Conditional sampling revisited

There is a continued need for simple, robust, yet accurate methods for measuring the surface/atmosphere exchange of a wide variety of trace gases and particulates. Conditional sampling is a relatively new method that has received increasing attention in recent years because it is related to theoretically attractive eddy covariance, but does not require a rapid response sensor for the covariate, It does require rapid measurement of the vertical wind speed, w, and sorting of sampled air into two separate lines based on the direction of w. As originally proposed, the flux was then calculated as F = beta Delta C sigma(w), where Delta C is the mean difference in concentration between the upward and downward moving eddies, sigma(w) the standard deviation of the vertical wind speed, and beta an empirical coefficient. Subsequent exposition showed that beta was derivable from the statistics of joint Gaussian distribution, although field experiments have consistently found values in the range of 0.56 to 0.58, somewhat lower than the theoretical expectation of approximate to 0.62-0.63. Here, we reexamine the method, and show that if the flux is instead expressed as F = b(l)sigma(w)(2), where b(l) is the regression-estimated slope of the concentration vs, wind speed relation, then it is exactly equivalent to eddy covariance. The aim of conditional sampling then becomes an estimation of bl as Delta C/Delta W. We show that this quantity has a consistent positive bias when samples are sorted simply into positive and negative excursions from mean w. Inclusion of a sampling deadband, symmetric about the mean w, improves the accuracy of the slope estimate and decreases its variance as well. A potential problem with conditional sampling, regardless of which formulation may be used, is the effect of random measurement error (noise) in the wind speed measurement. We show that this introduces systematic errors into conditional sampling, while eddy covariance measurements are unaffected. Direct and indirect assessments indicate that these errors are too small to be significant for the sonic anemometer that we used, but it is probably wise for practitioners of the method to make certain that such is the case for the instruments used in their particular systems. We conclude that conditional sampling is a maturing method, with an increasing body of evidence indicating that the underlying relationships between scalar concentration and wind speed are sufficiently robust to support widespread use. Published by Elsevier Science B.V.