Evaluation of radar polarimetric ice microphysical retrievals using in-situ aircraft measurements from the OLYMPEX campaign

Polarimetric microphysical retrievals are of great value for data assimilation, numerical model evaluation and improvement. However, the accuracy of ice microphysical retrievals remains poorly explored. In order to evaluate these retrievals and assess their accuracy, polarimetric radar measurements are spatially and temporally collocated with in-situ aircraft measurements conducted during the Olympic Mountain Experiment (OLYMPEX) campaign. Retrievals for ice water content, total number concentration, and mean volume diameter of ice particles derived from the polarimetric X-band Doppler on Wheels (DOW) measurements are evaluated utilizing an in-situ data set of the University of Dakota (UND) Citation aircraft. Vertical profiles of microphysical retrievals are derived from sector-averaged RHI scans. The comparison of these estimates with in-situ data from ten flight missions provides insights into strengths, weaknesses, and accuracy of the retrievals, and quantifies the improvements of polarimetry-informed retrievals compared to non-polarimetric, conventional ones. Especially the recently introduced hybrid IWC retrieval exploiting reflectivity ZH, differential reflectivity ZDR and specific differential phase KDP outperforms other retrievals based on either (ZH, ZDR) or (ZH, KDP) or non-polarimetric retrievals in terms of root mean square error and correlations with in-situ measurements. Only IWC retrievals derived via optimal fitting parameters from the High Altitude Ice Crystal – High Ice Water Content (HAIC-HIWC) field campaign data using either KDP or ZDR and KDP achieve comparable correlations, but exhibit a higher root mean square error. ZH-based retrievals for the mean volume diameter partly exhibit significant deviations from airborne in-situ measurements, while polarimetric retrievals show good agreement. For the latter, however, a discrepancy can be observed for large particles at warmer temperatures near the melting layer. On the basis of our evaluation study, the most accurate ice microphysical retrievals are now used to evaluate the ICON numerical weather prediction model to reveal potential biases and deficiencies as a first step towards model improvements.