Imtiaz Dharssi is a Land Surface Data Assimilation Scientist at Centre for Australian Weather and Climate Research, having previously worked for The Met Office in the UK for over 11 years. Hi reserach interests include:
- Assimilation of satellite derived soil moisture
- The Unified Model soil moisture nudging scheme
- Parametrization of the soil physical properties
- High-resolution soil texture maps for the Unified Model
This project will improve Australia’s ability to manage extreme events by developing a state of the art, world’s best practice in soil moisture analysis.
The accuracy of FDI's are largely dependent on their input variables and advancements in remote sensing are yet to be utilized to improve accuracy and scalability. This study aims to address this through the use of remotely sensed data of soil moisutre, fire radiative power, temperature and precipitation. In doing so, combining risk with likely fire intensity.
Emerging new approaches to evaluate landscape dryness through the use of satellite remote sensing data, land surface modelling and data assimilation techniques are available, measuring dryness more systematically than the empirical methods. Satellite measurements can be blended with land surface model simulations to provide more accurate, detailed and confident estimates and forecasts of land dryness.
This project aims to improve the estimation of landscape moisture through the assimilation of AMSR2 derived near surface soil moisture and vegetation moisture content. Prior to assimilation, the AMSR2 observations must be quality controlled and bias corrected. The first step of this project is validating the AMSR2 observations against ground based measurements.