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Submitted to: American Meteorological Society
Publication Type: Proceedings Publication Acceptance Date: 4/8/1998 Publication Date: N/A Citation: N/A Interpretive Summary: Technical Abstract: There is a need for simple, accurate methods for measuring surface /atmosphere exchange of trace gases and particulates. Conditional sampling has received increasing attention 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 windspeed, w, and sorting of sampled air into two separate lines on the basis of w. As originally proposed, the flux was calculated as F=bDCsw, where DC is the mean difference in concentration between the upward and downward moving eddies, sw is the standard deviation of the vertical windspeed, and b is an empirical coefficient. Here we reexamine the method, and show that if the flux is instead expressed as F=b1sw2, where b1 is the regression estimated slope of the concentration versus windspeed relation, then it is exactly equivalent to eddy covariance. The aim of conditional sampling then becomes estimation of b1 as DC/DW. This quantity has a consistent positive bias when samples are sorted simply into positive and negative excursions from mean w. Use of a sampling deadband improves the accuracy of the slope estimate and decreases its variance as well. A potential problem with conditional sampling is the effect of random measurement error in the windspeed measurement. This introduces systematic errors into conditional sampling, while eddy covariance measurements are unaffected. Assessments indicate that these errors are small for the sonic anemometer we used, but others should make certain that this is also the case for their systems. Conditional sampling is a maturing method, with increasing evidence indicating that underlying relationships between scalar concentration and windspeed are sufficiently robust for widespread use. |
