[S25-1] Development and application of geothermal databases

[S25-1-03] Mapping the continental surface temperature of Australia: the surface boundary condition for conductive thermal models

^○Marcus Haynes¹, Frank Horowitz², Malcolm Sambridge¹, Ed Gerner³, Graeme Beardsmore⁴ (1.Australian National University, Canberra, Australia, 2.Cornell University, Ithaca, United States of America, 3.Geoscience Australia, Canberra, Australia, 4.Hot Dry Rocks Pty Ltd, Melbourne, Australia)

The mean crustal surface temperature represents an important boundary condition for many geothermal studies. This boundary is particularly important to help constrain the information provided by bottom-hole temperature measurements made in mineral and petroleum boreholes, many of which are shallow in nature, observing relatively small changes in temperature from surface to depth. Onshore, this boundary represents the mean land-surface temperature. A mean land-surface temperature map of the Australian continent has therefore been produced from 13 years of MODIS satellite imagery, for the period 2003-2015. The map shows good agreement with independent methods of estimating average land-surface temperature, including borehole surface-temperature extrapolation and long-term, near-surface ground measurements. The MODIS-based method provides spatially continuous estimates (1km pixels) of land-surface temperature and can be employed in regions free from seasonal ground cover of snow. Offshore, this boundary represents the mean sea-floor temperature. A mean sea-floor temperature map of the region surrounding the Australian continent has therefore been produced from models of pelagic temperature data. The mean thermocline observed through each pixel in these models is extrapolated to sea-floor depth. The use of pelagic temperature models also enables spatially continuous temperature estimates (1/8 degree pixels on-shelf, 1/2 degree pixels across the abyssal plain), that will be applicable throughout the world's oceans. When examined in the context of an extensive real-world bottom-hole temperature dataset, the new maps diminished thermal gradient values up to 10% compared to previous methods.