Flux Sampling Errors for Aircraft and Towers

L. Mahrt College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon

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Abstract

Various errors and influences leading to differences between tower- and aircraft-measured fluxes are surveyed. This survey is motivated by reports in the literature that aircraft fluxes are sometimes smaller than tower-measured fluxes. Both tower and aircraft flux errors are larger with surface heterogeneity due to several independent effects. Surface heterogeneity may cause tower flux errors to increase with decreasing wind speed.

Techniques to assess flux sampling errors are reviewed. Such error estimates suffer various degrees of inapplicability in real geophysical time series due to nonstationarity of tower time series (or inhomogeneity of aircraft data). A new measure for nonstationarity is developed that eliminates assumptions on the form of the nonstationarity inherent in previous methods. When this nonstationarity measure becomes large, the surface energy imbalance increases sharply. Finally, strategies for obtaining adequate flux sampling using repeated aircraft passes and grid patterns are outlined.

* Visiting scientist at Agricultural Canada, Ottawa, Ontario, Canada, and the National Center for Atmospheric Research, Boulder, Colorado.

Corresponding author address: Larry Mahrt, Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331-2209.

Abstract

Various errors and influences leading to differences between tower- and aircraft-measured fluxes are surveyed. This survey is motivated by reports in the literature that aircraft fluxes are sometimes smaller than tower-measured fluxes. Both tower and aircraft flux errors are larger with surface heterogeneity due to several independent effects. Surface heterogeneity may cause tower flux errors to increase with decreasing wind speed.

Techniques to assess flux sampling errors are reviewed. Such error estimates suffer various degrees of inapplicability in real geophysical time series due to nonstationarity of tower time series (or inhomogeneity of aircraft data). A new measure for nonstationarity is developed that eliminates assumptions on the form of the nonstationarity inherent in previous methods. When this nonstationarity measure becomes large, the surface energy imbalance increases sharply. Finally, strategies for obtaining adequate flux sampling using repeated aircraft passes and grid patterns are outlined.

* Visiting scientist at Agricultural Canada, Ottawa, Ontario, Canada, and the National Center for Atmospheric Research, Boulder, Colorado.

Corresponding author address: Larry Mahrt, Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331-2209.

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