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Enhancing Weather Forecasts Through Assimilation of AMSR-E Soil Moisture Data

This project aims to improve numerical weather prediction models by assimilating remotely sensed soil moisture data from AMSR-E. Key goals include developing a soil moisture product from AMSR-E observations and integrating it into the LAPS model to assess its impact on forecast accuracy. The project focuses on verifying AMSR-E derived soil moisture products in Australia, considering near-surface soil moisture with a spatial scale of ~50x50 km and daily sampling frequency. Additionally, the verification of 1-D LAPS simulations will analyze the effects of AMSR data on various weather parameters.

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Enhancing Weather Forecasts Through Assimilation of AMSR-E Soil Moisture Data

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  1. A BMRC and eWater Perspective Clara Draper Dr. Jeffrey Walker & Dr. Peter Steinle (BMRC) 1

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  3. Project goal • Improve model performance by assimilating remotely sensed (AMSR-E) soil moisture into the Bureau’s numerical weather prediction models. • Develop a soil moisture product from AMSR-E observations • Assimilate this into LAPS, and investigate the impact on forecast skill 3

  4. Verification of AMSR-E derived soil moisture products in an Australian context • Near surface soil moisture • Spatial scale similar to AMSR-E (~50 x 50 km) • Sampling frequency close to daily • Understanding of finer spatial variation, diurnal cycle, and soil moisture profile dynamics 4

  5. Verification of 1-D LAPS simulation for NAFE region, with and without AMSR data: • Latent and sensible heat flux, atmospheric temperature, rainfall, soil moisture • Spatial scale similar to AMSR-E (~50 x 50 km) • High sampling frequency (hourly) 5

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