Location: Location not imported yet.Title: Improving satellite rainfall accumulation using multiple microwave satellite soil moisture products is Australia) Author
Submitted to: Meeting Abstract
Publication Type: Abstract only
Publication Acceptance Date: 2/1/2012
Publication Date: 2/22/2012
Citation: Crow, W.T., Ryu, D. 2012. Improving satellite rainfall accumulation using multiple microwave satellite soil moisture products is Australia [abstract]. Meeting Abstract. 2012 CDROM. Interpretive Summary:
Technical Abstract: Real-time satellite precipitation product is important input information for streamflow forecasting and for understanding hydrological cycles in ungauged basins. The inner basins of Australia are monitored by a very sparse gauge network and rainfall estimation in the regions does not capture the variability of precipitation that can be used as an input to proper streamflow forecasting and for understanding the dry land ecosystems. Currently available satellite precipitation products utilize the thermal and microwave signals to generate near-global coverage of precipitation, however the accuracy of the products is still not well quantified. In this work, we quantify and correct errors in the satellite-based precipitation product using the Soil Moisture Analysis Rainfall Tool (SMART). In order to analyze the errors of the precipitation product, continental scale real-time satellite precipitation product, TRMM 3B42RT, is used as an input to a simple soil moisture accounting model and the output is compared with the satellite-based microwave retrievals of soil moisture. Soil moisture products observed by multiple satellite instruments, the Advanced Microwave Scanning Radiometer - EOS (AMSR-E), the Soil Moisture and Ocean Salinity (SMOS), and the Advanced Scatterometer (ASCAT), are used to analyze the precipitation error. The result is compared with the interpolated gauge-based precipitation product called the Australian Water Availability Project (AWAP) produced by the Australian Bureau of Meteorology. It is shown that the efficiency of the error correction is affected largely by the surface vegetation density and the annual precipitation of the location.