COMPARISON OF RADAR RAINFALL RETRIEVAL ALGORITHMS IN CONVECTIVE RAIN DURING TOGA COARE

The authors compare deterministic and stochastic rain-rare retrieval a lgorithms by applying them to 14-GHz nadir-looking airborne radar refl ectivity profiles acquired in tropical convective rain during the Trop ical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experim ent. The deterministic algorithms both use the path-integrated attenua tion (PIA), measured by the surface reference technique, as a constrai nt. One deterministic algorithm corrects the k-R relation, while the s econd corrects the Z-R relation. The stochastic algorithms are based o n applying an extended Kalman filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. The authors find that the stochastic algorithm, which uses the PIA, is the most robust algorithm with regard to incorrect assumptions about the drop size distribution (DSD). The deterministic algorithm that use s the PIA to adjust the Z-R relation is also fairly robust and produce s rain rates similar to the stochastic algorithm that uses the PIA. Th e deterministic algorithm that adjusts only the k-R relation and the s tochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, es pecially if the DSD is erroneously assumed to be appropriate for strat iform rain conditions.