In-situ observations are essential to a broad range of applications including the development, calibration, and validation of both the numerical and remote sensing-based models. For example, in the case of surface energy balance models, observational data are requisite to evaluate model skill both to represent the complex biogeophysical processes regulating evapotranspiration (ET), and to predict the magnitude of the moisture flux. As such, by propagating into these subsequent activities, any uncertainty or errors associated with the observational data have the potential to adversely impact the accuracy and utility of these models. It is, therefore, critical that the factors driving measurement uncertainty are fully understood so that steps can be taken to account for their effects and mitigate their impact on subsequent analyses. Field measurements of ET can be collected using a variety of techniques including eddy covariance (EC), lysimetry (LY), and scintillometry (SC). Each of these methods is underpinned by a unique set of theoretical considerations and practical constraints; and, as a result, each method is susceptible to differing types of systematic and random error. Since the uncertainty associated with the field measurements is predicated on how well numerous factors – for example, environmental conditions – adhere to those prescribed by the underlying assumptions, the quality of in-situ observations collected via the differing methods can vary significantly both over time and from site-to-site. Using data from both individual field sites and large field campaigns, such as IHOP_2002 and BEAREX08, the sources of uncertainty in field observations will be discussed. The impact of measurement uncertainty on model validation studies will also be illustrated.
Dr. Alfieri is a research scientist with the USDA-ARS Hydrology and Remote Sensing Laboratory. His research interests focus on integrating in-situ, remotely-sensed, and modeled data to characterize the impact of spatiotemporal variability in atmospheric and land surface conditions on atmosphere-biosphere interactions, boundary layer processes, and the subsequent meteorological, hydrological, and other environmental processes. Currently, his research projects include investigating the linkage between surface heterogeneity and measurement uncertainty, quantifying the role of canopy architecture in controlling the turbulent transport of water vapor and other scalar quantities, and leveraging thermal remote sensing data to monitor pesticide volatilization. Dr. Alfieri received his M.S. from the University of Colorado in 2005 and Ph.D. from Purdue University in 2009.