Daytime sensible and latent heat flux estimates for a mountain meadow using in-situ slow-response measurements

Abstract A new procedure based on surface renewal (SR) analysis has been derived to estimate the latent heat flux (λE) under unstable conditions. Traditional application of SR-based approaches requires measurement of the scalar concentration taken at high frequency. However, the SR-based approach proposed (λE SR-LST ) requires the following measurements taken at low frequency (half-hourly); the land surface temperature ( LST ), the horizontal mean wind speed, the mean temperature and relative humidity of the air and the available net surface energy. After estimating the sensible heat flux (Η SR-LST ), for a period of few days the procedure simultaneously calibrates λE SR-LST and forces the closure of the surface energy balance (SEB) equation in a generalized form by imposing that the slope of the linear regression analysis comparing (Η SR-LST  + λE SR-LST ) vs. the available net surface energy is one. Therefore, the intercept of the linear regression analysis estimated the sensible and latent heat fluxes that the SR- LST method cannot explain, such as the role of low-frequency circulations. The procedure has been tested for a case where the soil water content did not limit the development of the vegetation and where the EC method produced an imbalance of 19% of the available net surface energy. The assumptions made for deriving λE SR-LST were tested and found to be reliable, and the procedure enabled the following; (1) closing the SEB equation with a correlation comparable to that obtained using the Eddy Covariance (EC) method; (2) producing latent heat flux estimates that overestimated moderately (14%) λE EC and; (3) proposing an approach to estimate the actual sensible heat flux on the basis that most of the imbalance partitions into sensible heat flux. The equation of Penman-Monteith and the residual method cannot be recommended because they produced a large overestimation of the latent heat flux.