Abstract

ABSTRACTIn this study, we compared different remote-sensing (RS)-based land surface models (LSM) and reanalysis latent heat flux (LE) products over different forest ecosystems. We analysed the performance of three RS products, the MOD16A2, the Breathing Earth System Simulator (BESS) model, and a combined optical-microwave model (COM) in their ability to replicate eddy covariance (EC) flux observations of LE at eight southern hemisphere forest ecosystems and compared their results to simulated LE from the offline LSM (GLDAS/NOAH) and a reanalysis LE dataset (MERRA). To determine spatial uncertainties, we used the triple collocation (TC) method, which does not require a priori knowledge of the true LE value, at selected Australian EC locations and over an area without in situ measurement (the Dry Chaco Forest (DCF), Argentina). The spatial pattern of the TC results was commensurable with uncertainties calculated using EC observations, indicating that the TC method is a robust technique to estimate spatial uncertainties. As global products have been validated with EC measurement from Ozflux stations, we hypothesized and found, using the TC model, that LE products achieve a better performance over areas with EC from networks than over sites without ground-based measurements and may reflect over-calibration of models or a need for a more diverse representation of ecosystems at flux tower networks.

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