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Conventional and recently developed approaches for estimating turbulentscalar fluxes under stable conditions are evaluated. The focus is on methodsthat do not require fast scalar sensors such as the relaxed eddy accumulation(REA) approach, the disjunct eddy-covariance (DEC) approach, and a novel mixinglength parametrization labelled as A22. Using high-frequency measurementscollected from two contrasting sites (Utqiagvik, Alaska and Wendell, Idaho"during winter"), it is shown that the REA and A22 models outperform theconventional Monin-Obukhov Similarity Theory (MOST) utilized in Earth SystemModels. With slow trace gas sensors used in disjunct eddy-covariance (DEC)approaches and the more complex signal filtering associated with REA devices(here simulated using filtered signals from fast-response sensors), A22outperforms REA and DEC in predicting the observed unfiltered (total)eddy-covariance (EC) fluxes. However, REA and DEC can still capture theobserved filtered EC fluxes computed with the filtered scalar signal. Thisfinding motivates the development of a correction, blending the REA and DECmethods, for the underestimated net averaged fluxes to incorporate the effectof sensor filtering. The only needed parameter for this correction is the meanvelocity at the instrument height, a surrogate of the advective timescale.

Estimating scalar turbulent fluxes with slow response sensors in the stable atmospheric boundary layer