@article {bnh-6237,
	title = {Disaggregation of JASMIN soil moisture product to 1KM resolution},
	number = {521},
	year = {2019},
	month = {12/2019},
	institution = {Bushfire and Natural Hazards CRC},
	address = {Melbourne},
	abstract = {<p>Fire intensity, spread rate, and ignition are very sensitive to fuel dryness which in turn is strongly linked to soil moisture deficit. Though the value of soil moisture deficit in predicting fire danger has been long established, very few fire danger rating systems employ a comprehensive methodology to estimate it. Most such fire danger rating systems use very simple empirical water balance models which are found to have errors. The Bureau of Meteorology has recently developed a prototype, highresolution, land surface modelling based, state-of-the-art soil moisture analysis for Australia. The product, called Joint United Kingdom Land Environment Simulator (JULES) based Australian Soil Moisture Information (JASMIN), has a spatial resolution of 5 km at hourly timesteps. However, applications like fire danger mapping may require soil moisture information at higher spatial resolution due to the large spatial variability of soil moisture in the landscape. We focus on some of the research carried out to downscale the JASMIN product from 5 km to 1 km spatial resolution. We discuss the application of three downscaling algorithms: two regression-based methods and one with a theoretical basis. The three methods applied are based on the well-known surface temperature {\textendash} vegetation index space. We present an overview of the application of each method, along with an evaluation and comparison against each other and against ground-based soil moisture observations. Results from comparison with ground-based soil moisture measurements indicate that there is no significant degradation of the bias in the three methods, when going into higher spatial resolutions. However, the regression methods, in general, fail to capture the observed temporal variability. The theoretical based method, on the other hand, provides a temporal correlation of 0.81 and captures the skill of the parent JASMIN product.</p>},
	keywords = {dryness, Emergency management, JASMIN, resolution, Soil moisture},
	issn = {521},
	author = {Vinod Kumar and Imtiaz Dharssi and Paul Fox-Hughes}
}
