Using Relationships between Radar Surface Backscatter and Microwave Emissivity to Improve TRMM and GPM Combined Radar-Radiometer Precipitation Retrievals

Precipitation retrievals from downward-looking (aircraft and satellite) radars at attenuating frequencies often take advantage of an estimate of the path-integrated attenuation (PIA) to constrain the retrieval. This is commonly done by comparing the surface radar backscatter cross-section (σ₀) under raining and non-raining conditions. However, the surface radar backscatter in non-raining conditions is not uniform and depends on incidence angle, wind-induced surface roughness (over ocean) and a combination of surface roughness, topography, soil type, soil moisture, and vegetation coverage and water content over land. Similarly, the brightness temperatures that are observed by passive microwave radiometers are influenced by both the surface emissivity, which is dependent on many of the above factors, as well as properties of the precipitation column and atmosphere.

This research seeks to exploit the relationships between surface backscatter cross-section and multi-frequency emissivity in combined radar-radiometer precipitation retrievals. Instead of treating emissivity and σ₀ as independent random variables, we constrain the solution space to the observed joint distribution of emissivity and σ₀. In addition to reducing the uncertainty in the retrieved precipitation, another useful outcome of this method is that the surface properties can be obtained at higher resolution and with improved accuracy relative to the radiometer algorithms, particularly over water surfaces where a physical model is used to calculate surface emissivity and σ₀ as a function of wind speed and incidence angle.

To derive the relationships between σ₀ and emissivity over land, the 15-year data record of TRMM's radiometer (TMI) and precipitation radar (PR) data has been analyzed to derive the covariance matrix between multi-channel emissivity and multi-angle σ₀ at 0.25 degree spatial and monthly temporal resolution. These covariances indicate strong relationships between emissivity and σ₀ in regions with sparse vegetation and high variability in soil moisture content, with correlations (r²) between σ₀ and horizontally polarized emissivity at 19 GHz as high as 0.8 over parts of India, Australia, and the African Sahel region. The use of these relationships and impact on rainfall retrievals in the proposed GPM combined algorithm framework will be demonstrated.