This geostationary land surface temperature (LST) collection was retrieved using Himawari/AHI observations and calibrated against MODerate-resolution Imaging Spectroradiometer (MODIS) best-quality retrievals for Australia. It was developed under an academic collaboration between the Australian National University (ANU) and the Commonwealth Scientific and Industrial Research Organisation (CSIRO). It has a spatial resolution of 2 km and temporal frequency of 10 min, and has been periodically updated since its inception in July 2015. This record has a temporal length of 8.5 years (i.e., Jul 2015 - Dec 2023) and the subsequent updates will be published annually.

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.

The far north Queensland microclimate (FNQ-microclim) is an ongoing long-term microclimate monitoring project from across five tropical rainforest sites (Daintree Rainforest SuperSite, Cape Tribulation; Daintree Rainforest SuperSite, Cow Bay; Rex Range; Mt. Lewis National Park; and Mt. Bellenden Ker), located within an elevation range of 40 - 1550 m a.s.l. Microclimate parameters include: a) air temperature (about 15 cm above ground), b) near surface temperature at the interface between soil and air (less than 1 cm above ground), c) top soil temperature (about 8 cm below ground), and d) top soil moisture (up to 10 cm below ground). Data are recorded every 15 minutes using the TMS-4 sensors (Temperature Moisture Sensor, T.M.O.S.T s.r.o, Prague, Czech Republic).

River sites were sampled during the summers of 2008/09 and 2009/10 in a survey designed to identify correlations between commonly used river condition variables and grazing land-use. Potential stream sites in northern Tasmania were screened by catchment size, northing and slope, and according to attributes aimed at minimising confounding variables, maintaining broad consistency in landscape and geomorphological context, and promoting independence among sites. A set of 27 survey sites was selected across a gradient from low to high proportion of land under grazing in their upstream catchments. Catchment sizes varied from 20-120 km2 and proportion grazing from 0-80%. Macroinvertebrates were sampled using Surber sampler. All macroinvertebrates within a 20% sub-sample identified to family and counted, with individuals from the insect orders Ephemeroptera, Plecoptera and Trichoptera identified to genus/species (by Laurie Cook, UTAS). Algal abundance was estimated at each site as the proportion of algal cover and as areal density of benthic chlorophyll a. Physical data variables collected were: water temperature, conductivity, turbidity, pH, total alkalinity, nitrate+nitrate, dissolved reactive phosphorus, total nitrogen, total phosphorus, overhead shading, the proportion of fine sediments within the sampled riffle zone, accumulated abstraction index and accumulated regulation index. For more information see: See Magierowski RH, Read SM, Carter SJB, Warfe DM, Cook LS, Lefroy EC and Davies PE. Inferring landscape-scale land-use impacts on rivers using data from mesocosm experiments and artificial neural networks. PLOS ONE.