Automated rain rate estimates using the Ka-band ARM zenith radar (KAZR)

[摘要] The use of millimeter wavelength radars for probing precipitation hasrecently gained interest. However, estimation of precipitation variables isnot straightforward due to strong signal attenuation, radar receiversaturation, antenna wet radome effects and natural microphysical variability.Here, an automated algorithm is developed for routinely retrieving rain ratesfrom the profiling Ka-band (35-GHz) ARM (Atmospheric RadiationMeasurement) zenith radars (KAZR). A 1-dimensional, simple, steady statemicrophysical model is used to estimate impacts of microphysical processesand attenuation on the profiles of radar observables at 35-GHz and thusprovide criteria for identifying situations when attenuation or microphysicalprocesses dominate KAZR observations. KAZR observations are also screened forsignal saturation and wet radome effects. The algorithm is implemented in twosteps: high rain rates are retrieved by using the amount of attenuation inrain layers, while low rain rates are retrieved from the reflectivity–rainrate (Z_e–R) relation. Observations collected by the KAZR, rain gauge,disdrometer and scanning precipitating radars during the DYNAMO/AMIE fieldcampaign at the Gan Island of the tropical Indian Ocean are used to validatethe proposed approach. The differences in the rain accumulation from theproposed algorithm are quantified. The results indicate that the proposedalgorithm has a potential for deriving continuous rain rate statistics in thetropics.

[学科分类] 几何与拓扑