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.
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
Purpose
Managing and understanding water resources requires data on latent heat flux (λE) dynamics across climatic zones at scales from regions to continents in both space and time. Large-scale dynamic λE is not directly observed, however, and hence using remote sensing approaches to scale point flux tower measurements may be a solution to provide the required spatially and temporally dynamic information. The interaction between λE and the sensible heat flux (H) describes the partitioning of the available energy (A) and can provide important context for soil water dynamics and is thus a key to understanding how an ecosystem will use water and respond to heat stress. Having spatially and temporally dynamic estimates of λE and H for all of Australia means this data source can be used to model the water and energy dynamics of any ecosystem, catchment, or land management unit in Australia.