The Basic Performance of a Precipitation Retrieval Algorithm for the Global Precipitation Measurement Mission\u27s Single/Dual-Frequency Radar Measurements

A precipitation retrieval algorithm is proposed for the dual-frequency precipitation radar (DPR) on the core satellite of the Global Precipitation Measurement mission. The proposed algorithm is called the HB-DFR algorithm, in reference to the combination of Histchfeld-Bordan\u27s attenuation correction method (HB method) and the dual-frequency ratio (DFR) method. The HB-DFR algorithm is tested with a synthetic DPR dataset produced from the standard product of the PR on the Tropical Rainfall Measuring Mission. Precipitation rates estimated by the HB-DFR algorithm at the lowest (near-surface) range bin are evaluated by comparing them with the corresponding values calculated from the drop size distribution of the synthetic dataset. For \u27light precipitation\u27 (below 1 mm h-1), precipitation rates are slightly underestimated because of the multiple-solution problem in the DFR method. For \u27heavy precipitation\u27 (above 10 mm h-1), the precipitation rates are severely underestimated, and the biases become large when thick liquid phase precipitation occurs. For \u27medium precipitation\u27 (between 1 and 10 mm h -1), the estimates are satisfactory. As almost 50% of precipitation falls as medium precipitation in the synthetic dataset, this result validates the usefulness of DPR measurements and the HB-DFR algorithm. Because the HB-DFR algorithm is a forward retrieval algorithm, it has multiple solutions and produces larger errors when applied to lower (farther) range bins. Unlike other dual-frequency algorithms, the HB-DFR algorithm can be easily switched to a single-frequency algorithm at a range bin where a measurement at one of the two frequencies is not available