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    This dataset comprises spatially and temporally dynamic estimates of the monthly latent heat flux (λE) and sensible heat flux (H) for all of Australia. The available energy (A, being net radiation [Rn] less the gound heat flux [G]) can be obtained by adding the λE and H datasets provided. Energy variables have been provided as hydrological equivalent units of depth, normalised to daily rates (mm/d). TERN OzFlux Surface Energy Balance (SEB) data were used to scale MODIS-based covariates of surface temperature less air temperature (Ts – Ta) and Rn using a Spatial and Temporal General Linear Model (ST-GLM) to third order. The ST-GLM SEB model was implemented across all of Australia on a 0.005° spatial grid (~ 500 m) on a monthly timestep from March 2000 through June 2023. Coefficients of the model were determined from the OzFlux network of eddy covariance flux tower data. Three flux tower sites were used to independently validate the accuracy of the model, being Calperum, SA, Howard Springs, NT, and Tumbarumba, NSW. The mean absolute difference (MAD) for λE, H and A was estimated as: 0.37, 0.39 and 0.34 mm/d, respectively. The relative errors determined by the MAD percentage (MADP) for λE, H, and A were estimated to be: 16%, 26%, and 9%, respectively. This dataset represents a new pathway for operational regional- to global-scale estimation of dynamic SEB variables.

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    This terrestrial LiDAR dataset captures detailed vegetation structural information at the Tumbarumba Wet Eucalypt site in NSW, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.