Gridded near-surface (2 and 10 m) daily average wind datasets for Australia from 1975 to 2018 have been constructed by interpolating observational data collected by the Australian Bureau of Meteorology (BoM). The new datasets span Australia at 0.05 × 0.05° resolution with a daily time step. The datasets were constructed by blending observational data collected at various heights using local surface roughness information.

The data set contains distance measures of primary (wind-borne) and secondary (on ground) seed dispersal during spring, summer and autumn, using empirical observations and detailed measurement of wind characteristics. Seeds were collected from populations of <i>Callitris verrucosa</i> within the reserve and was placed parallel to, and 100 m from the burn edge within the burnt site. For the empirical observation of seed dispersal we chose six release locations, three locations in each of the two sites, about 6 km apart that had both recently undergone a planned burn, one in spring 2009 and the other in autumn 2011. Within those two sites the three release locations were positioned 800 m apart from each other along a transect that was placed parallel to, and 100 m from the burn edge within the burnt site. To assess primary (wind-borne) seed dispersal, 20 randomly chosen seeds were released from each of three different heights (1 m, 2 m and 3 m) at each of the six sites, giving a total of 360 seeds released per season. Seeds were only released within a horizontal wind speed range of 8 - 25 km/h. At lower wind speeds seeds would not take-off and at higher wind speeds seeds could not be relocated. This data set could be reused in a similar study carried out for the same species in a different location. <br> To understand the effect of standing vegetation on the secondary (on-ground) seed dispersal, we established groups of 10 seeds on the ground within 10 m of each of the six previous release locations. Seed were left for 4 days before relocated and distances to the starting point were measured. This was repeated during all 3 seasons. Out of the 180 seeds released,161 (89%) seeds could be relocated. <br> Wind measurements were taken on a sand dune crest in the site that was burned during autumn 2011 using an ultrasonic anemometer (Model WindMaster (Part 1590-PK-020), Gill Instruments Ltd, Lymington, UK). Measurements continued for two weeks in spring, summer and autumn. The anemometer measured horizontal wind speed, horizontal wind direction, and vertical wind speed every 0.1 s, producing a dynamic, three dimensional wind speed vector. Measurements were taken at 2 m height. The data can be used for studies dealing with wind movements in mallee during Spring, Summer and Autumn as well as comparative seed dispersal studies using the same or other wind dispersed plant species.

The data set contains information on air temperature and relative humidity at heights 1m and 3m from three sensors at each height and a global solar radiation at 3m, mean wind speed and gust speed at 3m measured from the Bowen ratio energy balance Flux tower site, Great Western Woodlands Site.

<p>Quantifying the impact of climate change on actual and potential evapotranspiration (AET and PET) is essential for water security, agriculture production and environmental management. AET and PET are strongly influenced by local factors such as topography, land cover and soil moisture, which limits the usability of global climate models for their projections. Here, we dynamically downscale Coupled Model Intercomparison Project Phase 6 (CMIP6) models using Conformal Cubic Atmospheric Model (CCAM) to a 10km resolution over Australia and derive AET and PET at a daily time step using the Morton method and project future changes under SSP126, 245 and 370. Three AET / PET datasets are provided by Queensland Government Climate Projection Service team, which include Areal AET, Wet Environment Areal PET and Point PET. These datasets are computed offline based on Morton&rsquo;s Complementary Relationship Areal Evapotranspiration (CRAE) model.</p> <p>In addition, we also provide datasets for Pan Evaporation (linear regression model), Short and Tall Crop Reference Evapotranspiration (Penman&ndash;Monteith model) and Shallow Lake Evaporation (Morton&rsquo;s Complementary Relationship Wet-surface Evaporation CRWE model). They have used dynamically downscaled CMIP6 models datasets as input.</p>

Data on weather conditions at the Daintree Rainforest, Cape Tribulation site collected between 2006 - 2014. Weather station data includes daily records of air temperature, wind speed, solar radiation, relative humidity and rainfall.

Data on weather conditions at the Warra Tall Eucalypt site collected between 2004 - 2012. Data includes daily maximum and minimum temperatures, wind speed, wind direction, rainfall and humidity.

Data on weather conditions at the Robson Creek Rainforest site collected between 2010 - 2014. Weather station data includes daily records of air temperature, wind speed, solar radiation, relative humidity and rainfall.

Data on weather conditions at the Great Western Woodlands site collected between 2012 - 2016. Data includes half-hourly records of radiation and net radiation at 3 m (2012) and 36 m (2013 - 2016), mean wind speed and wind direction at 3 m (2012) and 36 m (2013 - 2016), air temperature and relative humidity at 3 m (2012) and 36 m (2013 - 2016), atmospheric pressure at 3 m (2012) and 36 m (2013 - 2016), ground heat flux at -8cm, and rainfall at 0.5m

Data on weather conditions at the Daintree Rainforest, Cow Bay site collected between 2008 - 2014. Weather station data includes daily records of air temperature, wind speed, solar radiation, relative humidity and rainfall.

Dynamically downscaled high-resolution (~10 km spatial resolution) climate change projection data for Queensland. Downscaling was completed using CSIRO Conformal Cubic Atmospheric Model (CCAM) for two RCPs (RCP4.5 and RCP8.5) from 11 CMIP5 global coarse resolution models for period 1980-2099. The Queensland Future Climate Dashboard (www.longpaddock.qld.gov.au/qld-future-climate/ ) provides easy access to climate projection for Queensland. The dashboard allows users to explore, visualize and download the latest high-resolution climate modelling data for specific regions, catchments, disaster areas, local government areas and grid squares. Underlying data is provided via TERN for easy access for each of 11 downscaled models. The Queensland Future Climate Dataset provides high resolution data for over 30 different metrics grouped in six climate themes: (i) Mean Climate; (ii) Heatwaves; (iii) Extreme Temperature Indices; (iv) Extreme Precipitation Indices; (v) Droughts; and (vi) Floods. In addition selected variables at daily and monthly intervals are also available.