncertainties in the concentration measurements are amplified in the flux calculations. The models performed similarly except for the 1 st order closure, which overestimated CO 2 positive fluxes during night time. Similarity between sensible heat and CO 2 fluxes seems to exist and can be used during day-time. In an ensemble sense (i.e. not event by event), the models were able to capture the carbon assimilation. None of the models captured storage flux properly due to the fact that they did not consider transients in their formulations. This is a subject of on-going research in our group. Conclusions At the canopy top, the diffusive flux seems to be dominant opening the possibility of applying flux-gradient relationships for constraining and gap-filling EC data. Diffusivity models should include the effects of buoyancy to properly capture the flux, specially at night. Highly accurate measurements of the gradient should improve flux estimation during carbon assimilation periods. Transients should be considered to capture the rise in flux in the early morning. Experiment Acknowledgements: The authors acknowledge support from LBA-ECO on data collection, and DOE’s NIGEC-SERC, FACE, TCP, and NSF- WEAVE. References: Siqueira, M. and G. Katul, ‘Estimating Heat Sources and Fluxes in Thermally stratified Canooppy Flows using Hihger-Order Closure Models’, Boundary- Layer Meteorology, 103,125-1452, 2002. Leuning, R., ‘Estimation of Scalar Source/Sink Distributions in Plant Canopies Using Lagrangian Dispersion Analysis: Corrections for Atmospheric Stability and Comparison with a Multilayer Canopy Model’, Boundary-Layer Meteorology, 96,293-314, 2000. Hsieh, C.I. and G. Katul, ‘Dissipation Methods, Taylor’s Hypothesis, and Stability Correction Functions in the Atmospheric Surface Layer’, Journal Geophysical Research, 102, 16,391-16,405, 1997. Saleska S.R., S.D. Miller, D.M. Matross, M.L. Goulden, S.C. Wofsy, H.R. Rocha, P.B. Camargo, P. Crill, B.C. Daube, H.C. Freitas, L. Hutyra, M. Keller, V. Kirchhoff, M. Menton, J.W. Munger, E.H. Pyle, A.H. Rice, H. Silva, ‘Carbon in Amazon Forests: Unexpected Seasonal Fluxes and Disturbance-Induced Losses, Science, 302, 1554-1557, 2003. The data were collected in a 40 m tall tropical forest on the Floresta Nacional do Tapajós, Para, Brazil. Eddy covariance measurements of sensible and latent heat, CO 2 and momentum fluxes were collected at 64m. Temperature measurements were made at 64, 40, 30, 20 and 10 m from the forest floor. CO 2 and water vapor concentration profiles were measured at 64, 50, 40, 35, 20, 10.7, 6, 3, 1.4, 0.7, 0.35 and 0.1 m from the forest floor (Saleska et al., 2003).