U.S. Department of Agriculture: Agricultural Research Service, Lincoln, Nebraska

 

Date of this Version

2011

Citation

Journal of Atmospheric and Oceanic Technology Volume 28; DOI: 10.1175/2011JTECH1514.1

Comments

Copyright 2011 American Meteorological Society

Abstract

Land–atmosphere interactions play a critical role in regulating numerous meteorological, hydrological, and environmental processes. Investigating these processes often requires multiple measurement sites representing a range of surface conditions. Before these measurements can be compared, however, it is imperative that the differences among the instrumentation systems are fully characterized. Using data collected as a part of the 2008 Bushland Evapotranspiration and Agricultural Remote Sensing Experiment (BEAREX08), measurements from nine collocated eddy covariance (EC) systems were compared with the twofold objective of 1) characterizing the interinstrument variation in the measurements, and 2) quantifying the measurement uncertainty associated with each system. Focusing on the three turbulent fluxes (heat, water vapor, and carbon dioxide), this study evaluated the measurement uncertainty using multiple techniques. The results of the analyses indicated that there could be substantial variability in the uncertainty estimates because of the advective conditions that characterized the study site during the afternoon and evening hours. However, when the analysis was limited to nonadvective, quasi-normal conditions, the response of the nine EC stations were remarkably similar. For the daytime period, both the method of Hollinger and Richardson and the method of Mann and Lenschow indicated that the uncertainty in the measurements of sensible heat, latent heat, and carbon dioxide flux were approximately 13 W m‒2, 27 W m‒2, and 0.10 mg m‒2 s‒1, respectively. Based on the results of this study, it is clear that advection can greatly increase the uncertainty associated with EC flux measurements. Since these conditions, as well as other phenomena that could impact the measurement uncertainty, are often intermittent, it may be beneficial to conduct uncertainty analyses on an ongoing basis.

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