Upscaling tower-observed turbulent exchange at fine spatio-temporal resolution using environmental response functions

Ke Xu, Stefan Metzger, Ankur R. Desai
2017 Agricultural and Forest Meteorology  
Eddy-covariance measurements are widely used to develop and test parameterizations of landatmosphere interactions in earth system models. However, a fundamental challenge for model-data comparisons lies in the scale mismatch between the eddy-covariance observations with small (10 −1 -10 1 km 2 ) and temporally varying flux footprint, and the continuous regional-scale (10 2 -10 4 km 2 ) gridded predictions made in simulations. Here, a new approach was developed to project turbulent flux maps at
more » ... egional scale and hourly temporal resolution using environmental response functions (ERFs). This is based on an approach employed in airborne flux observations, and relates turbulent flux observations to meteorological forcings and surface properties across the flux footprint. In this study, the fluxes of sensible heat, latent heat and CO 2 integrated over a 20 × 20 km 2 target domain differed substantially from the tower observations in their expected value (+27%, −9%, and −17%) and spatio-temporal variation (−22%, −21%, and −3%, repsectively) ERF systematic uncertainties are bound within −11%, −1.5% and +16%, respectively, indicating that tower location bias might be even more pronounced for heat and CO 2 fluxes than currently detectable. The ERF-projected fluxes showed general agreement with independent observations at a nearby tower location. Lastly, advantages and limitations of ERF compared to other scaling approaches are discussed, and pathways for improving model-data synthesis utilizing the ERF scaling method are pointed out. (K. Xu). observation uncertainty and representativeness of observations for the model grid scale. Here, we test a specific approach for improving representativeness and estimating corresponding uncertainty of eddy-covariance (EC) flux tower observations of carbon, water, and heat fluxes. Eddy-covariance observations of these fluxes have been increasingly used to constrain model uncertainty, because they, in theory, provide reliable spatially distributed and temporally continuous observations of surface-atmosphere exchanges (Bonan et al., 2011; Baldocchi et al., 2001) . Parameter sensitivities in photosynthetic rates, respiration allocation, and temperature sensitivity of decomposition in models can, in principle, be constrained by flux tower observations (Dietze et al., 2014) , especially when autocorrelation of time series are taken into account (Desai et al., 2010; Desai, 2014) . Recently, large model-to-tower syntheses, as part of the North American Carbon Program, have found limitations in modeled spring phenology (Richardson et al., 2012) , light use efficiency (Schaefer et al., 2012) , and drought sensitivity (Schwalm et al., 2010) .
doi:10.1016/j.agrformet.2016.07.019 fatcat:r6igrx427zg6npdbreqzpbuyma