Airborne Radar and Passive Microwave-based Classification and Characterization of Tropical Precipitation Profiles

Data from a series of experiments (CAMEX-3, TEFLUN-B, TRMM LBA) are used to characterize some clearly-defined tropical precipitation types that are well-recognized as distinct, with both in situ cloud and vertical motion data, and with radar and passive microwave data. In essence there is a distinction between convective and stratiform precipitation. Geerts and Heymsfield (2000) developed a discrimination algorithm based on high-resolution profiles of reflectivity, as obtained for instance from the ER-2 Doppler radar (EDOP) nadir antenna. To allow comparison, this method was designed to be similar to the 'V-method' used to classify TRMM Precipitation Radar (PR) rainfall. Convective/stratiform classification is controversial in hurricanes, because of the dominance of stratiform precipitation (defined either by the H method [Steiner et al 1995] or the V method) even in areas that are generally assumed to be convective, such as the eyewall.

We further present composite profiles of some objectively-defined specific types of precipitation, mainly because they have proven to be a major challenge for the microwave or radar rainrate estimation. These include hurricanes (stratiform and convective), warm rain events, vigorous convection, and rain not reaching the ground. Much effort will be devoted to warm rain events, because they are poorly understood yet quite significant in the global precipitation and latent heating budgets. Unfortunately, none of the warm-rain events overflown by the ER-2 in these experiments were also visited by a cloud physics aircraft. We focus on EDOP flight legs for which proximity in situ cloud information is available.

We further characterize the convective/stratiform reflectivity profiles (and those of specific types) in terms of variables that are important for microwave or radar precipitation estimation, especially satellite-based. We show composites (presented as CFADs) of reflectivity and radial velocity profiles from the EDOP nadir antenna. Vertical air motion will be estimated as well, although this imports more uncertainty because of the variability of the Z-Vt relationship. Other variables include echo top and near-surface reflectivity (or rainrate). For EDOP profiles we will also estimate the distribution of microwave brightness temperatures, mainly at 37 and 85 GHz, from the Advanced Microwave Precipitation Radiometer, on the ER-2, and the lightning frequency (from the LIP probe on the ER-2). We plan to supplement the composite depiction of each type with in situ measurements at various altitudes. This supplementation is on a case-by-case basis because of coincident in situ cloud measurements right below the ER-2 are very rare. No strict time/space limits are used to determine the representativeness of proximity in situ data. Rather, this is examined for each case through mapped radar data. These measurements include drop size distribution, liquid water content, vertical air motion, and ice characteristics (amount of riming and crystal habit, as determined by a Cloud Particle Imager).