A statewide grid surface (80m spatial resolution) delineating recent air temperature (Degree Celsius, oC) of Tasmania is produced in near real-time. The outputs are dynamic with air temperature maps updated at half-hourly intervals (there is a production time lag where outputs typically take 30 minutes to be produced from the true observation time). Refer to the following link for details of the latest map updates: https://sdi.tas-hires-weather.cloud.edu.au/shiny/ Map outputs are based on records produced from 43 Bureau of Meteorology (BoM) Automatic Weather Station sites with further bias correction provided by 267 independent air temperature logger recording sites (courtesy of the Tasmanian Government Department of Primary Industries, Parks, Water and Environment (DPIPWE)). For operational real-time application, the mapping was fully automated in the R programming language and hosted on a cloud-based computing platform courtesy of Sense-T and hosted on the high performance computing cluster provided by the Tasmanian Partnership of Advanced Computing (TPAC) of the University of Tasmania.

Cross validation analysis of the interpolation procedure was carried out for previous years to ascertain the quality of future map outputs. We used the mean absolute error (MAE) statistic to cross validate previous map predictions against actual historical data recordings provided by 267 DPIPWE loggers recordings sites. Across the seasons, the MAE was 1.06oC, 1.05oC, 1.02oC and 1.03oC for summer, autumn, winter and spring, respectively. This indicates that on average, predictions are approximately within 1oC of the true temperature. It should be cautioned, however, that on occasions it was found that predictions can be erroneous by as much as 5oC from the true temperature. As such, the map products produced from this system should be treated as indicative of the true temperature and not relied as a true representation. Note that a peer reviewed journal article in reference to the evaluation of the proposed methodology is available here: https://rdcu.be/b4tXu Additionally, model cross validation analysis for temperature predictions recently produced (as displayed in https://sdi.tas-hires-weather.cloud.edu.au/shiny/) can be accessed from the following link. This provides model evaluation metrics including the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Concordance (CC) and Correlation (R2) coefficients. https://www.dropbox.com/s/n83v6ubq3igtqhf/ModelEvaluation_AirTemp.csv?dl=0 GIS datasets (i.e. geotiff raster files) for temperature predictions recently produced can also be downloaded from here: https://www.dropbox.com/scl/fo/izet3gk0uh0hko1t2urk7/h?dl=0&rlkey=nbvlekulead5tly8tho1hy7o9 Alternatively, the following web map service (wms) can be used to import live updates into a GIS: https://sdi.tas-hires-weather.cloud.edu.au/geoserver/Temperature/wms Reference: WEBB, M. A., KIDD, D. & MINASNY, B. 2020. Near real-time mapping of air temperature at high spatiotemporal resolutions in Tasmania, Australia. Theoretical and Applied Climatology, 141, 1181-1201.