  The Monin--Obukhov similarity theory-based wind speed and potential
temperature profiles are inherently coupled to each other. We have developed
hybrid approaches to disentangle them, and as a direct consequence, the
estimation of Obukhov length (and associated turbulent fluxes) from either
wind-speed or temperature measurements becomes an effortless task.
Additionally, our approaches give rise to two easily measurable indices of
atmospheric stability. We compare these approaches with the traditional
gradient and profile methods that require both wind-speed and temperature
profile data. Using Monte-Carlo-type numerical experiments we demonstrate that,
if the input profiles are free of any random errors, the performance of the
proposed hybrid approaches is almost equivalent to the profile method and
better than the gradient method. However, the proposed hybrid approaches are
less competitive in comparison to their traditional counterparts in the
presence of random errors.
