title: Constraining ecosystem processes from tower fluxes and atmospheric profiles.
abstract: The planetary boundary layer (PBL) provides an important link between the scales and processes resolved by global atmospheric sampling/modeling and site-based flux measurements. The PBL is in direct contact with the land surface, both driving and responding to ecosystem processes. Measurements within the PBL (e.g., by radiosondes, aircraft profiles, and flask measurements) have a footprint, and thus an integrating scale, on the order of  1-100 km. We use the coupled atmosphere-biosphere model (CAB) and a Bayesian data assimilation framework to investigate the amount of biosphere process information that can be inferred from PBL measurements. We investigate the information content of PBL measurements in a two-stage study. First, we demonstrate consistency between the coupled model (CAB) and measurements, by comparing the model to eddy covariance flux tower measurements (i.e., water and carbon fluxes) and also PBL scalar profile measurements (i.e., water, carbon dioxide, and temperature) from Canadian boreal forest. Second, we use the CAB model in a set of Bayesian inversions experiments using synthetic data for a single day. In the synthetic experiment, leaf area and respiration were relatively well constrained, whereas surface albedo and plant hydraulic conductance were only moderately constrained. Finally, the abilities of the PBL profiles and the eddy covariance data to constrain the parameters were largely similar and only slightly lower than the combination of both observations.
authors.affiliation: School of GeoSciences and NERC Centre for Terrestrial Carbon Dynamics, University of Edinburgh EH9 3JN, United Kingdom. thill@staffmail.ed.ac.uk
authors.forename: T C
authors.initials: TC
authors.lastname: Hill
authors.forename: M
authors.initials: M
authors.lastname: Williams
authors.forename: F I
authors.initials: FI
authors.lastname: Woodward
authors.forename: J B
authors.initials: JB
authors.lastname: Moncrieff
mesh_terms: D001272:Atmosphere; D002245:Carbon Dioxide / Q000378:metabolism; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D017753:Ecosystem; D008962:Models, Theoretical; D018526:Plant Transpiration / Q000502:physiology; D010944:Plants / Q000378:metabolism
chemical_list: D002245:Carbon Dioxide