… Using covariant symmetries, we show that correlation functions can be constructed from
inexpensive approximations … We introduce a new class of covariant approximation averaging …

… called as covariant approximation averaging (CAA). We proposed all-modeaveraging (AMA), …
are taken into account in the averaged approximation with the sloppy CG using deflation. …

… We present two new covariant and general prescriptions for averaging scalar observables …
procedures are illustrated by computing the averaged energy flux received by distant sources …

… The idea of exploiting covariance [14,15] to improve statistical errors has a wider range of
applicability than LMA, so in general we call it covariant approximation averaging (CAA). …

… We introduce a generalization of the 4-dimensional averaging window function of Gasperini
… The covariant nature of spatial scalar averaging schemes to address the averaging problem …

… ► Effective technique to reduce statistical error of correlation function without additional
computational cost, by using covariant symmetry … ► Effective technique to reduce …

… We then derive Reynolds averaged approximations for use … eddy covariance based on
fixed-interval Reynolds averaging … average of the exchange, even if a moving average is used for …

… averaging and mean removal on the cospectra is somewhat involved but it can be approximated
… in Section 2.3 below, so long as the averaging time T is much longer than the period of …

… attenuation of eddy covariance fluxes due to sensor response, path-length averaging, sensor
… Although not shown in this study, the analytical approximation performed very well for the …

… a covariant generalisation of the guiding centre of motion. In 0 4.1, the covariant approximate
… This approximation involves a time average for slowly changing quantities over a period of …