Uncertainties in retrieving microphysical properties of rain profiles using ground‐based dual‐frequency radar

Abstract

AbstractDual‐frequency radar (DFR) could improve the accuracy of estimating the microphysical properties of rain profiles. Unfortunately, factors that cause inaccuracies in retrieved rain profiles include uncertainties in raindrop size distribution (DSD) parameterizations, DFR retrieval methods and radar measurement errors. The primary objective of this study was to assess the uncertainties in retrieving rain profiles to offer insight into application considerations for ground‐based DFRs in China. The uncertainties caused by DSD models are assessed by comparing attenuation coefficients and rain rates from DFR algorithms with those directly derived from DSD spectra from disdrometers. Then, based on a DSD model, the impacts of retrieval methods, radar range resolution, measurement error and errors in temperature on DFR retrievals are explored by comparing the rain profiles obtained using DFR algorithms with those directly output from the Weather Research and Forecasting model. Overall, the impact of measurement error on the DFR retrievals is relatively significant for both the forward retrieval method and the iterative backward retrieval method and should be eliminated in practical applications. At an individual uncertainty level, the impact of DSD parameterizations on the retrievals from the dual‐frequency technique is less than ±10% bias when the shape factor μ of the gamma distribution ranges from 2 to 4. The retrieved rain profiles from the forward retrieval method are relatively sensitive to radar range resolution and the retrieval performance can be improved with increasing the range resolution, while the iterative backward retrieval method exhibits stable retrieval performance. The impact of temperature errors on the retrieved rain profiles is negligible.